Note: Descriptions are shown in the official language in which they were submitted.
ASSEMBLIES AND METHODS FOR ENHANCING CONTROL OF FLUID
CATALYTIC CRACKING (FCC) PROCESSES USING SPECTROSCOPIC
ANALYZERS
Technical Field
[0001] The present disclosure relates to assemblies and methods to enhance
control of fluid
catalytic cracking (FCC) processes and, more particularly, to assemblies and
methods to enhance
control of FCC processes using one or more spectroscopic analyzers during one
or more FCC
processes.
Background
[0002] Fluid catalytic cracking (FCC) processes may be used to produce desired
petroleum-based
intermediate and final products from hydrocarbon feeds. FCC processes are
inherently complex
because they involve a large number of variables and processing parameters
associated with the
hydrocarbon feeds and operation of FCC processing units and downstream
processing units.
Optimization, design, and control of fluid catalytic cracking (FCC) processing
units may benefit
from analytical models that describe conversion of hydrocarbon feeds to
products. Analytical
models, however, may only be useful if provided with timely and accurate
information. If the
information lacks sufficient accuracy, the analytical model may provide
inaccurate outputs, for
example, relating to hydrocarbon feedstock monitoring and control, and/or
control of FCC and
related processing units, and resulting products may lack desired properties.
If the information is
not provided to the analytical model in a sufficiently responsive manner,
desired changes based on
the information and model outputs may be delayed, resulting in extending the
time during which
the FCC processes are performed below optimum efficiency. Conventional
laboratory analysis of
the hydrocarbon feeds and related materials or processes may suffer from
insufficiently responsive
results to provide effective monitoring and control of the FCC process and
related materials. For
example, off-line laboratory analysis and related modeling studies may involve
response times of
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hours, days, or even weeks, during which processing parameters are not
optimized. As a result,
the value of such monitoring and control may be reduced when used to monitor
and control FCC
processes in during operation.
[0003] Although some FCC processes may include devices and processes for
monitoring and
controlling the FCC process, Applicant has recognized that such devices and
processes may suffer
from delayed acquisition of useful information and/or inaccuracies due to the
nature of the devices
or processes. As a result, Applicant has recognized that there may be a desire
to provide assemblies
and methods for more accurately monitoring and/or controlling FCC processes
and/or for more
responsively determining properties and/or characteristics of hydrocarbon
feeds, processing unit
product materials, intermediate materials, FCC effluent, and/or upstream
materials or downstream
materials related to the FCC processes. Such assemblies and methods may result
in enhanced
control of FCC processes for more efficiently producing FCC products and/or
downstream
products.
[0004] The present disclosure may address one or more of the above-referenced
considerations,
as well as other possible considerations.
Summary
[0005] Monitoring and control of FCC processes may be important for producing
FCC-related
products having certain characteristics or properties to meet industry and/or
marketing standards.
Using current systems and processes, it may be difficult to achieve desired
standards because the
systems and methods may suffer from delayed acquisition of useful information
and/or
inaccuracies due to the nature of the devices or processes. At least some
embodiments of the
present disclosure may advantageously provide assemblies and/or methods for
monitoring and/or
controlling FCC processes, such that the resulting FCC-related products have
desired
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characteristics or properties that may be achieved more efficiently. In some
embodiments, the
assemblies and/or methods disclosed herein may result in acquisition of useful
information and/or
provide more accurate information for monitoring and/or controlling FCC
processes. This, in turn,
may result in producing FCC-related products having desired characteristics or
properties in a
more efficient manner. For example, in at least some embodiments, at least
some of the acquired
information may be used to monitor and prescriptively control FCC processes,
resulting in
producing FCC-related products having desired characteristics or properties in
a more
economically efficient manner. For example, prescriptively controlling the FCC
process assembly
and/or the FCC process, according to some embodiments, may result in enhancing
accuracy of
target content of one or more of the intermediate materials, the unit product
materials, or
downstream materials produced by one or more downstream processing units,
thereby to more
responsively control the FCC processing assembly to achieve material outputs
that more accurately
and responsively converge on target properties.
[0006] According to some embodiments, a method to enhance control of a fluid
catalytic cracking
(FCC) processing assembly associated with a refining operation, may include
supplying a
hydrocarbon feedstock to one or more first processing units associated with
the refining operation.
The one or more first processing units may include an FCC processing unit. The
method further
may include operating the one or more first processing units to produce one or
more corresponding
unit materials, and the one or more corresponding unit materials may include
one or more of
intermediate materials or unit product materials including FCC effluent. The
method also may
include conditioning a hydrocarbon feedstock sample to one or more of filter
the hydrocarbon
feedstock sample, change a temperature of the hydrocarbon feedstock sample,
dilute the
hydrocarbon feedstock sample in solvent, or degas the hydrocarbon feedstock
sample. The
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method still further may include analyzing the hydrocarbon feedstock sample
via a first
spectroscopic analyzer to provide hydrocarbon feedstock sample spectra. The
method also may
include conditioning a unit material sample to one or more of filter the unit
material sample, change
a temperature of the unit material sample, dilute the unit material sample in
solvent, or degas the
unit material sample. The method further may include analyzing the unit
material sample via one
or more of the first spectroscopic analyzer or a second spectroscopic analyzer
to provide unit
material sample spectra. One or more of the first spectroscopic analyzer or
the second
spectroscopic analyzer may be calibrated to generate standardized spectral
responses. The method
further may include predicting one or more hydrocarbon feedstock sample
properties associated
with the hydrocarbon feedstock sample based at least in part on the
hydrocarbon feedstock sample
spectra, and predicting one or more unit material sample properties associated
with the unit
material sample based at least in part on the unit material sample spectra.
The method also may
include prescriptively controlling, via one or more FCC process controllers
based at least in part
on the one or more hydrocarbon feedstock sample properties and the one or more
unit material
sample properties, one or more of: (i) a feedstock parameter associated with
the hydrocarbon
feedstock supplied to the one or more first processing units; (ii) content of
the intermediate
materials produced by one or more of the first processing units; (iii)
operation of the one or more
first processing units; (iv) content of the unit material; or (v) operation of
one or more second
processing units positioned downstream relative to the one or more first
processing units, so that
the prescriptively controlling results in enhancing accuracy of target content
of one or more of the
intermediate materials, the unit product material, or downstream materials
produced by the one or
more second processing units, thereby to more responsively control the FCC
processing assembly
to achieve material outputs that more accurately and responsively converge on
target properties.
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[0007] According to some embodiments, a fluid catalytic cracking (FCC) control
assembly to
enhance control of a fluid catalytic cracking (FCC) process associated with a
refining operation,
may include a first spectroscopic analyzer positioned to: receive a
hydrocarbon feedstock sample
of a hydrocarbon feedstock positioned to be supplied to one or more first
processing units
associated with the refining operation, the one or more first processing units
including an FCC
processing unit; and analyze the hydrocarbon feedstock sample to provide
hydrocarbon feedstock
sample spectra. The FCC control assembly further may include a second
spectroscopic analyzer
positioned to: receive on-line a unit material sample of one more unit
materials produced by one
or more first processing units, the one or more unit materials including one
or more of intermediate
materials or unit product materials including FCC effluent. The first
spectroscopic analyzer and
the second spectroscopic analyzer may be calibrated to generate standardized
spectral responses,
and analyze the unit material sample to provide unit material sample spectra.
The FCC control
assembly also may include a sample conditioning assembly positioned to one or
more of: (i)
condition the hydrocarbon feedstock sample, prior to being supplied to the
first spectroscopic
analyzer, to one or more of filter the hydrocarbon feedstock sample, change a
temperature of the
hydrocarbon feedstock sample, dilute the hydrocarbon feedstock sample, or
degas the hydrocarbon
feedstock sample; or (ii) condition the unit material sample, prior to being
supplied to the second
spectroscopic analyzer, to one or more of filter the unit material sample,
change a temperature of
the unit material sample, dilute the unit material sample in solvent, or degas
the unit material
sample. The FCC control assembly still further may include an FCC process
controller in
communication with the first spectroscopic analyzer and the second
spectroscopic analyzer. The
FCC process controller may be configured to predict one or more hydrocarbon
feedstock sample
properties associated with the hydrocarbon feedstock sample based at least in
part on the
Date Recue/Date Received 2023-02-21
hydrocarbon feedstock sample spectra, and predict one or more unit material
sample properties
associated with the unit material sample based at least in part on the unit
material sample spectra.
The FCC process controller further may be configured to prescriptively
control, based at least in
part on the one or more hydrocarbon feedstock sample properties and the one or
more unit material
sample properties, one or more of: (i) a feedstock parameter associated with
the hydrocarbon
feedstock supplied to the one or more first processing units; (ii) content of
the intermediate
materials produced by one or more of the first processing units; (iii)
operation of the one or more
first processing units; (iv) content of the unit material; or (v) operation of
one or more second
processing units positioned downstream relative to the one or more first
processing units, so that
the prescriptively controlling results in enhancing accuracy of target content
of one or more of the
intermediate materials, the unit product material, or downstream materials
produced by the one or
more second processing units, thereby to more responsively control the FCC
processing assembly
to achieve material outputs that more accurately and responsively converge on
target properties.
[0008] According to some embodiments, a fluid catalytic cracking (FCC) process
controller to
enhance control of a fluid catalytic cracking (FCC) processing assembly
associated with a refining
operation, the FCC process controller being in communication with one or more
spectroscopic
analyzers and one or more first processing units, may be configured to predict
one or more
hydrocarbon feedstock sample properties associated with a hydrocarbon
feedstock sample based
at least in part on hydrocarbon feedstock sample spectra generated by the one
or more
spectroscopic analyzers. The FCC process controller further may be configured
to predict one or
more unit material sample properties associated with a unit material sample
based at least in part
on unit material sample spectra generated by the one or more spectroscopic
analyzers. The FCC
process controller also may be configured to prescriptively control, based at
least in part on the
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one or more hydrocarbon feedstock sample properties and the one or more unit
material sample
properties, one or more of: (i) a feedstock parameter associated with the
hydrocarbon feedstock
supplied to the one or more first processing units; (ii) content of the
intermediate materials
produced by one or more of the first processing units; (iii) operation of the
one or more first
processing units; (iv) content of the one or more unit materials; or (v)
operation of one or more
second processing units positioned downstream relative to the one or more
first processing units,
so that the prescriptively controlling results in enhancing accuracy of target
content of one or more
of the intermediate materials, the unit product materials, or downstream
materials produced by the
one or more second processing units, thereby to more responsively control the
FCC process to
achieve material outputs that more accurately and responsively converge on
target properties.
[0009] According to some embodiments, a fluid catalytic cracking (FCC)
assembly associated
with a refining operation may include one or more first FCC processing units
associated with the
refining operation including one or more of an FCC reactor or an FCC
regenerator. The FCC
processing assembly may further include a first spectroscopic analyzer
positioned to receive a
hydrocarbon feedstock sample of a hydrocarbon feedstock positioned to be
supplied to the one or
more first FCC processing units, and analyze the hydrocarbon feedstock sample
to provide
hydrocarbon feedstock sample spectra. The FCC processing assembly further may
include a
second spectroscopic analyzer positioned to receive on-line a unit material
sample of one more
unit materials produced by the one or more first FCC processing units, the one
or more unit
materials including one or more of intermediate materials or unit product
materials including FCC
effluent. The first spectroscopic analyzer and the second spectroscopic
analyzer may be calibrated
to generate standardized spectral responses, and analyze the unit material
sample to provide unit
material sample spectra. The FCC processing assembly also may include a sample
conditioning
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Date Recue/Date Received 2023-02-21
assembly positioned to one or more of (i) condition the hydrocarbon feedstock
sample, prior to
being supplied to the first spectroscopic analyzer, to one or more of filter
the hydrocarbon
feedstock sample, change a temperature of the hydrocarbon feedstock sample,
dilute the
hydrocarbon feedstock sample, or degas the hydrocarbon feedstock sample; or
(ii) condition the
unit material sample, prior to being supplied to the second spectroscopic
analyzer, to one or more
of filter the unit material sample, change a temperature of the unit material
sample, dilute the unit
material sample in solvent, or degas the unit material sample. The FCC
processing assembly also
may include an FCC process controller in communication with the first
spectroscopic analyzer and
the second spectroscopic analyzer. The FCC process controller may be
configured to predict one
or more hydrocarbon feedstock sample properties associated with the
hydrocarbon feedstock
sample based at least in part on the hydrocarbon feedstock sample spectra, and
predict one or more
unit material sample properties associated with the unit material sample based
at least in part on
the unit material sample spectra. The FCC process controller also may be
configured to
prescriptively control, based at least in part on the one or more hydrocarbon
feedstock sample
properties and the one or more unit material sample properties, one or more
of: (i) a feedstock
parameter associated with the hydrocarbon feedstock supplied to the one or
more first FCC
processing units; (ii) content of the intermediate materials produced by one
or more of the first
FCC processing units; (iii) operation of the one or more first FCC processing
units; (iv) content of
the unit material; or (v) operation of one or more second processing units
positioned downstream
relative to the one or more first FCC processing units, so that the
prescriptively controlling results
in enhancing accuracy of target content of one or more of the intermediate
materials, the unit
product materials, or the downstream materials produced by the one or more
second processing
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units, thereby to more responsively control the FCC processing assembly to
achieve material
outputs that more accurately and responsively converge on target properties.
[0010] Still other aspects, examples, and advantages of these exemplary
aspects and embodiments
are discussed in more detail below. It is to be understood that both the
foregoing information and
the following detailed description are merely illustrative examples of various
aspects and
embodiments, and are intended to provide an overview or framework for
understanding the nature
and character of the claimed aspects and embodiments. Accordingly, these and
other objects,
along with advantages and features of the present disclosure herein disclosed,
may become
apparent through reference to the following description and the accompanying
drawings.
Furthermore, it is to be understood that the features of the various
embodiments described herein
are not mutually exclusive and may exist in various combinations and
permutations.
Brief Description of the Drawings
[0011] The accompanying drawings, which are included to provide a further
understanding of the
embodiments of the present disclosure, are incorporated in and constitute a
part of this
specification, illustrate embodiments of the present disclosure, and together
with the detailed
description, serve to explain principles of the embodiments discussed herein.
No attempt is made
to show structural details of this disclosure in more detail than may be
necessary for a fundamental
understanding of the exemplary embodiments discussed herein and the various
ways in which they
may be practiced. According to common practice, the various features of the
drawings discussed
below are not necessarily drawn to scale. Dimensions of various features and
elements in the
drawings may be expanded or reduced to more clearly illustrate the embodiments
of the disclosure.
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Date Recue/Date Received 2023-02-21
[0012] FIG. 1 is a schematic block diagram illustrating an example FCC
processing assembly
including an example FCC reactor, an example catalyst regenerator, and an
example FCC control
assembly, according to embodiments of the disclosure.
[0013] FIG. 2 is a schematic block diagram illustrating an example FCC
processing assembly
including an example FCC control assembly and an example sample conditioning
assembly,
according to embodiments of the disclosure.
[0014] FIG. 3 is a schematic block diagram illustrating an example sample
conditioning assembly,
according to embodiments of the disclosure.
[0015] FIG. 4A is a block diagram of a spectroscopic analyzer assembly
including a first
standardized spectroscopic analyzer and a first analyzer controller configured
to standardize a
plurality of spectroscopic analyzers and showing example inputs and example
outputs in relation
to an example timeline, according to embodiments of the disclosure.
[0016] FIG. 4B is a continuation of the block diagram shown in FIG. 4A showing
the plurality of
example standardized spectroscopic analyzers outputting respective analyzer
portfolio sample-
based corrections based at least in part on respective variances, and
analyzing conditioned
materials for outputting respective corrected material spectra, according to
embodiments of the
disclosure.
[0017] FIG. 4C is a continuation of the block diagrams shown in FIGS. 4A and
4B showing
respective corrected material spectra output by the plurality of standardized
spectroscopic
analyzers used to output predicted (or determined) material data for the
materials for use in an
example FCC process, according to embodiments of the disclosure.
Date Recue/Date Received 2023-02-21
[0018] FIG. 5A is a block diagram of an example method to enhance control of a
fluid catalytic
cracking (FCC) processing assembly associated with a refining operation,
according to
embodiments of the disclosure.
[0019] FIG. 5B is a continuation of the block diagram shown in FIG. 5A,
according to
embodiments of the disclosure.
[0020] FIG. 5C is a continuation of the block diagram shown in FIG. 5A and
FIG. 5B, according
to embodiments of the disclosure.
[0021] FIG. 5D is a continuation of the block diagram shown in FIG. 5A, FIG.
5B, and FIG. 5C,
according to embodiments of the disclosure.
[0022] FIG. 5E is a continuation of the block diagram shown in FIG. 5A, FIG.
5B, FIG. 5C, and
FIG. 5D, according to embodiments of the disclosure.
[0023] FIG. 6A is a table illustrating spectroscopic analysis data associated
with an example FCC
process including samples of hydrotreater charges and products, and FCC feeds
used to control
relative amounts of each hydrocarbon class shown in weight percent, according
to embodiments
of the disclosure.
[0024] FIG. 6B is a table illustrating minimum and maximum amounts for a
calibration set shown
in weight percent for example hydrocarbon classes related to the data shown in
FIG. 6A, according
to embodiments of the disclosure.
[0025] FIG. 7 illustrates an example of on-line model tuning using example
gasoline yield in
volume percent, according to embodiments of the disclosure.
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Date Recue/Date Received 2023-02-21
[0026] FIG. 8 is a schematic diagram of an example fluid catalytic cracking
(FCC) process
controller configured to at least partially control an FCC processing
assembly, according to
embodiments of the disclosure.
Detailed Description
[0027] Referring now to the drawings in which like numerals indicate like
parts throughout the
several views, the following description is provided as an enabling teaching
of exemplary
embodiments, and those skilled in the relevant art will recognize that many
changes may be made
to the embodiments described. It also will be apparent that some of the
desired benefits of the
embodiments described may be obtained by selecting some of the features of the
embodiments
without utilizing other features. Accordingly, those skilled in the art will
recognize that many
modifications and adaptations to the embodiments described are possible and
may even be
desirable in certain circumstances. Thus, the following description is
provided as illustrative of
principles of the embodiments and not in limitation thereof.
[0028] The phraseology and terminology used herein is for the purpose of
description and should
not be regarded as limiting. Any examples of operating parameters and/or
environmental
conditions are not exclusive of other parameters/conditions of the disclosed
embodiments.
Additionally, it should be understood that references to "one embodiment," "an
embodiment,"
"certain embodiments," or "other embodiments" of the present disclosure are
not intended to be
interpreted as excluding the existence of additional embodiments that also
incorporate the recited
features. When introducing elements of various embodiments of the present
disclosure, the articles
"a," "an," "the," and "said" are intended to mean that there are one or more
of the elements. As
used herein, the term "plurality" refers to two or more items or components. A
multi-component
sample may refer to a single (one) sample including a plurality of components,
such as two or
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Date Recue/Date Received 2023-02-21
more components. The terms "comprising," "including," "carrying," "having,"
"containing," and
"involving," whether in the written description or the claims and the like,
are open-ended terms,
in particular, to mean "including but not limited to," unless otherwise
stated. Thus, the use of such
terms is meant to encompass the items listed thereafter, and equivalents
thereof, as well as
additional items. The transitional phrases "consisting of" and "consisting
essentially of," are
closed or semi-closed transitional phrases, respectively, with respect to any
claims. Use of ordinal
terms such as "first," "second," "third," and the like in the claims to modify
a claim element does
not necessarily, by itself, connote any priority, precedence, or order of one
claim element over
another or the temporal order in which acts of a method are performed, but are
used merely as
labels to distinguish one claim element having a certain name from another
element having a same
name (but for use of the ordinal term) to distinguish claim elements.
