Note: Descriptions are shown in the official language in which they were submitted.
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MOTOR EFFICIENCY AND DEGRADATION INTERPRETATION SYSTEM
RELATED APPLICATION
[0001] This application claims priority to and the benefit of a US
Provisional
Application having Serial No. 63/199071, filed 4 December 2020 and entitled
"Motor
Efficiency and Degradation Interpretation Application", which is incorporated
by
reference herein.
BACKGROUND
[0002] A reservoir can be a subsurface formation that can be
characterized at
least in part by its porosity and fluid permeability. As an example, a
reservoir may be
part of a basin such as a sedimentary basin. A basin can be a depression
(e.g.,
caused by plate tectonic activity, subsidence, etc.) in which sediments
accumulate.
As an example, where hydrocarbon source rocks occur in combination with
appropriate depth and duration of burial, a petroleum system may develop
within a
basin, which may form a reservoir that includes hydrocarbon fluids (e.g., oil,
gas,
etc.).
[0003] In oil and gas exploration, interpretation is a process that
involves
analysis of data to identify and locate various subsurface structures (e.g.,
horizons,
faults, geobodies, etc.) in a geologic environment. Various types of
structures (e.g.,
stratigraphic formations) may be indicative of hydrocarbon traps or flow
channels, as
may be associated with one or more reservoirs (e.g., fluid reservoirs). In the
field of
resource extraction, enhancements to interpretation can allow for construction
of a
more accurate model of a subsurface region, which, in turn, may improve
characterization of the subsurface region for purposes of resource extraction.
Characterization of one or more subsurface regions in a geologic environment
can
guide, for example, performance of one or more operations (e.g., field
operations,
etc.). As an example, a more accurate model of a subsurface region may make a
drilling operation more accurate as to a borehole's trajectory where the
borehole is to
have a trajectory that penetrates a reservoir, etc., where fluid may be
produced via
the borehole (e.g., as a completed well, etc.). As an example, one or more
workflows may be performed using one or more computational frameworks and/or
one or more pieces of equipment that include features for one or more of
analysis,
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acquisition, model building, control, etc., for exploration, interpretation,
drilling,
fracturing, production, etc.
SUMMARY
[0004] A method can include receiving real-time data during a drilling
operation performed by a drillstring that includes a mud motor and a bit
characterized by an expected performance profile; determining actual
performance
of the drillstring based at least in part on the real-time data; predicting
degraded
performance of the drillstring based at least in part on the real-time data
and a mud
motor degradation model; and updating the expected performance profile based
on a
comparison of the actual performance and the degraded performance. A system
can include a processor; memory accessible to the processor; processor-
executable
instructions stored in the memory and executable by the processor to instruct
the
system to: receive real-time data during a drilling operation performed by a
drillstring
that includes a mud motor and a bit characterized by an expected performance
profile; determine actual performance of the drillstring based at least in
part on the
real-time data; predict degraded performance of the drillstring based at least
in part
on the real-time data and a mud motor degradation model; and update the
expected
performance profile based on a comparison of the actual performance and the
degraded performance. One or more computer-readable media can include
computer-executable instructions executable by a system to instruct the system
to:
receive real-time data during a drilling operation performed by a drillstring
that
includes a mud motor and a bit characterized by an expected performance
profile;
determine actual performance of the drillstring based at least in part on the
real-time
data; predict degraded performance of the drillstring based at least in part
on the
real-time data and a mud motor degradation model; and update the expected
performance profile based on a comparison of the actual performance and the
degraded performance. Various other apparatuses, systems, methods, etc., are
also
disclosed.
[0005] This summary is provided to introduce a selection of concepts that
are
further described below in the detailed description. This summary is not
intended to
identify key or essential features of the claimed subject matter, nor is it
intended to
be used as an aid in limiting the scope of the claimed subject matter.
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BRIEF DESCRIPTION OF THE DRAWINGS
[0006] Features and advantages of the described implementations can be
more readily understood by reference to the following description taken in
conjunction with the accompanying drawings.
[0007] Fig. 1 illustrates an example system that includes various
framework
components associated with one or more geologic environments;
[0008] Fig. 2 illustrates examples of systems;
[0009] Fig. 3 illustrates an example of a system;
[0010] Fig. 4 illustrates an example of a system;
[0011] Fig. 5 illustrates an example of an environment and examples of
equipment;
[0012] Fig. 6 illustrates an example of a system;
[0013] Fig. 7 illustrates an example of a graphical user interface;
[0014] Fig. 8 illustrates examples of graphical user interfaces;
[0015] Fig. 9 illustrates an example of a graphical user interface;
[0016] Fig. 10 illustrates examples of graphical user interfaces;
[0017] Fig. 11 illustrates an example of a graphical user interface;
[0018] Fig. 12 illustrates examples of graphical user interfaces;
[0019] Fig. 13 illustrates an example of a system;
[0020] Fig. 14 illustrates an example of a system and workflow;
[0021] Fig. 15 illustrates examples of graphical user interfaces;
[0022] Fig. 16 illustrates an example of a system and workflow;
[0023] Fig. 17 illustrates an example of a graphical user interface;
[0024] Fig. 18 illustrates examples of graphical user interfaces;
[0025] Fig. 19 illustrates examples of graphical user interfaces;
[0026] Fig. 20 illustrates an example of a graphical user interface;
[0027] Fig. 21 illustrates an example of a graphical user interface;
[0028] Fig. 22 illustrates an example of a graphical user interface;
[0029] Fig. 23 illustrates an example of a graphical user interface;
[0030] Fig. 24 illustrates examples of graphical user interfaces;
[0031] Fig. 25 illustrates examples of graphical user interfaces;
[0032] Fig. 26 illustrates an example of a graphical user interface;
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[0033] Fig. 27 illustrates examples of graphical user interfaces;
[0034] Fig. 28 illustrates an example of a graphical user interface;
[0035] Fig. 29 illustrates an example of a graphical user interface;
[0036] Fig. 30 illustrates examples of graphical user interfaces;
[0037] Fig. 31 illustrates an example of a graphical user interface;
[0038] Fig. 32 illustrates examples of graphical user interfaces;
[0039] Fig. 33 illustrates an example of a graphical user interface;
[0040] Fig. 34 illustrates an example of a graphical user interface;
[0041] Fig. 35 illustrates an example of a graphical user interface;
[0042] Fig. 36 illustrates an example of a graphical user interface;
[0043] Fig. 37 illustrates an example of a graphical user interface;
[0044] Fig. 38 illustrates an example of a graphical user interface;
[0045] Fig. 39 illustrates an example of a graphical user interface;
[0046] Fig. 40 illustrates an example of a graphical user interface;
[0047] Fig. 41 illustrates an example of a graphical user interface;
[0048] Fig. 42 illustrates an example of a graphical user interface;
[0049] Fig. 43 illustrates an example of a graphical user interface;
[0050] Fig. 44 illustrates an example of a graphical user interface;
[0051] Fig. 45 illustrates an example of a graphical user interface;
[0052] Fig. 46 illustrates an example of a graphical user interface;
[0053] Fig. 47 illustrates examples of graphical user interfaces;
[0054] Fig. 48 illustrates examples of graphical user interfaces;
[0055] Fig. 49 illustrates an example of a graphical user interface;
[0056] Fig. 50 illustrates an example of a system and an example of a
graphical user interface;
[0057] Fig. 51 illustrates an example of a graphical user interface;
[0058] Fig. 52 illustrates examples of graphical user interfaces;
[0059] Fig. 53 illustrates an example of a method and an example of a
system;
[0060] Fig. 54 illustrates examples of computer and network equipment;
and
[0061] Fig. 55 illustrates example components of a system and a networked
system.
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DETAILED DESCRIPTION
[0062] This description is not to be taken in a limiting sense, but
rather is
made merely for the purpose of describing the general principles of the
implementations. The scope of the described implementations should be
ascertained with reference to the issued claims.
[0063] Fig. 1 shows an example of a system 100 that includes a workspace
framework 110 that can provide for instantiation of, rendering of,
interactions with,
etc., a graphical user interface (GUI) 120. In the example of Fig. 1, the GUI
120 can
include graphical controls for computational frameworks (e.g., applications)
121,
projects 122, visualization 123, one or more other features 124, data access
125,
and data storage 126.
[0064] In the example of Fig. 1, the workspace framework 110 may be
tailored
to a particular geologic environment such as an example geologic environment
150.
For example, the geologic environment 150 may include layers (e.g.,
stratification)
that include a reservoir 151 and that may be intersected by a fault 153. As an
example, the geologic environment 150 may be outfitted with a variety of
sensors,
detectors, actuators, etc. For example, equipment 152 may include
communication
circuitry to receive and to transmit information with respect to one or more
networks
155. Such information may include information associated with downhole
equipment
154, which may be equipment to acquire information, to assist with resource
recovery, etc. Other equipment 156 may be located remote from a wells ite and
include sensing, detecting, emitting or other circuitry. Such equipment may
include
storage and communication circuitry to store and to communicate data,
instructions,
etc. As an example, one or more satellites may be provided for purposes of
communications, data acquisition, etc. For example, Fig. 1 shows a satellite
in
communication with the network 155 that may be configured for communications,
noting that the satellite may additionally or alternatively include circuitry
for imagery
(e.g., spatial, spectral, temporal, radiometric, etc.).
[0065] Fig. 1 also shows the geologic environment 150 as optionally
including
equipment 157 and 158 associated with a well that includes a substantially
horizontal
portion that may intersect with one or more fractures 159. For example,
consider a
well in a shale formation that may include natural fractures, artificial
fractures (e.g.,
hydraulic fractures) or a combination of natural and artificial fractures. As
an
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example, a well may be drilled for a reservoir that is laterally extensive. In
such an
example, lateral variations in properties, stresses, etc. may exist where an
assessment of such variations may assist with planning, operations, etc. to
develop
a laterally extensive reservoir (e.g., via fracturing, injecting, extracting,
etc.). As an
example, the equipment 157 and/or 158 may include components, a system,
systems, etc. for fracturing, seismic sensing, analysis of seismic data,
assessment of
one or more fractures, etc.
[0066] In the example of Fig. 1, the GUI 120 shows some examples of
computational frameworks, including the DRILLPLAN, PETREL, TECHLOG,
PETROMOD, ECLIPSE, PIPESIM, and INTERSECT frameworks (Schlumberger
Limited, Houston, Texas).
[0067] The DRILLPLAN framework provides for digital well construction
planning and includes features for automation of repetitive tasks and
validation
workflows, enabling improved quality drilling programs (e.g., digital drilling
plans,
etc.) to be produced quickly with assured coherency.
[0068] The PETREL framework can be part of the DELFI cognitive E&P
environment (Schlumberger Limited, Houston, Texas) for utilization in
geosciences
and geoengineering, for example, to analyze subsurface data from exploration
to
production of fluid from a reservoir.
[0069] The TECHLOG framework can handle and process field and laboratory
data for a variety of geologic environments (e.g., deepwater exploration,
shale, etc.).
The TECHLOG framework can structure wellbore data for analyses, planning, etc.
[0070] The PETROMOD framework provides petroleum systems modeling
capabilities that can combine one or more of seismic, well, and geological
information to model the evolution of a sedimentary basin. The PETROMOD
framework can predict if, and how, a reservoir has been charged with
hydrocarbons,
including the source and timing of hydrocarbon generation, migration routes,
quantities, and hydrocarbon type in the subsurface or at surface conditions.
[0071] The ECLIPSE framework provides a reservoir simulator (e.g., as a
computational framework) with numerical solutions for fast and accurate
prediction of
dynamic behavior for various types of reservoirs and development schemes.
[0072] The INTERSECT framework provides a high-resolution reservoir
simulator for simulation of detailed geological features and quantification of
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uncertainties, for example, by creating accurate production scenarios and,
with the
integration of precise models of the surface facilities and field operations,
the
INTERSECT framework can produce reliable results, which may be continuously
updated by real-time data exchanges (e.g., from one or more types of data
acquisition equipment in the field that can acquire data during one or more
types of
field operations, etc.). The INTERSECT framework can provide completion
configurations for complex wells where such configurations can be built in the
field,
can provide detailed chemical-enhanced-oil-recovery (EOR) formulations where
such formulations can be implemented in the field, can analyze application of
steam
injection and other thermal EOR techniques for implementation in the field,
advanced
production controls in terms of reservoir coupling and flexible field
management, and
flexibility to script customized solutions for improved modeling and field
management
control. The INTERSECT framework, as with the other example frameworks, may
be utilized as part of the DELFI cognitive E&P environment, for example, for
rapid
simulation of multiple concurrent cases. For example, a workflow may utilize
one or
more of the DELFI on demand reservoir simulation features.
[0073] The aforementioned DELFI environment provides various features for
workflows as to subsurface analysis, planning, construction and production,
for
example, as illustrated in the workspace framework 110. Such an environment
may
be referred to as a process operations environment that can include a variety
of
frameworks (e.g., applications, etc.). As shown in Fig. 1, outputs from the
workspace framework 110 can be utilized for directing, controlling, etc., one
or more
processes in the geologic environment 150 and, feedback 160, can be received
via
one or more interfaces in one or more forms (e.g., acquired data as to
operational
conditions, equipment conditions, environment conditions, etc.).
[0074] As an example, a workflow may progress to a geology and geophysics
("G&G") service provider, which may generate a well trajectory, which may
involve
execution of one or more G&G software packages. Examples of such software
packages include the PETREL framework. As an example, a system or systems
may utilize a framework such as the DELFI framework (Schlumberger Limited,
Houston, Texas). Such a framework may operatively couple various other
frameworks to provide for a multi-framework workspace. As an example, the GUI
120 of Fig. 1 may be a GUI of the DELFI framework.
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[0075] In the example of Fig. 1, the visualization features 123 may be
implemented via the workspace framework 110, for example, to perform tasks as
associated with one or more of subsurface regions, planning operations,
constructing
wells and/or surface fluid networks, and producing from a reservoir.
[0076] As an example, a visualization process can implement one or more
of
various features that can be suitable for one or more web applications. For
example,
a template may involve use of the JAVASCRIPT object notation format (JSON)
and/or one or more other languages/formats. As an example, a framework may
include one or more converters. For example, consider a JSON to PYTHON
converter and/or a PYTHON to JSON converter. Such an approach can provide for
compatibility of devices, frameworks, etc., with respect to one or more sets
of
instructions.
