Note: Descriptions are shown in the official language in which they were submitted.
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METHOD FOR ABANDONING WELLBORES
CROSS-REFERENCE TO RELATED APPLICATIONS
100011 Not applicable.
BACKGROUND
[0002] Within a hydrocarbon production well, various fluids such as
hydrocarbons, water,
gas, and the like can be produced from the formation into the wellbore. The
production of
the fluid can result in the movement of the fluids in various downhole
regions, including with
the subterranean formation, from the formation into the wellbore, and within
the wellbore
itself. Following production, plugs are positioned in a well to be abandoned
in order to
prevent leaks of fluid from the well.
BRIEF SUMMARY OF THE DISCLOSURE
[0003] In an embodiment, a method of abandoning a wellbore comprises obtaining
a first
sample data set within a wellbore, wherein the first sample data set is a
sample of an acoustic
signal originating within the wellbore; determining a first plurality of
frequency domain
features of the first sample data set; identifying a first fluid flow location
within the wellbore
using the first plurality of frequency domain features; setting a first
barrier at or above the
first fluid flow location; obtaining a second sample data set within the
wellbore above the
first barrier, wherein the second sample data set is a sample of an acoustic
signal originating
within the wellbore above the first barrier; determining a second plurality of
frequency
domain features of the second sample data set; and identifying that that a
fluid flow rate or
fluid flow mechanism at the first fluid flow location has been reduced or
eliminated and/or
identifying a second fluid flow location within the wellbore using the second
plurality of
frequency domain features. The first sample data and the second sample data
set can
comprise a sample of an acoustic signal originating within the wellbore, and
can be
representative of the acoustic signal across a frequency spectrum.
[0004] In an embodiment, a system for abandoning a wellbore, the system
comprising: a
receiver unit comprising a processor and a memory, wherein the receiver unit
is configured to
receive an acoustic signal from a sensor disposed in a wellbore, wherein a
processing
application is stored in the memory, and wherein the processing application,
when executed
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on the processor, configures the processor to: receive a first baseline
acoustic signal data set
from the sensor, wherein the first baseline acoustic signal data set comprises
an indication of
the acoustic signal received over a first depth interval while the wellbore is
shut in; receive a
first flowing acoustic signal data set, wherein the first flowing acoustic
signal data set
comprises an indication of the acoustic signal received over the first depth
interval while a
first pressure differential is induced within the wellbore; determine a
baseline fluid flow log
using the first baseline acoustic signal data set; determine a flowing fluid
flow log using the
first flowing acoustic signal data set; subtract the baseline fluid flow log
from the flowing
fluid flow log to provide a first sample data set; determine a first plurality
of frequency
domain features of the first sample data set; identify a first fluid flow
location within the
wellbore using the first plurality of frequency domain features; determine a
change in a flow
rate or flow mechanism at the first fluid flow location using the first sample
data set; and
generate an output indicative of the first fluid flow location and a change in
the flow rate or
flow mechanism at the first fluid flow location. The acoustic signal can be
indicative of the
acoustic signal across a frequency spectrum.
[0005] In an embodiment, a method of comparing acoustic signals obtained
between
different acoustic sensor operations in a wellbore comprises: obtaining a
first baseline
sample data set over a first depth interval within a wellbore, wherein the
first baseline data set
is a sample of an acoustic signal originating within the wellbore; determining
at least one
frequency domain feature of the first baseline sample data set; inducing a
first pressure
differential within the wellbore; obtaining a first acoustic data set over the
first depth interval
within the wellbore while inducing the first pressure differential;
determining at least one
frequency domain feature of the first acoustic data set; subtracting the at
least one frequency
domain feature of the first baseline sample data set from the at least one
frequency domain
feature of the first acoustic data set to obtain a first sample data set over
the first depth
interval; obtaining a second baseline sample data set over a second depth
interval within the
wellbore, wherein the second baseline sample data set is a sample of an
acoustic signal
originating within the wellbore, wherein the second depth interval overlaps
with the first
depth interval; determining at least one frequency domain feature of the
second baseline
sample data set; inducing a second pressure differential within the wellbore;
obtaining a
second acoustic data set over the second depth interval within the wellbore
while inducing the
second pressure differential; determining at least one frequency domain
feature of the second
acoustic data set; subtracting the at least one frequency domain feature of
the second baseline
sample data set from the at least one frequency domain feature of the second
acoustic data set
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to obtain a second sample data set over the second depth interval; and
comparing the second
sample data set to the first sample data set over the second depth interval.