[0029] Certain terminology used herein may have definitions provided for the
purpose of
illustration and not limitation. For example, as used herein, the "sampling
circuit" may refer to an
assembly for facilitating separation of a sample of a material, a sample of a
composition of
material, and/or a sample of an FCC product, for example, for processing
and/or analysis of the
sample.
[0030] As used herein, the term "sample conditioner" may refer to an assembly
for facilitating
preparation of a sample for analysis, for example, to improve the accuracy of
analysis of the sample
and/or to provide consistency and/or repeatability of the analysis of the
sample or more than one
sample.
[0031] As used herein, the term "spectroscopic analyzer" may refer an analyzer
that may be used
to measure or predict one or more properties of a sample of, for example, a
material, a composition
of materials, and/or an FCC product. In some embodiments, the spectroscopic
analyzers may be
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Date Recue/Date Received 2023-02-21
used on-line or in a laboratory setting. "Spectroscopic analyzer" may refer in
some instances to a
spectroscopic analyzer assembly, which may include a spectroscopic analyzer
and an analyzer
controller in communication with one or more spectroscopic analyzers. The
analyzer controller
may be configured for use with a corresponding spectroscopic analyzer for pre-
processing and/or
post-processing steps or procedures related to a spectroscopic analysis, as
will be understood by
those skilled in the art. In some embodiments, the analyzer controller may be
physically connected
to the spectroscopic analyzer. In some such embodiments, the spectroscopic
analyzer may include
a housing, and at least a portion of the analyzer controller may be contained
in the housing. In
some embodiments, the analyzer controller may be in communication with the
spectroscopic
analyzer via a hard-wired communications link and/or wireless communications
link. In some
embodiments, the analyzer controller may be physically separated from the
spectroscopic analyzer
and may be in communication with the spectroscopic analyzer via a hard-wired
communications
link and/or a wireless communications link. In some embodiments, physical
separation may
include being spaced from one another, but within the same building, within
the same facility (e.g.,
located at a common manufacturing facility, such as a refinery), or being
spaced from one another
geographically (e.g., anywhere in the world). In some physically separated
embodiments, both the
spectroscopic analyzer and the analyzer controller may be linked to a common
communications
network, such as a hard-wired communications network and/or a wireless
communications
network. Such communications links may operate according to any known hard-
wired
communications protocols and/or wireless communications protocols, as will be
understood by
those skilled in the art.
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Date Recue/Date Received 2023-02-21
[0032] As used herein, the term "sample introducer" may refer to a component
or assembly that
may be used to facilitate the provision of a conditioned sample (portion or
stream) to one or more
spectroscopic analyzers for analysis.
[0033] As used herein, the term "sample stream" may refer to a portion of a
sample stream
supplied to one or more spectroscopic analyzers for spectroscopic analysis by
the one or more
spectroscopic analyzers.
[0034] As used herein, the term "predicting" may refer to measuring,
estimating, determining,
and/or calculating one or more properties of a material, a composition of
materials, and/or an FCC
product based on, for example, a mathematical relationship, a correlation, an
analytical model,
and/or a statistical model.
[0035] As used herein, the term "sample probe" may refer to a component or an
interface used to
facilitate collection of a sample for analysis by, for example, one or more
spectroscopic analyzers.
[0036] As used herein, the term "analyzer probe" may refer to a component of
one or more
spectroscopic analyzers that facilitates direction of electromagnetic
radiation (e.g., light energy)
from a source through a sample stream (e.g., a conditioned sample stream) to
detect and/or measure
one or more of absorbance, transmittance, reflectance, transflectance, or
scattering intensity
associated with the sample stream.
[0037] As used herein, the term "sample cell" may refer to a receptacle or
cell for receipt of
samples for analysis or measurement, for example, by a spectroscopic analyzer.
[0038] As used herein, the term "on-line" may refer to equipment and/or
processes that are
physically located at or adjacent to processing assemblies during operation
and, for at least some
embodiments, may be capable of providing real-time and/or near real-time
analysis and/or data
Date Recue/Date Received 2023-02-21
capable of real-time and/or near real-time analysis. For example, in some
embodiments, an on-line
spectroscopic analyzer may receive one or more sample streams directly from a
processing
assembly or process and analyze the one or more sample streams in real-time or
near real-time to
provide results that may, in some embodiments, be used to at least partially
control operation of
one or more processing assemblies and/or one or more processes in real-time or
near real-time. In
some embodiments, the on-line spectroscopic analyzer or analyzers may be
physically located in
a laboratory setting. This may be either extractive (e.g., a sample stream is
drawn off of a
processing unit and supplied to a spectroscopic analyzer and/or to one or more
sensors) or in situ
(e.g., a probe of a spectroscopic analyzer or one or more sensors is present
in a conduit associated
with the processing assembly).
[0039] As used herein, the term "at-line" may refer to equipment and/or
processes that are
physically located at or adjacent to processing assemblies during operation,
but which, for at least
some embodiments, are not capable of providing real-time and/or near real-time
analysis and/or
are not capable providing data capable of real-time and/or near real-time
analysis. For example,
in an "at-line" process, a "field analyzer" located physically at or adjacent
a processing assembly
may be used to analyze a sample withdrawn from the processing assembly or
process and manually
taken to the field analyzer for analysis. In some embodiments, the on-line
spectroscopic analyzer
or analyzers may be physically located in a laboratory setting. For example,
in some embodiments,
an at-line spectroscopic analyzer would not receive a sample stream directly
from processing
assemblies, but instead, would manually receive a sample manually withdrawn
from a processing
unit by an operator and manually taken or delivered by the operator to the at-
line spectroscopic
analyzer.
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Date Recue/Date Received 2023-02-21
[0040] FIG. 1 is a schematic block diagram illustrating an example fluid
catalytic cracking (FCC)
assembly 10 including an example FCC reactor 12, an example catalyst
regenerator 14, and an
example FCC control assembly 16, according to embodiments of the disclosure.
In some
embodiments, the example FCC processing assembly 10 may be used in association
with a
refinery. For example, catalytic cracking may be used to convert hydrocarbon
feedstock or
feed/charge 18, for example, heavy feeds including hydrocarbons having boiling
points ranging
from about 600 degrees Fahrenheit (F) to about 1,050 degrees, such as, for
example, atmospheric
gas oil, vacuum gas oil, coker gas oil, lube extracts, and/or slop streams,
into lighter products, such
as, for example, light gases, olefins, gasoline, distillate, and/or coke, by
catalytically cracking large
molecules into smaller molecules. In some embodiments, catalytic cracking may
be performed at
relatively low pressures (e.g., pressures ranging from about 15 pounds per
square inch (psig) to
about 30 psig), for example, in the absence of externally supplied hydrogen
(}12), or in some
embodiments (e.g., including hydrocracking), in which hydrogen is added during
one or more
cracking steps.
[0041] In some embodiments, the hydrocarbon feed/charge 18 may include FCC
feedstocks
including a fraction of crude oil having boiling points ranging from about 650
degrees F to about
1,000 degrees F, which, in some embodiments, may be relatively free of coke
precursors and/or
heavy metal contamination, such as, for example, feedstock sometimes referred
to as "vacuum gas
oil" (VGO), which, in some instances, may be generally obtained from crude oil
by distilling off
the fractions of the feedstock having boiling points below 650 degrees F at
atmospheric pressure
and thereafter separating by further vacuum distillation from the heavier
fractions a cut having
boiling points ranging from about 650 degrees F to about 900 degrees to 1,025
degrees F, for
example, as will be understood by those skilled in the art. Fractions of the
feedstock having boiling
17
Date Recue/Date Received 2023-02-21
points ranging from above about 900 degrees F to about 1,025 degrees F may be
used for other
purposes, such as, for example, asphalt, residual fuel oil, #6 fuel oil,
and/or marine Bunker C fuel
oil. In some embodiments, some of the cuts having higher boiling points may be
used, for example,
as feedstock in association with FCC processes that use carbo-metallic oils
formed by reduced
crude conversion (RCC), for example, using a progressive flow-type reactor
having an elongated
reaction chamber. In some embodiments, the hydrocarbon feed/charge 18 may be
selected to
increase or optimize production of propylene by an FCC processing assembly,
such as, for
example, the hydrocarbon feedstock/charge 18 may be selected to contain
feedstocks having a
particular aromatics content, a particular hydrogen content, and/or other
particular feedstock
characteristics known to those skilled in the art to increase, enhance, or
optimize propylene
production by an FCC processing assembly.
[0042] As schematically shown in FIG. 1, the example fluid catalytic cracking
(FCC) assembly
includes the example FCC reactor 12 and the example catalyst regenerator 14,
and the example
FCC control assembly 16 may be used to at least partially (e.g., semi-
autonomously,
autonomously, and/or fully) control an FCC process performed by the FCC
processing assembly
10. As shown in FIG. 1, in some embodiments, the FCC control assembly 16 may
include one or
more spectroscopic analyzers 20 (e.g., 20A through 20N as shown), which may be
used to receive
(e.g., on-line), analyze, and generate one or more spectra indicative of
properties of samples of the
feed/charge 18 and/or indicative of properties of samples of one or more unit
materials produced
by one or more FCC processing units 22. In some embodiments, one or more of
the spectroscopic
analyzers 20 may be configured to receive more than a single stream of
material for analysis. In
some such embodiments, a multiplexer may be associated with the one or more
spectroscopic
analyzers 20 to facilitate analysis of two or streams of material by a single
spectroscopic analyzer.
18
Date Recue/Date Received 2023-02-21
In some embodiments, one or more of the spectroscopic analyzers 20A though 20N
may be used
and/or located on-line and/or in a laboratory setting. In some embodiments,
the one or more unit
materials may include one or more of intermediate materials or unit product
materials, for example,
including FCC effluent and/or other associated materials taken from any point
or any stage of the
FCC process. In some embodiments, two or more of the spectroscopic analyzers
20A through 20N
may be calibrated to generate standardized spectral responses, for example, as
described herein.
For example, a first spectroscopic analyzer 20A and additional spectroscopic
analyzers 20B
through 20N may be calibrated to generate standardized spectral responses, for
example, such that
each of the first spectroscopic analyzer 20A and the additional spectroscopic
analyzers 20B
through 20N output a respective corrected material spectrum, including a
plurality of signals
indicative of a plurality of material properties of an analyzed material based
at least in part on the
corrected material spectrum, such that the plurality of material properties of
the analyzed material
outputted by the first spectroscopic analyzer 20A are substantially consistent
with a plurality of
material properties of the analyzed material outputted by the additional
spectroscopic analyzers
20B through 20N. In some embodiments, one of more of the spectroscopic
analyzers 20A through
20N may be located in a laboratory setting, for example, as schematically
depicted in FIG. 1 with
respect to the first spectroscopic analyzer 20A.
[0043] In some embodiments, the one or more hydrocarbon feed/charge 18 sample
properties
and/or the one or more unit material sample properties may include a content
ratio indicative of
relative amounts of one or more hydrocarbon classes present in one or more of
the hydrocarbon
feed/charge 18 sample and/or the unit material samples. Other hydrocarbon
feed/charge 18 sample
properties and/or unit material sample properties are contemplated. Although
many embodiments
described herein use more than one spectroscopic analyzer, it is contemplated
that a single
19
Date Recue/Date Received 2023-02-21
spectroscopic analyzer may be used for at least some embodiments of the FCC
processes described
herein. One or more of the spectroscopic analyzers 20A through 20N may include
one or more
near-infrared (NIR) spectroscopic analyzers, one or more mid-infrared (mid-IR)
spectroscopic
analyzers, one or more combined NIR and mid-IR spectroscopic analyzers, and/or
one or more
Raman spectroscopic analyzers. In some embodiments, one or more of the
spectroscopic
analyzer(s) 20A through 20N may include a Fourier Transform near infrared
(FTNIR)
spectroscopic analyzer, a Fourier Transform infrared (FTIR) spectroscopic
analyzer, or an infrared
(IR) type spectroscopic analyzer. In some embodiments, one or more of the
spectroscopic
analyzers 20A through 20N may be ruggedized for use in an on-line analyzing
process and/or in a
laboratory setting, and in some embodiments, one or more of the spectroscopic
analyzers 20A
through 20N may be at least partially housed in a temperature-controlled
and/or explosion-resistant
cabinet. For example, some embodiments of the one or more spectroscopic
analyzers 20A through
20N may be configured to withstand operating conditions, such as, for example,
temperature,
pressure, chemical compatibility, vibrations, etc., that may be present in an
on-line environment
and/or in a laboratory setting. For example, the one or more spectroscopic
analyzers 20A through
20N may be designed to be operated in a particular environment of use and/or
an environment that
meets area classifications, such as, for example, a Class 1, Division 2
location. In some
embodiments, a photometer with present optical filters moving successively
into position, may be
used as a type of spectroscopic analyzer.
[0044] As shown in FIG. 1, in some embodiments, the FCC processing assembly 10
also may
include one or more FCC process controllers 24 in communication with one or
more of the
spectroscopic analyzers 20A through 20N and that control one or more aspects
of the FCC process.
For example, in some embodiments, the FCC process controller(s) 24 may be
configured to predict
Date Recue/Date Received 2023-02-21
one or more hydrocarbon feedstock sample properties associated with samples of
the hydrocarbon
feed/charge 18, for example, based at least in part on hydrocarbon feedstock
sample spectra
generated by the one or more spectroscopic analyzers 20A through 20N (e.g.,
first spectroscopic
analyzer 20A, as shown in FIG. 1). In some embodiments, the FCC process
controller(s) 24 may
be configured to predict (or determine) one or more unit material sample
properties associated with
the unit material samples based at least in part on the unit material sample
spectra generated by
the one or more spectroscopic analyzers 20A through 20N. For example, as
described herein, each
of the one or more spectroscopic analyzer(s) 20A through 20N may output a
signal communicated
to the one or more FCC process controller(s) 24, which may mathematically
manipulate the signal
(e.g., take a first or higher order derivative of the signal) received from
the spectroscopic analyzer,
and subject the manipulated signal to a defined model to generate material
properties of interest,
for example, as described herein. In some embodiments, such models may be
derived from signals
obtained from spectroscopic analyzer measurement of the one or more unit
materials (e.g., the
cracking products). In some examples, an analyzer controller in communication
with a
corresponding one or more of the spectroscopic analyzer(s) 20A through 20N may
be configured
to receive the signal output by the one or more corresponding spectroscopic
analyzers and
mathematically manipulate the signal, for example, prior to the one or more
FCC process
controller(s) 24 receiving the signal.
[0045] In some embodiments, the FCC process controller(s) 24 may be configured
to
prescriptively control, based at least in part on the one or more hydrocarbon
feedstock sample
properties and the one or more unit material sample properties: (i) a
feedstock parameter associated
with the hydrocarbon feed/charge 18 supplied to the one or more FCC processing
units 22; (ii)
content of the intermediate materials produced by one or more of the FCC
processing units 22;
21
Date Recue/Date Received 2023-02-21
operation of the one or more FCC processing units 22; (iii) content of the one
or more unit
materials; and/or operation of one or more processing units positioned
downstream relative to the
one or more FCC processing units 22 such as, for example, a fractionator 26
configured to separate
various hydrocarbon products of FCC effluent received from the FCC reactor 12.
In some
embodiments, the prescriptive control may result in enhancing accuracy of
target content of one
or more of the intermediate materials, the unit product materials, or
downstream materials
produced by the one or more processing units downstream from the one or more
FCC processing
units, for example, thereby to more responsively control the FCC processing
assembly 10 to
achieve material outputs that more accurately and responsively converge on
target properties.
[0046] In some embodiments, the FCC processing assembly 10 further may include
a sample
conditioning assembly 28 configured to condition the hydrocarbon feed/charge
18, for example,
prior to being supplied to the one or more spectroscopic analyzer(s) 20A
through 20N. In some
embodiments, the sample conditioning assembly 28 may be configured to filter
samples of the
hydrocarbon feed/charge 18, change (e.g., control) the temperature of the
samples of the
hydrocarbon feed/charge 18, dilute samples of the hydrocarbon feed/charge 18
with a solvent (e.g.,
on-line and/or in a laboratory setting), and/or degas the samples of the
hydrocarbon feed/charge
18. In some embodiments, one or more sample conditioning procedures may be
performed without
using the sample conditioning assembly 28, for example, in a laboratory
setting. In some
embodiments, the sample conditioning assembly 28 also may be configured to
condition samples
of the unit materials, for example, prior to being supplied to the one or more
spectroscopic
analyzer(s) 20A through 20N, to filter the samples of the unit materials, to
change (e.g., control)
the temperature of the samples of the unit materials, to dilute samples of the
unit materials in
solvent, and/or degas the samples of the unit materials. With respect to
diluting samples, for
22
Date Recue/Date Received 2023-02-21
example, in some embodiments, this may include diluting samples of the
hydrocarbon feed/charge
18 and/or the unit materials, such dilution may be used for analysis in a
laboratory setting, and in
some embodiments, the dilution may be performed in a laboratory setting. In
some such
embodiments, the resulting spectra of the diluted sample may be manipulated,
for example, to back
out account for the infrared absorption or the Raman scattering due to the
presence of the solvent
used. In some embodiments, sample conditioning by the sample conditioning
assembly 28 may
result in more accurate, more repeatable, and/or more consistent analysis of
the hydrocarbon
feed/charge 18 and/or the one or more unit materials, which may in turn result
in improved and/or
more efficient control and/or more accurate control of the FCC process.
Example embodiments
of a sample conditioning assembly 28 are described herein, for example, with
respect to FIG. 3.
In some embodiments, the one or more FCC process controller(s) 24 may be
configured to control
at least some aspects of operation of the sample conditioning assembly 28, for
example, as
described herein.
[0047] As shown in FIG. 1, in some embodiments, the one or more FCC process
controller(s) 24
may be configured to prescriptively control one or more process parameters
associated with
operation of one or more of the FCC processing units 22. For example, the FCC
process
controller(s) 24 may be configured to generate one or more processing unit
control signal(s) 30
indicative of parameters associated with operation of the FCC processing units
22, such as, for
example, the rate of supply of the hydrocarbon feed/charge 18 the one or more
FCC processing
units 22; the pressure of the hydrocarbon feed/charge 18 supplied to the one
or more FCC
processing units 22; a preheating temperature of the hydrocarbon feed/charge
18 supplied to the
one or more FCC processing units 22; the temperature in the FCC reactor 12 or
one or more other
FCC processing units 22; or a reactor pressure associated with a reaction
mixture in the FCC
23
Date Recue/Date Received 2023-02-21
reactor 12, wherein the reaction mixture may include the hydrocarbon
feed/chargel8 and catalyst
to promote catalytic cracking of the hydrocarbon feed/charge 18. Control of
other parameters
associated with operation of the FCC processing units 22 are contemplated.
[0048] For example, according to some embodiments, the assemblies and
processes described
herein may be used to produce propylene. In some such embodiments, the one or
more process
parameters may include, for example, residence time in the reactor, reaction
temperature,
catalyst-to-oil ratio, hydrocarbon partial pressure, and/or other process
parameters associated with
the production of propylene by an FCC processing assembly known to those skill
in the art.