[0077] As an example, visualization features can provide for
visualization of
various earth models, properties, etc., in one or more dimensions. As an
example,
visualization features can provide for rendering of information in multiple
dimensions,
which may optionally include multiple resolution rendering. In such an
example,
information being rendered may be associated with one or more frameworks
and/or
one or more data stores. As an example, visualization features may include one
or
more control features for control of equipment, which can include, for
example, field
equipment that can perform one or more field operations. As an example, a
workflow may utilize one or more frameworks to generate information that can
be
utilized to control one or more types of field equipment (e.g., drilling
equipment,
wireline equipment, fracturing equipment, etc.).
[0078] As to a reservoir model that may be suitable for utilization by a
simulator, consider acquisition of seismic data as acquired via reflection
seismology,
which finds use in geophysics, for example, to estimate properties of
subsurface
formations. As an example, reflection seismology may provide seismic data
representing waves of elastic energy (e.g., as transmitted by P-waves and S-
waves,
in a frequency range of approximately 1 Hz to approximately 100 Hz). Seismic
data
may be processed and interpreted, for example, to understand better
composition,
fluid content, extent and geometry of subsurface rocks. Such interpretation
results
can be utilized to plan, simulate, perform, etc., one or more operations for
production
of fluid from a reservoir (e.g., reservoir rock, etc.).
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[0079] Field acquisition equipment may be utilized to acquire seismic
data,
which may be in the form of traces where a trace can include values organized
with
respect to time and/or depth (e.g., consider 1D, 2D, 3D or 4D seismic data).
For
example, consider acquisition equipment that acquires digital samples at a
rate of
one sample per approximately 4 ms. Given a speed of sound in a medium or
media,
a sample rate may be converted to an approximate distance. For example, the
speed of sound in rock may be on the order of around 5 km per second. Thus, a
sample time spacing of approximately 4 ms would correspond to a sample "depth"
spacing of about 10 meters (e.g., assuming a path length from source to
boundary
and boundary to sensor). As an example, a trace may be about 4 seconds in
duration; thus, for a sampling rate of one sample at about 4 ms intervals,
such a
trace would include about 1000 samples where latter acquired samples
correspond
to deeper reflection boundaries. If the 4 second trace duration of the
foregoing
example is divided by two (e.g., to account for reflection), for a vertically
aligned
source and sensor, a deepest boundary depth may be estimated to be about 10 km
(e.g., assuming a speed of sound of about 5 km per second).
[0080] As an example, a model may be a simulated version of a geologic
environment. As an example, a simulator may include features for simulating
physical phenomena in a geologic environment based at least in part on a model
or
models. A simulator, such as a reservoir simulator, can simulate fluid flow in
a
geologic environment based at least in part on a model that can be generated
via a
framework that receives seismic data. A simulator can be a computerized system
(e.g., a computing system) that can execute instructions using one or more
processors to solve a system of equations that describe physical phenomena
subject
to various constraints. In such an example, the system of equations may be
spatially
defined (e.g., numerically discretized) according to a spatial model that that
includes
layers of rock, geobodies, etc., that have corresponding positions that can be
based
on interpretation of seismic and/or other data. A spatial model may be a cell-
based
model where cells are defined by a grid (e.g., a mesh). A cell in a cell-based
model
can represent a physical area or volume in a geologic environment where the
cell
can be assigned physical properties (e.g., permeability, fluid properties,
etc.) that
may be germane to one or more physical phenomena (e.g., fluid volume, fluid
flow,
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pressure, etc.). A reservoir simulation model can be a spatial model that may
be
cell-based.
[0081] A simulator can be utilized to simulate the exploitation of a real
reservoir, for example, to examine different productions scenarios to find an
optimal
one before production or further production occurs. A reservoir simulator does
not
provide an exact replica of flow in and production from a reservoir at least
in part
because the description of the reservoir and the boundary conditions for the
equations for flow in a porous rock are generally known with an amount of
uncertainty. Certain types of physical phenomena occur at a spatial scale that
can
be relatively small compared to size of a field. A balance can be struck
between
model scale and computational resources that results in model cell sizes being
of the
order of meters; rather than a lesser size (e.g., a level of detail of pores).
A modeling
and simulation workflow for multiphase flow in porous media (e.g., reservoir
rock,
etc.) can include generalizing real micro-scale data from macro scale
observations
(e.g., seismic data and well data) and upscaling to a manageable scale and
problem
size. Uncertainties can exist in input data and solution procedure such that
simulation results too are to some extent uncertain. A process known as
history
matching can involve comparing simulation results to actual field data
acquired
during production of fluid from a field. Information gleaned from history
matching,
can provide for adjustments to a model, data, etc., which can help to increase
accuracy of simulation.
[0082] As an example, a simulator may utilize various types of
constructs,
which may be referred to as entities. Entities may include earth entities or
geological
objects such as wells, surfaces, reservoirs, etc. Entities can include virtual
representations of actual physical entities that may be reconstructed for
purposes of
simulation. Entities may include entities based on data acquired via sensing,
observation, etc. (e.g., consider entities based at least in part on seismic
data and/or
other information). As an example, an entity may be characterized by one or
more
properties (e.g., a geometrical pillar grid entity of an earth model may be
characterized by a porosity property, etc.). Such properties may represent one
or
more measurements (e.g., acquired data), calculations, etc.
[0083] As an example, a simulator may utilize an object-based software
framework, which may include entities based on pre-defined classes to
facilitate
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modeling and simulation. As an example, an object class can encapsulate
reusable
code and associated data structures. Object classes can be used to instantiate
object instances for use by a program, script, etc. For example, borehole
classes
may define objects for representing boreholes based on well data. A model of a
basin, a reservoir, etc. may include one or more boreholes where a borehole
may
be, for example, for measurements, injection, production, etc. As an example,
a
borehole may be a wellbore of a well, which may be a completed well (e.g., for
production of a resource from a reservoir, for injection of material, etc.).
[0084] While several simulators are illustrated in the example of Fig. 1,
one or
more other simulators may be utilized, additionally or alternatively. For
example,
consider the VISAGE geomechanics simulator (Schlumberger Limited, Houston
Texas) or the PIPESIM network simulator (Schlumberger Limited, Houston Texas),
etc. The VISAGE simulator includes finite element numerical solvers that may
provide simulation results such as, for example, results as to compaction and
subsidence of a geologic environment, well and completion integrity in a
geologic
environment, cap-rock and fault-seal integrity in a geologic environment,
fracture
behavior in a geologic environment, thermal recovery in a geologic
environment, CO2
disposal, etc. The PIPESIM simulator includes solvers that may provide
simulation
results such as, for example, multiphase flow results (e.g., from a reservoir
to a
wellhead and beyond, etc.), flowline and surface facility performance, etc.
The
PIPESIM simulator may be integrated, for example, with the AVOCET production
operations framework (Schlumberger Limited, Houston Texas). As an example, a
reservoir or reservoirs may be simulated with respect to one or more enhanced
recovery techniques (e.g., consider a thermal process such as steam-assisted
gravity drainage (SAGD), etc.). As an example, the PIPESIM simulator may be an
optimizer that can optimize one or more operational scenarios at least in part
via
simulation of physical phenomena. The MANGROVE simulator (Schlumberger
Limited, Houston, Texas) provides for optimization of stimulation design
(e.g.,
stimulation treatment operations such as hydraulic fracturing) in a reservoir-
centric
environment. The MANGROVE framework can combine scientific and experimental
work to predict geomechanical propagation of hydraulic fractures, reactivation
of
natural fractures, etc., along with production forecasts within 3D reservoir
models
(e.g., production from a drainage area of a reservoir where fluid moves via
one or
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more types of fractures to a well and/or from a well). The MANGROVE framework
can provide results pertaining to heterogeneous interactions between hydraulic
and
natural fracture networks, which may assist with optimization of the number
and
location of fracture treatment stages (e.g., stimulation treatment(s)), for
example, to
increased perforation efficiency and recovery.
[0085] The PETREL framework provides components that allow for
optimization of exploration and development operations. The PETREL framework
includes seismic to simulation software components that can output information
for
use in increasing reservoir performance, for example, by improving asset team
productivity. Through use of such a framework, various professionals (e.g.,
geophysicists, geologists, and reservoir engineers) can develop collaborative
workflows and integrate operations to streamline processes (e.g., with respect
to one
or more geologic environments, etc.). Such a framework may be considered an
application (e.g., executable using one or more devices) and may be considered
a
data-driven application (e.g., where data is input for purposes of modeling,
simulating, etc.).
[0086] As mentioned, a framework may be implemented within or in a manner
operatively coupled to the DELFI cognitive exploration and production (E&P)
environment (Schlumberger, Houston, Texas), which is a secure, cognitive,
cloud-
based collaborative environment that integrates data and workflows with
digital
technologies, such as artificial intelligence and machine learning. As an
example,
such an environment can provide for operations that involve one or more
frameworks. The DELFI environment may be referred to as the DELFI framework,
which may be a framework of frameworks. As an example, the DELFI framework
can include various other frameworks, which can include, for example, one or
more
types of models (e.g., simulation models, etc.).
[0087] As an example, data can include geochemical data. For example,
consider data acquired using X-ray fluorescence (XRF) technology, Fourier
transform infrared spectroscopy (FTIR) technology and/or wireline geochemical
technology.
[0088] As an example, one or more probes may be deployed in a bore via a
wireline or wirelines. As an example, a probe may emit energy and receive
energy
where such energy may be analyzed to help determine mineral composition of
rock
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surrounding a bore. As an example, nuclear magnetic resonance may be
implemented (e.g., via a wireline, downhole NMR probe, etc.), for example, to
acquire data as to nuclear magnetic properties of elements in a formation
(e.g.,
hydrogen, carbon, phosphorous, etc.).
[0089] As an example, lithology scanning technology may be employed to
acquire and analyze data. For example, consider the LITHO SCANNER technology
marketed by Schlumberger Limited (Houston, Texas). As an example, a LITHO
SCANNER tool may be a gamma ray spectroscopy tool.
[0090] As an example, a tool may be positioned to acquire information in
a
portion of a borehole. Analysis of such information may reveal vugs,
dissolution
planes (e.g., dissolution along bedding planes), stress-related features, dip
events,
etc. As an example, a tool may acquire information that may help to
characterize a
fractured reservoir, optionally where fractures may be natural and/or
artificial (e.g.,
hydraulic fractures). Such information may assist with completions,
stimulation
treatment, etc. As an example, information acquired by a tool may be analyzed
using a framework such as the aforementioned TECH LOG framework
(Schlumberger Limited, Houston, Texas).
[0091] As an example, a workflow may utilize one or more types of data
for
one or more processes (e.g., stratigraphic modeling, basin modeling,
completion
designs, drilling, production, injection, etc.). As an example, one or more
tools may
provide data that can be used in a workflow or workflows that may implement
one or
more frameworks (e.g., PETREL, TECHLOG, PETROMOD, ECLIPSE, etc.).
[0092] Fig. 2 shows an example of a geologic environment 210 that
includes
reservoirs 211-1 and 211-2, which may be faulted by faults 212-1 and 212-2, an
example of a network of equipment 230, an enlarged view of a portion of the
network
of equipment 230, referred to as network 240, and an example of a system 250.
Fig.
2 shows some examples of offshore equipment 214 for oil and gas operations
related to the reservoir 211-2 and onshore equipment 216 for oil and gas
operations
related to the reservoir 211-1.
[0093] In the example of Fig. 2, the various equipment 214 and 216 can
include drilling equipment, wireline equipment, production equipment, etc. For
example, consider the equipment 214 as including a drilling rig that can drill
into a
formation to reach a reservoir target where a well can be completed for
production of
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hydrocarbons. In such an example, one or more features of the system 100 of
Fig. 1
may be utilized. For example, consider utilizing a drilling or well plan
framework, a
drilling execution framework, etc., to plan, execute, etc., one or more
drilling
operations.
[0094] In Fig. 2, the network 240 can be an example of a relatively small
production system network. As shown, the network 240 forms somewhat of a tree
like structure where flowlines represent branches (e.g., segments) and
junctions
represent nodes. As shown in Fig. 2, the network 240 provides for
transportation of
oil and gas fluids from well locations along flowlines interconnected at
junctions with
final delivery at a central processing facility.
[0095] In the example of Fig. 2, various portions of the network 240 may
include conduit. For example, consider a perspective view of a geologic
environment that includes two conduits which may be a conduit to Mani and a
conduit to Man3 in the network 240.
[0096] As shown in Fig. 2, the example system 250 includes one or more
information storage devices 252, one or more computers 254, one or more
networks
260 and instructions 270 (e.g., organized as one or more sets of
instructions). As to
the one or more computers 254, each computer may include one or more
processors
(e.g., or processing cores) 256 and memory 258 for storing the instructions
270 (e.g.,
one or more sets of instructions), for example, executable by at least one of
the one
or more processors. As an example, a computer may include one or more network
interfaces (e.g., wired or wireless), one or more graphics cards, a display
interface
(e.g., wired or wireless), etc. As an example, imagery such as surface imagery
(e.g.,
satellite, geological, geophysical, etc.) may be stored, processed,
communicated,
etc. As an example, data may include SAR data, GPS data, etc. and may be
stored,
for example, in one or more of the storage devices 252. As an example,
information
that may be stored in one or more of the storage devices 252 may include
information about equipment, location of equipment, orientation of equipment,
fluid
characteristics, etc.
[0097] As an example, the instructions 270 can include instructions
(e.g.,
stored in the memory 258) executable by at least one of the one or more
processors
256 to instruct the system 250 to perform various actions. As an example, the
system 250 may be configured such that the instructions 270 provide for
establishing
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a framework, for example, that can perform network modeling (see, e.g., the
PIPESIM framework of the example of Fig. 1, etc.). As an example, one or more
methods, techniques, etc. may be performed using one or more sets of
instructions,
which may be, for example, the instructions 270 of Fig. 2.
[0098] Fig. 3 shows an example of a wellsite system 300 (e.g., at a
wellsite
that may be onshore or offshore). As shown, the wellsite system 300 can
include a
mud tank 301 for holding mud and other material (e.g., where mud can be a
drilling
fluid), a suction line 303 that serves as an inlet to a mud pump 304 for
pumping mud
from the mud tank 301 such that mud flows to a vibrating hose 306, a drawworks
307 for winching drill line or drill lines 312, a standpipe 308 that receives
mud from
the vibrating hose 306, a kelly hose 309 that receives mud from the standpipe
308, a
gooseneck or goosenecks 310, a traveling block 311, a crown block 313 for
carrying
the traveling block 311 via the drill line or drill lines 312, a derrick 314,
a kelly 318 or
a top drive 340, a kelly drive bushing 319, a rotary table 320, a drill floor
321, a bell
nipple 322, one or more blowout preventors (B0Ps) 323, a drillstring 325, a
drill bit
326, a casing head 327 and a flow pipe 328 that carries mud and other material
to,
for example, the mud tank 301.