[NW In an embodiment, a system for of comparing acoustic signals obtained
between
different acoustic sensor operations in a wellbore, the system comprising: a
receiver unit
comprising a processor and a memory, wherein the receiver unit is configured
to receive an
acoustic signal from a sensor disposed in a wellbore, wherein a processing
application is
stored in the memory, and wherein the processing application, when executed on
the
processor, configures the processor to: receive a first baseline sample data
set over a first
depth interval within the wellbore, wherein the first baseline data set is a
sample of an
acoustic signal originating within the wellbore; determine at least one
frequency domain
feature of the first baseline sample data set; receive a first acoustic data
set over the first
depth interval within the wellbore, wherein the first acoustic data sat is an
acoustic signal
obtained while a first pressure differential is induced within the wellbore;
determine at least
one frequency domain feature of the first acoustic data set; subtract the at
least one frequency
domain feature of the first baseline sample data set from the at least one
frequency domain
feature of the first acoustic data set to obtain a first sample data set over
the first depth
interval; receive a second baseline sample data set over a second depth
interval within the
wellbore, wherein the second baseline sample data set is a sample of an
acoustic signal
originating within the wellbore, wherein the second depth interval overlaps
with the first
depth interval; determine at least one frequency domain feature of the second
baseline sample
data set; receive a second acoustic data set over the second depth interval
within the wellbore,
wherein the second acoustic data sat is an acoustic signal obtained while a
second pressure
differential is induced within the wellbore; determine at least one frequency
domain feature
of the second acoustic data set; subtract the at least one frequency domain
feature of the
second baseline sample data set from the at least one frequency domain feature
of the second
acoustic data set to obtain a second sample data set over the second depth
interval; compare
the second sample data set to the first sample data set over the second depth
interval; and
generate an output indicative of the comparison between the second sample data
set and the
first sample data set..
(0007] In an embodiment, a method of abandoning a wellbore comprises:
obtaining a first
sample data set over a first depth interval within a wellbore, wherein the
first sample data set
comprises a first acoustic data set having a first baseline acoustic sample
data set subtracted
therefrom, wherein the first acoustic data set is obtained over the first
depth interval while a
first pressure differential is induced in the wellbore, and wherein the first
baseline acoustic
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sample data set is obtained over the first depth interval while the wellbore
is shut in;
identifying a fluid flow location within the first depth interval using the
first sample data set;
obtaining a second sample data set over a second depth interval within a
wellbore, wherein
the second sample data set is obtained after a barrier is set at or above the
fluid flow location,
wherein the second sample data set comprises a second acoustic data set having
a second
baseline acoustic sample data set subtracted therefrom, wherein the second
acoustic data set
is obtained over the second depth interval while a second pressure
differential is induced in
the wellbore, wherein the second baseline acoustic sample data set is obtained
over the
second depth interval while the wellbore is shut in, and wherein the second
depth interval is
overlaps the first depth interval; comparing the first sample data set to the
second sample data
set; and determining whether or not fluid flow at the fluid flow location is
substantially
blocked by the barrier.