[0049] In some embodiments, a feedstock parameter associated with the
hydrocarbon feed/charge
18 supplied to the one or more FCC processing units may include content,
temperature, pressure,
flow rate, API gravity, UOP K factor, carbon residue content, nitrogen
content, sulfur content,
single-ring aromatics content, dual-ring aromatics content, triple-ring
aromatics content, and/or
quad-ring aromatics content.
[0050] In some embodiments, one or more of the FCC process controller(s) 24
may be configured
to prescriptively control at least a portion of the FCC process by, for
example, operating an
analytical cracking model, which may be executed by one or more computer
processors. In some
embodiments, the analytical cracking model may be configured to improve the
accuracy of:
predicting (or determining) the content of the hydrocarbon feed/charge 18
supplied to the one or
more FCC processing units 22; predicting (or determining) the content of
intermediate materials
produced by the one or more FCC processing units 22; controlling the content
of the hydrocarbon
feed/charge 18 supplied to the one or more FCC processing units 22;
controlling the content of the
intermediate materials produced by the one or more FCC processing units;
controlling the content
of the FCC effluent produced by the one or more FCC processing units; the
target content of the
24
Date Recue/Date Received 2023-02-21
unit product materials produced by the one or more FCC processing units;
and/or the target content
of downstream materials produced by one or more of the downstream processing
units, such as,
for example, the fractionator 26 and/or processing units associated with
operation of the
fractionator 26.
100511 In some embodiments, the analytical cracking model may include or be a
machine-learning-trained model. In at least some such embodiments, the FCC
process
controller(s) 24 may be configured to: (a) provide, to the analytical cracking
model, catalytic
cracking processing data related to: (i) material data including one or more
of: feedstock data
indicative of one or more parameters and/or properties associated with the
hydrocarbon
feed/charge 18; unit material data indicative of one or more unit material
properties associated
with the one or more unit materials; and/or downstream material data
indicative of one or more
downstream material properties associated with one or more downstream
materials produced by
the one or more downstream processing units 36; and/or (ii) processing
assembly data including:
first processing unit data indicative of one or more operating parameters 32
associated with
operation of the one or more processing units 34, such as, for example, the
one or more FCC
processing units 22; second processing unit data indicative of one or more
operating parameters
associated with operation of the one or more of the processing units 34
(collectively), such as, for
example, the one or more downstream processing units 36; and/or conditioning
assembly data
indicative of operation of a sample conditioning assembly 28 configured to one
or more of control
a sample temperature of a material sample, remove particulates from the
material sample, dilute
the material samples in solvent, or degas the material sample; and/or (b)
prescriptively controlling,
based at least in part on the catalytic cracking processing data: one or more
hydrocarbon feedstock
parameters and/or properties associated with the hydrocarbon feed/charge 18;
one or more first
Date Recue/Date Received 2023-02-21
operating parameters associated with operation of the one or more FCC
processing units 22; one
or more properties associated with the one or more unit materials; content of
the one or more unit
materials; one or more second operating parameters associated with operation
of the one or more
downstream processing units 36 positioned downstream relative to the one or
more FCC
processing units; one or more properties associated with the one or more
downstream materials
produced by the one or more downstream processing units 36; content of the one
or more
downstream materials; and/or one or more sample conditioning assembly
operating parameters
associated with operation of the sample conditioning assembly 28.
[0052] In some embodiments, the analytical cracking model may include one or
more cracking
algorithms. The cracking algorithms may be configured to determine, based at
least in part on the
catalytic cracking data, target material properties for one or more of the
hydrocarbon feed/charge
18, the unit materials, or the downstream materials. In some embodiments, the
cracking algorithms
further may be configured to prescriptively control operation of one or more
of the FCC processing
units 22 and/or the one or more downstream processing units 36, for example,
to produce one or
more of unit materials having unit material properties within a first
predetermined range of target
unit material properties for the unit materials, or one or more of downstream
materials having
downstream material properties within a second predetermined range of target
material properties
for the downstream materials. Within range may include within a range above
(but not below) the
target unit material properties or the target material properties of the
downstream materials, within
a range below (but not above) the target unit material properties or the
target material properties
of the downstream materials, or within a range surrounding (on either or both
sides of) the target
unit material properties or the target material properties of the downstream
materials. The cracking
algorithms also may be configured to determine one or more of actual unit
material properties for
26
Date Recue/Date Received 2023-02-21
the unit materials produced by the one or more FCC processing units 24 or one
or more of actual
downstream material properties for the downstream materials produced by the
one or more
downstream processing units 36. The cracking algorithms, in some embodiments,
further may be
configured to determine one or more of unit material differences between the
actual unit material
properties and the target unit material properties or downstream material
differences between the
actual downstream material properties and the target downstream material
properties. In some
embodiments, the cracking algorithms further still may be configured to
change, based at least in
part on one or more of the unit material differences or the downstream
material differences, the
one or more cracking algorithms to reduce the one or more of the unit material
differences or the
downstream material differences. In some embodiments, the cracking algorithms
may result in
more responsively controlling the FCC processing assembly 10, the FCC
processing unit(s) 22,
and/or the downstream processing unit(s) 36 to achieve material outputs that
more accurately and
responsively converge on the target properties.
[0053] In some embodiments, the one or more FCC process controller(s) 24 may
be configured to
prescriptively control by one or more of (i) generating, based at least in
part on the target unit
material properties, one or more first processing unit control signals
configured to control at least
one first processing parameter associated with operation of the one or more
FCC processing unit(s)
22 to produce one or more unit materials having unit material properties
within the first preselected
range of the target unit material properties; or (ii) generating, based at
least in part on the target
downstream material properties, a second processing unit control signal
configured to control at
least one second processing parameter associated with operation of the one or
more downstream
processing unit(s) 36 to produce one or more downstream materials having
downstream material
properties within the second preselected range of the target downstream
material properties. In
27
Date Recue/Date Received 2023-02-21
some embodiments, the FCC process controller(s) 24 still further may be
configured to
prescriptively control operation of the sample conditioning assembly 28, for
example, by
generating, based at least in part on the catalytic cracking data, a
conditioning control signal
configured to control at least one conditioning parameter related to operation
of the sample
conditioning assembly 28.
[0054] In some embodiments, the FCC process controller(s) 24 may be configured
to predict the
one or more hydrocarbon feed/charge 18 sample properties, for example, by
mathematically
manipulating a feedstock spectra signal indicative of the hydrocarbon
feedstock sample spectra to
provide a manipulated feedstock signal, and communicating the manipulated
feedstock signal an
analytical property model configured to predict, based at least in part on the
manipulated feedstock
signal, the one or more hydrocarbon feedstock sample properties. In some
examples, the FCC
process controller(s) 24 may be configured to predict the one or more unit
material sample
properties by mathematically manipulating a unit material spectra signal
indicative of the unit
material sample spectra to provide a manipulated unit material signal, and
communicating the
manipulated unit material signal to an analytical property model configured to
predict, based at
least in part on the manipulated unit material signal, the one or more unit
material sample
properties. In some embodiments, the mathematical manipulation may be
performed, for example,
for an individual wavelength and/or a plurality of wavelengths over a range of
wavelengths, and
the mathematical manipulation may be based on, for example, a mathematical
relationship, which
may include one or more of a ratio, a correlation, an addition, a subtraction,
a multiplication, a
division, taking one or more derivatives, an equation, or a combination
thereof, and/or other
mathematically-derived relationships.
28
Date Recue/Date Received 2023-02-21
[0055] In some embodiments, the one or more FCC process controller(s) 24 may
be configured to
prescriptively control one or more aspects of the FCC process by, for example,
generating, based
at least in part on one or more of the hydrocarbon feed/charge 18 sample
properties or one or more
of the unit material sample properties, the one or more processing unit
control signal(s) 30 to
control on-line one or more of the processing parameter(s) 32 related to
operation of one or more
of the FCC processing unit(s) 22 and/or one or more of the downstream
processing unit(s) 36. For
example, in some embodiments, the one or more unit sample properties may
include reaction
effluent yield, and the prescriptive control may include controlling a riser
outlet temperature based
at least in part on the reaction effluent yield and/or riser lift velocity
based at least in part on the
reaction effluent yield. In some embodiments, the one or more unit material
sample properties
may include FCC product yield (e.g., gasoline yield and/or propylene yield),
and the prescriptive
control may include, for example, controlling riser lift steam rate based at
least in part on the FCC
product yield. In some embodiments, the one or more unit material sample
properties may include
riser stripper effluent, and the prescriptive control may include, for
example, controlling FCC
catalyst stripping based at least in part on the riser stripper effluent. In
some embodiments, the
one or more unit material sample properties may include one or more of an
amount of butane free
gasoline, an amount of total butane, an amount of dry gas, an amount of coke,
an amount of
propylene (e.g., propylene yield), an amount of gasoline, octane rating, an
amount of light fuel oil,
an amount of heavy fuel oil, an amount of hydrogen sulfide, an amount of
sulfur in light fuel oil,
or an aniline point of light fuel oil.
[0056] In some embodiments, the one or more unit material sample properties
may include one or
more reaction effluent properties, and the FCC process controller(s) 24 may
further be configured
to on-line model, based at least in part on the one or more reaction effluent
properties, operation
29
Date Recue/Date Received 2023-02-21
of the one or more FCC processing unit(s) 22. In some embodiments, the one or
more FCC process
controller(s) 24 may be configured to prescriptively control, real-time for
improvement or
optimization of the FCC process. The FCC process controller(s) 24 may be
configured, in at least
some embodiments, to provide the one or more hydrocarbon feed/charge 18 sample
properties
and/or the one or more unit material sample properties to fluid catalytic
cracking (FCC) simulation
software, for example, to model FCC processing unit material yields and/or FCC
unit material
characteristics. For example, the one or more FCC process controller(s) 24 may
be configured to
determine, via the FCC simulation software, based at least in part on the one
or more hydrocarbon
feed/charge 18 sample properties and/or the one or more unit material sample
properties, one or
more processing unit control parameters to achieve the FCC processing unit
material yields and/or
the FCC unit material characteristics.
[0057] As shown in FIG. 1, the FCC reactor 12 may be configured to receive the
hydrocarbon
feed/charge 18 and a catalyst to promote catalytic cracking of the hydrocarbon
feed/charge 18 into
the FCC effluent 38, with the hydrocarbon feed/charge 18 and the catalyst
providing a reaction
mixture. In some such embodiments, the FCC control assembly 16 may include the
one or more
spectroscopic analyzers 20A through 20N, which may be configured to analyze
reaction mixture
samples taken from one or more locations of the FCC reactor 12 to obtain unit
material samples
of, for example, catalyst stripper vapor, reactor dilute vapor, riser vapor,
and/or reactor effluent,
for example, to determine respective catalyst stripper vapor yield, reactor
dilute vapor yield, riser
vapor yield, and/or reactor effluent yield.
[0058] In some embodiments, the unit sample properties may include one or more
properties
associated with reactor dilute vapors, and the FCC process controller(s) 24
may be configured to
prescriptively control riser outlet conditions based at least in part on the
reactor dilute vapors,
Date Recue/Date Received 2023-02-21
and/or vapor quench based at least in part on the reactor dilute vapors. The
one or more unit
material properties may include one more unit material yields, and, in some
embodiments, the FCC
process controller(s) 24 may be configured to tune, based at least in part on
the one or more unit
material yields, a fluid catalytic cracking (FCC) simulation model, and/or
benchmark, based at
least in part on the one or more unit material yields, refinery linear program
predicted yields.
[0059] As shown in FIG. 1, some embodiments of the FCC processing assembly 10
may include
the FCC reactor 12, the catalyst regenerator 14, and the FCC control assembly
16 configured to
enhance control of operation of at least some aspects of the FCC processing
assembly 10 and
related processes, such as the FCC process, as described herein. As shown in
FIG. 1, the
hydrocarbon feed/charge 18 may be supplied via a feed conduit 40, and a heater
42 may be
provided and configured to preheat the feed/charge 18 prior to being supplied
to the FCC reactor
12. The heater 42 may be any temperature control unit capable of heating the
feed-charge 18 to a
predetermined preheating temperature, such as, for example, a fossil-fuel-
fired heater (e.g., a gas
burner) and/or an electrically-powered heater. The heat flux supplied to the
hydrocarbon
feed/charge 18 may be controlled by, for example, the FCC process
controller(s) 24, which may
control a flow of fuel (e.g., via a control valve) and/or electrical power
supplied to the heater 42.
As shown in FIG. 1, in some embodiments, a sample of the hydrocarbon
feed/charge 18 may be
extracted upstream (before) the hydrocarbon feed/charge 18 is preheated, and
the sample of the
hydrocarbon feed/charge 18 may be supplied to the sample conditioning assembly
28 via a
feed/charge sample conduit 44 for conditioning prior to be supplied to the one
or more
spectroscopic analyzer(s) 20A through 20N for analysis, for example, as
described herein. In some
embodiments, a fiber optic probe in communication with the one or more
spectroscopic analyzer(s)
20A through 20N may be inserted directly into the feed conduit 40 to
facilitate analysis of the
31
Date Recue/Date Received 2023-02-21
hydrocarbon feed/charge 18 by one or more of the spectroscopic analyzer(s) 20A
through 20N,
which may prevent a need to extract the sample of the hydrocarbon feed/charge
18 for analysis via
the feed/charge sample conduit 44. In some embodiments, water/steam 46 may be
added to the
preheated hydrocarbon feed/charge 18 via a water/steam conduit 48, for
example, as shown in
FIG. 1.
[0060] As shown in FIG. 1, some embodiments of the FCC processing assembly 10
may include
a riser 50 for conveying the preheated hydrocarbon feed/charge 18 to the FCC
reactor 12 and for
combining catalyst 52, which may be received from the catalyst regenerator 14,
with the
hydrocarbon feed/charge 18 forming a reaction mixture 54, for example, to
promote catalytic
cracking of the hydrocarbon feed/charge 18 into the FCC effluent 38 in the FCC
reactor 12. For
example, the catalyst 52 may be supplied to a lower portion of the riser 50,
for example, via a
catalyst return line 56, as shown in FIG. 1. In some embodiments, the catalyst
regenerator 14 may
be configured to receive spent catalyst from the FCC reactor 12 via a catalyst
stripper line 80 and
at least partially recondition the spent catalyst, for example, by
facilitating contact between the
spent catalyst and air to burn-off carbon and produce flue gas that may exit
the catalyst regenerator
14 via a regenerator cyclone 57 and a flue gas line 58. The reaction mixture
54 may be in the form
of vaporized products, which ascend the riser 50 and may be recovered, for
example, via a reactor
cyclone 59 in the form of the FCC effluent 38. In some embodiments, the FCC
processing unit(s)
22 may include a catalyst cooler 60, and the FCC process controller(s) 24 may
be configured to
control operation of the catalyst cooler 60.
[0061] As shown in FIG. 1, the FCC effluent 38 may be supplied to one or more
downstream
processing units 36, which may include, for example, the fractionator 26
and/or other associated
downstream processing units 36. The fractionator 26 may be configured to
separate various
32
Date Recue/Date Received 2023-02-21
hydrocarbon products of the FCC effluent 38 received from the FCC reactor 12,
such as, for
example, hydrocarbon gases 60 (e.g., propane, butane, methane, and/or ethane),
gasoline 62, light
gas oil 64, and/or heavy gas oil 66. In some embodiments, at least a portion
of the heavy gas oil
66 (e.g., naphtha) may be recycled and added to the hydrocarbon feed/charge 18
via a recycle line
67. In some embodiments, the FCC reactor 12 and/or the catalyst regenerator 14
may operate
according to known FCC reactor and catalyst regenerator processes, except as
described herein.
[0062] As shown in FIG. 1, the one or more spectroscopic analyzers 20A through
20B may be
configured to receive material samples from one or more locations associated
with the FCC
processes and/or downstream processes. In some embodiments, the material
samples, prior to
being received by the one or more spectroscopic analyzers 20A through 20N for
analysis, may be
conditioned, for example, via the sample conditioning assembly 28, as
described herein.
[0063] For example, the one or more spectroscopic analyzers 20A through 20N
may be configured
to receive (e.g., on-line and/or in a laboratory) a sample of the hydrocarbon
feed/charge 18 to be
supplied to the one or more FCC processing units 22 associated with the
refining operation via the
feed/charge sample conduit 44. The one or more spectroscopic analyzers 20A
through 20N may
be configured to analyze the sample of the hydrocarbon feed/charge 18 to
provide hydrocarbon
feedstock sample spectra.
[0064] In some embodiments, for example, as shown FIG. 1, the one or more
spectroscopic
analyzers 20A through 20N may be configured to receive on-line a sample of the
one or more unit
materials produced by the one or more FCC processing units 22. The one or more
unit materials
may include intermediate materials and/or unit product materials. The one or
more spectroscopic
analyzers 20A through 20N may be configured to analyze the samples of the unit
materials to
provide unit material sample spectra.
33
Date Recue/Date Received 2023-02-21
[0065] For example, as shown in FIG. 1, one or more of the spectroscopic
analyzers 20A through
20N may be configured to receive on-line a sample of the FCC effluent 38 from
the outlet of the
FCC reactor 12, for example, via an effluent conduit 68, and the one or more
spectroscopic
analyzers 20A through 20N may be configured to analyze the FCC effluent 38 to
generate one or
more effluent sample spectra. In some embodiments, the one or more of the
spectroscopic
analyzers 20A through 20N may be configured to receive on-line a sample of the
reaction mixture
54, for example, taken from one or more locations of the FCC reactor 12 and/or
the riser 50 via a
reaction mixture conduit 70, and analyze the reaction mixture 54 to generate
one or more reaction
mixture spectra. In some such embodiments, samples of the reaction mixture 54
may be taken
from two or more locations of the FCC reactor 12 and/or riser 50, and
respective samples of the
reaction mixture 54 may be analyzed to generate two or more sets of reaction
mixture spectra.
[0066] As shown in FIG. 1, one or more of the spectroscopic analyzers 20A
through 20N may be
configured to receive on-line two or more samples of the reaction mixture 54
taken from two or
more respective different points along the height of the riser 50 via two or
more riser sample
conduits 72 (e.g., 72A, 72B, 72C, 72D, etc., as shown in FIG. 1), and
respective samples of the
reaction mixture 54 may be analyzed to generate two or more sets of reaction
mixture spectra. In
some embodiments, the one or more of the spectroscopic analyzers 20A through
20N may be
configured to receive on-line a sample of the reaction mixture 54, for
example, taken at the outlet
of the riser 50 via a riser outlet conduit 74, and the sample of the reaction
mixture 54 taken from
the outlet of the riser 50 may be analyzed to generate reaction mixture outlet
spectra.
[0067] In some embodiments, one or more of the spectroscopic analyzers 20A
through 20N may
be configured to analyze sample of the reaction mixture 54 taken at the outlet
of the riser 50, and
another one of the spectroscopic analyzers 20A through 20N may be configured
to analyze the
34
Date Recue/Date Received 2023-02-21
FCC effluent 38 taken at the outlet of the FCC reactor 12, the sample of the
reaction mixture 54
and the sample of the FCC effluent 38 may be analyzed substantially
concurrently. In some
embodiments, one or more of the spectroscopic analyzers 20A through 20N may be
configured to
receive on-line two or more reaction mixture samples 54 taken from two or more
respective
different locations of the cross section of the riser 50 (e.g., form two or
more respective different
locations of the diameter), and the two or more samples of the reaction
mixture 54 may be analyzed
to generate two or more respective sets of reaction mixture spectra. In some
embodiments, one or
more of the spectroscopic analyzers 20A through 20N may be configured to
receive on-line a
sample of the reaction mixture 54 taken from the inlet of the riser 50 via a
riser inlet conduit 76,
and the sample taken from the inlet of the riser 50 may be analyzed to
generate one or more riser
inlet sample spectra.