[0099] In the example system of Fig. 3, a borehole 332 is formed in
subsurface formations 330 by rotary drilling; noting that various example
embodiments may also use one or more directional drilling techniques,
equipment,
etc.
[00100] As shown in the example of Fig. 3, the drillstring 325 is
suspended
within the borehole 332 and has a drillstring assembly 350 that includes the
drill bit
326 at its lower end. As an example, the drillstring assembly 350 may be a
bottom
hole assembly (BHA).
[00101] The wellsite system 300 can provide for operation of the
drillstring 325
and other operations. As shown, the wellsite system 300 includes the traveling
block
311 and the derrick 314 positioned over the borehole 332. As mentioned, the
wellsite system 300 can include the rotary table 320 where the drillstring 325
pass
through an opening in the rotary table 320.
[00102] As shown in the example of Fig. 3, the wellsite system 300 can
include
the kelly 318 and associated components, etc., or the top drive 340 and
associated
components. As to a kelly example, the kelly 318 may be a square or hexagonal
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metal/alloy bar with a hole drilled therein that serves as a mud flow path.
The kelly
318 can be used to transmit rotary motion from the rotary table 320 via the
kelly drive
bushing 319 to the drillstring 325, while allowing the drillstring 325 to be
lowered or
raised during rotation. The kelly 318 can pass through the kelly drive bushing
319,
which can be driven by the rotary table 320. As an example, the rotary table
320 can
include a master bushing that operatively couples to the kelly drive bushing
319 such
that rotation of the rotary table 320 can turn the kelly drive bushing 319 and
hence
the kelly 318. The kelly drive bushing 319 can include an inside profile
matching an
outside profile (e.g., square, hexagonal, etc.) of the kelly 318; however,
with slightly
larger dimensions so that the kelly 318 can freely move up and down inside the
kelly
drive bushing 319.
[00103] As to a top drive example, the top drive 340 can provide functions
performed by a kelly and a rotary table. The top drive 340 can turn the
drillstring
325. As an example, the top drive 340 can include one or more motors (e.g.,
electric
and/or hydraulic) connected with appropriate gearing to a short section of
pipe called
a quill, that in turn may be screwed into a saver sub or the drillstring 325
itself. The
top drive 340 can be suspended from the traveling block 311, so the rotary
mechanism is free to travel up and down the derrick 314. As an example, a top
drive
340 may allow for drilling to be performed with more joint stands than a
kelly/rotary
table approach.
[00104] In the example of Fig. 3, the mud tank 301 can hold mud, which can
be
one or more types of drilling fluids. As an example, a wellbore may be drilled
to
produce fluid, inject fluid or both (e.g., hydrocarbons, minerals, water,
etc.).
[00105] In the example of Fig. 3, the drillstring 325 (e.g., including one
or more
downhole tools) may be composed of a series of pipes threadably connected
together to form a long tube with the drill bit 326 at the lower end thereof.
As the
drillstring 325 is advanced into a wellbore for drilling, at some point in
time prior to or
coincident with drilling, the mud may be pumped by the pump 304 from the mud
tank
301 (e.g., or other source) via a the lines 306, 308 and 309 to a port of the
kelly 318
or, for example, to a port of the top drive 340. The mud can then flow via a
passage
(e.g., or passages) in the drillstring 325 and out of ports located on the
drill bit 326
(see, e.g., a directional arrow). As the mud exits the drillstring 325 via
ports in the
drill bit 326, it can then circulate upwardly through an annular region
between an
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outer surface(s) of the drillstring 325 and surrounding wall(s) (e.g., open
borehole,
casing, etc.), as indicated by directional arrows. In such a manner, the mud
lubricates the drill bit 326 and carries heat energy (e.g., frictional or
other energy)
and formation cuttings to the surface where the mud (e.g., and cuttings) may
be
returned to the mud tank 301, for example, for recirculation (e.g., with
processing to
remove cuttings, etc.).
[00106] The mud pumped by the pump 304 into the drillstring 325 may, after
exiting the drillstring 325, form a mudcake that lines the wellbore which,
among other
functions, may reduce friction between the drillstring 325 and surrounding
wall(s)
(e.g., borehole, casing, etc.). A reduction in friction may facilitate
advancing or
retracting the drillstring 325. During a drilling operation, the entire
drillstring 325 may
be pulled from a wellbore and optionally replaced, for example, with a new or
sharpened drill bit, a smaller diameter drillstring, etc. As mentioned, the
act of
pulling a drillstring out of a hole or replacing it in a hole is referred to
as tripping. A
trip may be referred to as an upward trip or an outward trip or as a downward
trip or
an inward trip depending on trip direction.
[00107] As an example, consider a downward trip where upon arrival of the
drill
bit 326 of the drillstring 325 at a bottom of a wellbore, pumping of the mud
commences to lubricate the drill bit 326 for purposes of drilling to enlarge
the
wellbore. As mentioned, the mud can be pumped by the pump 304 into a passage
of the drillstring 325 and, upon filling of the passage, the mud may be used
as a
transmission medium to transmit energy, for example, energy that may encode
information as in mud-pulse telemetry.
[00108] As an example, mud-pulse telemetry equipment may include a
downhole device configured to effect changes in pressure in the mud to create
an
acoustic wave or waves upon which information may modulated. In such an
example, information from downhole equipment (e.g., one or more modules of the
drillstring 325) may be transmitted uphole to an uphole device, which may
relay such
information to other equipment for processing, control, etc.
[00109] As an example, telemetry equipment may operate via transmission of
energy via the drillstring 325 itself. For example, consider a signal
generator that
imparts coded energy signals to the drillstring 325 and repeaters that may
receive
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such energy and repeat it to further transmit the coded energy signals (e.g.,
information, etc.).
[00110] As an example, the drillstring 325 may be fitted with telemetry
equipment 352 that includes a rotatable drive shaft, a turbine impeller
mechanically
coupled to the drive shaft such that the mud can cause the turbine impeller to
rotate,
a modulator rotor mechanically coupled to the drive shaft such that rotation
of the
turbine impeller causes said modulator rotor to rotate, a modulator stator
mounted
adjacent to or proximate to the modulator rotor such that rotation of the
modulator
rotor relative to the modulator stator creates pressure pulses in the mud, and
a
controllable brake for selectively braking rotation of the modulator rotor to
modulate
pressure pulses. In such example, an alternator may be coupled to the
aforementioned drive shaft where the alternator includes at least one stator
winding
electrically coupled to a control circuit to selectively short the at least
one stator
winding to electromagnetically brake the alternator and thereby selectively
brake
rotation of the modulator rotor to modulate the pressure pulses in the mud.
[00111] In the example of Fig. 3, an uphole control and/or data
acquisition
system 362 may include circuitry to sense pressure pulses generated by
telemetry
equipment 352 and, for example, communicate sensed pressure pulses or
information derived therefrom for process, control, etc.
[00112] The assembly 350 of the illustrated example includes a logging-
while-
drilling (LWD) module 354, a measurement-while-drilling (MWD) module 356, an
optional module 358, a rotary-steerable system (RSS) and/or motor 360, and the
drill
bit 326. Such components or modules may be referred to as tools where a
drillstring
can include a plurality of tools.
[00113] As to a RSS, it involves technology utilized for directional
drilling.
Directional drilling involves drilling into the Earth to form a deviated bore
such that
the trajectory of the bore is not vertical; rather, the trajectory deviates
from vertical
along one or more portions of the bore. As an example, consider a target that
is
located at a lateral distance from a surface location where a rig may be
stationed. In
such an example, drilling can commence with a vertical portion and then
deviate
from vertical such that the bore is aimed at the target and, eventually,
reaches the
target. Directional drilling may be implemented where a target may be
inaccessible
from a vertical location at the surface of the Earth, where material exists in
the Earth
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that may impede drilling or otherwise be detrimental (e.g., consider a salt
dome,
etc.), where a formation is laterally extensive (e.g., consider a relatively
thin yet
laterally extensive reservoir), where multiple bores are to be drilled from a
single
surface bore, where a relief well is desired, etc.
[00114] One approach to directional drilling involves a mud motor;
however, a
mud motor can present some challenges depending on factors such as rate of
penetration (ROP), transferring weight to a bit (e.g., weight on bit, WOB) due
to
friction, etc. A mud motor can be a positive displacement motor (PDM) that
operates
to drive a bit (e.g., during directional drilling, etc.). A PDM operates as
drilling fluid is
pumped through it where the PDM converts hydraulic power of the drilling fluid
into
mechanical power to cause the bit to rotate.
[00115] As an example, a PDM may operate in a combined rotating mode
where surface equipment is utilized to rotate a bit of a drillstring (e.g., a
rotary table,
a top drive, etc.) by rotating the entire drillstring and where drilling fluid
is utilized to
rotate the bit of the drillstring. In such an example, a surface RPM (SRPM)
may be
determined by use of the surface equipment and a downhole RPM of the mud motor
may be determined using various factors related to flow of drilling fluid, mud
motor
type, etc. As an example, in the combined rotating mode, bit RPM can be
determined or estimated as a sum of the SRPM and the mud motor RPM, assuming
the SRPM and the mud motor RPM are in the same direction.
[00116] As an example, a PDM mud motor can operate in a so-called sliding
mode, when the drillstring is not rotated from the surface. In such an
example, a bit
RPM can be determined or estimated based on the RPM of the mud motor.
[00117] A RSS can drill directionally where there is continuous rotation
from
surface equipment, which can alleviate the sliding of a steerable motor (e.g.,
a
PDM). A RSS may be deployed when drilling directionally (e.g., deviated,
horizontal,
or extended-reach wells). A RSS can aim to minimize interaction with a
borehole
wall, which can help to preserve borehole quality. A RSS can aim to exert a
relatively consistent side force akin to stabilizers that rotate with the
drillstring or
orient the bit in the desired direction while continuously rotating at the
same number
of rotations per minute as the drillstring.
[00118] The LWD module 354 may be housed in a suitable type of drill
collar
and can contain one or a plurality of selected types of logging tools. It will
also be
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understood that more than one LWD and/or MWD module can be employed, for
example, as represented at by the module 356 of the drillstring assembly 350.
Where the position of an LWD module is mentioned, as an example, it may refer
to a
module at the position of the LWD module 354, the module 356, etc. An LWD
module can include capabilities for measuring, processing, and storing
information,
as well as for communicating with the surface equipment. In the illustrated
example,
the LWD module 354 may include a seismic measuring device.
[00119] The MWD module 356 may be housed in a suitable type of drill
collar
and can contain one or more devices for measuring characteristics of the
drillstring
325 and the drill bit 326. As an example, the MWD tool 354 may include
equipment
for generating electrical power, for example, to power various components of
the
drillstring 325. As an example, the MWD tool 354 may include the telemetry
equipment 352, for example, where the turbine impeller can generate power by
flow
of the mud; it being understood that other power and/or battery systems may be
employed for purposes of powering various components. As an example, the MWD
module 356 may include one or more of the following types of measuring
devices: a
weight-on-bit measuring device, a torque measuring device, a vibration
measuring
device, a shock measuring device, a stick slip measuring device, a direction
measuring device, and an inclination measuring device.
[00120] Fig. 3 also shows some examples of types of holes that may be
drilled.
For example, consider a slant hole 372, an S-shaped hole 374, a deep inclined
hole
376 and a horizontal hole 378.
[00121] As an example, a drilling operation can include directional
drilling
where, for example, at least a portion of a well includes a curved axis. For
example,
consider a radius that defines curvature where an inclination with regard to
the
vertical may vary until reaching an angle between about 30 degrees and about
60
degrees or, for example, an angle to about 90 degrees or possibly greater than
about 90 degrees.
[00122] As an example, a directional well can include several shapes where
each of the shapes may aim to meet particular operational demands. As an
example, a drilling process may be performed on the basis of information as
and
when it is relayed to a drilling engineer. As an example, inclination and/or
direction
may be modified based on information received during a drilling process.
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[00123] As an example, deviation of a bore may be accomplished in part by
use of a downhole motor and/or a turbine. As to a motor, for example, a
drillstring
can include a positive displacement motor (PDM).
[00124] As an example, a system may be a steerable system and include
equipment to perform method such as geosteering. As mentioned, a steerable
system can be or include an RSS. As an example, a steerable system can include
a
PDM or of a turbine on a lower part of a drillstring which, just above a drill
bit, a bent
sub can be mounted. As an example, above a PDM, MWD equipment that provides
real time or near real time data of interest (e.g., inclination, direction,
pressure,
temperature, real weight on the drill bit, torque stress, etc.) and/or LWD
equipment
may be installed. As to the latter, LWD equipment can make it possible to send
to
the surface various types of data of interest, including for example,
geological data
(e.g., gamma ray log, resistivity, density and sonic logs, etc.).
[00125] The coupling of sensors providing information on the course of a
well
trajectory, in real time or near real time, with, for example, one or more
logs
characterizing the formations from a geological viewpoint, can allow for
implementing
a geosteering method. Such a method can include navigating a subsurface
environment, for example, to follow a desired route to reach a desired target
or
targets.
[00126] As an example, a drillstring can include an azimuthal density
neutron
(ADN) tool for measuring density and porosity; a MWD tool for measuring
inclination,
azimuth and shocks; a compensated dual resistivity (CDR) tool for measuring
resistivity and gamma ray related phenomena; one or more variable gauge
stabilizers; one or more bend joints; and a geosteering tool, which may
include a
motor and optionally equipment for measuring and/or responding to one or more
of
inclination, resistivity and gamma ray related phenomena.
[00127] As an example, geosteering can include intentional directional
control
of a wellbore based on results of downhole geological logging measurements in
a
manner that aims to keep a directional wellbore within a desired region, zone
(e.g., a
pay zone), etc. As an example, geosteering may include directing a wellbore to
keep
the wellbore in a particular section of a reservoir, for example, to minimize
gas
and/or water breakthrough and, for example, to maximize economic production
from
a well that includes the wellbore.
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[00128] Referring again to Fig. 3, the wellsite system 300 can include one
or
more sensors 364 that are operatively coupled to the control and/or data
acquisition
system 362. As an example, a sensor or sensors may be at surface locations. As
an example, a sensor or sensors may be at downhole locations. As an example, a
sensor or sensors may be at one or more remote locations that are not within a
distance of the order of about one hundred meters from the wellsite system
300. As
an example, a sensor or sensor may be at an offset wellsite where the wellsite
system 300 and the offset wellsite are in a common field (e.g., oil and/or gas
field).