[0068] As shown in FIG. 1, one or more of the spectroscopic analyzers 20A
through 20N may be
configured to receive on-line samples of the one or more downstream unit
materials produced by
one or more of the downstream processing units 36, such as the fractionator
26, and generate one
or more downstream unit material sample spectra. For example, one or more of
the spectroscopic
analyzers 20A through 20N may be configured to receive on-line samples of one
or more of a
sample of the hydrocarbon gases 60 via a gas sample conduit 84, a sample of
the gasoline 62 via
a gasoline sample conduit 86, a sample of the light gas oil 64 via a light gas
oil sample conduit 88,
or a sample of the heavy gas oil 66 via a heavy gas oil sample conduit 90. The
one or more
spectroscopic analyzers 20A through 20N may be configured to analyze one or
more of the
downstream unit materials and generate one or more downstream material spectra
indicative of
one or more properties of the downstream unit materials, which may be used to
predict (or
determine) the one or more properties of the downstream unit materials.
Date Recue/Date Received 2023-02-21
[0069] As shown in FIG. 1, the analysis of the one or more spectroscopic
analyzers 20A through
20N may be communicated to the one or more FCC process controller(s) 24. In
some
embodiments, the one or more FCC process controller(s) 24 may be configured to
receive one or
more signals indicative of the spectra associated with the feed/charge 18, the
spectra associated
with the reaction mixture 54, the spectra associated with the FCC effluent 38,
and/or the spectra
associated with unit materials produced by the one or more downstream
processing units 36,
compare one or more respective material properties associated therewith (e.g.,
hydrocarbon group
type) against an optimum materials slate desired for improved or optimum
efficiency. In some
embodiments, such as comparison may be used to control supply of the
hydrocarbon feed/charge
18 (e.g., flow rate, temperature, pressure, and/or content), and/or operation
of one or more of the
FCC processing units 22, operation of the sample conditioning assembly 28,
and/or or operation
of one or more of the downstream processing units (e.g., the fractionator 26).
The FCC process
controller(s) 24 may be configured to generate one or more processing unit
control signal(s) 30,
which may be communicated to one or more actuators (e.g., flow control valves
and/or pumps), to
one or more of the FCC processing units 22, and/or to one or more of the
downstream processing
units 36, to control one or more processing parameters 32 associated with the
FCC process and/or
associated processes. In some embodiments, the one or more processing control
signal(s) 30 may
be used to control the content, pressure, and/or temperature of the
hydrocarbon feed/charge 18,
and/or to control operation of the sample conditioning assembly 28, for
example, as described
herein.
[0070] As shown in FIG. 1, in some embodiments, the FCC processing assembly 10
may include
a network 92 providing communication between components of the FCC processing
assembly 10.
The network 92 may be any type of communications network, such as, for
example, a hard-wired
36
Date Recue/Date Received 2023-02-21
communications network and/or a wireless communications network. Such
communications links
may operate according to any known hard-wired communications protocols and/or
wireless
communications protocols, as will be understood by those skilled in the art.
[0071] FIG. 2 is a schematic block diagram illustrating an example FCC
processing assembly 10
including an example FCC control assembly 16 and an example sample
conditioning assembly 28,
according to embodiments of the disclosure. As schematically shown in FIG. 2,
the example FCC
control assembly 16 may be used to at least partially (e.g., fully) control an
FCC process performed
by the FCC processing assembly 10. As shown in FIG. 2, in some embodiments,
the FCC control
assembly 16 may include a sample conditioning assembly 28 and one or more
spectroscopic
analyzers, such as, for example, a feed/charge spectroscopic analyzer 94
configured to receive
(e.g., on-line and/or in a laboratory) via a feed sample conduit 96 a sample
of the hydrocarbon
feed/charge 18, an FCC spectroscopic analyzer 98 configured to receive on-line
via an FCC sample
conduit 100 a sample of one or more unit product materials 102 (e.g., samples
of reaction mixture
and/or FCC effluent), an intermediates spectroscopic analyzer 104 configured
to receive on-line
via an intermediates sample conduit 105 a sample of one or more intermediate
materials 106 (e.g.,
materials taken from points anywhere in the process between the hydrocarbon
feed/charge 18 and
downstream materials 108 produced by one or more downstream processing units
36), a unit
products spectroscopic analyzer 110 configured to receive on-line via a unit
products sample
conduit 112 a sample of one or more unit product materials 102 produced by one
or more of the
FCC processing unit(s) 22, and/or a downstream products spectroscopic analyzer
114 configured
to receive on-line via a downstream materials sample conduit 116 a sample of
one or more of the
downstream material(s) 108 produced by one or more of the downstream
processing unit(s) 36. In
some embodiments, one or more of the spectroscopic analyzers shown in FIG. 2
may substantially
37
Date Recue/Date Received 2023-02-21
correspond to one or more of the spectroscopic analyzers 20A through 20N shown
FIG. 1. In some
embodiments, one or more of the spectroscopic analyzers shown in FIG. 2 may be
configured to
receive (e.g., on-line), analyze, and generate one or more spectra indicative
of properties of the
received samples.
[0072] As shown in FIG. 2, in some embodiments, the FCC processing assembly 10
also may
include one or more FCC process controller(s) 24 in communication with one or
more of the
spectroscopic analyzers and control one or more aspects of the FCC process.
For example, in
some embodiments, the FCC process controller(s) 24 may be configured to
predict one or more
hydrocarbon feedstock sample properties associated with samples of the
hydrocarbon feed/charge
18, for example, based at least in part on hydrocarbon feedstock sample
spectra generated by the
feed/charge spectroscopic analyzer 94. In some embodiments, the FCC process
controller(s) 24
may be configured to predict (or determine) one or more unit material sample
properties associated
with the unit material samples based at least in part on the unit material
sample spectra generated
by the unit products spectroscopic analyzer 110. For example, as described
herein, each of the one
or more spectroscopic analyzer(s) shown in FIG. 2 may output a signal
communicated to the one
or more FCC process controller(s) 24, which may mathematically manipulate the
signal (e.g., take
a first or higher order derivative of the signal) received from the
spectroscopic analyzer, and
subject the manipulated signal to a defined model to generate material
properties of interest, for
example, as described herein. In some embodiments, such models may be derived
from signals
obtained from spectroscopic analyzer measurement of the one or more unit
materials (e.g., the
cracking products). In some examples, an analyzer controller in communication
with a
corresponding one or more of the spectroscopic analyzer(s) may be configured
to receive the signal
38
Date Recue/Date Received 2023-02-21
output by the one or more corresponding spectroscopic analyzers and
mathematically manipulate
the signal, for example, prior to the one or more FCC process controller(s) 24
receiving the signal.
[0073] In some embodiments, the FCC process controller(s) 24 may be configured
to
prescriptively control, based at least in part on the one or more hydrocarbon
feedstock sample
properties and the one or more unit material sample properties: (i) one or
more feedstock
parameters and/or properties associated with the hydrocarbon feed/charge 18
supplied to the one
or more FCC processing units 22; (ii) content of the intermediate materials
106 produced by one
or more of the FCC processing units 22; operation of the one or more FCC
processing units 22;
(iii) content of the one or more unit product materials 102; and/or operation
of one or more
downstream processing units 36 positioned downstream relative to the one or
more FCC
processing units 22, such as, for example, a fractionator 26 (see FIG. 1)
configured to separate
various hydrocarbon products of FCC effluent 38 received from the FCC reactor
12. In some
embodiments, the prescriptive control may result in enhancing accuracy of
target content of one
or more of the intermediate materials 106, the unit product materials 102, or
downstream materials
108 produced by the one or more downstream processing units 36 downstream from
the one or
more FCC processing units, thereby to more responsively control the FCC
processing assembly 10
and/or the downstream processing unit(s) 36 to achieve material outputs that
more accurately and
responsively converge on target properties.
[0074] A shown in FIG. 2, the FCC processing assembly 10 further may include a
sample
conditioning assembly 28 configured to condition the hydrocarbon feed/charge
18, for example,
prior to being supplied to the one or more spectroscopic analyzer(s). In some
embodiments, the
sample, conditioning assembly 28 may be configured to filter samples of the
hydrocarbon
feed/charge 18, change (e.g., control) the temperature of the samples of the
hydrocarbon
39
Date Recue/Date Received 2023-02-21
feed/charge 18, dilute samples of the hydrocarbon feed/charge 18 in solvent
(e.g., in a laboratory
setting), and/or degas the samples of the hydrocarbon feed/charge 18. In some
embodiments, the
sample conditioning assembly 28 also may be configured to condition samples of
one or more of
the intermediate materials 106, the unit product materials 102, and/or the
downstream materials
108, for example, prior to being supplied to the one or more spectroscopic
analyzer(s), to filter the
samples, to change (e.g., control) the temperature of the samples, to dilute
the samples in solvent,
and/or to degas the samples. In some embodiments, the sample conditioning
assembly 28 may
result in more accurate, more repeatable, and/or more consistent analysis of
the hydrocarbon
feed/charge 18 and/or the one or more materials, which may in turn result in
improved and/or more
efficient control and/or more accurate control of the FCC process. and/or
downstream processes.
Example embodiments of a sample conditioning assembly 28 are described herein,
for example,
with respect to FIG. 3. In some embodiments, the one or more FCC process
controller(s) 24 may
be configured to control at least some aspects of operation of the sample
conditioning assembly
28, for example, as described herein.
[0075] As shown in FIG. 2, in some embodiments, the one or more FCC process
controller(s) 24
may be configured to prescriptively control one or more process parameters
associated with
operation of one or more of the FCC processing units 22. For example, the FCC
process
controller(s) 24 may be configured to generate one or more processing unit
control signal(s) 30
indicative of parameters associated with operation of the FCC processing units
22, such as, for
example, content of the hydrocarbon feed/charge 18, the rate of supply of the
hydrocarbon
feed/charge 18 the one or more FCC processing unit(s) 22; the pressure of the
hydrocarbon
feed/charge 18 supplied to the one or more FCC processing unit(s) 22; a
preheating temperature
of the hydrocarbon feed/charge 18 supplied to the one or more FCC processing
unit(s) 22; the
Date Recue/Date Received 2023-02-21
temperature in the FCC reactor 12 or one or more other FCC processing unit(s)
22; or a reactor
pressure associated with a reaction mixture in the FCC reactor 12, wherein the
reaction mixture
may include the hydrocarbon feed/charge 18 and catalyst to promote catalytic
cracking of the
hydrocarbon feed/charge 18. Control of other parameters associated with
operation of the FCC
processing units 22 are contemplated.
[0076] In some embodiments, a feedstock parameter associated with the
hydrocarbon feed/charge
18 supplied to the one or more FCC processing units may include content,
temperature, pressure,
flow rate, API gravity, UOP K factor, carbon residue content, nitrogen
content, sulfur content,
single-ring aromatics content, dual-ring aromatics content, triple-ring
aromatics content, and/or
quad-ring aromatics content.
[0077] In some embodiments, one or more of the FCC process controllers 24 may
be configured
to prescriptively control at least a portion of the FCC process by, for
example, operating an
analytical cracking model, which may be executed by one or more computer
processors. In some
embodiments, the analytical cracking model may be configured to improve the
accuracy of:
predicting the content of the hydrocarbon feed/charge 18 supplied to the one
or more FCC
processing unit(s) 22; predicting the content of intermediate materials
produced by the one or more
FCC processing unit(s) 22; controlling the content of the hydrocarbon
feed/charge 18 supplied to
the one or more FCC processing unit(s) 22; controlling the content of the
intermediate materials
produced by the one or more FCC processing unit(s) 22; controlling the content
of the FCC effluent
produced by the one or more FCC processing unit(s) 22; the target content of
the unit product
materials produced by the one or more FCC processing unit(s) 22; and/or the
target content of
downstream materials produced by one or more of the downstream processing
unit(s) 36, such as,
41
Date Recue/Date Received 2023-02-21
for example, the fractionator 26 and/or processing units associated with
operation of the
fractionator 26.
[0078] As shown in FIG. 2, in some embodiments, the FCC processing assembly 10
may include
a network 92 providing communication between components of the FCC processing
assembly 10.
The network 92 may be any type of communications network, such as, for
example, a hard-wired
communications network and/or a wireless communications network. Such
communications links
may operate according to any known hard-wired and/or wireless communications
protocols, as
will be understood by those skilled in the art.
[0079] FIG. 3 is a schematic block diagram illustrating an example sample
conditioning assembly
28, according to embodiments of the disclosure. In some embodiments, the
sample conditioning
assembly 28 may be configured to condition a sample (e.g., an at least
partially continuous sample
stream) of one or more materials associated with an FCC process and/or one
more processes
upstream and/or downstream relative to the FCC process, for example, to
enhance analysis of the
sample by one or more spectroscopic analyzer(s) 20 (e.g., one or more of the
spectroscopic
analyzer(s) 20A through 20N shown in FIG. 1) associated with the process or
processes. As
described herein, in some embodiments, operation of one or more components of
the sample
conditioning assembly 28 may be at least partially controlled (e.g.,
prescriptively controlled) via
the one or more FCC process controller(s) 24, which may further enhance the
analysis of the
sample(s) by one or more spectroscopic analyzer(s) 20.
[0080] As shown in FIG. 3, in some embodiments, the sample conditioning
assembly 28 may
include a sampling circuit 120 positioned to direct samples (e.g., an on-line
sample stream) from
any point taken along the FCC process, an upstream process, and/or a
downstream process, to
provide the samples for analysis. In some embodiments, the sampling circuit
120 may include a
42
Date Recue/Date Received 2023-02-21
sampler 122 including one or more of a sample probe, a sample supply pump, or
a pressure adjuster
to control a supply of the sample from a header 124 configured to provide a
flow of the sample.
The sample conditioning assembly 28 further may include a sample conditioner
126 in fluid
association with the sampling circuit 120 and positioned to receive the sample
via the sampling
circuit 120. The sample conditioner 126 may be configured to condition the
sample for analysis
by the one or more spectroscopic analyzer(s) 20.
[0081] As shown in FIG. 3, in some embodiments, the sample conditioner 126 may
include a first
stage 128 and a second stage 130. For example, the first stage 128 of the
sample conditioner 126
may include a first set of one or more filters 132 including filter media
positioned to remove one
or more of water, particulates, or other contaminants from the sample to
provide a filtered sample
(e.g., a filtered sample stream). In some embodiments including the second
stage 130, the second
stage 130 may include, for example, a first temperature control unit 134 in
fluid communication
with the first set of the one or more filters 132 and configured to receive
the filtered sample and to
change (e.g., control) the temperature of the filtered sample of the to
provide a temperature-
adjusted sample (e.g., a temperature-adjusted sample stream), such that the
temperature of the
temperature-adjusted sample is within a first preselected temperature range.
For example, the first
temperature control unit 134 may include a cooler or heat exchanger configured
to reduce the
temperature of the filtered sample. In some embodiments, the first preselected
temperature range
may be from about 45 degrees F to about 50 degrees F, although other
temperature ranges are
contemplated.
[0082] In some embodiments, as shown in FG. 3, the second stage 130 also may
include a
degassing unit 136 configured to degas the temperature-adjusted sample to
provide a degassed
sample (e.g., a degassed sample stream). As shown in FIG. 3, some embodiments
may include a
43
Date Recue/Date Received 2023-02-21
second set of one or more filters 138 (e.g., one or more coalescing filters)
in fluid communication
with the first temperature control unit 134 and configured to remove one or
more of water,
particulates, or other contaminants from the degassed sample. In some
embodiments, the second
stage 130 further may include a third set of one or more filters 140 (e.g.,
one or more hydrophobic
and/or liquid-to-liquid filters) configured to further filter the sample. The
second stage 130 further
may include a second temperature control unit 142 in fluid communication with
one or more of
the degassing unit 136 or the second set of the one or more filters 138 and
configured to change
(e.g., control) the temperature of the degassed sample to provide a
temperature-adjusted degassed
sample (e.g., a temperature-adjusted degassed sample stream), such that the
temperature-adjusted
degassed sample has a temperature within a second preselected temperature
range to feed to the
one or more spectroscopic analyzers for more accurate, more consistent, and/or
more repeatable
analysis (e.g., for more accurate property measurements). In some embodiments,
the second
temperature control unit 142 may include a heater or heat exchanger configured
to increase the
temperature of the degassed sample. In some embodiments, the second
preselected temperature
range may be from about 70 degrees F to about 75 degrees F, although other
temperature ranges
are contemplated.
[0083] As shown in FIG. 3, some embodiments of the sample conditioning
assembly 28 may
include an auxiliary filter 144 in fluid communication with the sampling
circuit 120 and connected
in parallel relative to the first set of the one or more filters 132. The
auxiliary filter 144 may be
configured to receive the sample and remove one or more of water,
particulates, or other
contaminants from the sample, for example, to output a filtered sample when
the first set of the
one or more filters 132 are not in use, for example, during maintenance or
service. In some
embodiments, the sample conditioning assembly 28 may include a bypass conduit
146 configured
44
Date Recue/Date Received 2023-02-21
to facilitate passage of one or more of water, particulates, or contaminates
removed from the
sample to one or more of, for example, a process, a sample recovery assembly,
or a pump, for
example, as depicted in FIG. 3 as a reclamation process 148.
[0084] As shown in FIG. 3, the sample conditioning assembly 28 may include one
or more
temperature sensors 150 associated with the sample conditioning assembly 28
and configured to
generate one or more temperature signals indicative of the temperature of one
or more of the
filtered sample, the temperature-adjusted sample, the degassed sample, or the
temperature-adjusted
degassed sample. The sample conditioning assembly 28 further may include a
sample
conditioning controller 152 in communication with the one or more temperature
sensors 150 and
configured to receive the one or more temperature signals and communicate the
one or more
temperature signals to the FCC process controller(s) 24, which may use the one
or more
temperature signals to control an aspect of the FCC process and/or operation
of the first
temperature control unit 134 and/or the second temperature control unit 142.
[0085] As shown in FIG. 3, some embodiments may include an insulated sample
line 154 in flow
communication with, for example, the second temperature control unit 142. Some
such
embodiments further may include a sample introducer 156 in flow communication
with the second
temperature control unit 142 via the insulated sample line 154, and the sample
introducer 156 may
be configured to provide fluid flow from the second temperature control unit
142 to the one or
more spectroscopic analyzer(s) 20 to supply the temperature-adjusted degassed
sample to the one
or more spectroscopic analyzer(s) 20, for example, after at least partially
conditioning the sample.
Some embodiments further may include an optical fiber cable connected to the
second temperature
control unit 142 and the sample introducer 156, and the optical fiber cable
may be configured to
substantially maintain the temperature of the temperature-adjusted degassed
sample within the
Date Recue/Date Received 2023-02-21
second preselected temperature range, for example, until the sample reaches
the one or more
spectroscopic analyzer(s) 20.
[0086] As shown in FIG. 3, some embodiments of the sample conditioning
assembly 28 may
include a nitrogen source 158 in selective fluid communication via a nitrogen
conduit 160 with the
first stage 128 of the sample conditioning assembly 28. The nitrogen source
158 may be used to
flush portions of the sample conditioning assembly 28, for example, between
receipt of different
samples, to improve the accuracy of analysis of the sample by the one or more
spectroscopic
analyzer(s) 20. In some embodiments, the nitrogen source 158 may be used to
flush particulates,
fluid, and/or contaminates from the sample conditioning assembly 28.
[0087] As shown in FIG. 3, the sample conditioning assembly 28 may include one
or more flow
control devices 162, such as valves configured to control the flow of samples
to, within, and/or at
exit of the sample conditioning assembly 28. In some embodiments, the flow
control devices 162
may include one or more pumps, one or more flow regulators, etc., configured
to control the flow
of samples to, within, and/or at exit of the sample conditioning assembly 28.
In some
embodiments, one or more actuators (e.g., electrical, hydraulic, and/or
pneumatic actuators) may
be connected to one or more of the flow control devices 162, and operation of
the one or more
actuators may be controlled via the sample conditioning controller 152 and/or
one or more of the
FCC process controller(s) 24 to control flow of the samples to, within, and/or
at exit of the sample
conditioning assembly 28.
[0088] FIG. 4A. FIG. 4B, and FIG. 4C are a block diagram of a spectroscopic
analyzer assembly
170 including a first standardized spectroscopic analyzer 172A and a first
analyzer controller 174A
configured to standardize a plurality of spectroscopic analyzers and showing
example inputs and
example outputs in relation to an example timeline, according to embodiments
of the disclosure.
46
Date Recue/Date Received 2023-02-21
FIG. 4B shows the plurality of example standardized spectroscopic analyzers
172A through 172N
(collectively 172) and/or the analyzer controllers 174A through 174N
(collectively 174) analyzing
conditioned materials to output predicted (or determined) material data for
the materials for use in
example processes, such as the FCC process and related processes described
herein, according to
embodiments of the disclosure. According to some embodiments, the
spectroscopic analyzers
172A through 172N and the analyzer controllers 174A through 174N shown in
FIGS. 4A through
4C may substantially correspond the spectroscopic analyzer(s) 20A through 20N
shown in FIG. 1
and/or the spectroscopic analyzers(s) shown in FIG. 2. In some embodiments,
the spectroscopic
analyzers 172 and/or the analyzer controllers 174 may analyze unconditioned
material samples,
semi-conditioned material samples, and/or conditioned material samples to
output predicted (or
determined) material data for the material samples for use in example
processes, such as the
processes described herein.
[0089] FIG. 4B is a continuation of the block diagram shown in FIG. 4A showing
the plurality of
example standardized spectroscopic analyzers 172 outputting respective
analyzer portfolio
sample-based corrections based at least in part on respective variances, and
analyzing conditioned
materials for outputting respective corrected material spectra, according to
embodiments of the
disclosure. FIG. 4C is a continuation of the block diagrams shown in FIGS. 4A
and 4B showing
respective corrected material spectra output by the plurality of standardized
spectroscopic
analyzers 172 used to output predicted (or determined) material data for the
materials for use in an
example FCC process, according to embodiments of the disclosure.
[0090] Spectroscopic analyzers may be used to non-destructively predict (or
determine)
properties associated with materials. For example, a sample of material may be
fed to a
spectroscopic analyzer for analysis, and a beam of electromagnetic radiation
may be transmitted
47
Date Recue/Date Received 2023-02-21
into the material sample, resulting in the spectroscopic analyzer measuring a
spectral response
representative of the chemical composition of the sample material, which may
be used to predict
(or determine) properties of the sample material via the use of modeling. The
spectral response
may include a spectrum related to the absorbance, transmission,
transflectance, reflectance, or
scattering intensity caused by the material sample over a range of
wavelengths, wavenumbers, or
frequencies of the electromagnetic radiation.
[0091] Applicant has recognized that over time the results of analysis using a
spectroscopic
analyzer may change, for example, due to changes or degradation of the
components of the
spectroscopic analyzer, such as its lamp, laser, detector, or grating.
Changing or servicing
components of the spectroscopic analyzer may alter its spectral responses
relative to the spectral
responses outputted prior to the changes, necessitating recalibration.
Further, for some
applications (e.g., as described herein), more than one spectroscopic analyzer
may be used in
association with analysis of materials at, for example, a production facility
(e.g., a refinery), and
it may be desirable for two or more of the spectroscopic analyzers to generate
results that are
reproducible and consistent with one another to enhance control of the
production process, such
as an FCC process and/or related upstream processes and/or downstream
processes. Due to the
complex nature, sensitivity, and principle of operation of spectroscopic
analyzers, however, two
spectroscopic analyzers may not be likely to provide equivalent results within
the variability of the
primary test method with which calibration models were made without additional
activity (e.g.,
extensive testing), even when analyzing the same sample of material. This may
result in a lack of
reproducibility or consistency of results across different spectroscopic
analyzers, potentially
rendering comparisons between the results outputted by two or more
spectroscopic analyzers of
48
Date Recue/Date Received 2023-02-21
little value, unless the spectroscopic analyzers have been calibrated to
achieve the same spectral
responses.
[0092] In some embodiments, methods and assemblies described herein may be
used for
determining and using standardized spectral responses for calibration (or
recalibration) of
spectroscopic analyzers. For example, in some embodiments, the methods and
assemblies may be
used to calibrate or recalibrate a spectroscopic analyzer when the
spectroscopic analyzer changes
from a first state to a second state, for example, the second state being
defined as a period of time
after a change to the spectroscopic analyzer causing a need to calibrate the
spectroscopic analyzer.
In some embodiments, the recalibration may result in the spectroscopic
analyzer outputting a
standardized spectrum, for example, such that the spectroscopic analyzer
outputs a corrected
material spectrum for an analyzed material, including one or more of an
absorption-corrected
spectrum, a transmittance-corrected spectrum, a transflectance-corrected
spectrum, a reflectance-
corrected spectrum, or an intensity-corrected spectrum and defining the
standardized spectrum. In
some embodiments, the corrected material spectrum, output when the calibrated
or recalibrated
spectroscopic analyzer is in the second state, may include a plurality of
signals indicative of a
plurality of material properties of an analyzed material (e.g., a sample of
the material) based at
least in part on the corrected material spectrum, the plurality of material
properties of the material
being substantially consistent with a plurality of material properties of the
material outputted by
the spectroscopic analyzer in the first state. This may enhance the accuracy,
reproducibility, and/or
consistency of results outputted by the second-state recalibrated
spectroscopic analyzer prior to
recalibration relative to results outputted by the first-state spectroscopic
analyzer.
[0093] In some embodiments, using calibration of a first spectroscopic
analyzer to calibrate one
or more additional spectroscopic analyzers may include using standardized
analyzer spectra for
49
Date Recue/Date Received 2023-02-21
calibration of a spectroscopic analyzer, for example, such that each of the
one or more
spectroscopic analyzers outputs a corrected material spectrum, including a
plurality of signals
indicative of a plurality of material properties of an analyzed material based
at least in part on the
corrected material spectrum, such that the plurality of material properties of
the material are
substantially consistent with a plurality of material properties of the
material outputted by the first
spectroscopic analyzer. In some embodiments, this may result in achieving
desired levels of
accuracy, reproducibility, and/or consistent results from a plurality of
spectroscopic analyzers,
potentially rendering comparisons between the results outputted by two or more
of the
spectroscopic analyzers more valuable, for example, when incorporated into a
complex process
including a plurality of different material altering processes, such as, for
example, an FCC process
and/or related upstream processes and/or downstream processes.
[0094] According to some embodiments, a method for determining and using
standardized
analyzer spectral responses to enhance a process for calibration of a
plurality of spectroscopic
analyzers, such that for a given material each of the plurality of
spectroscopic analyzers outputs a
plurality of signals indicative of a plurality of material properties of the
material, the plurality of
material properties of the material output by each of the plurality of
spectroscopic analyzers being
substantially consistent with one another, may include transferring one or
more spectral models to
each of the plurality of spectroscopic analyzers. Each of the one or more
spectral models may be
indicative of relationships between a spectrum or spectra and one or more of
the plurality of
material properties of one or more materials. The method also may include
analyzing, via the first
spectroscopic analyzer when in a first state, a selected one or more first-
state portfolio samples to
output a standardized analyzer spectra portfolio for the selected one or more
first-state portfolio
samples. The standardized analyzer spectra portfolio may include a first-state
portfolio sample
Date Recue/Date Received 2023-02-21
spectrum for each of the first-state portfolio samples. The method further may
include analyzing,
via each of a remainder of the plurality of spectroscopic analyzers when in a
second state a selected
one or more second-state portfolio samples to output second-state portfolio
sample spectra for the
selected one or more second-state portfolio samples. Each of the second-state
portfolio sample
spectra may be associated with a corresponding second-state portfolio sample.
The analysis of the
selected one or more second-state portfolio samples may occur during a second-
state time period.
The multi-component samples may include a significantly greater number of
samples than a
number of samples included in the second-state portfolio samples, and the
second-state time period
for analyzing the second-state portfolio samples may be significantly less
than the first-state time
period. The method also may include comparing one or more of the second-state
portfolio sample
spectra for the selected plurality of portfolio samples to the first-state
sample spectra of a selected
plurality of corresponding first-state multi-component samples. The method
still further may
include determining, based at least in part on the comparison, for the one or
more of the selected
plurality of portfolio samples of the second-state portfolio sample spectra, a
variance at one or
more of a plurality of wavelengths or over a range of wavelengths between the
second-state
portfolio sample spectra output by each of the remainder of the plurality of
spectroscopic analyzers
when in the second state and the first-state sample spectra corresponding to
the selected one or
more first-state multi-component material samples output by the first
spectroscopic analyzer in the
first state.
[0095] In some embodiments, the method still further may include analyzing,
via one or more of
the remainder of the plurality of spectroscopic analyzers when in the second
state, a material
received from a material source to output a material spectrum. The method also
may include
transforming, based at least in part on the standardized analyzer spectra
portfolio, the material
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Date Recue/Date Received 2023-02-21
spectrum to output a corrected material spectrum for the material when in the
second state, the
corrected material spectrum including one or more of an absorption-corrected
spectrum,
transmittance-corrected spectrum, a transflectance-corrected spectrum, a
reflectance-corrected
spectrum, or an intensity-corrected spectrum and defining a standardized
spectrum, for example,
and/or a mathematical treatment of the material spectrum, such as, for
example, a second derivative
of the material spectrum.
[0096] In the example embodiments shown in FIGS. 4A, 4B, and 4C, the
spectroscopic analyzer
assembly 170 may include a first spectroscopic analyzer 172A and a first
analyzer controller 174A
configured to determine and use standardized analyzer spectral responses to
standardize spectral
responses of one or more (e.g., each) of the plurality of spectroscopic
analyzers (e.g., a second
spectroscopic analyzer 172B, a third spectroscopic analyzer 172C, and a fourth
spectroscopic
analyzer 172D through an Nth spectroscopic analyzer 172N), such that for a
given material one or
more of the plurality of spectroscopic analyzers outputs a plurality of
signals indicative of a
plurality of material properties of the material, the plurality of material
properties of the material
output by each of the plurality of spectroscopic analyzers being substantially
consistent with one
another. In some embodiments, the spectroscopic analyzer assembly 170 may
further include a
plurality of analyzer controllers (e.g., a second analyzer controller 174B, a
third analyzer controller
174C, and a fourth analyzer controller 174D through an Nth analyzer controller
174N), each
associated with a corresponding spectroscopic analyzer.
[0097] In some embodiments, each of the analyzer controllers 174 may be in
communication with
a respective one of the spectroscopic analyzers 172. For example, the analyzer
controllers 174
may each be physically connected to the respective spectroscopic analyzer 172.
In some such
embodiments, the spectroscopic analyzers 172 may each include a housing and at
least a portion
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Date Recue/Date Received 2023-02-21
of the respective analyzer controller 174 may be contained in the housing. In
some embodiments,
the respective analyzer controllers 174 may be in communication with the
respective spectroscopic
analyzers 172 via a hard-wired and/or wireless communications link. In some
embodiments, the
respective analyzer controllers 174 may be physically separated from the
respective spectroscopic
analyzers 172 and may be in communication with the respective spectroscopic
analyzers 172 via
a hard-wired communications link and/or a wireless communications link. In
some embodiments,
physical separation may include being spaced from one another, but within the
same building,
within the same facility (e.g., located at a common manufacturing facility,
such as a refinery), or
being spaced from one another geographically (e.g., anywhere in the world). In
some physically
separated embodiments, both the spectroscopic analyzer 172 and/or the
respective analyzer
controller 174 may be linked to a common communications network, such as a
hard-wired
communications network and/or a wireless communications network. Such
communications links
may operate according to any known hard-wired and/or wireless communications
protocols as will
be understood by those skilled in the art. Although FIG. 4A schematically
depicts each of the
analyzer controllers 174A through 174N being separate analyzer controllers, in
some
embodiments, one or more of the analyzer controllers 174A through 174N may be
part of a
common analyzer controller configured to control one or more the spectroscopic
analyzers 172A
through 172N.
[0098] In some embodiments, using the standardized analyzer spectra may
include transferring
one or more spectral models of the first spectroscopic analyzer 172A when in
the first state to one
or more of the second through Nth spectroscopic analyzers 172b through 172N
with respective
analyzer controllers 174B through 174N after a change to the second through
Nth spectroscopic
analyzers 172B through 172N, such that, when in the second state, analysis by
the second through
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Date Recue/Date Received 2023-02-21
Nth spectroscopic analyzers 172B through 172N of multi-component materials
results in
generation of second through Nth material spectra 208B through 208N (FIGS. 4B
and 4C) that are
consistent with a first-state material spectrum outputted by the first
spectroscopic analyzer 172A,
when in the first state, resulting from analysis of the first multi-component
material 32A. Thus, in
some embodiments, the first spectroscopic analyzer 172A and one or more of the
second through
Nth spectroscopic analyzers 172B through 172N will be capable of generating
the substantially
same spectrum after an event causing the need to calibrate (or recalibrate)
one or more of the
second through Nth spectroscopic analyzers 172B through 172N (e.g., a change
to one or more of
the second through Nth spectroscopic analyzers 172B through 172N, such as
maintenance and/or
component replacement). In some embodiments, this may improve one or more of
the accuracy,
reproducibility, or consistency of results outputted by the one or more of the
second through Nth
spectroscopic analyzers 172B through 172 N after a change in state from the
first state to the
second state. For example, one or more of the second through Nth spectroscopic
analyzers 172B
through 172N with one or more of the respective second through Nth analyzer
controllers 174B
through 174N may be configured to analyze a multi-component material and
output plurality of
signals indicative of a plurality of material properties of the material based
at least in part on a
corrected material spectrum, such that the plurality of material properties of
the material predicted
(or determined) by one or more of the second through Nth spectroscopic
analyzers 172B through
172N and/or one or more of the second through Nth analyzer controllers 174B
through 174N are
substantially consistent with (e.g., substantially the same as) a plurality of
material properties
outputted by the first spectroscopic analyzer 172A with first analyzer
controller 174A in the first
state. This may result in standardizing the one or more second through Nth
spectroscopic analyzers
172B through 172N with the corresponding one or more of the second through Nth
analyzer
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Date Recue/Date Received 2023-02-21
controllers 174B through 174N based at least in part on the first
spectroscopic analyzer 172A with
the first analyzer controller 174A.
[0099] As shown in FIG. 4A, in some embodiments, the first analyzer controller
174A may be
configured to determine standardized analyzer spectra for calibration of the
plurality of
spectroscopic analyzer 172B through 172N when one or more of the spectroscopic
analyzers 172B
through 172N changes from a first state to a second state. For example, the
first analyzer controller
174A, while in the first state and during a first-state time period T1, may be
configured to analyze
a plurality of different multi-component samples 176 and, based at least in
part on the multi-
component samples 176, output first-state sample spectra 178 of the different
multi-component
samples 176. In some embodiments, each of the first-state sample spectra 178
may be collected
and stored, for example, in a database. In some embodiments, each of the first-
state sample spectra
178 may be associated with a corresponding different multi-component sample
176 and may be
indicative of a plurality of different multi-component sample properties. In
some embodiments,
the first-state sample spectra 178, in combination with material data 179
associated with each of
the multi-component samples 176, may be used to output (e.g., develop) one or
more spectral
model(s) 180, which, in turn, may be used to calibrate the first spectroscopic
analyzer 172A with
the first analyzer controller 174A, resulting in an analyzer calibration 182.
The material data 179
may include any data related to one or more properties associated with one or
more of the
respective multi-component samples 176. The one or more spectral model(s) 180
may be
indicative of relationships (e.g., correlations) between a spectrum or spectra
of the first-state
sample spectra 178 and one or more properties associated with one or more of
respective multi-
component samples 176, and the relationships may be used to provide the
analyzer calibration 182.
In some embodiments, the one or more spectral model(s) 180 may represent a
univariate or
Date Recue/Date Received 2023-02-21
multivariate regression (e.g., a least-squares regression, a multiple linear
regression (MLR), a
partial least squares regression (PLS), a principal component regression
(PCR)), such as a
regression of material data (e.g., one or more properties of the multi-
component sample) against a
corresponding spectrum of the first-state sample spectra 178. In some
embodiments, the one or
more spectral model(s) 180 may represent topological modeling by use of
nearest neighbor
positioning to calculate properties, based on the material data (e.g., one or
more properties of the
multi-component sample) against a corresponding spectrum of the first-state
sample spectra 178,
as also will be understood by those skilled in the art. This may facilitate
prediction of one or more
properties of a material analyzed by the spectroscopic analyzers 172A through
172N, once
calibrated, based at least in part on a spectrum associated with the material.
[0100] In some embodiments, the plurality of different multi-component samples
176 may include
a relatively large number of samples. For example, in some embodiments, in
order to calibrate the
first spectroscopic analyzer 172A with the first analyzer controller 174A to a
desired level of
accuracy and/or reproducibility, it may be necessary to analyze hundreds or
thousands of multi-
component samples 176 that have corresponding material data 179. Due to the
relatively large
number of multi-component samples 176 used for calibration, the first-state
time period T1, which
may generally correspond to the time period during which the multi-component
samples 176 are
analyzed, may take a significant amount of time to complete. For example, in
some embodiments,
in order to calibrate the first spectroscopic analyzer 172A with the first
analyzer controller 174A
to a desired level of accuracy and/or reproducibility, due to the relatively
large number of samples
analyzed, the first-state time period T1 may take dozens of hours or longer to
complete.
[0101] Following calibration of the first spectroscopic analyzer 172A with the
first analyzer
controller 174A, the spectral responses of the first spectroscopic analyzer
172A with the first
56
Date Recue/Date Received 2023-02-21
analyzer controller 174A may be standardized, for example, by analyzing one or
more first-state
portfolio sample(s) 183 to output a standardized analyzer spectra portfolio
184 including one or
more first-state portfolio sample spectra 185. For example, the first
spectroscopic analyzer 172A
with the first analyzer controller 174A, when in the first state, may be used
to analyze one or more
first-state portfolio sample(s) 183 to output a first-state portfolio spectrum
185 for each of the one
or more first-state portfolio sample(s) 183. In some embodiments, the
respective first-state
portfolio sample spectrum 185 associated with a respective first-state
portfolio sample 183 may be
stored to develop the standardized analyzer spectra portfolio 184, which may
be used to reduce a
variance between a second-state portfolio sample spectrum (outputted during a
second state) and
a corresponding first-state portfolio sample spectrum 185 of the standardized
analyzer spectra
portfolio 184.
[0102] As shown in FIG. 4A, following calibration and/or standardization of
the first
spectroscopic analyzer 172A with the first analyzer controller 174A, the first
spectroscopic
analyzer 172A with the first analyzer controller 174A may be used to analyze
multi-component
materials to predict properties of the multi-component materials analyzed. For
example, in some
embodiments, the first spectroscopic analyzer 172A with the first analyzer
controller 174A may
be used as part of a manufacturing process, for example, as described herein
with respect to FIGS.