[00129] As an example, one or more of the sensors 364 can be provided for
tracking pipe, tracking movement of at least a portion of a drillstring, etc.
[00130] As an example, the system 300 can include one or more sensors 366
that can sense and/or transmit signals to a fluid conduit such as a drilling
fluid
conduit (e.g., a drilling mud conduit). For example, in the system 300, the
one or
more sensors 366 can be operatively coupled to portions of the standpipe 308
through which mud flows. As an example, a downhole tool can generate pulses
that
can travel through the mud and be sensed by one or more of the one or more
sensors 366. In such an example, the downhole tool can include associated
circuitry
such as, for example, encoding circuitry that can encode signals, for example,
to
reduce demands as to transmission. As an example, circuitry at the surface may
include decoding circuitry to decode encoded information transmitted at least
in part
via mud-pulse telemetry. As an example, circuitry at the surface may include
encoder circuitry and/or decoder circuitry and circuitry downhole may include
encoder circuitry and/or decoder circuitry. As an example, the system 300 can
include a transmitter that can generate signals that can be transmitted
downhole via
mud (e.g., drilling fluid) as a transmission medium.
[00131] As an example, one or more portions of a drillstring may become
stuck.
The term stuck can refer to one or more of varying degrees of inability to
move or
remove a drillstring from a bore. As an example, in a stuck condition, it
might be
possible to rotate pipe or lower it back into a bore or, for example, in a
stuck
condition, there may be an inability to move the drillstring axially in the
bore, though
some amount of rotation may be possible. As an example, in a stuck condition,
there may be an inability to move at least a portion of the drillstring
axially and
rotationally.
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[00132] As to the term "stuck pipe", this can refer to a portion of a
drillstring that
cannot be rotated or moved axially. As an example, a condition referred to as
"differential sticking" can be a condition whereby the drillstring cannot be
moved
(e.g., rotated or reciprocated) along the axis of the bore. Differential
sticking may
occur when high-contact forces caused by low reservoir pressures, high
wellbore
pressures, or both, are exerted over a sufficiently large area of the
drillstring.
Differential sticking can have time and financial cost.
[00133] As an example, a sticking force can be a product of the
differential
pressure between the wellbore and the reservoir and the area that the
differential
pressure is acting upon. This means that a relatively low differential
pressure (delta
p) applied over a large working area can be just as effective in sticking pipe
as can a
high differential pressure applied over a small area.
[00134] As an example, a condition referred to as "mechanical sticking"
can be
a condition where limiting or prevention of motion of the drillstring by a
mechanism
other than differential pressure sticking occurs. Mechanical sticking can be
caused,
for example, by one or more of junk in the hole, wellbore geometry anomalies,
cement, keyseats or a buildup of cuttings in the annulus.
[00135] Fig. 4 shows an example of a wellsite system 400, specifically,
Fig. 4
shows the wellsite system 400 in an approximate side view and an approximate
plan
view along with a block diagram of a system 470.
[00136] In the example of Fig. 4, the wellsite system 400 can include a
cabin
410, a rotary table 422, drawworks 424, a mast 426 (e.g., optionally carrying
a top
drive, etc.), mud tanks 430 (e.g., with one or more pumps, one or more
shakers,
etc.), one or more pump buildings 440, a boiler building 442, an HPU building
444
(e.g., with a rig fuel tank, etc.), a combination building 448 (e.g., with one
or more
generators, etc.), pipe tubs 462, a catwalk 464, a flare 468, etc. Such
equipment
can include one or more associated functions and/or one or more associated
operational risks, which may be risks as to time, resources, and/or humans.
[00137] As shown in the example of Fig. 4, the wellsite system 400 can
include
a system 470 that includes one or more processors 472, memory 474 operatively
coupled to at least one of the one or more processors 472, instructions 476
that can
be, for example, stored in the memory 474, and one or more interfaces 478. As
an
example, the system 470 can include one or more processor-readable media that
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include processor-executable instructions executable by at least one of the
one or
more processors 472 to cause the system 470 to control one or more aspects of
the
wellsite system 400. In such an example, the memory 474 can be or include the
one
or more processor-readable media where the processor-executable instructions
can
be or include instructions. As an example, a processor-readable medium can be
a
computer-readable storage medium that is not a signal and that is not a
carrier wave.
[00138] Fig. 4 also shows a battery 480 that may be operatively coupled to
the
system 470, for example, to power the system 470. As an example, the battery
480
may be a back-up battery that operates when another power supply is
unavailable
for powering the system 470. As an example, the battery 480 may be operatively
coupled to a network, which may be a cloud network. As an example, the battery
480 can include smart battery circuitry and may be operatively coupled to one
or
more pieces of equipment via a SMBus or other type of bus.
[00139] In the example of Fig. 4, services 490 are shown as being
available, for
example, via a cloud platform. Such services can include data services 492,
query
services 494 and drilling services 496. As an example, the services 490 may be
part
of a system such as the system 300 of Fig. 3.
[00140] As an example, the system 470 may be utilized to generate one or
more rate of penetration drilling parameter values, which may, for example, be
utilized to control one or more drilling operations.
[00141] As explained, drilling operations may utilize positive
displacement
motors (PDMs), which can be operationally more effective than rotary drilling
alone.
Various drilling operations may still use a bit and motor combination to drill
a curved
portion and a lateral portion of a wellbore where it can be frequently
observed via
downhole measurements that an average bit RPM decreases over time without a
substantial change in surface parameters. As a mud motor provides additional
energy to a system, such a decrease in RPM indicates some deterioration of
motor
efficiency. If such changes continue, it will likely entail worsening drilling
dynamics
and surface/downhole equipment failures. Estimating energy and efficiency of a
mud motor based on available data can provide for monitoring the status of a
mud
motor.
[00142] Fig. 5 shows an example of a drilling assembly 500 in a geologic
environment 501 that includes a borehole 503 where the drilling assembly 500
(e.g.,
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a drillstring) includes a bit 504 and a motor section 510 where the motor
section 510
can drive the bit 504 (e.g., cause the bit 504 to rotate and deepen the
borehole 503).
[00143] As shown, the motor section 500 includes a dump valve 512, a power
section 514, a surface-adjustable bent housing 516, a transmission assembly
518, a
bearing section 520 and a drive shaft 522, which can be operatively coupled to
a bit
such as the bit 504.
[00144] As to the power section 514, two examples are illustrated as a
power
section 514-1 and a power section 514-2 each of which includes a housing 542,
a
rotor 544 and a stator 546. The rotor 544 and the stator 546 can be
characterized by
a ratio. For example, the power section 514-1 can be a 5:6 ratio and the power
section 514-2 can be a 1:2 ratio, which, as seen in cross-sectional views, can
involve
lobes (e.g., a rotor/stator lobe configuration). The motor section 510 of Fig.
5 may
be a POWERPAK family motor section (Schlumberger Limited, Houston, Texas) or
another type of motor section. The POWERPAK family of motor sections can
include ratios of 1:2, 2:3, 3:4, 4:5, 5:6 and 7:8 with corresponding lobe
configurations.
[00145] A power section can convert hydraulic energy from drilling fluid
into
mechanical power to turn a bit. For example, consider the reverse application
of the
Moineau pump principle. During operation, drilling fluid can be pumped into a
power
section at a pressure that causes the rotor to rotate within the stator where
the
rotational force is transmitted through a transmission shaft and drive shaft
to a bit.
[00146] A motor section may be manufactured in part of corrosion-resistant
stainless steel where a thin layer of chrome plating may be present to reduce
friction
and abrasion. As an example, tungsten carbide may be utilized to coat a rotor,
for
example, to reduce abrasion wear and corrosion damage. As to a stator, it can
be
formed of a steel tube, which may be a housing (see, e.g., the housing 542)
with an
elastomeric material that lines the bore of the steel tube to define a stator.
An
elastomeric material may be referred to as a liner or, when assembled with the
tube
or housing, may be referred to as a stator. As an example, an elastomeric
material
may be molded into the bore of a tube. An elastomeric material can be
formulated to
resist abrasion and hydrocarbon induced deterioration. Various types of
elastomeric
materials may be utilized in a power section and some may be proprietary.
Properties of an elastomeric material can be tailored for particular types of
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operations, which may consider factors such as temperature, speed, rotor type,
type
of drilling fluid, etc. Rotors and stators can be characterized by helical
profiles, for
example, by spirals and/or lobes. A rotor can have one less fewer spiral or
lobe than
a stator (see, e.g., the cross-sectional views in Fig. 5).
[00147] During operation, the rotor and stator can form a continuous seal
at
their contact points along a straight line, which produces a number of
independent
cavities. As fluid is forced through these progressive cavities, it causes the
rotor to
rotate inside the stator. The movement of the rotor inside the stator is
referred to as
nutation. For each nutation cycle, the rotor rotates by a distance of one lobe
width.
The rotor nutates each lobe in the stator to complete one revolution of the
bit box.
For example, a motor section with a 7:8 rotor/stator lobe configuration and a
speed
of 100 RPM at the bit box will have a nutation speed of 700 cycles per minute.
Generally, torque output increases with the number of lobes, which corresponds
to a
slower speed. Torque also depends on the number of stages where a stage is a
complete spiral of a stator helix. Power is defined as speed times torque;
however, a
greater number of lobes in a motor does not necessarily mean that the motor
produces more power. Motors with more lobes tend to be less efficient because
the
seal area between the rotor and the stator increases with the number of lobes.
[00148] The difference between the size of a rotor mean diameter (e.g.,
valley
to lobe peak measurement) and the stator minor diameter (lobe peak to lobe
peak) is
defined as the rotor/stator interference fit. Various motors are assembled
with a
rotor sized to be larger than a stator internal bore under planned downhole
conditions, which can produce a strong positive interference seal that is
referred to
as a positive fit. Where higher downhole temperatures are expected, a positive
fit
can be reduced during motor assembly to allow for swelling of an elastomeric
material that forms the stator (e.g., stator liner). Mud weight and vertical
depth can
be considered as they can influence the hydrostatic pressure on the stator
liner. A
computational framework such as, for example, the POWERFIT framework
(Schlumberger Limited, Houston, Texas), may be utilized to calculate a desired
interference fit.
[00149] As to some examples of elastomeric materials, consider nitrile
rubber,
which tends to be rated to approximately 138 C (280 F), and highly saturated
nitrile,
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which may be formulated to resist chemical attack and be rated to
approximately 177
C (350 F).
[00150] The spiral stage length of a stator is defined as the axial length
for one
lobe in the stator to rotate 360 degrees along its helical path around the
body of the
stator. The stage length of a rotor differs from that of a stator as a rotor
has a
shorter stage length than its corresponding stator. More stages can increase
the
number of fluid cavities in a power section, which can result in a greater
total
pressure drop. Under the same differential pressure conditions, the power
section
with more stages tends to maintain speed better as there tends to be less
pressure
drop per stage and hence less leakage.
[00151] Drilling fluid temperature, which may be referred to as mud
temperature or mud fluid temperature, can be a factor in determining an amount
of
interference in assembling a stator and a rotor of a power section. As to
interference, greater interference can result in a stator experiencing higher
shearing
stresses, which can cause fatigue damage. Fatigue can lead to premature
chunking
failure of a stator liner. As an example, chlorides or other such halides may
cause
damage to a power section. For example, such halides may damage a rotor
through
corrosion where a rough edged rotor can cut into a stator liner (e.g., cutting
the top
off an elastomeric liner). Such cuts can reduce effectiveness of a
rotor/stator seal
and may cause a motor to stall (e.g., chunking the stator) at a low
differential
pressure. For oil-based mud (0BM) with supersaturated water phases and for
salt
muds, a coated rotor can be beneficial.
[00152] As to differential pressure, it is defined as the difference
between the
on-bottom and off-bottom drilling pressure, which is generated by the
rotor/stator
section (power section) of a motor. As mentioned, for a larger pressure
difference,
there tends to be higher torque output and lower shaft speed. A motor that is
run
with differential pressures greater than recommended can be more prone to
premature chunking. Such chunking may follow a spiral path or be uniform
through
the stator liner. A life of a power section can depend on factors that can
lead to
chunking (e.g., damage to a stator), which may depend on characteristics of a
rotor
(e.g., surface characteristics, etc.).
[00153] As to trajectory of a wellbore to be drilled, it can be defined in
part by
one or more dogleg severities (DLSs). Rotating a motor in high DLS interval of
a
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well can increase risk of damage to a stator. For example, the geometry of a
wellbore can cause a motor section to bend and flex. A power section stator
can be
relatively more flexible that other parts of a motor. Where the stator housing
bends,
the elastomeric liner can be biased or pushed upon by the housing, which can
result
in force being applied by the elastomeric liner to the rotor. Such force can
lead to
excessive compression on the stator lobes and cause chunking.
[00154] A motor can have a power curve. A test can be performed using a
dynamo meter in a laboratory, for example, using water at room temperature to
determine a relationship between input, which is flow rate and differential
pressure,
to power output, in the form of RPM and torque. Such information can be
available
in a motor handbook. However, what is actually happening downhole can differ
due
to various factors. For example, due to effect of downhole pressure and
temperature, output can be reduced (e.g., the motor power output). Such a
reduction may lead one to conclude that a motor is not performing. In
response, a
driller may keep pushing such that the pressure becomes too high, which can
damage elastomeric material due to stalling (e.g., damage a stator).
[00155] As an example, power can be reduced downhole due to effects of
temperature and pressure and/or one or more other factors. For example,
consider
a plot of power versus differential pressure where differences between surface
and
downhole may increase with higher differential pressures.
[00156] As to damage to an elastomeric material of a stator of a motor,
separation from a tube or housing may occur in association with chunking.
[00157] Fig. 6 shows an example of a schematic of a system 600 that
includes
inputs that can be accounted for by a motor engine (see, e.g., the motor
engine 930).
As shown, information may be input from various sources. As an example, one or
more filters may be available to, for example, filter by borehole size, filter
by
inventory (e.g., business system), filter by offset well analysis, etc.
[00158] As an example, a method can provide for evaluating mud motor
energy
and efficiency and, for example, estimating mud motor degradation. In such an
example, with surface drilling parameters and downhole rotational speed
synchronized, flow rate, mud motor rotational speed and differential pressure
can be
obtained from measured data. By utilizing mud motor power characteristic
curves,
mud motor torque and power output can be calculated. In such an example, this
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allows for computing mud motor efficiency from a ratio of motor power input to
power
output. As an example, a method can include using an equation derived to
incorporate mud motor off bottom pressure to calculate motor efficiency. As an
example, a change rate of motor efficiency can be obtained by fitting time-
based
and/or depth-based efficiency results.
[00159] As an example, a method can include generating a mud motor
degradation indicator that provides an estimate as to how much a mud motor has
degraded over time. In such an example, the degradation indicator can be based
on
calculating a difference between measured mud motor rotational speed and
nominal
rotational speed based on a motor characteristic curve. By fitting of a
calculated
degradation indicator over drilling time and/or drilling depth, a degradation
rate can
be estimated, for example, as to one or more future times, future depths,
future
drilling runs, etc.
[00160] As explained, a mud motor can be characterized by various
parameters and/or conditions. One manner of characterization is a motor
characteristic curve. Various approaches may be utilized to obtain a motor
characteristic curve or curves. For example, consider use of a mud motor
specification library where pre-defined mud motor curves are stored. Another
approach can utilize a mud motor engine, which may be trained using machine
learning, for example, based on mud motor power section finite element
analysis
(FEA) modeling results. With mud motor torque, differential pressure and power
output being available, as an example, a method can include calculating torque
rating, differential pressure rating and power rating, which may be used to
evaluate
whether a motor is working at the optimum zone.
[00161] As explained, a simulator may be utilized to compute a downhole
power curve, optionally along with fatigue life. Such a simulator can model
the
geometry of the motor power section, and combine FEA and computational fluid
dynamics (CFD) computation, optionally together with lab tests for elastomeric
materials. As an example, computing clusters can run simulations to generate a
simulation results database. Based on such a database, a machine learning
model
can be trained to predict simulation results. As an example, one or more
application
programming interfaces (APIs) can be built and implemented so that an
application
or framework can readily query a mud motor engine (e.g., a computational
engine).
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[00162] As an example, a method can include generating various types of
information such as, for example, the difference between mud motor torque and
top
drive torque may be utilized to evaluate torque loss within a drillstring.
Also,
downhole rotation mechanical specific energy (MSE) can be calculated by
plugging
in the motor torque to MSE equation, which will be useful to estimate bit
wear. MSE
is a metric that can describe the energy spent in removing a unit volume of
rock/formation mass.
[00163] As an example, a system can provide for utilization of hardware,
sensors, data and modeling to deliver an answer product that can to be applied
to
post run analysis and/or real-time analysis, which may include output of
instructions,
recommendations, control signals, etc.
[00164] As an example, a system can include utilization of a large number
of
downhole and surface data sets. As an example, a data analytics platform such
as,
for example, the DATAIKU platform, etc., may be used to create an analysis
workflow (e.g., on thousands of field runs, etc.). Through data analytics and
data
mining, output of an analysis can be applied in offset well analysis in well
planning
(e.g. drill planning, etc.) to better match a bit mud motor system. As
mentioned, a
system may be implemented in real-time operation (e.g., drilling operations,
etc.), for
example, to assist decision making, control, etc., by monitoring motor
efficiency,
motor performance and degradation.
[00165] As an example, a system can provide for calculating motor
efficiency;
calculating motor degradation; determining motor efficiency ranges for certain
applications; determining motor degradation ranges for certain applications
and
degradation upper limits; applying ranges in motor job planning; applying
ranges in
motor job monitoring (e.g., with associated graphical user interfaces, etc.);
and/or
applying ranges for motor predictive health monitoring, re-run recommendation,
etc.
[00166] Drilling with positive displacement motors dominates oil field
operation.
In many cases, it provides operational and economic advantages over
conventional
rotary drilling. In US land drilling for example, many jobs using an RSS
system use a
configuration with a mud motor. Moreover, many wells in US land drilling are
still
using the traditional bit and motor combination to drill the curve and
lateral. It's quite
frequent to see in downhole measurement that the average bit RPM decreases
over
time without any major change in surface parameters. Since mud motor provides
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additional energy to the system, the decrease in RPM indicates the
deterioration of
motor efficiency. If such changes continue, it will likely to entail worsen
drilling
dynamics and surface/downhole equipment failures. It is beneficial to estimate
the
energy and efficiency of the mud motor based on available data, and to enable
a
way of monitoring the status of the mud motor.
[00167] An analysis method has been developed to evaluate mud motor energy
and efficiency and to estimate the mud motor degradation. With the surface
drilling
parameter and downhole rotational speed synchronized, the flow rate, mud motor
rotational speed and differential pressure are obtained from the measured
data. By
utilizing mud motor power characteristic curves, the mud motor torque and
power
output are calculated, thus the mud motor efficiency can be computed from the
ratio
of motor power input to power output. In addition, an alternative equation can
be
used to incorporate the mud motor off bottom pressure to calculate the motor
efficiency. The change rate of the motor efficiency is also obtained by
fitting the time-
based or depth-based efficiency results. Meanwhile, a mud motor degradation
indicator is developed to estimate how much the mud motor has degraded over
time.
The degradation indicator is based on calculating the difference between the
measured mud motor rotational speed and the nominal rotational speed based on
the motor characteristic curve. Also, by fitting the calculated degradation
indicator
over drilling time or drilling depth, the degradation rate can be estimated.
[00168] The motor characteristic curves can play an important role in the
method. Two approaches can be used to obtain the curves. The first approach is
to
use the mud motor specification library where the pre-defined mud motor curves
are
stored. The other approach is to utilize a mud motor engine trained using
machine
learning based on mud motor power section FEA modeling results. With the mud
motor torque, differential pressure and power output being available, the
method can
calculate the torque rating, differential pressure rating and power rating,
hence to
evaluate whether the motor is working in an optimum zone.
[00169] The method can also generate other useful information. For
instance,
the difference between the mud motor torque and top drive torque can be used
to
evaluate the torque loss within the drill string. Also, downhole rotation MSE
can be
calculated by plugging in the motor torque to MSE equation, which can be
useful to
estimate bit wear.
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[00170] This analysis method leverages the hardware, sensors, data and
modeling to deliver an answer product that can to be applied to post run
analysis as
well as in real-time. The analysis method can be applied to massive number of
downhole and surface data sets. A cloud based data analytics platform can be
used
to create an analysis workflow and apply the method on thousands of field
runs.
Through data analytics and data mining, the output of the analysis can be
applied in
offset well analysis in well planning to better match the bit mud motor
system. The
method can be implemented in real-time operation to assist decision making by
monitoring the motor efficiency, motor performance and degradation.
[00171] This approach can be used for calculating motor efficiency,
calculating
motor degradation, determining motor efficiency ranges for certain
applications,
determining motor degradation ranges for certain applications and degradation
upper
limits, applying the ranges in motor job planning, applying the ranges in
motor job
monitoring (including the UI), and applying the ranges for motor predictive
health
monitoring, and re-run recommendation.
[00172] As an example, a system can provide for one or more real-time mud
motor efficiency metrics, which can include, for example, one or more
degradation
metrics. As explained, a system can acquire real-time data, compare
performance
with predicted performance based on estimated degradation (e.g., wear, etc.),
and
update expected performance (e.g., efficiency, life, etc.) for a motor as it
is utilized in
drilling.
[00173] Figs. 7 and 8 show examples of graphical user interfaces (GUIs)
700,
800 and 810. The GUIs 700, 800 and 810 include plots of examples of data
measurements associated with motor drilling. The plots illustrate a tendency
for
downhole ROP to decrease even when surface parameters remain relatively
constant.
[00174] In the examples of Figs. 7 and 8, a motorized RSS BHA was used
with
CC RPM and CCRPM_AV showing downhole rotational speed. As shown, the
downhole RPM kept decreasing while surface RPM and flow rate was consistent,
which means mud motor RPM must be decreasing. The decreasing of mud motor
RPM indicates the loss of mud motor efficiency. Towards the end of the run,
due to
the efficiency decay, the mud motor is unable to sustain torque demanded,
resulting
in reduction of ROP and relatively severe stick-slip.
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[00175] Fig. 9 shows an example of a GUI 900 that includes a plot
pertaining to
a power section specification from a mud motor engine. As shown, the torque
slope
changes by approximately 3 percent when temperature increases from 30 C to 90
C
for a motor with 600 gpm flow.
[00176] As an example, a system can provide for motor input energy from
hydraulics flow:
HPin =¨AP = ¨Flow
where AP is differential pressure and Flow is flow rate.
[00177] As an example, a system can provide for motor output energy given
by:
HPout = T = RPMm
where T is motor torque output and RPMm is motor RPM.
[00178] As an example, a system can provide for motor torque T as
approximated by:
= All = TorqueSlope
where TorqueSlope can be obtained from a power section spec or mud motor
engine where AP, is the active differential pressure which contributes to
torque
generation.
[00179] As an example, motor efficiency can be given by:
HPout T = RPMm All = TorqueSlope = RP Mm
e = ¨ ________ ¨ _____________________
1113in AP = Flow AP = Flow
AP,õ = TorqueSlope = RPMm AP0-0 TorqueSlope = RP Mm
(AP + AP=) = Flow Flow
where AP0 is the no load differential pressure can be obtained from motor
engine or specification.
[00180] Fig. 10 shows example GUIs 1000 and 1010 relating to efficiency.
As
shown in the GUI 1010, contours can exist as to efficiencies that may change
with
respect to time, drilling depth, etc. In such an example, the GUI 1010 may be
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rendered in real-time to show a current status and past status(es) along with
predicted future status(es) such that one or more decisions may be made (e.g.,
manually, semi-automatically, automatically, etc.).
[00181] Fig. 11 shows an example GUI 1100 that includes a plot of RPM
versus differential pressure where nominal and measured RPM are indicated via
an
equation for "R", which is a degradation metric (e.g., R metric, R ratio,
etc.). As
shown, the nominal RPM can be represented by co and the measured motor RPM
can be represented by co*. As shown, R can be defined as a difference between
nominal and measured RPM (e.g., measured less than nominal) divided by nominal
RPM. As shown, in the plot of the GUI 1100, for an operational differential
pressure,
a difference can exist between nominal and measured RPM, which may be for a
particular flow rate (e.g., gallons per minute, etc.). As an example,
performance of a
power section (see, e.g., the power section 514 in Fig. 5) can depend on type
of liner
(e.g., type of elastomeric material, etc.) installed in the power section. As
to a
nominal RPM, it can be computed on based on conditions, etc., given
specifications
for a power section of a mud motor.
[00182] Fig. 12 shows examples of GUIs 1200 and 1210 that show two
different degradation rates (e.g., 0.484 percent per hour and 0.641 percent
per hour)
where, for example, a linear fit can be utilized to obtain a motor degradation
change
rate. As an example, R metric values may be computed for data pairs of nominal
and measured and the R metric values may be fit using a regression technique,
etc.
In the example GUIs 1200 and 1210, the degradation rate (e.g., degradation
change
rate) may be with respect to time and/or depth (e.g., distance, etc.).
[00183] Fig. 13 shows an example of a system 1300 that includes data
blocks
1312 and 1314, a synchronization block 1320, a motor torque/RPM block 1330 and
an energy block 1340. As shown, the blocks 1312, 1314, 1320, 1330 and 1340 can
provide one or more outputs per an output block 1350. For example, consider
bit/motor torque, drilling torque loss, motor power output, motor power input,
bit/motor efficiency, power/max power, etc. Such a system may utilize one or
more
of the foregoing equations, mud motor engine, etc. In the example of Fig. 13,
an
approach can acquire surface data and downhole data and synchronizes them
automatically. Once the data sources are synchronized, the motor torque and
RPM
can be calculated and used to calculate energy.
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[00184] Fig. 14 shows an example of a workflow 1400 where data may be
collected from a variety of sources; for example, tool life data, dump files,
real-time
data captures, simulation results, and others may be captured as part of data
collection. A variety of data preparation actions may be performed to clean
the data.
As noted above, data may also be synchronized. From such data, motor power and
efficiency analysis may be performed where results may be rendered to one or
more
displays via one or more visualizations.
[00185] As an example, visualizations based on results may provide
insights
into which entities are operating with higher motor efficiency, which motors
are less
susceptible to efficiency decay, and which combinations of bit, motors, and
other
BHA components provide the most product configuration in particular
circumstances.
[00186] As explained, a system, a method, a workflow, etc., may be
configured
to run in real-time. In such instances, real-time data channels may be
utilized and,
for example, a demand for synchronization may be less in such circumstances.
[00187] Fig. 15 shows example GUIs 1500 and 1510 as to motor type and
motor size, respectively. Such motors may be utilized as part of a library of
motors
with parameters that may be, for example, generated at least in part using
simulation
data.
[00188] Fig. 16 shows an example of a GUI 1600 that shows various workflow
elements that can be utilized in a data analytics platform (e.g., DATAIKU,
etc.) that
can provide for motor power and efficiency analysis. As shown, various
elements in
the workflow pertain to automatic state detection and reference connections,
application of time synchronization (e.g., as may be appropriate for stored
and/or live
data), and mud motor power and efficiency indicators (e.g., efficiency with
respect to
depth, efficiency with respect to time, and/or one or more other efficiency
indicators).
In the example of FIG. 16, various sources of data are on the left side and
various
outputs are on the right side.
[00189] Fig. 17 shows an example of a GUI 1700 that includes a table of
motor
power and efficiency, drilling mechanics, and performance indicators. Such a
table
may be considered a table of some examples of motor efficiency computation
outputs.
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[00190] Fig. 18 shows example GUIs 1800 and 1810, which include plots as
to
motor efficiency over depth drilled and/or time drilled. As shown, decay rates
can
vary.
[00191] Fig. 19 shows example GUIs 1900 and 1910 that correspond to the
GUIs 1800 and 1810 of Fig. 18, respectively. The GUIs 1900 and 1910 show
efficiency decay statistics.
[00192] Figs. 20, 21, 22 and 23 show various GUIs 2000, 2100, 2200 and
2300
that include plots relating to torque loss. As explained, motor torque can be
computed using differential pressures and torque slopes of motor curves.
[00193] Fig. 24 shows example GUIs 2400 and 2410 as to motor run torsional
MSE. In the examples of Fig. 24, motor torque is computed with both surface
and
downhole MSE, for example, as follows:
WOB 120 = Tr = RPM = TQ
MSE = -Ab ROP = Ab
[00194] Fig. 25 shows example GUIs 2500 and 2510 as to motor degradation
with respect to depth drilled. As shown, motor degradation is inversely
correlated
with drilled length (e.g., measured depth, etc.).
[00195] Figs. 26 and 27 show example GUIs 2600, 2700 and 2710 for motor
degradation in the Midland Area in the State of Texas. Per the data, a
majority of the
runs show relatively low degradation rate (e.g., less than approximately 0.2
percent).