1, 2, and 3. For example, the first spectroscopic analyzer 172A with the first
analyzer controller
174A may be used to analyze multi-component materials, and the corresponding
material
properties predicted (or determined) from the analyses may be used to assist
with at least partial
control of the manufacturing process or processes.
[0103] For example, as shown in FIG. 4A, a manufacturing process may result in
generating
conditioned materials for analysis 186A (e.g., fluids, such as gases and/or
liquids) during the
57
Date Recue/Date Received 2023-02-21
manufacturing process, and multi-component materials associated with the
manufacturing process
may be diverted for analysis by the first spectroscopic analyzer 172A with the
first analyzer
controller 174A. In some embodiments, for example, as shown in FIG. 4A, the
multi-component
material may be conditioned via a sample conditioning assembly to output
conditioned material
for analysis 186A by the first spectroscopic analyzer 172A with the first
analyzer controller 174a,
for example, as described previously herein with respect to FIG. 3. In some
embodiments, the
material conditioning may include one or more of filtering particulates and/or
fluid contaminants
from the multi-component material, controlling the temperature of the multi-
component material
(e.g., reducing or increasing the temperature to be within a desired range of
temperatures), or
controlling the pressure of the multi-component material (e.g., reducing or
increasing the pressure
to be within a desired range of pressures). In some embodiments, the
spectroscopic analyzers 172
and/or the analyzer controllers 174 may analyze unconditioned materials and/or
semi-conditioned
materials to output predicted (or determined) material data for the materials
for use in example
processes.
[0104] Upon analysis of the multi-component materials, which may be a feed to
a processing unit
and/or an output from a processing unit, the first spectroscopic analyzer 172A
with the first
analyzer controller 174A, using the analyzer calibration 182, may output a
plurality of material
spectra 188A and, based at least in part on the material spectra 188A, predict
a plurality of material
properties associated with the multi-component materials. In some embodiments,
the material
spectra 188A and the associated predicted or determined material properties
may be stored in a
database as predicted (or determined) material data 190A. It is contemplated
that additional
material data associated with the multi-component materials analyzed may also
be included in the
database to supplement the predicted or determined material properties. For
example, the database
58
Date Recue/Date Received 2023-02-21
may define a library including material data including correlations between
the plurality of
material spectra and the plurality of different material properties of the
corresponding material.
[0105] In some embodiments, the analysis of the multi-component materials may
occur during a
first material time period T1, as shown in FIG. 4A. As shown in FIG. 42A, in
some embodiments,
the first analyzer controller 174A (and/or one or more of the plurality of
analyzer controllers 174B
through 174N, as explained herein) may also be configured to output one or
more output signals
192A indicative of the multi-component material properties. The output
signal(s) 192A may be
used to at least partially control a manufacturing process, for example, as
described with respect
to FIGS. 1, 2, and 3 (e.g., output signals 192A through 192N). Although the
output signals 192A
through 192N are shown as individually being communicated to the FCC process
controller(s) 24
(FIG. 4C) independently of one another, in some examples, two or more of the
output signals 192A
through 192N may be combined prior to being communicated to the FCC process
controller(s) 24.
For example, two or more (e.g., all) of the output signals 192A through 192N
may be received at
a single receiver, which in turn, communicates the two or more of the combined
signals to the FCC
process controller(s) 24. In some examples, at least some of the output
signal(s) 192A through
192N may be communicated to one or more output device(s) 214 (FIG. 4C), either
independently
of communication to the FCC process controller(s) 24 or via the FCC process
controller(s) 24, for
example, following receipt of the output signals 192A through 192N by the FCC
process
controller(s) 24. The output device(s) 214 may include display devices, such
as, for example, a
computer monitor and/or portable output devices, such as a laptop computer, a
smartphone, a tablet
computing device, etc., as will be understood by those skilled in the art.
Such communication
may be enabled by a communications link, such as a hard-wired and/or wireless
communications
59
Date Recue/Date Received 2023-02-21
link, for example, via one or more communications networks (e.g., the network
92 described
herein).
[0106] As referenced above, in some embodiments, the first analyzer controller
174A may be
configured to use the first-state-portfolio sample spectra 185 of the
standardized analyzer spectra
portfolio 184 to calibrate or recalibrate one or more of the plurality of
spectroscopic analyzers
172A through 172N with the respective analyzer controllers 174A through 174N.
For example,
as shown in FIG. 4A, such change(s) 194 to the plurality of spectroscopic
analyzers 172B through
172N that might necessitate recalibration may include, but are not limited to,
for example,
maintenance performed on the plurality of spectroscopic analyzers 172B through
172N,
replacement of one or more components of the plurality of spectroscopic
analyzers 172B through
172N, cleaning of one or more components of the plurality of spectroscopic
analyzers 172B
through 172N, re-orienting one or more components of the plurality of
spectroscopic analyzers
172B through 172N, a change in path length (e.g., relative to the path length
for prior calibration),
or preparing the plurality of spectroscopic analyzers 172B through 172N for
use, for example,
prior to a first use and/or calibration (or recalibration) of the plurality of
spectroscopic analyzers
172B through 172N specific to the materials to which they are intended to
analyze.
[0107] In some embodiments, using respective portfolio sample-based
correction(s) 200B through
200N (see FIG. 4B) based at least in part on the standardized analyzer spectra
portfolio 184 to
calibrate or recalibrate the plurality of spectroscopic analyzers 172B through
172N may result in
the plurality of spectroscopic analyzers 172B through 172N with the respective
analyzer
controllers 174B through 174N outputting analyzed material spectra and/or
predicting
corresponding material properties in a manner substantially consistent with a
plurality of material
properties of the material outputted by the first spectroscopic analyzer 172A
with the first analyzer
Date Recue/Date Received 2023-02-21
controller 174A in the first state, for example, in a state prior to the
change(s) 194 to the plurality
of spectroscopic analyzers 172B through 172N.
[0108] For example, as shown in FIG. 4A, in some embodiments, the plurality of
analyzer
controllers 174B through 174N may be configured to analyze, via the respective
spectroscopic
analyzers 172B through 172N, when in the second state, a selected plurality of
portfolio sample(s)
183 to output second-state portfolio sample spectra 198 for the selected
plurality of different
second-state portfolio sample(s) 196. In some embodiments, the portfolio
sample(s) 183 may be
the first-state portfolio sample(s) 183 and/or the second-state portfolio
sample(s) 196. In some
embodiments, each of the second-state portfolio sample spectra 196A through
196N may be
associated with a corresponding different portfolio sample 183. As shown in
FIG. 4A, in some
embodiments, the portfolio sample(s) 183 may include a number of samples
significantly lower
than the number of samples of the plurality of multi-component samples 176.
For example, in
some embodiments, in order to calibrate or recalibrate the plurality of
spectroscopic analyzers
172B through 172N with the respective analyzer controllers 174B through 174N
after the
change(s) 194 to achieve a desired level of accuracy and/or reproducibility,
for example, an
accuracy and/or reproducibility substantially equal to or better than the
level of accuracy and/or
reproducibility of the first spectroscopic analyzer 172A with the first
analyzer controller 174A, in
some embodiments, it may only be necessary to analyze as few as ten or fewer
of the portfolio
sample(s) 183, as explained in more detail herein.
[0109] As shown in FIG. 4A, in some embodiments, because it may be necessary
to only analyze
substantially fewer portfolio sample(s) 183 to achieve results substantially
consistent with the
results achieved prior to the change(s) 194, a second-state time period T2
during which the portfolio
sample(s) 183 or the portfolio sample(s) 196 are analyzed may be significantly
less than the first-
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Date Recue/Date Received 2023-02-21
state time period T1 during which the multi-component samples 176 are analyzed
for the output
(e.g., the development) of spectral model(s) 180 and analyzer calibration 182.
For example, as
noted above, in some embodiments, the first-state time period T1 may exceed
100 hours, as
compared with the second-state time period T2, which may be less than 20 hours
(e.g., less than 16
hours, less than 10 hours, less than 8 hours, less than 4 hours, or less than
2 hours) for each of the
plurality of spectroscopic analyzers 172B through 172N.
[0110] Thus, in some embodiments, the plurality of spectroscopic analyzers
172B through 172N
with the respective analyzer controllers 174B through 174N may be configured
to be calibrated or
recalibrated to achieve substantially the same accuracy and/or reproducibility
of analysis as the
first spectroscopic analyzer 172A with first analyzer controller 174A, while
using significantly
fewer samples to calibrate or recalibrate each of the plurality of
spectroscopic analyzers 172B
through 172N with the respective analyzer controllers 174B through 174N, as
compared to the
number of multi-component samples 176 used to calibrate or recalibrate the
first spectroscopic
analyzer 172A with the first analyzer controller 174A for the development of
spectral model(s)
180 and analyzer calibration 182, thus requiring significantly less time for
calibration or
recalibration. In some embodiments, the calibrated or recalibrated plurality
of spectroscopic
analyzers 172B through 172N and/or the plurality of analyzer controllers 174B
through 174N,
calibrated or recalibrated in such a manner, may be capable of generating
substantially the same
spectra following calibration or recalibration as outputted by the first
spectroscopic analyzer 172A
with the first analyzer controller 174A, which may result in improved accuracy
and/or
reproducibility by the first spectroscopic analyzer 172A and each of the
plurality of spectroscopic
analyzers 172B through 172N. Such accuracy and/or reproducibility may provide
the ability to
compare analysis results outputted by either the first spectroscopic analyzer
172A or the plurality
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Date Recue/Date Received 2023-02-21
of spectroscopic analyzers 172B through 172N, which may result in the first
spectroscopic
analyzer 172A and the plurality of spectroscopic analyzers 172B through 172N
being relatively
more useful, for example, when incorporated into a manufacturing process
involving the
processing of multi-component materials received from material sources, such
as shown in FIGS.
1 and 2, for example, a petroleum refining-related process, such as an FCC
process, a
pharmaceutical manufacturing process, or other processes involving the
processing of materials.
[0111] As shown in FIG. 4A, in some embodiments, each of the plurality of
analyzer controllers
174B through 174N also may be configured to compare one or more of the
respective second-state
portfolio sample spectra 198A through 198B from the portfolio samples to the
first-state portfolio
sample spectra 185. Based at least in part on the comparison, the plurality of
analyzer controllers
174B through 174N further may be configured to determine for one or more of
the respective
second-state portfolio sample spectra 198A through 198N, a variance 212 (e.g.,
respective
variances 212B through 212N) over a range of wavelengths, wavenumbers, and/or
frequencies
between the respective second-state portfolio sample spectra 189A through 198N
outputted by
each of the respective spectroscopic analyzers 172B through 172N and the first-
state portfolio
sample spectra 185 of the standardized analyzer spectra portfolio 184
outputted by the first
spectroscopic analyzer 172A. For example, in some embodiments, the plurality
of analyzer
controllers 174B through 174N may be configured to determine a difference in
magnitude between
each of the second-state portfolio sample spectra 198 and the first-state
portfolio sample spectra
185 for each of a plurality of wavelengths, wavenumbers, and/or frequencies
over one or more
ranges of wavelengths, wavenumbers, and/or frequencies, respectively.
[0112] In some embodiments, each of the plurality of analyzer controllers 174B
through 174N
may be configured to determine respective variances 212B through 212N by
determining a mean
63
Date Recue/Date Received 2023-02-21
average variance, one or more ratios of variances at respective individual
wavelengths, or a
combination thereof, for a plurality of wavelengths, wavenumbers, and/or
frequencies over a range
of wavelengths, wavenumbers, and/or frequencies, respectively. In some
embodiments, each of
the plurality of analyzer controllers 174B through 174N may be configured to
determine a
relationship for a plurality of wavelengths, wavenumbers, and/or frequencies
over the range of
wavelengths, wavenumbers, and/or frequencies, respectively, between the
respective second-state
portfolio sample spectra 198B through 198N and the first-state portfolio
sample spectra 185, and
the relationship may include one or more of a ratio, an addition, a
subtraction, a multiplication, a
division, one or more derivatives, or an equation.
[0113] As shown in FIG. 4A and 4B, in some embodiments, each of the plurality
of analyzer
controllers 174B through 174N still further may be configured to reduce the
respective variance
212B through 212N (FIG. 4B) between the respective second-state portfolio
sample spectra 198B
through 198N and the first-state portfolio sample spectra 185. For example,
each of the plurality
of analyzer controllers 174B through 174N may be configured to use respective
analyzer portfolio
sample-based correction(s) 200B through 200N based at least in part on the
previously outputted
standardized analyzer spectra portfolio 184 to reduce the respective variances
212B through 212N
between the respective second-state portfolio sample spectra 198B through 198N
and the first-
state portfolio sample spectra 185, so that each of the respective ones of the
plurality of
spectroscopic analyzers 172B through 172N and/or the respective ones of the
plurality of analyzer
controllers 174B through 174N is able to output, when in the second state
following the change(s)
194 (e.g., during initial set-up or after maintenance), a plurality of signals
indicative of a plurality
of material properties of an analyzed multi-component material, such that the
plurality of material
properties of the multi-component material are substantially consistent with a
plurality of material
64
Date Recue/Date Received 2023-02-21
properties of the multi-component material that were, or would be, outputted
by the first
spectroscopic analyzer 172A with the first analyzer controller 174A in the
first state. For example,
as shown in FIG. 4B, the plurality of spectroscopic analyzers 172B through
172N with the
respective analyzer controllers 174B through 174N may be configured to output
respective
portfolio sample-based correction(s) 200B through 200N, which reduce or
substantially eliminate
the respective variance 212B through 212N between the second-state portfolio
sample spectra
198B through 198N and the respective first-state portfolio sample spectra 185
(FIG. 4A), which,
in turn, may reduce or substantially eliminate the respective variance between
second-state multi-
component material spectra 202 and first-state multicomponent spectra 178, for
example, should
the same sample be analyzed in both the first and second states.
[0114] As shown in FIG. 4B, in some embodiments, following the change(s) 194
to the plurality
of spectroscopic analyzers 172B through 172N and/or the plurality of analyzer
controllers 174B
through 174N and the calibration or recalibration in the second state, the
plurality of spectroscopic
analyzers 172B through 172N may be used to analyze a plurality of multi-
component materials.
For example, as shown in FIG. 4B, a manufacturing process may include a
plurality of material
sources for respective multi-component materials (e.g., fluids, such as gases
and/or liquids) of the
manufacturing process (e.g., an FCC process and/or a related upstream process
and/or downstream
process), and multi-component materials associated with the manufacturing
process may be
diverted for analysis by one or more of the plurality of spectroscopic
analyzers 172B through 172N
with the respective analyzer controllers 174B through 174N. In some
embodiments, for example,
as shown in FIG. 4B, the multi-component materials may be conditioned via
material
conditioning (e.g., as described herein) to output conditioned materials for
analysis 204B through
204N by the respective spectroscopic analyzers 172B through 172N with the
respective analyzer
Date Recue/Date Received 2023-02-21
controllers 174B through 174N. In some embodiments, material conditioning may
include one or
more of filtering particulates and/or fluid contaminants from the multi-
component material,
controlling the temperature of the multi-component material (e.g., reducing or
increasing the
temperature to be within a desired range of temperatures), or controlling the
pressure of the multi-
component material (e.g., reducing or increasing the pressure to be within a
desired range of
pressures). In some embodiments, the manufacturing processes, the material
sources, the material
conditioning, and/or the conditioned materials for analysis 204B through 204N,
may substantially
correspond to the previously-discussed FCC process, material source(s),
material conditioning,
and/or the conditioned material for analysis (see, e.g., FIGS. 1-3).
[0115] In some embodiments, each of the plurality of spectroscopic analyzers
172B through 172N
with each of the respective analyzer controllers 174B through 174N may be
configured to analyze,
when in the second state, the multi-component materials received from the
respective material
sources and output a material spectrum corresponding to the respective multi-
component
materials, for example, as described previously herein with respect to FIGS. 1
and 2. As shown in
FIG. 4B, the plurality of spectroscopic analyzers 172B through 172N with the
respective analyzer
controllers 174B through 174N also may be configured to use the second through
Nth material
spectrum 202B through 202N to output respective corrected material spectra
206B through 206N,
based at least in part on the standardized analyzer spectra portfolio 184, the
respective portfolio
sample-based correction(s) 200B' through 200N', for each of the respective
multi-component
materials. In some embodiments, each of the corrected material spectra 206B
through 206N may
include one or more of an absorption-corrected spectrum, a transmittance-
corrected spectrum, a
transflectance-corrected spectrum, a reflectance-corrected spectrum, or an
intensity-corrected
spectrum, for example, and/or a mathematical treatment of the material
spectrum, such as, for
66
Date Recue/Date Received 2023-02-21
example, a second derivative of the material spectrum. For example, based at
least in part on the
respective corrected material spectra 206B through 206N, the respective
analyzer controllers 174B
through 174N may be configured to output a plurality of signals indicative of
a plurality of material
properties of the respective multi-component materials, and the plurality of
material properties
may be substantially consistent with (e.g., substantially the same as) a
plurality of material
properties of the multi-component materials that would be outputted by the
first spectroscopic
analyzer 172A with the first analyzer controller 174A. Thus, in some such
embodiments, the
respective corrected material spectra 206B through 206N may result in
standardized spectra, such
that the corrected material spectra 208B through 208N have been standardized
based at least in
part on the standardized analyzer spectra portfolio 184, so that the
respective corrected material
spectra 208B through 208N are the substantially the same material spectra that
would be outputted
by the first spectroscopic analyzer 172A with the first analyzer controller
174A.
[0116] In some embodiments, this may render it possible to directly compare
the results of analysis
by the plurality of spectroscopic analyzers 172B through 172N with the
respective analyzer
controllers 174B through 174N with results of analysis by the first
spectroscopic analyzer 172A
with the first analyzer controller 174A. In some embodiments, this may render
it possible to
directly compare the results of analysis by each of the plurality of
spectroscopic analyzers 172B
through 172N with each of the respective analyzer controllers 174B through
174N with one
another. In addition, as noted above, in some embodiments, using the portfolio
sample-based
correction(s) 200B through 200N to calibrate or recalibrate of the plurality
of spectroscopic
analyzers 172B through 172N with the respective analyzer controllers 174B
through 174N to
achieve the standardization may require the analysis of significantly fewer
samples (e.g., the
second-state portfolio samples 198) as compared to the original calibration of
the first
67
Date Recue/Date Received 2023-02-21
spectroscopic analyzer 172A with first analyzer controller 174A during the
first state. This may
also significantly reduce the time required to calibrate or recalibrate each
of the plurality of
spectroscopic analyzers 172B through 172N with each of the respective analyzer
controllers 174B
through 174N.
[0117] Upon analysis of the multi-component materials from the material
source(s), which may
be feed(s) to one or more processing units and/or an output(s) from one or
more processing units,
the plurality of spectroscopic analyzers 172B through 172N with the respective
analyzer
controllers 174B through 174N may establish a plurality of corrected material
spectra 208B
through 208N and, based at least in part on the corrected material spectra
208B through 208N,
predict a plurality of material properties associated with the multi-component
materials. In some
embodiments, the corrected material spectra 208B through 208N and the
associated predicted or
determined material properties may be stored in a database as respective
predicted (or determined)
material data 210B through 210N. It is contemplated that additional material
data associated with
the multi-component materials analyzed may also be included in the database to
supplement the
predicted or determined material properties. For example, the database may
define a library
including material data and/or including correlations between the plurality of
material spectra and
the plurality of different material properties of the corresponding materials.
[0118] As shown in FIG. 4C, in some embodiments, the plurality of analyzer
controllers 174B
through 174N may also be configured to output one or more output signals 192B
through 192N
indicative of the respective multi-component material properties. The output
signal(s) 192B
through 192N may be used to at least partially control a manufacturing
process. For example, as
shown in FIG. 4C, the output signal(s) 192B through 192N may be communicated
to one or more
FCC process controllers 24 (see also FIG. 1) configured, based at least in
part on the output
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Date Recue/Date Received 2023-02-21
signal(s) 192B through 192N, to output one or more processing unit control
signals 30 (see also
FIG. 1) for at least partially controlling operation of one or more material
processing unit(s) 34
configured to process a multi-component material. In some embodiments, the FCC
process
controller(s) 24 also may be configured to receive one or more processing
parameter(s) 32 and
based at least partially on the output signal(s) 192A through 192N and/or the
processing
parameter(s) 32, output the one or more processing unit control signal(s) 30
to at least partially
control operation of the one or more material processing unit(s) 34, for
example, as described
herein with respect to FIGS. 1 and 2. In some examples, at least some of the
output signal(s) 192A
through 192N may be communicated to one or more output devices 214, such as,
for example,
printers, display devices, such as a computer monitor and/or portable output
devices, such as a
laptop computer, a smartphone, a tablet computing device, a printer, etc., as
will be understood by
those skilled in the art. Such communication may be enabled by one or more
communications
links, such as a hard-wired and/or wireless communications link, for example,
via one or more
communication networks.
[0119] In some embodiments, as explained herein, using the portfolio sample-
based correction(s)
200B through 200N to calibrate or recalibrate the plurality of spectroscopic
analyzers 172B
through 172N may result in the plurality of spectroscopic analyzers 172B
through 172N with the
respective analyzer controllers 174B through 174N generating analyzed material
spectra and/or
predicting corresponding material properties in a manner substantially
consistent with a plurality
of material properties outputted by the first spectroscopic analyzer 172A with
the first analyzer
controller 174A.
[0120] Although not shown in FIGS. 4A and 4B, in some embodiments, the
plurality of analyzer
controllers 174B through 174N, based at least in part on the respective
portfolio sample-based
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Date Recue/Date Received 2023-02-21
correction(s) 200B through 200N, may be configured to output one or more gain
signals for
controlling one or more analyzer sources, analyzer detectors, and/or detector
responses, such that
the plurality of spectroscopic analyzers 172B through 172N with the respective
analyzer
controllers 174B through 174N, when analyzing a multi-component material,
output a corrected
material spectrum or spectra that are standardized according to the
standardized analyzer spectra
portfolio 184. Thus, in some embodiments, rather than generating a material
spectrum when
analyzing a multi-component material, and thereafter correcting the material
spectrum based at
least in part on the variance and the portfolio sample-based correction(s) 200
developed to reduce
the variance to output a corrected material spectrum, the plurality of
spectroscopic analyzers 172B
through 172N with the respective analyzer controllers 174B through 174N may be
configured to
output a respective corrected material spectrum 206B through 206N by adjusting
the detector gain,
for example, without prior generation of a material spectrum, which is
thereafter corrected. Rather,
in some embodiments, based at least in part on the respective variance(s) 212B
through 212N, the
plurality of spectroscopic analyzers 172B through 172N with the plurality of
analyzer controllers
174B through 174N may be configured to adjust the gain associated with the
respective analyzer
sources, detectors, and/or detector responses, so that the plurality of
spectroscopic analyzers 172B
through 172N with the respective analyzer controllers 174B through 174N output
corrected
material spectra 208B through 208N that reduces or substantially eliminates
the respective
variance(s) 212B through 212N.
[0121] FIG. 5A, FIG. 5B, FIG. 5C, FIG. 5D, and FIG. 5E are a block diagram of
an example
method 500 to enhance control of a fluid catalytic cracking (FCC) processing
assembly associated
with a refining operation, according to embodiments of the disclosure. The
example method 500
is illustrated as a collection of blocks in a logical flow graph, which
represent a sequence of
Date Recue/Date Received 2023-02-21
operations. In the context of software, where applicable, the blocks represent
computer-executable
instructions stored on one or more computer-readable storage media that, when
executed by one
or more processors, perform the recited operations. Generally, computer-
executable instructions
include routines, programs, objects, components, data structures, and the like
that perform
particular functions or implement particular data types. The order in which
the operations are
described is not intended to be construed as a limitation, and any number of
the described blocks
may be combined in any order and/or in parallel to implement the method.
[0122] FIG. 5A through FIG. 5E are a block diagram of the example method 500
to enhance
control of an FCC processing assembly associated with a refining operation,
according to
embodiments of the disclosure. At 502 (FIG. 5A), the example method 500 may
include supplying
hydrocarbon feedstock to an FCC processing assembly for FCC processing to
produce an FCC
effluent, for example, as described herein.
[0123] At 504, the example process 500 may include determining whether the
hydrocarbon
feedstock is within a target temperature range, a target pressure range,
and/or a target flow rate,
for example, as described herein.
[0124] If, at 504, it is determined that the temperature, pressure, or target
flow rate is not within
one or more of the target ranges, at 506, the example method 500 may include
adjusting the
temperature, the pressure, and/or the flow rate of the hydrocarbon feedstock
to be within the target
ranges and returning to 504 to repeat the determination.
[0125] If, at 504, it is determined that the temperature, pressure, or target
flow rate are within the
target ranges, at 508, the example method 500 may include conditioning, via a
sample conditioning
assembly, a sample of the hydrocarbon feedstock for analysis by a
spectroscopic analyzer, for
example, as described herein.
71
Date Recue/Date Received 2023-02-21
[0126] At 510, the example method 500 may include determining whether the
conditioned
hydrocarbon feedstock sample is within target parameters for analysis. This
may include
determining whether water, particulates, and/or other contaminates have been
removed from the
conditioned hydrocarbon feedstock sample, and/or whether the conditioned
sample is within a
desired predetermined temperature range for improving the accuracy of the
analysis by the
spectroscopic analyzer(s).
[0127] If, at 510, it is determined that the conditioned hydrocarbon feedstock
sample is not within
target parameters for analysis, the example method 500, at 512, may include
adjusting one or more
parameters associated with operation of the sample conditioning assembly, such
that the
conditioned hydrocarbon feedstock sample is within the target parameters and
returning to 510 to
repeat the determination.
[0128] If, at 510, it is determined that the conditioned hydrocarbon feedstock
sample is within
target parameters for analysis, the example method 500, at 514, may include
supplying the
conditioned hydrocarbon feedstock sample to the spectroscopic analyzer(s) for
analysis, for
example, as described herein.
[0129] The example method 500, at 516, may include analyzing, via the
spectroscopic analyzer(s),
the conditioned hydrocarbon feedstock sample to predict (or determine)
hydrocarbon feedstock
properties, for example, as described herein.
[0130] At 518 (FIG. 5B), the example method 500 may include determining
whether the
hydrocarbon feedstock properties are within desired ranges of property targets
for the hydrocarbon
feedstock.
72
Date Recue/Date Received 2023-02-21
[0131] If, at 518, it is determined that the hydrocarbon feedstock properties
are not within the
desired ranges of the property targets for the hydrocarbon feedstock, the
example method 500, at
520, may include altering the hydrocarbon feedstock toward the target
properties to be within the
desired ranges of property targets for the hydrocarbon feedstock and returning
to 518 to repeat the
determination.
[0132] If, at 518, it is determined that the hydrocarbon feedstock properties
are within the desired
ranges of the property targets for the hydrocarbon feedstock, the example
method 500, at 522, may
include supplying the hydrocarbon feedstock to a riser of the FCC processing
assembly, for
example, as described herein.
[0133] At 524, the example method 500 may include determining whether the
riser is operating
within a desired range of a predetermined target riser temperature.
[0134] If, at 524, it is determined that the riser is not operating within the
desired range of the
predetermined target riser temperature, the example method 500, at 526, may
include altering the
riser temperature toward the target riser temperature and returning to 524 to
repeat the
determination.
[0135] If, at 524, it is determined that the riser is operating within the
desired range of the
predetermined target riser temperature, the example method 500, at 528, may
include supplying
catalyst to the riser to provide a reaction mixture including the hydrocarbon
feedstock and catalyst,
for example, as described herein.
[0136] At 530 (FIG. 5C), the example method 500 may include determining
whether the FCC
reactor is operating within desired ranges of predetermined target FCC reactor
parameters.
73
Date Recue/Date Received 2023-02-21
[0137] If, at 530, it is determined that the FCC reactor is not operating
within the desired ranges
of the predetermined target FCC reactor parameters, the example method 500, at
532, may include
altering the FCC reactor operating parameters toward the predetermined target
FCC reactor
parameters and returning to 530 to repeat the determination.
[0138] If, at 530, it is determined that the FCC reactor is operating within
the desired ranges of
the predetermined target FCC reactor parameters, the example method 500, at
534, may include
supplying the reaction mixture to an FCC reactor to produce FCC effluent, for
example, as
described herein.
[0139] At 536, the example method 500 may include conditioning, via a sample
conditioning
assembly, a reaction mixture sample and/or an FCC effluent sample for analysis
by one or more
spectroscopic analyzers. In some embodiments, the one or more spectroscopic
analyzers may be
calibrated to generate standardized spectral responses, for example, as
described herein.
[0140] At 538, the example method 500 may include determining whether the
conditioned reaction
mixture sample and/or the FCC effluent sample is/are within desired ranges of
target parameters
for analysis. This may include determining whether water, particulates, and
other contaminates
have been removed from the conditioned reaction mixture sample and/or the FCC
effluent sample,
and/or whether the conditioned sample is within a predetermined temperature
range for improving
the accuracy of the analysis by the spectroscopic analyzer.
[0141] If, at 538, it is determined that the conditioned reaction mixture
sample and/or the FCC
effluent sample is/are not within the desired ranges of the target parameters
for analysis, the
example method 500, at 540, may include adjusting one or more parameters
associated with
operation of the sample conditioning assembly such that the conditioned
reaction mixture sample
74
Date Recue/Date Received 2023-02-21
and/or the FCC effluent sample is/are within the target parameters and
returning to 538 to repeat
the determination.
[0142] If, at 538, it is determined that the conditioned reaction mixture
sample and/or the FCC
effluent sample is/are within the desired ranges of the target parameters for
analysis, the example
method 500, at 542, may include supplying the conditioned reaction mixture
sample and/or the
FCC effluent sample to the one or more spectroscopic analyzers for analysis,
for example, as
described herein.
[0143] At 544 (FIG. 5D), the example method 500 may include analyzing, via the
one or more
spectroscopic analyzers, the conditioned reaction mixture sample and/or the
conditioned FCC
effluent sample to predict (or determine) the reaction mixture properties
and/or the FCC effluent
properties, for example, as described herein. In some embodiments, the one or
more spectroscopic
analyzers may be calibrated to generate standardized spectral responses, for
example, as described
herein.
[0144] At 546, the example method may include determining whether the reaction
mixture
properties and/or the FCC effluent properties is/are within desired ranges of
respective property
targets.
[0145] If, at 546, it is determined that the reaction mixture properties
and/or the FCC effluent
properties is/are not within the desired ranges of the respective property
targets, the example
method 500, at 548, may include altering one or more of the hydrocarbon
feedstock, the riser
operating parameters, or the FCC reactor operating parameters according to
differences between
the reaction mixture properties and/or the FCC effluent properties and the
property targets, and
returning to 546 to repeat the determination.
Date Recue/Date Received 2023-02-21
[0146] If, at 546, it is determined that the reaction mixture properties
and/or the FCC effluent
properties is/are within the desired ranges of the respective property
targets, the example method
500, at 550, may include supplying the FCC effluent to one or more downstream
processing units
to separate the FCC effluent into downstream products, for example, as
described herein.
[0147] At 552, the example method 500 may include conditioning, via a sample
conditioning
assembly, one or more downstream product samples for analysis by one or more
spectroscopic
analyzers, for example, as described herein.
[0148] At 554 (FIG. 5E), the example method 500 may include determining
whether the
conditioned one or more downstream product samples is/are within desired
ranges of target
parameters for analysis. This may include determining whether water,
particulates, and other
contaminates have been removed from the conditioned one or more downstream
product samples,
and/or whether the conditioned samples is/are within a desired predetermined
temperature range
for improving the accuracy of the analysis by the spectroscopic analyzer.
[0149] If, at 554, it is determined that the conditioned one or more
downstream product samples
is/are not within the desired ranges of the target parameters for analysis,
the example method 500,
at 556, may include adjusting one or more parameters associated with operation
of the sample
conditioning assembly such that the conditioned one or more downstream product
samples is/are
within the desired ranges of the target parameters, and returning to 554 to
repeat the determination.
[0150] If, at 554, it is determined that the conditioned one or more
downstream product samples
is/are within the desired ranges of the target parameters for analysis, the
example method 500, at
558, may include supplying the conditioned one or more downstream product
samples to the one
or more spectroscopic analyzers for analysis, for example, as described
herein.
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Date Recue/Date Received 2023-02-21
[0151] At 560, the example method 500 may include analyzing, via the one or
more spectroscopic
analyzers, the conditioned one or more downstream product samples to predict
the properties of
the one or more downstream products, for example, as described herein. In some
embodiments,
the one or more spectroscopic analyzers may be calibrated to generate
standardized spectral
responses, for example, as described herein.
[0152] At 562, the example method 500 may include determining whether the
properties of the
one or more downstream products are within desired ranges of property targets.
[0153] If, at 562, it is determined that the properties of the one or more
downstream products are
not within the desired ranges of the property targets, the example method 500,
at 564, may include
altering one or more of the hydrocarbon feedstock, the riser operating
parameters, the FCC reactor
operating parameters, or the downstream processing units operating parameters
according to
differences between the properties of the one or more downstream products and
the property
targets, for example, as described herein. Thereafter, at 566, the example
method may include
returning to 502 and continuing to alter the hydrocarbon feedstock and/or
operating parameters to
drive the FCC process toward target properties.
[0154] If, at 562, it is determined that the properties of the one or more
downstream products are
within the desired ranges of the property targets, the example method 500, at
566, may include
returning to 502 and continuing to monitor and/or control the FCC process
according to the method
500.
EXAMPLE 1
[0155] Different hydrocarbon feedstocks will result in different yields from
an FCC process. If
an FCC processing unit is operating against a constraint or constraints, the
FCC process may need
77
Date Recue/Date Received 2023-02-21
to adjust to avoid exceeding equipment limitations. Typical process parameters
or process
variables for an FCC process may include feed rate, reactor temperature, feed
preheat, and/or
pressure. Process responses from each of the process parameters or variables
may be non-linear.
The optimum set of conditions to increase process and/or economic efficiency
in view of unit
constraints may depending on, for example, feed quality. Table 1 below
provides example feed
properties, process conditions, equipment constraints, and product yields,
that may be adjusted to
increase or optimize process and/or economic efficiency, for four test
conditions: normal FCC
process operation, new feed with multivariable optimization, new feed with
only feed rate varied,
and new feed with only real time optimization.
Normal New Feed w/ New Feed w/ New Feed w/
Operation Multivariable Only Rate Only RTO
Optimization Varied Varied
Feed Properties
API 24.6 21.8 21.8 21.8
UOP K 11.69 11.77 11.77 11.77
Concarbon (%) 0.15 0.59 0.59 0.59
Nitrogen (ppm) 1150 162 162 162
Sulfur (%) 0.34 0.55 0.55 0.55
1-Ring Aromatics (%) 35 29 29 29
2-Ring Aromatics (%) 34 26 26 26
3-Ring Aromatics (%) 17 25 25 25
4-Ring Aromatics (%) 14 20 20 20
Process Conditions
Feed Rate (% capacity) 100 95.3 83.8 100
Reactor Temp. (F) 1010 992 1006 986
Reactor Pressure (psig) 34.7 33.6 32.3 34.2
Equipment Constraints
Wet Gas Compressor (%) 100 100 100 100
Main Air Blower (%) 100 90 84 94
Yields
Conversion (lv %) 77.55 74.33 76.83 73.59
TABLE 1
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Date Recue/Date Received 2023-02-21
[0156] The results in Table I show that the application of real time
optimization using
spectroscopic analyzers may facilitate the FCC process to automatically adjust
processing
conditions, for example, to maximize processing as feedstock quality changes.
Without
determining feedstock quality using spectroscopic analyzers and real time
optimization, the FCC
process may operate at a non-optimum condition until a model optimizer is run
and the results
implemented. In some embodiments, advanced process control and on-line
material analysis by
spectroscopic analyzers may be used to manipulate multiple FCC processing
variables (e.g., one
or more of the variables shown in Table I and/or any variables and/or
parameters described herein)
to push the FCC processing unit against unit operational constraints, for
example, to improve or
maximize economic and/or processing efficiency associated with the FCC
process. In some
embodiments, on-line real time optimization may be used to choose a set of
operating conditions
to improve or maximize economic and/or processing efficiency.
79
Date Recue/Date Received 2023-02-21
EXAMPLE 2
[0157] FIG. 6A is a table illustrating spectroscopic analysis data associated
with an example FCC
process including samples of hydrotreater charges and products, and FCC feeds
used to control
relative amounts of each hydrocarbon class shown in weight percent, according
to embodiments
of the disclosure. FIG. 6B is a table illustrating minimum and maximum amounts
for a calibration
set shown in weight percent for example hydrocarbon classes related to the
data shown in FIG.
6A, according to embodiments of the disclosure. Two hundred-fifty samples,
including
hydrotreater charges and products, and FCC feeds were used to create a PLS
model for predicting
weight percent for each hydrocarbon class. The samples were analyzed using an
on-line
spectroscopic analyzer for example, as described herein, according to some
embodiments. Wavelengths ranging from about 1140 nanometers to about 2300
nanometers,
and/or one or more bands within the range were chosen for each group, and a
results summary
appears in FIG. 6B. In some embodiments, wavelengths for near-infrared (NIR)
analysis may
range from about 780 nanometers to about 2500 nanometers, and/or one or more
wavelength bands
within the range may be analyzed; wavenumbers for Raman analysis may range
from about 200
wavenumbers (cm-1) to about 3700 wavenumbers (cm-1), and/or one or more
wavenumber bands
within the range may be analyzed; wavenumbers for mid-infrared (MIR) analysis
may range from
about 200 wavenumbers (cm-1) to about 4000 wavenumbers (cm-1), and/or one or
more
wavenumber bands within the range may be analyzed; and wavelengths for
combination NIR
analysis and MIR analysis may range from about 780 nanometers (about 12820
wavenumbers) to
about 25000 nanometers (about 400 wavenumbers), and/or one or more wavelength
bands within
the range may be analyzed.
Date Recue/Date Received 2023-02-21
EXAMPLE 3
[0158] Example 3 illustrates the effect of riser temperature on FCC processes.
One common type
of process variable study completed via the use of reaction effluent testing
is the impact of riser
outlet temperature on FCC reactor yields. This set of data may be used, for
example, to optimize
the performance of an FCC processing unit. Table 2 below includes results from
a series of riser
temperature tests. For this study, reactor effluent samples were collected at
three different riser
outlet temperatures, with the maximum riser temperature constrained by the
ability to handle gas
volumes in the FCC gas plant.