As indicated in the distributions, an inverse correlation exists between
degradation
rate and drilled time.
[00196] Figs. 28 and 29 show example GUIs 2800 and 2900 where an
envelope may be defined, for example, using a regression analysis and a
selected
function (e.g., exponential, etc.). Such an approach can be utilized to
determine a
degradation limit or degradation limits. As an example, a method can include
estimating motor life limit in terms of drilling time and/or drilling depth
given
degradation rate in real-time. Such an approach may be utilized to determine
one or
more parameters of a drilling operation (e.g., ROP, etc.). As an example, an
envelope or region may be determined and utilized in one or more field
operations,
for example, to control drilling to maintain degradation below a particular
degradation
rate.
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[00197] Figs. 30 and 31 show example GUIs 3000, 3010 and 3100 as to motor
degradation with field incident information. As shown, incident coding may be
utilized such that information regarding incidents and drilling can be
understood,
controlled, etc. In Fig. 31, a bar chart shows counts versus incident type.
[00198] Fig. 32 shows example GUIs 3200 and 3210 as to motor degradation
and field incidents, along with pull out of hole (POOH) reasons. As an
example, a
system can provide for extracting runs with degradation rate no less than a
desired
limit such as, for example, 0.5% /100ft. In Fig. 32, two incident types with
the
highest counts are power drive and mud motor failure. As indicated, there is
higher
chance of motor failure where the degradation rate is higher than 1.0% /100ft.
As to
the POOH reason, the highest counts were for downhole tool failure and
steerable
tool failure.
[00199] Figs. 33 and 34 show example GUIs 3300 and 3400 for a particular
motor where failure occurred. In particular, motor degradation rate
accelerated at
the end of the run where the mud motor eventually lost power and could not
spin. In
such an example, a possibility may have existed to save the mud motor, for
example, if a call was made before the degradation rate accelerated. As an
example, a real-time system can provide for indications of one or more types
of
issues, which may be utilized for control, alarms, etc. In another example for
another
motor, a relatively high motor degradation rate existed where, eventually, the
mud
motor lost differential pressure and the drive shaft broke.
[00200] Figs. 35 and 36 show example GUIs 3500 and 3600 for a particular
motor where pressure loss occurred. In such an example, there was a possible
washout in the BHA.
[00201] Figs. 37 and 38 show example GUIs 3700 and 3800 for a particular
motor where a failure occurred. In the example of Figs. 37 and 38, the BHA
showed
a 45 degree washed crack, indicating high frequency torsional oscillation
(HFTO).
HFTO can create cyclic fatigue loading and limit tool life and drilling
performance.
As an example, a system can provide for mitigation of HFTO, for example, by
considering rock drilled, bit design, mud motor, mechanics of RSS and other
tools in
a BHA, as well as drilling parameters. Such a system can help to reduce
premature
drilling component failure and improve drilling performance, especially in
high energy
drilling applications (e.g., North America land, etc.). In the example of
Figs. 37 and
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38, the bit box being free to rotate at POOH indicates motor failure. The
degradation
of the mud motor may have led to HFTO. In such an example, one or more
indicators, alarms, control signals, etc., may be issued by a system to
mitigate
degradation of a mud motor, which may help to reduce one or more effects of
HFTO
(e.g., as to other components, a borehole, etc.).
[00202] Fig. 39 shows an example of GUI 3900 that includes a degradation
distribution plot for cumulative distribution per degradation. As an example,
a
system may provide guidelines for motor degradation that can issue one or more
alerts in real-time. For example, consider thresholds of greater than or equal
to 20
percent as being high degradation and greater than or equal to 30 percent as
being
severe degradation. As indicated in the GUI 3900, P80 and P90 may be utilized
to
determine one or more thresholds (e.g., as to acceptable, high, severe, etc.).
[00203] Fig. 40 shows an example of GUI 4000 that includes a degradation
distribution plot for cumulative distribution per degradation. As an example,
a
system may provide guidelines for motor degradation that can issue one or more
alerts in real-time. For example, consider thresholds of greater than or equal
to 20
percent as being high degradation and greater than or equal to 30 percent as
being
severe degradation. As indicated in the GUI 4000, P80 and P90 may be utilized
to
determine one or more thresholds (e.g., as to acceptable, high, severe, etc.).
[00204] Figs. 41 and 42 show example GUIs 4100 and 4200 as to degradation
rate distribution. As shown in the GUI 4200, P80 and P90 (e.g., or other
metrics)
may be utilized to determine one or more thresholds in terms of degradation
rate, for
example, in terms of percent per amount of distance and/or per amount of time
(e.g.,
drilling time). As shown, P80 corresponds to approximately 0.3 percent per
100ft
and P90 corresponds to approximately 0.8 percent per 100ft.
[00205] Fig. 43 shows an example GUI 4300 that includes a degradation
change distribution plot that is based on start and end data. For example,
degradation start and end can be defined as below:
If Depth Drilled > 900 ft (10std): Degradation Start = average degradation of
first 90 ft drilling, Degradation End = average degradation of last 90ft; or
If Depth Drilled < 900ft: Degradation Start = average degradation of first 10%
of depth drilled, Degradation End = average degradation of 10% of depth
drilled.
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[00206] Fig. 44 shows an example GUI 4400 that includes a mud motor
efficiency distribution plot. As shown, one or more probabilistic and/or
statistical
techniques may be utilized, for example, the GUI 4400 shows that P50
corresponds
to an efficiency of approximately 76 percent.
[00207] As an example, a system may be utilized in a bit and motor
planning
operation (e.g., a planning framework, etc.). As an example, a system may be
utilized in combination with a dynamic drilling interpretation framework
(e.g., consider
the TECH LOG framework, etc.). As an example, a system may be utilized in real-
time, for example, for motor efficiency and decay monitoring (e.g., consider
integration with a drilling operations framework). As an example, a system may
be
utilized for mud motor health analysis. As explained, one or more
probabilistic
and/or statistical techniques may be utilized for analysis. As an example, one
or
more data-driven approach may be utilized, for example, consider one or more
machine learning techniques. As an example, a machine learning technique may
be
utilized to generate a trained machine learning model that may be operable in
real-
time to provide real-time guidance, control, decision making, etc.,
capabilities of a
system.
[00208] Fig. 45 shows an example of a GUI 4500 of a system where the GUI
4500 provides various graphical controls, fields, visualizations, etc., for
bit and motor
runs, which can include historical runs, real-time runs, etc. Such a GUI may
be
utilized for planning, forensics, operations, etc. In Fig. 45, the GUI 4500
includes a
map with wellsite locations, which can be for actual wells and/or planned
wells. As
shown, a distance control can provide for ranging of the map, for example, to
provide
for selection, visualization, etc., of one or more wellsites. As shown, for a
map
region, various runs can be listed along with details. In such an example,
offset well
analyses may be performed for a target well, which may be in planning,
development, operation, etc. The GUI 4500 shows a field with a number of runs
that
may exist within a map region, etc. As an example, a well may include one or
more
branches. As an example, multiple wells may be drilled from a common pad.
[00209] In the example of Fig. 45, the GUI 4500 includes a ranking panel
with a
ranking of motor and bit combinations. As shown, various graphical controls
may be
utilized for filtering, searching, etc., information pertaining to motors,
bits, motor and
bit combinations, etc. For example, consider one or more graphical controls as
to
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one or more of bore diameter, BHA type, bit model, bit manufacturer, year,
company
(e.g., drilling company, owner, etc.).
[00210] Fig. 46 shows an example of a GUI 4600 of a system where the GUI
4600 includes various graphics associated with bits and motors. Such a GUI may
be
utilized for performing planning, operations, etc. For example, consider
performing
an offset well data analysis to identify runs, better efficiency runs and
operating
parameter ranges, etc. As an example, the IDEAS framework (Schlumberger
Limited, Houston, Texas) can provide for modeling and simulations as to
drillstring
performance (e.g., rate of penetration, etc.), for example, for comparisons of
performance of bit and motor combinations. As shown, various bits and various
motors may be utilized in assessing combinations. As an example, a system can
provide for bit and motor matching, which may provide for consideration of one
or
more of highest ROP, most stable drilling, balanced motor efficiency and
durability,
etc.
[00211] As an example, a system can include one or more controllers and
may
be referred to as an autodriller system or an "AutoROP" system or a "ROPO"
system
(rate of penetration optimization system). For example, consider a weight on
bit
(WOB) controller, a drilling torque (TQA) controller, a differential pressure
(DIFF_P)
controller and a rate of penetration (ROP) controller. Each of the controllers
may
receive a corresponding set point (SP) value where each of the controllers
receives
a measured value (e.g., a WOB measurement, a TQA measurement and a DIFF_P
measurement, respectively). Each of the controllers may output a normalized
(NM)
value (e.g., scaled from 0 to 1, etc.) that is received by the ROP controller
where the
ROP controller can utilize the normalized (NM) values and a ROP set point (SP)
value to generate a ROP output. As an example, such a system can be
operatively
coupled to and/or include a degradation and/or efficiency system (e.g., a
degradation
and/or efficiency engine, framework, etc.) where, for example, control signals
for
drilling may be based at least in part on one or more of degradation and
efficiency of
a mud motor, where a mud motor is utilized (e.g., as part of a drillstring).
As an
example, sliding mode and/or rotating mode decisions and/or operations may be
based at least in part on one or more of degradation and efficiency. Such
decisions
and/or operations may aim to maintain sufficient life in a power section of a
mud
motor to complete a run without having to pull a drillstring out of hole
(POOH) for
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servicing, etc. Such an approach can help to reduce non-productive time (NPT)
during drilling operations for one or more wells.
[00212] As an example, an agent may be trained to provide for output as to
one
or more of WOB, TQA, DIFF_P, ROP, etc. For example, such an agent may be part
of a ROP system where output of the agent guides drilling to achieve a
desirable
ROP.
[00213] As an example, a system can include features for prediction of
propagation direction of a drill bit, which may be operatively coupled to a
mud motor,
based on forces and bit and/or motor characteristics. Such a system may
utilize a
computational framework that includes one or more features of a framework such
as,
for example, the IDEAS framework. The IDEAS framework utilizes the finite
element
method (FEM) to model various physical phenomena, which can include reaction
force at a bit (e.g., using a static, physics-based model). The FEM utilizes a
grid or
grids that discretize one or more physical domains. Equations such as, for
example,
continuity equations, are utilized to represent physical phenomena. The IDEAS
framework, as with other types of FEM-based approaches, provides for numerical
experimentation that approximates real-physical experimentation. In various
instances, a framework can be a simulator that performs simulations to
generation
simulation results that approximate results that have occurred, are occurring
or may
occur in the real-world. In the context of drilling, such a framework can
provide for
execution of scenarios that can be part of a workflow or workflows as to
planning,
control, etc. As to control, a scenario may be based on data acquired by one
or
more sensors during one or more well construction operations such as, for
example,
directional drilling. In such an approach, determinations can be made using
scenario
result(s) that can directly and/or indirectly control one or more aspects of
directional
drilling. For example, consider control of sliding and/or rotating as modes of
performing directional drilling.
[00214] Figs. 47 and 48 show example GUIs 4700 and 4800 that include
various types of information with respect to time, which may be a proxy for
depth. As
example, the GUIs 4700 and 4800 can be part of a data workflow integration
that
can provide for measured bit RPM for mud motor runs, etc. As an example, a
motor
efficiency computation workflow can be integrated with a data workflow for
downhole
data and/or other data acquisition. As an example, a system may receive data
from
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one or more downhole components, which may include one or more of
accelerometers, gyroscopes, location circuitry (e.g., GPS, etc.), etc.
[00215] Fig. 49 shows an example of a GUI 4900 of a data acquisition
framework (e.g., consider a TECHLOG plugin framework, etc.). As shown, a
graphical control for mud motor interpretation may be provided for actuating
one or
more mud motor and/or bit analysis, control, etc., components.
[00216] Fig. 50 shows an example of a system 5000 and a GUI 5010. As
shown, the system 5000 can be described in terms of an architecture for real-
time
mud motor health monitoring, which may be operatively coupled to field
equipment
for purposes of decision making, control, etc. As shown, various inputs can be
field-
based such as via one or more Internet of things (loT) components. Data may be
acquired via one or more systems, databases, etc. (e.g., QTRAC, MySQL, QUEST,
Performance Took Kit (PTK), INTERACT, etc.).
[00217] As shown, processing can provide for processing of data such as,
for
example, temperature, mud flow, standpipe pressure (SPP), status(es) (e.g.,
bit on
bottom, etc.), hole depth (e.g., measured depth, etc.), time, etc. As
indicated,
specific properties for each power section can be utilized along with, for
example,
one or more physics-based models of a power section and/or one or more data-
driven approaches that utilize one or more machine learning techniques (e.g.,
one or
more machine learning models, etc.). As shown, the system 5000 can include a
surrogate reduced order model of a mud motor power section. Such an approach
may function to provide for fatigue analysis for a mud motor power section.
[00218] As shown, the system 5000 can utilize cloud-based resources. Such
a
system may operate in real-time to output results (e.g., degradation results,
etc.),
which may be utilized in a feedback manner to field operations at one or more
wellsites. As indicated, a result may be a remaining useful life (RUL), which
can be
based at least in part on degradation results. As shown in the example GUI
5010, a
plot may be rendered for RUL during drilling with respect to time and/or
depth. As
shown, a particular power section can be identified along with a type of mud
motor
material (e.g., a type of rubber, etc.). As explained, degradation of an
elastomeric
material during drilling may result in a decrease in RUL. As explained,
integrity of
elastomeric material of a mud motor can depend on various factors. As
indicated,
wellsite data can be provided in real-time where such data can be processed
using
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one or more types of models along with specific properties of a power section
in real-
time to provide real-time output (e.g., results, etc.), which can be utilized
in control of
real-time operations at a wellsite.
[00219] As explained with respect to various GUIs, one or more types of
possible degradation and/or failure mechanisms may be identified using results
of a
system such as the system 5000 of Fig. 50. In such an approach, one or more
notifications may be issued as to one or more actions that may be taken at a
wellsite
to address a trend as to possible degradation, failure, etc. In such an
example, a
drilling operation may be controlled such that one or more goals are met such
as, for
example, reaching an end of a planned drilling run (e.g., a desired measured
depth,
etc.) before having to pull a drillstring out of the hole (POOH). As
explained, an
unplanned trip (e.g., POOH followed by RIH), can result in non-productive time
(NPT). In general, drilling operations aim to minimize NPT.
[00220] As an example, a mud motor can be re-used, from run-to-run,
whether
for a common hole, another hole, etc. In such an example, where reuse occurs,
maintenance may be performed on the mud motor, which may involve replacement
of elastomeric material. As explained, elastomeric material may degrade or
fail
during a run. Where degradation is monitored during a run, one or more
decisions
may be made (e.g., at surface) in preparation of a subsequent run. For
example, a
decision may be made as to whether maintenance and/or replacement of
elastomeric material is/are to occur before a subsequent run or whether
another mud
motor is to be utilized for the subsequent run. As explained, condition of
elastomeric
material may be relevant to drillstring behavior such as, for example,
vibrational
behavior, oscillatory behavior, etc., as a mud motor includes a rotating
component or
rotating components that can give rise to various types of drillstring
behaviors.
[00221] Fig. 51 shows an example of a GUI 5100 of a system such as, for
example, a drilling operations framework. As shown in Fig. 51, the GUI 5100
can
include various graphics, graphical controls, etc., as to drilling operations
such as, for
example, depth (e.g., actual and planned), toolface angle, differential
pressure,
weight on bit (WOB), flow rate (e.g., mud flow rate), RPM, etc. As shown,
various
types of information such as hookload, standpipe pressure and torque may be
rendered in such a GUI.
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[00222] Fig. 52 shows various examples of GUIs 5200, which include a RPM
GUI 5210, a torque GUI 5220, a motor degradation GUI 5230, a motor power GUI
5240, a motor differential pressure GUI 5250 and a motor efficiency GUI 5260.
Such
GUIs can be part of a system such as, for example, the system 5000 of Fig. 50,
etc.
As shown, various operational limits, thresholds, etc., may be set in the GUIs
5200
that can provide for visualization of operations, issuance of notifications,
control
signals, alarms, etc.
[00223] As shown in the GUI 5230, a high degradation ratio (see, e.g., the
metric "R") can be set that can correspond to a pull out of hole (POOH)
signal. For
example, if the degradation ratio reaches the indicated limit, a notification
can be
issued to stop drilling and to pull the drillstring out of the bore for
servicing the mud
motor (e.g., replacing a liner, replacing the mud motor, replacing the mud
motor and
the bit, etc.). The GUI 5230 can provide a range of degradation where a low
degradation may indicate that drilling can be more aggressive if appropriate
and
where a higher degradation may indicate that drilling can be less aggressive
if
appropriate (e.g., to conserve life of the mud motor to increase probability
of
completing a drilling run, etc.).
[00224] As shown in the GUI 5260, motor efficiency can be rendered
utilizing
one or more graphics where an operator, controller, etc., may aim to operate
within a
particular efficiency range (e.g., 30 percent to 60 percent). In the GUIs 5230
and
5260, current motor degradation and current motor efficiency may be rendered
such
that an operator, controller, etc., can be aware of one or more relationships
between
degradation and efficiency such that one or more tradeoffs may be made during
drilling operations.
[00225] As explained, degradation and/or efficiency may depend on
location,
type of formation, etc., such that results may be associated with particular
locations
(e.g., particular fields, basins, etc.). As an example, a system may provide
differences in motor efficiencies and/or degradations at different locations
along with
different motor models, etc.
[00226] As mentioned, motor torque may be calculated using different
pressure
and torque slope of a motor curve. As an example, mechanical specific energy
(MSE) can be calculated at the surface and/or downhole/torsional MSE. In such
an
example, MSE may be split into a surface and a downhole component. As an
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example, a system may provide for estimates of motor power output, which may
be
with respect to time, depth, etc. As explained, a system can provide for
degradation
rate and one or more predictions as to life of a motor, which may include
providing
an estimate of when the motor may fail. As explained, one or more
notifications may
be issued as to field operations that can be taken to increase life to assure
that a
motor reaches an end of a run. For example, clustering of degradation change
rates
may be utilized for various runs where such clusters can be used to advise how
long
or how far an engineer (e.g., or an automated drilling system) can drill
before a
change in mud motor or operation thereof is likely be demanded.
[00227] As explained, a motor efficiency analysis can be used in real-time
to
provide recommendations for motor changes, tripping, and/or provide more
accurate
estimations for time and depth. Such an analysis may be used to help plan
wells by
allowing planners to do bit-motor offset analysis and select the best bit-
motor-BHA
combination for a drillstring for a particular well based on performance of
offset wells.
Such an approach can account for formation characteristics (e.g., lithology,
etc.) and
may account for factors such as vibration, oscillation, etc. As an example, a
method
may account for borehole integrity such that a sufficiently sturdy borewall is
formed
that is not likely to collapse.
[00228] As an example, a method can include performing simulations, which
may provide results to quality control estimates, to supplement estimates, to
enhance estimates, etc. For example, consider a system that can output a
remaining life of a power section of a mud motor with a particular bit where
bit wear,
etc., may be taken into account. In such an example, where an issue may exist
as to
an ability to successfully complete a run, a simulator may be utilized to
perform
simulations to double check the remaining life, an ability to complete the
run, etc.
Such an approach may utilized cloud-based resources where simulation results
may
or may not be provided in real-time or near real-time. For example, consider a
simulation that can run in about 30 minutes as to a future state of a drilling
operation
that may be expected to be encountered in an amount of time that is greater
than 30
minutes. In such an example, real-time results of remaining life as to future
drilling
can be checked via detailed simulation where the detailed simulation results
are
available without having to halt drilling (e.g., encounter NPT, etc.) and in
advance of
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a future drilling state where one or more control actions may be taken to
enhance
remaining life, if appropriate.
[00229] As
explained, a system can provide for implementation of a real-time
efficiency workflow. Such a workflow may generate instantaneous motor power,
torque, and efficiency and illustrate an optimization range. For example, one
or
more of the GUIs of Figs. 51 and 52 may be utilized to show real-time and
track
history of the motor torque, motor efficiency, and motor power and/or to set
one or
more warning thresholds for motor efficiency, motor power, differential
pressure, and
a motor degradation indicator. As explained, one or more GUIs may show one or
more degradation status indicators and provide an indicator for a driller
(e.g., human,
machine, etc.) when degradation jeopardizes one or more objectives and/or
performance indicators (Pis).
[00230] As
explained, the GUI 4500 of Fig. 45 can provide for performing bit-
motor offset analysis as part of an offset well analysis at a planning stage
and/or
provide for one or more analyses in real-time. As explained, a system can
provide
output such as an indicator as to when (e.g., time and/or depth) a trip out
(POOH) is
to occur, for example, to replace and/or service a mud motor and/or a bit.
Such a
system can provide information on parameter optimization for a bit and motor
system
(e.g., for planning, replacement, etc.). As an example, information from one
run for a
section of a well may inform decision making as to another run for the same
section
or another section of the well. In such an approach, engineers may have a
better
understanding of which combinations of mud motors and bits are most efficient
for
drilling operations (see, e.g., the GUI 4600 of Fig. 46, etc.).
[00231] As
explained, a mud motor health analyzer may be used for real-time
mud motor health monitoring. For example, in Fig. 50, the system 5000 can
provide
an indicator that can inform a GUI such that a red, yellow and/or green
light(s) may
be shown as output for a human where red indicates poor health, yellow
indicates an
intermediate health and green indicates good health. As explained, an
indication
may be provided as to whether, for example, a motor can be re-run, whether the
motor is at the end of its life, or an expected remaining life for the motor.
As an
example, a system may recommend servicing of a mud motor by replacing a liner
with a same type of liner or a different liner (e.g., a different elastomeric
material,
etc.).
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[00232] As an example, a system can provide for computing motor
degradation, motor efficiency, motor remaining life from drilling data, motor
efficiency
range from drilling data, etc. As an example, such a system may include and/or
be
operatively coupled to a visualization framework that can call for rendering
of one or
more GUIs. For example, consider the ability to format of displaying
degradation in
real-time, which may utilize a time history, a box whisker, a dial plot, etc.
In such
examples, one or more GUIs may provide risk level indicators, which may be
based
target well drilling and/or offset drilling data, for example, to issue an
alert as to
motor severe degradation. As an example, a system may provide for formatting
of
displays for efficiency in real-time (e.g., time history, box whisker, dial
plot, etc.),
which may include risk levels based on target well drilling and/or offset
drilling data
(e.g., to recommend appropriate drilling parameters, etc.).
[00233] As explained, a system may provide for selections,
recommendations,
etc., as to one or more drilling parameters (e.g., consider a parameter
advisory
system, etc.). As explained, a system may provide for manual, semi-automated
and/or automated control. For example, a system may be operatively coupled to
an
AutoROP system, etc.
[00234] Fig. 53 shows an example of a method 5300 and an example of a
system 5390. In the example of Fig. 53, the method can include a reception
block
5310 for receiving real-time data during a drilling operation performed by a
drillstring
that includes a mud motor and a bit characterized by an expected performance
profile; a determination block 5320 for determining actual performance of the
drillstring based at least in part on the real-time data; a prediction block
5330 for
predicting degraded performance of the drillstring based at least in part on
the real-
time data and a mud motor degradation model; and an update block 5340 for
updating the expected performance profile based on a comparison of the actual
performance and the degraded performance.
[00235] In the example of Fig. 53, the system 5390 includes one or more
information storage devices 5391, one or more computers 5392, one or more
networks 5395 and instructions 5396. As to the one or more computers 5392,
each
computer may include one or more processors (e.g., or processing cores) 5393
and
memory 5394 for storing the instructions 5396, for example, executable by at
least
one of the one or more processors. As an example, a computer may include one
or
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more network interfaces (e.g., wired or wireless), one or more graphics cards,
a
display interface (e.g., wired or wireless), etc.
[00236] The method 5300 is shown along with various computer-readable
media blocks 5311, 5321, 5331 and 5341 (e.g., CRM blocks). Such blocks may be
utilized to perform one or more actions of the method 5300. For example,
consider
the system 5390 of Fig. 53 and the instructions 5396, which may include
instructions
of one or more of the CRM blocks 5311, 5321, 5331 and 5341.
[00237] As mentioned, one or more machine learning techniques may be
utilized to enhance process operations, a process operations environment, a
communications framework, etc. As explained, various types of information can
be
generated via operations of a communications framework where such information
may be utilized for training one or more types of machine learning models to
generate one or more trained machine learning models, which may be deployed
within one or more frameworks, environments, etc.
[00238] As to types of machine learning models, consider one or more of a
support vector machine (SVM) model, a k-nearest neighbors (KNN) model, an
ensemble classifier model, a neural network (NN) model, etc. As an example, a
machine learning model can be a deep learning model (e.g., deep Boltzmann
machine, deep belief network, convolutional neural network, stacked auto-
encoder,
etc.), an ensemble model (e.g., random forest, gradient boosting machine,
bootstrapped aggregation, AdaBoost, stacked generalization, gradient boosted
regression tree, etc.), a neural network model (e.g., radial basis function
network,
perceptron, back-propagation, Hopfield network, etc.), a regularization model
(e.g.,
ridge regression, least absolute shrinkage and selection operator, elastic
net, least
angle regression), a rule system model (e.g., cubist, one rule, zero rule,
repeated
incremental pruning to produce error reduction), a regression model (e.g.,
linear
regression, ordinary least squares regression, stepwise regression,
multivariate
adaptive regression splines, locally estimated scatterplot smoothing, logistic
regression, etc.), a Bayesian model (e.g., naive Bayes, average on-dependence
estimators, Bayesian belief network, Gaussian nave Bayes, multinomial naive
Bayes, Bayesian network), a decision tree model (e.g., classification and
regression
tree, iterative dichotomiser 3, C4.5, C5.0, chi-squared automatic interaction
detection, decision stump, conditional decision tree, M5), a dimensionality
reduction
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model (e.g., principal component analysis, partial least squares regression,
Sammon
mapping, multidimensional scaling, projection pursuit, principal component
regression, partial least squares discriminant analysis, mixture discriminant
analysis,
quadratic discriminant analysis, regularized discriminant analysis, flexible
discriminant analysis, linear discriminant analysis, etc.), an instance model
(e.g., k-
nearest neighbor, learning vector quantization, self-organizing map, locally
weighted
learning, etc.), a clustering model (e.g., k-means, k-medians, expectation
maximization, hierarchical clustering, etc.), etc.
[00239] As an example, a machine model may be built using a computational
framework with a library, a toolbox, etc., such as, for example, those of the
MATLAB
framework (MathWorks, Inc., Natick, Massachusetts). The MATLAB framework
includes a toolbox that provides supervised and unsupervised machine learning
algorithms, including support vector machines (SVMs), boosted and bagged
decision
trees, k-nearest neighbor (KNN), k-means, k-medoids, hierarchical clustering,
Gaussian mixture models, and hidden Markov models. Another MATLAB framework
toolbox is the Deep Learning Toolbox (DLT), which provides a framework for
designing and implementing deep neural networks with algorithms, pretrained
models, and apps. The DLT provides convolutional neural networks (ConyNets,
CNNs) and long short-term memory (LSTM) networks to perform classification and
regression on image, time-series, and text data. The DLT includes features to
build
network architectures such as generative adversarial networks (GANs) and
Siamese
networks using custom training loops, shared weights, and automatic
differentiation.
The DLT provides for model exchange various other frameworks.
[00240] As an example, the TENSORFLOW framework (Google LLC, Mountain
View, CA) may be implemented, which is an open source software library for
dataflow programming that includes a symbolic math library, which can be
implemented for machine learning applications that can include neural
networks. As
an example, the CAFFE framework may be implemented, which is a DL framework
developed by Berkeley Al Research (BAIR) (University of California, Berkeley,
California). As another example, consider the SCIKIT platform (e.g., scikit-
learn),
which utilizes the PYTHON programming language. As an example, a framework
such as the APOLLO Al framework may be utilized (APOLLO.AI GmbH, Germany).
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As an example, a framework such as the PYTORCH framework may be utilized
(Facebook Al Research Lab (FAIR), Facebook, Inc., Menlo Park, California).
[00241] As an example, a training method can include various actions that
can
operate on a dataset to train a ML model. As an example, a dataset can be
split into
training data and test data where test data can provide for evaluation. A
method can
include cross-validation of parameters and best parameters, which can be
provided
for model training.
[00242] The TENSORFLOW framework can run on multiple CPUs and GPUs
(with optional CUDA (NVIDIA Corp., Santa Clara, California) and SYCL (The
Khronos Group Inc., Beaverton, Oregon) extensions for general-purpose
computing
on graphics processing units (GPUs)). TENSORFLOW is available on 64-bit LINUX,
MACOS (Apple Inc., Cupertino, California), WINDOWS (Microsoft Corp., Redmond,
Washington), and mobile computing platforms including ANDROID (Google LLC,
Mountain View, California) and IOS (Apple Inc.) operating system based
platforms.