Effect of Riser Outlet Temperature on FCC Product Yields
Riser Outlet Temperature (F) +15 F Base -18 F
Unit Conversion: Volume % FF +1.4 Base -3.2
Gasoline Yield: Volume % -0.3 Base +0.2
Total C3 Plus C4 Yield: Volume % FF +1.3 Base -3.8
Ethane and Lighter Yield: Weight % FF +0.51 Base -0.63
Coke Yield: Weight % FF +0.17 Base -0.18
TABLE 2
EXAMPLE 4
[0159] Example 4 illustrates the effect of riser lift velocity on FCC product
yields. In order to
improve or optimize performance of an FCC processing unit, it may be important
to understand
the interaction of one or more (e.g., all) of the reaction process variables
on FCC product yields.
Reaction effluent testing was used to determine the effect of riser lift steam
rate on FCC processing
unit yields. In the test, the riser steam rate was increased by 165%, with
riser velocity increasing
from 10 feet per second (fps) to about 17 fps. Table 3 below shows the effects
of increasing the
riser steam rate injection while holding the feed rate constant.
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Effect of Riser Lift Steam Rate on FCC Product Yields
Riser Injection Steam Rate: PPH Base +165%
Catalyst Circulation Rate: TPM Base +4.5%
Unit Conversion: Volume % FF Base -0.3
Gasoline Yield: Volume % Base +1.3
Total C3 Plus C4 Yield: Volume % FF Base -1.6
Ethane and Lighter Yield: Weight % FF Base -0.2
Coke Yield: Weight % FF Base -0.07
TABLE 3
[0160] The heat requirement on the reactor side increases because of the need
to heat the steam
from the injection temperature to the riser outlet temperature. This results
in a need for increased
catalyst circulation to maintain the riser outlet temperature constant. The
increased catalyst-to-oil
ratio results in a greater degree of catalytic cracking relative to thermal
cracking. This is evident
because of the higher yield of catalytically cracked gasoline and the lower
yield of ethane and
lighter gas, which is generally the result of thermal cracking in the riser
and reactor. There is a
reduction in the feed residence time in the riser because of the increased
riser volumetric vapor
flow resulting from increased amount of riser lift steam. The increased
velocity creates a more
uniform distribution of catalyst near the wall of the riser where feed is
injected. This improves
feed contacting allowing for improved riser hydrodynamics. The FCC processing
unit used in this
test utilized a J-bend with modern feed nozzles.
EXAMPLE 5
[0161] Example 5 illustrates an example technique for on-line sampling of
reactor effluent
sometimes referred to as "reaction mix sampling." One potential advantage of
reaction mix
sampling testing is that the technique may be used for collection of reaction
mixture or vapor
stream samples from points in the reactor other than the overhead line or
outlet.
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[0162] When collecting effluent samples from the reactor overhead line to
downstream processing
units, such as a fractionator, a collection probe is open on the sampling end
because the reaction
effluent has already been disengaged from the catalyst via the riser
termination device and the
reactor cyclones. The reaction mix sampling probe may be configured such that
a sintered metal
filter may be installed on the collection end of the probe. This facilitates
collection of samples
from areas of high catalyst density, such as the FCC riser, the reactor,
and/or the stripper. In some
embodiments, sampling locations for collecting reaction mix sampling vapor
samples may include
one or more of the following: (i) the riser at multiple elevations above the
feed injection point to
monitor the extent of reaction as the oil/catalyst mixture flowed up the riser
and to determine the
impact of reaction contact time; (ii) the outlet of the riser to determine the
cracking yields before
the effects of any thermal cracking that would take place in the reactor
vessel; (iii) the outlet of the
riser termination device; (iv) substantially concurrently or simultaneously,
at the riser outlet and
the reactor effluent line to determine the degree of conversion and thermal
cracking that occurs in
the reactor vessel; (v) the riser at multiple points across the cross-section
or diameter to determine
the consistency of oil/catalyst distribution above the feed injectors; (vi)
the riser at the transition
from horizontal to vertical flow to determine the impact of the transition on
oil/catalyst
distribution; or the catalyst stripper bed and stripper transition into the
spent catalyst standpipe to
determine stripper vapor composition and determine stripping efficiency.
EXAMPLE 6
[0163] There may be interest in determining FCC catalyst stripping efficiency.
The reaction mix
sampling technique may be used to extract vapor samples from the stripper bed
and the transition
from the stripper into the spent catalyst standpipe. Table 4 below includes
the results from testing
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including reaction mix sampling of three strippers. As shown in in Table 4,
one of these strippers
operated very poorly, and one of them operated very efficiently.
FCC Stripper Outlet Reaction Mix Sampling Vapor Compositions
FCC Catalyst Stripper Unit Unit A Unit B Unit C
Total Water in Sample: wt% 35% 84% 91.5%
Total Hydrocarbon in Sample: wt% 65% 16% 8.5%
Gasoline in Sample: wt % 23.8% 0.08% 0.9%
650 F + Bottoms in Sample: wt % 6.1% 0.04% 1.8%
Ethane and Lighter in Sample: wt% 11.2% 14.8% 2.8%
TABLE 4
[0164] This data may thereafter be used in conjunction with an engineering
calculation to estimate
the amount of hydrocarbon flowing from the stripper to the catalyst
regenerator. The stripper
vapor composition may provide significant information as to processes
occurring in the stripper.
A first factor is the percentages of water and total hydrocarbon in the
recovered vapor stream. As
stripper efficiency increases, the percentage of water in the stripper vapor
sample will increase as
well. A second factor is the distribution of hydrocarbon in the reaction mix
sampling sample.
There are three potential sources of hydrocarbon in the FCC stripper: (i)
reaction effluent in
interstitial spaces between catalysts; (ii) reaction effluent in pores of the
catalyst; and (iii)
unreacted (and/or unvaporized) oil on the catalyst surface and in the catalyst
pores.
[0165] If the stripper outlet vapor contains more than a very small percentage
of gasoline on a
total sample weight basis, then it is likely that most or all of the reaction
effluent trapped with
catalyst does not disengage and flow upward into the reactor. For example, the
Unit A stripper
vapor sample contained 24 wt% gasoline. The Unit A stripper had no internals
of any type, and it
was clear that some significant portion of reaction effluent flowing to the
Unit A stripper was
reaching the regenerator. At the opposite end of the spectrum, the Unit C
stripper contained only
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Date Recue/Date Received 2023-02-21
0.9 wt% gasoline in the stripper vapor, which probably represents reaction
effluent diffused out of
the catalyst pores.
[0166] Another factor in reviewing stripper results is the content of ethane
and lighter gas in the
stripper vapor. The production of light gases in an FCC process, especially
methane and hydrogen,
is recognized as a by-product of thermal cracking. For these samples, the
weight percentage of
sample including ethane and lighter gas ranged from a low of 2.8 wt% to a high
of 14.8 wt%. The
production of light gases in the FCC stripper is believed to result from the
thermal decomposition
of heavy, unvaporized hydrocarbon molecules on the surface of the catalyst,
along with
condensation and polymerization of multi-ring aromatics. High levels of light
gas in the absence
of C5+ hydrocarbon in the FCC stripper effluent may indicate a problem with
the pore feed
atomization and vaporization, not a stripper mechanical problem. If an oil
molecule will not
vaporize in the presence of 1250 degrees F catalyst at the bottom of the
riser, it will not vaporize
in an FCC stripper at 960 degrees F to 980 degrees F.
EXAMPLE 7
[0167] An FCC process model, according to some embodiments, may be used to
determine
improved or optimum operating parameters to maximize processing and/or
economic efficiency,
and push the FCC processing unit to multiple constraints. Processing variables
and/or parameters
may include feed rate, reactor temperature, feed preheat, and catalyst
activity. The ability of any
model to estimate improved or optimum conditions may be dependent on its
ability to accurately
predict a true process response. Some models may be configured to allow a user
to adjust one or
more "tuning" factors, for example, to match the model response with
commercial data. FCC
processing unit technology may affect yield shifts associated with process
changes. A unit with a
poor stripper, such as Unit A above, may have a substantially different
response due to feed preheat
Date Recue/Date Received 2023-02-21
changers than a unit with a modern stripper, such as Unit C above. This may be
a result of the
effect of entrained hydrocarbon on delta coke with changes in catalyst
circulation. Another
example is reactor temperature. Modern rise termination devices have reduced
the post-riser
contact time and minimized secondary reactions changing the yield response to
process variables.
[0168] FIG. 7 shows an example of such an effect for a modern reactor system.
The default model
resulting in the data shown in FIG. 6 was "tuned" to an open riser termination
design that exhibited
gasoline over-cracking with increasing reactor temperature. As shown in FIG.
7, the modern
reactor system exhibited less over-cracking, and the model was tuned to
substantially match the
commercial data and provide greater confidence in improving or optimizing the
unit's economic
and/or processing efficiency.
EXAMPLE 8
[0169] FCC reaction effluent testing may facilitate an FCC revamp analysis
study. Reaction
effluent testing may be used as a method for developing FCC base operating
case data, for
example, by isolating reactor section yields. This may be performed when
modifications are
anticipated for the FCC product recovery section. Reaction effluent testing
may be suitable for
exploring conditions at various points in the FCC reaction section where
catalyst is present.
[0170] An example FCC revamp study was performed to determine the impact of
upgrading riser
termination to an available advanced design. Reaction effluent testing was
performed immediately
prior and immediately after completion of the revamp. Careful planning was
undertaken to ensure
that there were minimal differences in feed quality between the two test runs.
Results from the
two test runs are presented in Table 5 below. As shown in Table 5, the results
indicate that there
was significant yield benefit achieved with the revamp.
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Date Recue/Date Received 2023-02-21
FCC Revamp Audit Results
FCC Case Pre-Revamp Post-Revamp
Riser Outlet Temperature: F Base +2
Catalyst MAT Base +2
Unit Conversion: Volume % FF Base -0.4
Gasoline Yield: Volume % Base +3.8
Total C3 Plus C4 Yield: Volume % FF Base -3.0
Ethane and Lighter Yield: Weight % FF Base -0.13
Hydrogen Yield: Weight % FF Base -0.03
Coke Yield: Weight % FF Base -0.18
TABLE 5
[0171] Accurate yield determination and process variable response may be
important to FCC unit
optimization. Reaction mix sampling may provide an efficient method to define
such parameters
or variables. In some embodiments, the results may be used to tune an
analytical FCC process
model, update LP vectors, audit revamp or catalyst changes, and/or determine
optimum process
conditions to improve or maximize unit economic or processing efficiency
against multiple
constraints.
[0172] It should be appreciated that at least some subject matter presented
herein may be
implemented as a computer process, a computer-controlled apparatus, a
computing system, or an
article of manufacture, such as a computer-readable storage medium. While the
subject matter
described herein is presented in the general context of program modules that
execute on one or
more computing devices, those skilled in the art will recognize that other
implementations may be
performed in combination with other types of program modules. Generally,
program modules
include routines, programs, components, data structures, and other types of
structures that perform
particular tasks or implement particular abstract data types.
[0173] Those skilled in the art will also appreciate that aspects of the
subject matter described
herein may be practiced on or in conjunction with other computer system
configurations beyond
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Date Recue/Date Received 2023-02-21
those described herein, including multiprocessor systems, microprocessor-based
or programmable
consumer electronics, minicomputers, mainframe computers, handheld computers,
mobile
telephone devices, tablet computing devices, special-purposed hardware
devices, network
appliances, and the like.
[0174] FIG. 8 is a schematic diagram of an example FCC process controller 24
configured to at
least partially control an FCC processing assembly 10, according to
embodiments of the disclosure,
for example, as described herein. The FCC process controller 24 may include
one or more
processor(s) 800 configured to execute certain operational aspects associated
with implementing
certain systems and methods described herein. The processor(s) 800 may
communicate with a
memory 802. The processor(s) 800 may be implemented and operated using
appropriate hardware,
software, firmware, or combinations thereof. Software or firmware
implementations may include
computer-executable or machine-executable instructions written in any suitable
programming
language to perform the various functions described. In some examples,
instructions associated
with a function block language may be stored in the memory 802 and executed by
the
processor(s) 800.
[0175] The memory 802 may be used to store program instructions that are
loadable and
executable by the processor(s) 800, as well as to store data generated during
the execution of these
programs. Depending on the configuration and type of the FCC process
controller 24, the memory
802 may be volatile (such as random access memory (RAM)) and/or non-volatile
(such as read-
only memory (ROM), flash memory, etc.). In some examples, the memory devices
may include
additional removable storage 804 and/or non-removable storage 806 including,
but not limited to,
magnetic storage, optical disks, and/or tape storage. The disk drives and
their associated
computer-readable media may provide non-volatile storage of computer-readable
instructions,
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Date Recue/Date Received 2023-02-21
data structures, program modules, and other data for the devices. In some
implementations, the
memory 802 may include multiple different types of memory, such as static
random access
memory (SRAM), dynamic random access memory (DRAM), or ROM.
[0176] The memory 802, the removable storage 804, and the non-removable
storage 806 are all
examples of computer-readable storage media. For example, computer-readable
storage media
may include volatile and non-volatile, removable and non-removable media
implemented in any
method or technology for storage of information such as computer-readable
instructions, data
structures, program modules or other data. Additional types of computer
storage media that may
be present may include, but are not limited to, programmable random access
memory (PRAM),
SRAM, DRAM, RAM, ROM, electrically erasable programmable read-only memory
(EEPROM),
flash memory or other memory technology, compact disc read-only memory (CD-
ROM), digital
versatile discs (DVD) or other optical storage, magnetic cassettes, magnetic
tapes, magnetic disk
storage or other magnetic storage devices, or any other medium which may be
used to store the
desired information and which may be accessed by the devices. Combinations of
any of the above
should also be included within the scope of computer-readable media.
[0177] The FCC process controller 24 may also include one or more
communication connection(s)
808 that may facilitate a control device (not shown) to communicate with
devices or equipment
capable of communicating with the FCC process controller 24. The FCC process
controller 24
may also include a computer system (not shown). Connections may also be
established via various
data communication channels or ports, such as USB or COM ports to receive
cables connecting
the FCC process controller 24 to various other devices on a network. In some
examples, the FCC
process controller 24 may include Ethernet drivers that enable the FCC process
controller 24 to
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Date Recue/Date Received 2023-02-21
communicate with other devices on the network. According to various examples,
communication
connections 808 may be established via a wired and/or wireless connection on
the network.
[0178] The FCC process controller 24 may also include one or more input
devices 810, such as a
keyboard, mouse, pen, voice input device, gesture input device, and/or touch
input device. It may
further include one or more output devices 812, such as a display, printer,
and/or speakers. In
some examples, computer-readable communication media may include computer-
readable
instructions, program modules, or other data transmitted within a data signal,
such as a carrier
wave or other transmission. As used herein, however, computer-readable storage
media may not
include computer-readable communication media.
[0179] Turning to the contents of the memory 802, the memory 802 may include,
but is not limited
to, an operating system (OS) 814 and one or more application programs or
services for
implementing the features and embodiments disclosed herein. Such applications
or services may
include remote terminal units 816 for executing certain systems and methods
for controlling
operation of the FCC processing assembly 10 (e.g., semi- or fully-autonomously
controlling
operation of the FCC processing assembly 10), for example, upon receipt of one
or more control
signals generated by the FCC process controller 24. In some embodiments, one
or more remote
terminal unit(s) 816 may be located in the vicinity of the FCC processing
assembly 10. The remote
terminal unit(s) 816 may reside in the memory 802 or may be independent of the
FCC process
controller 24. In some examples, the remote terminal unit(s) 816 may be
implemented by software
that may be provided in configurable control block language and may be stored
in non-volatile
memory. When executed by the processor(s) 800, the remote terminal unit(s) 816
may implement
the various functionalities and features associated with the FCC process
controller 24 described
herein.
Date Recue/Date Received 2023-02-21
[0180] As desired, embodiments of the disclosure may include an FCC process
controller 24 with
more or fewer components than are illustrated in FIG. 8. Additionally, certain
components of the
example FCC process controller 24 shown in FIG. 8 may be combined in various
embodiments of
the disclosure. The FCC process controller 24 of FIG. 8 is provided by way of
example only.
[0181] References are made to block diagrams of systems, methods, apparatuses,
and computer
program products according to example embodiments. It will be understood that
at least some of
the blocks of the block diagrams, and combinations of blocks in the block
diagrams, may be
implemented at least partially by computer program instructions. These
computer program
instructions may be loaded onto a general purpose computer, special purpose
computer, special
purpose hardware-based computer, or other programmable data processing
apparatus to produce a
machine, such that the instructions which execute on the computer or other
programmable data
processing apparatus create means for implementing the functionality of at
least some of the blocks
of the block diagrams, or combinations of blocks in the block diagrams
discussed.
[0182] These computer program instructions may also be stored in a non-
transitory computer-
readable memory that can direct a computer or other programmable data
processing apparatus to
function in a particular manner, such that the instructions stored in the
computer-readable memory
produce an article of manufacture including instruction means that implement
the function
specified in the block or blocks. The computer program instructions may also
be loaded onto a
computer or other programmable data processing apparatus to cause a series of
operational steps
to be performed on the computer or other programmable apparatus to produce a
computer
implemented process such that the instructions that execute on the computer or
other
programmable apparatus provide task, acts, actions, or operations for
implementing the functions
specified in the block or blocks.
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Date Recue/Date Received 2023-02-21
[0183] One or more components of the systems and one or more elements of the
methods
described herein may be implemented through an application program running on
an operating
system of a computer. They may also be practiced with other computer system
configurations,
including hand-held devices, multiprocessor systems, microprocessor-based or
programmable
consumer electronics, mini-computers, mainframe computers, and the like.
[0184] Application programs that are components of the systems and methods
described herein
may include routines, programs, components, data structures, etc. that may
implement certain
abstract data types and perform certain tasks or actions. In a distributed
computing environment,
the application program (in whole or in part) may be located in local memory
or in other storage.
In addition, or alternatively, the application program (in whole or in part)
may be located in remote
memory or in storage to allow for circumstances where tasks can be performed
by remote
processing devices linked through a communications network.
[0185] Having now described some illustrative embodiments of the disclosure,
it should be
apparent to those skilled in the art that the foregoing is merely illustrative
and not limiting, having
been presented by way of example only. Numerous modifications and other
embodiments are
within the scope of one of ordinary skill in the art and are contemplated as
falling within the scope
of the disclosure. In particular, although many of the examples presented
herein involve specific
combinations of method acts or system elements, it should be understood that
those acts and those
elements may be combined in other ways to accomplish the same objectives.
Those skilled in the
art should appreciate that the parameters and configurations described herein
are exemplary and
that actual parameters and/or configurations will depend on the specific
application in which the
systems, methods, and/or aspects or techniques of the disclosure are used.
Those skilled in the art
should also recognize or be able to ascertain, using no more than routine
experimentation,
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Date Recue/Date Received 2023-02-21
equivalents to the specific embodiments of the disclosure. It is, therefore,
to be understood that
the embodiments described herein are presented by way of example only and
that, within the scope
of any appended claims and equivalents thereto, the disclosure may be
practiced other than as
specifically described.
[0186] Furthermore, the scope of the present disclosure shall be construed to
cover various
modifications, combinations, additions, alterations, etc., above and to the
above-described
embodiments, which shall be considered to be within the scope of this
disclosure. Accordingly,
various features and characteristics as discussed herein may be selectively
interchanged and
applied to other illustrated and non-illustrated embodiment, and numerous
variations,
modifications, and additions further may be made thereto without departing
from the spirit and
scope of the present disclosure as set forth in the appended claims.
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