[00243] TENSORFLOW computations can be expressed as stateful dataflow
graphs; noting that the name TENSORFLOW derives from the operations that such
neural networks perform on multidimensional data arrays. Such arrays can be
referred to as "tensors".
[00244] As an example, a device may utilize TENSORFLOW LITE (TFL) or
another type of lightweight framework. TFL is a set of tools that enables on-
device
machine learning where models may run on mobile, embedded, and loT devices.
TFL is optimized for on-device machine learning, by addressing latency (no
round-
trip to a server), privacy (no personal data leaves the device), connectivity
(Internet
connectivity is demanded), size (reduced model and binary size) and power
consumption (e.g., efficient inference and a lack of network connections).
Multiple
platform support, covering ANDROID and iOS devices, embedded LINUX, and
microcontrollers. Diverse language support, which includes JAVA, SWIFT,
Objective-C, C++, and PYTHON. High performance, with hardware acceleration and
model optimization. Machine learning tasks may include, for example, image
classification, object detection, pose estimation, question answering, text
classification, etc., on multiple platforms.
[00245] As an example, a system can provide for one or more real-time mud
motor efficiency metrics, which can include, for example, one or more
degradation
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metrics. As explained, a system can acquire real-time data, compare
performance
with predicted performance based on estimated degradation (e.g., wear, etc.),
and
update expected performance (e.g., efficiency, life, etc.) for a motor as it
is utilized in
drilling.
[00246] As an example, an expected performance profile can be generated
during a planning phase of a drilling operation. For example, a planning
framework
may utilize mud motor specifications along with conditions for drilling that
aim to
provide a desired wellbore according to a desired wellbore trajectory. In such
an
example, an expected performance profile may be account for mud motor
degradation or not. As an example, an expected performance profile may account
for mud motor wear and/or bit wear and/or combined mud motor and bit wear. As
an
example, a system that can predict degraded performance may be utilized in
planning, for example, to generate a more accurate expected performance
profile
(e.g., a profile with respect to depth and/or time). As explained, during an
actual
drilling operation, real-time data can be acquired such that predictions as to
degraded performance can be more relevant than predictions in a planning phase
(e.g., as may be based in part on simulated drilling, etc.). Thus, a real-time
system
for prediction of degraded performance can improve drilling operations beyond
that
provided by planning alone. As explained, with real-time predictions of
degraded
performance, drilling operations may be controlled in real-time for one or
more
purposes (e.g., to reach a target, to reach an end of a run, to reduce risk of
failure, to
reduce NPT, etc.).
[00247] As an example, an expected performance profile may be updated
during drilling operations such that it is continually refined. At the end of
a drilling
run, such a performance profile may mirror actual performance and may provide
insights as to improvements to performance, for example, for one or more
additional
runs in the same hole and/or in another hole (e.g., at least in part drilled
or to be
drilled).
[00248] As an example, a method can include receiving real-time data
during a
drilling operation performed by a drillstring that includes a mud motor and a
bit
characterized by an expected performance profile; determining actual
performance
of the drillstring based at least in part on the real-time data; predicting
degraded
performance of the drillstring based at least in part on the real-time data
and a mud
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motor degradation model; and updating the expected performance profile based
on a
comparison of the actual performance and the degraded performance. In such an
example, the mud motor degradation model can predict efficiency of the mud
motor.
For example, Fig. 50 shows the system 5000 as including a surrogate reduced
order
model of a mud motor power section where components can include one or more
physics-based models and one or more data-driven models (e.g., one or more
machine learning models). In such an example, degradation of a mud motor can
be
predicted, which can be an indication of fatigue (e.g., wear, etc.).
[00249] As explained, data from various drilling runs indicates that a
correlation
can exist between drilled length and motor degradation, which can be specific
to
particular equipment, fields, etc. As explained, various data can be utilized,
which
may be indicative of energy, power, etc. As explained, computed nominal RPM of
a
mud motor and measured RPM of a mud motor may be utilized in determining
various performance metrics. Where a drilling run is expected to drill a
particular
distance (e.g., length) with a mud motor, degradation may alter such
expectations.
As explained, a system can provide for predictions of degradation (e.g.,
degraded
performance, etc.) in real-time, which can inform drilling, particularly as to
whether or
not the drilling run can be completed (e.g., reach the particular distance)
with a
current mud motor (e.g., or mud motor and bit combination).
[00250] As an example, a mud motor degradation model can accounts for
degradation of a liner of the mud motor (e.g., directly and/or indirectly). In
such an
example, the liner can include an elastomeric material.
[00251] As an example, a method can include predicting degraded
performance in a manner that includes predicting a degradation rate. With a
degradation rate, future degradation of performance may be estimated. As an
example, a method can include accounting for past degradation (e.g., consider
cumulative degradation, etc.).
[00252] As an example, a method can include generating a target range for
degradation of a mud motor and/or generating a target range for efficiency of
a mud
motor.
[00253] As an example, a method can include, if degraded performance
exceeds a degraded performance threshold, issuing a pull out of hole (POOH)
notification. Such an approach can provide for removing a mud motor from a
hole
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prior to failure of the mud motor (e.g., degradation to a point of
inoperability, etc.).
As explained, degradation may result in drillstring behaviors that can be
detrimental
(e.g., vibration, oscillations, etc.).
[00254] As an example, a method can include rendering a graphical user
interface to a display that includes a mud motor degradation graphic and a mud
motor efficiency graphic.
[00255] As an example, a method can include rendering a graphical user
interface to a display that includes a graphic of remaining useful life of at
least a mud
motor versus time for a drilling operation.
[00256] As an example, a method can include rendering a graphical user
interface to a display that includes a graphic of mud flow rate, differential
pressure,
mud motor efficiency and a current status that is based at least in part on
real-time
data.
[00257] As an example, a method can include predicting degraded
performance by utilizing a computed nominal RPM of the mud motor and a
measured RPM of the mud motor, where the measured RPM of the mud motor is
less than the computed nominal RPM of the mud motor. In such an example, the
computed nominal RPM and the measured RPM can be for an operational
differential pressure. As an example, a measured RPM can be less than a
computed nominal RPM due at least in part to degradation of the mud motor.
[00258] As an example, a method can include receiving real-time data that
include surface data and downhole data.
[00259] As an example, a method can include issuing a control signal based
at
least in part on degraded performance. In such an example, issuing can issue a
control signal to an automated rate of penetration controller (e.g., AutoROP
controller, etc.).
[00260] As an example, a method can include, based at least in part on
degraded performance, identifying a potential type of failure.
[00261] As an example, a system can include a processor; memory accessible
to the processor; processor-executable instructions stored in the memory and
executable by the processor to instruct the system to: receive real-time data
during a
drilling operation performed by a drillstring that includes a mud motor and a
bit
characterized by an expected performance profile; determine actual performance
of
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the drillstring based at least in part on the real-time data; predict degraded
performance of the drillstring based at least in part on the real-time data
and a mud
motor degradation model; and update the expected performance profile based on
a
comparison of the actual performance and the degraded performance.
[00262] As an example, one or more computer-readable media can include
computer-executable instructions executable by a system to instruct the system
to:
receive real-time data during a drilling operation performed by a drillstring
that
includes a mud motor and a bit characterized by an expected performance
profile;
determine actual performance of the drillstring based at least in part on the
real-time
data; predict degraded performance of the drillstring based at least in part
on the
real-time data and a mud motor degradation model; and update the expected
performance profile based on a comparison of the actual performance and the
degraded performance.
[00263] As an example, a computer program product can include one or more
computer-readable storage media that can include processor-executable
instructions
to instruct a computing system to perform one or more methods and/or one or
more
portions of a method.
[00264] In some embodiments, a method or methods may be executed by a
computing system. Fig. 54 shows an example of a system 5400 that can include
one or more computing systems 5401-1, 5401-2, 5401-3 and 5401-4, which may be
operatively coupled via one or more networks 5409, which may include wired
and/or
wireless networks.
[00265] As an example, a system can include an individual computer system
or
an arrangement of distributed computer systems. In the example of Fig. 54, the
computer system 5401-1 can include one or more modules 5402, which may be or
include processor-executable instructions, for example, executable to perform
various tasks (e.g., receiving information, requesting information, processing
information, simulation, outputting information, etc.).
[00266] As an example, a module may be executed independently, or in
coordination with, one or more processors 5404, which is (or are) operatively
coupled to one or more storage media 5406 (e.g., via wire, wirelessly, etc.).
As an
example, one or more of the one or more processors 5404 can be operatively
coupled to at least one of one or more network interface 5407. In such an
example,
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the computer system 5401-1 can transmit and/or receive information, for
example,
via the one or more networks 5409 (e.g., consider one or more of the Internet,
a
private network, a cellular network, a satellite network, etc.).
[00267] As an example, the computer system 5401-1 may receive from and/or
transmit information to one or more other devices, which may be or include,
for
example, one or more of the computer systems 5401-2, etc. A device may be
located in a physical location that differs from that of the computer system
5401-1.
As an example, a location may be, for example, a processing facility location,
a data
center location (e.g., server farm, etc.), a rig location, a wellsite
location, a downhole
location, etc.
[00268] As an example, a processor may be or include a microprocessor,
microcontroller, processor module or subsystem, programmable integrated
circuit,
programmable gate array, or another control or computing device.
[00269] As an example, the storage media 5406 may be implemented as one
or more computer-readable or machine-readable storage media. As an example,
storage may be distributed within and/or across multiple internal and/or
external
enclosures of a computing system and/or additional computing systems.
[00270] As an example, a storage medium or storage media may include one
or more different forms of memory including semiconductor memory devices such
as
dynamic or static random access memories (DRAMs or SRAMs), erasable and
programmable read-only memories (EPROMs), electrically erasable and
programmable read-only memories (EEPROMs) and flash memories, magnetic disks
such as fixed, floppy and removable disks, other magnetic media including
tape,
optical media such as compact disks (CDs) or digital video disks (DVDs),
BLUERAY
disks, or other types of optical storage, or other types of storage devices.
[00271] As an example, a storage medium or media may be located in a
machine running machine-readable instructions, or located at a remote site
from
which machine-readable instructions may be downloaded over a network for
execution.
[00272] As an example, various components of a system such as, for
example,
a computer system, may be implemented in hardware, software, or a combination
of
both hardware and software (e.g., including firmware), including one or more
signal
processing and/or application specific integrated circuits.
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[00273] As an example, a system may include a processing apparatus that
may
be or include a general purpose processors or application specific chips
(e.g., or
chipsets), such as ASICs, FPGAs, PLDs, or other appropriate devices.
[00274] Fig. 55 shows components of an example of a computing system 5500
and an example of a networked system 5510 with a network 5520. The system 5500
includes one or more processors 5502, memory and/or storage components 5504,
one or more input and/or output devices 5506 and a bus 5508. In an example
embodiment, instructions may be stored in one or more computer-readable media
(e.g., memory/storage components 5504). Such instructions may be read by one
or
more processors (e.g., the processor(s) 5502) via a communication bus (e.g.,
the
bus 5508), which may be wired or wireless. The one or more processors may
execute such instructions to implement (wholly or in part) one or more
attributes
(e.g., as part of a method). A user may view output from and interact with a
process
via an I/O device (e.g., the device 5506). In an example embodiment, a
computer-
readable medium may be a storage component such as a physical memory storage
device, for example, a chip, a chip on a package, a memory card, etc. (e.g., a
computer-readable storage medium).
[00275] In an example embodiment, components may be distributed, such as
in
the network system 5510. The network system 5510 includes components 5522-1,
5522-2, 5522-3, . . . 5522-N. For example, the components 5522-1 may include
the
processor(s) 5502 while the component(s) 5522-3 may include memory accessible
by the processor(s) 5502. Further, the component(s) 5522-2 may include an I/O
device for display and optionally interaction with a method. A network 5520
may be
or include the Internet, an intranet, a cellular network, a satellite network,
etc.
[00276] As an example, a device may be a mobile device that includes one
or
more network interfaces for communication of information. For example, a
mobile
device may include a wireless network interface (e.g., operable via IEEE
802.11,
ETSI GSM, BLUETOOTH, satellite, etc.). As an example, a mobile device may
include components such as a main processor, memory, a display, display
graphics
circuitry (e.g., optionally including touch and gesture circuitry), a SIM
slot,
audio/video circuitry, motion processing circuitry (e.g., accelerometer,
gyroscope),
wireless LAN circuitry, smart card circuitry, transmitter circuitry, GPS
circuitry, and a
battery. As an example, a mobile device may be configured as a cell phone, a
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tablet, etc. As an example, a method may be implemented (e.g., wholly or in
part)
using a mobile device. As an example, a system may include one or more mobile
devices.
[00277] As an example, a system may be a distributed environment, for
example, a so-called "cloud" environment where various devices, components,
etc.
interact for purposes of data storage, communications, computing, etc. As an
example, a device or a system may include one or more components for
communication of information via one or more of the Internet (e.g., where
communication occurs via one or more Internet protocols), a cellular network,
a
satellite network, etc. As an example, a method may be implemented in a
distributed
environment (e.g., wholly or in part as a cloud-based service).
[00278] As an example, information may be input from a display (e.g.,
consider
a touchscreen), output to a display or both. As an example, information may be
output to a projector, a laser device, a printer, etc. such that the
information may be
viewed. As an example, information may be output stereographically or
holographically. As to a printer, consider a 2D or a 3D printer. As an
example, a 3D
printer may include one or more substances that can be output to construct a
3D
object. For example, data may be provided to a 3D printer to construct a 3D
representation of a subterranean formation. As an example, layers may be
constructed in 3D (e.g., horizons, etc.), geobodies constructed in 3D, etc. As
an
example, holes, fractures, etc., may be constructed in 3D (e.g., as positive
structures, as negative structures, etc.).
[00279] Although only a few example embodiments have been described in
detail above, those skilled in the art will readily appreciate that many
modifications
are possible in the example embodiments. Accordingly, all such modifications
are
intended to be included within the scope of this disclosure as defined in the
following
claims. In the claims, means-plus-function clauses are intended to cover the
structures described herein as performing the recited function and not only
structural
equivalents, but also equivalent structures. Thus, although a nail and a screw
may
not be structural equivalents in that a nail employs a cylindrical surface to
secure
wooden parts together, whereas a screw employs a helical surface, in the
environment of fastening wooden parts, a nail and a screw may be equivalent
structures.
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