[00081 in an embodiment, a system for abandoning a wellbore, the system
comprising: a
receiver unit comprising a processor and a memory, wherein the receiver unit
is configured to
receive an acoustic signal from a sensor disposed in a wellbore, wherein a
processing
application is stored in the memory, and wherein the processing application,
when executed
on the processor, configures the processor to: receive a first baseline
acoustic sample data set
and a first acoustic data set from the sensor, wherein the first acoustic data
set is an acoustic
signal obtained over a first depth interval while a first pressure
differential is induced in the
wellbore, and wherein the first baseline acoustic sample data set is an
acoustic signal
obtained over the first depth interval while the wellbore is shut in,
determine a first sample
data set over a first depth interval within the wellbore, wherein the first
sample data set
comprises the first acoustic data set having the first baseline acoustic
sample data set
subtracted therefrom; identify a fluid flow location within the first depth
interval using the
first sample data set; receive a second baseline acoustic sample data set and
a second acoustic
data set from the sensor, wherein the second acoustic data set is an acoustic
signal obtained
over a second depth interval while a second pressure differential is induced
in the wellbore
and after a barrier is set at or above the fluid flow location, and wherein
the second baseline
acoustic sample data set is an acoustic signal obtained over the second depth
interval while
the wellbore is shut in and after the barrier is set at or above the fluid
flow location;
determine a second sample data set over the second depth interval within the
wellbore,
wherein the second sample data set comprises the second acoustic data set
having the second
baseline acoustic sample data set subtracted therefrom; compare the first
sample data set to
the second sample data set; and determine whether or not fluid flow at the
fluid flow location
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is substantially blocked by the barrier; and generate an output indicative the
determination of
whether or not the fluid flow at the fluid flow location is substantially
blocked by the barrier.
100091 These and other features will be more clearly understood from the
following detailed
description taken in conjunction with the accompanying drawings and claims.
[0010] Embodiments described herein comprise a combination of features and
advantages
intended to address various shortcomings associated with certain prior
devices, systems, and
methods. The foregoing has outlined rather broadly the features and technical
advantages of
the invention in order that the detailed description of the invention that
follows may be better
understood. The various characteristics described above, as well as other
features, will be
readily apparent to those skilled in the art upon reading the following
detailed description,
and by referring to the accompanying drawings. It should be appreciated by
those skilled in
the art that the conception and the specific embodiments disclosed may be
readily utilized as
a basis for modifying or designing other structures for carrying out the same
purposes of the
invention. It should also be realized by those skilled in the art that such
equivalent
constructions do not depart from the spirit and scope of the invention as set
forth in the
appended claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[00111 For a detailed description of the preferred embodiments of the
invention, reference
will now be made to the accompanying drawings in which:
[0012] Figure 1 is a schematic, cross-sectional illustration of a downhole
wellbore
environment according to embodiments of this disclosure.
[0013] Figure 2 is a schematic, cross-sectional illustration of another
downhole wellbore
environment according to embodiments of this disclosure.
[0014] Figure 3A is a schematic view of a wellbore environment 100B prior to
placement of
well barriers.
[0015] Figure 313 is a schematic view of a wellbore environment 100C after
placement of
well barriers.
(00161 Figure 4A is a schematic, cross-sectional view of an embodiment of a
well with a
wellbore tubular having an optical fibre associated therewith.
[0017] Figure 4B is a schematic, cross-sectional view of another embodiment of
a well with a
wellbore tubular having an optical fibre associated therewith.
[0018] Figure 5 illustrates an embodiment of a schematic processing flow for
an acoustic
signal.
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[0019] Figures 6A and 6B illustrate exemplary acoustic depth-time block
graphs.
100201 Figures 7A, 713, and 7C illustrate exemplary filtered acoustic depth-
time graphs.
[00211 Figure 8 illustrates an exemplary fluid flow log according to
embodiments of this
disclosure.
[00221 Figure 9 schematically illustrates a computer that can be used to carry
out various
steps according to some embodiments of this disclosure.
(00231 Figure 10 is a schematic showing baseline logs for three runs of
Example 1: Run 1
prior to placement of a first well barrier element WBE1, referred to in Figure
10 as "Pre 'WBE1
placement; Run 2 after placement of first well barrier element WBE1, referred
to in Figure 10
as "Post WBE I placement"; and Run 3 after placement of second and third well
barrier
elements WBE2/3, referred to in Figure 10 as "Post WBE2/3 placement."
[0024] Figure Ills a schematic showing the DAS logs (e.g., the acoustic logs)
for the baseline
and C bleed of Run 3 (e.g., after setting of second and third well barrier
elements WBE2/3) of
Example I.
[00251 Figure 12 is a schematic of the DAS logs obtained during the B bleeds
of Run 2 (e.g.,
after placement of first well barrier element WBE I) and Run 3 (e.g., after
placement of second
and third well barrier elements WBE2/3) of Example 1.
[00261 Figure 13 is a schematic showing the DAS logs for the baseline, the B
bleed and the C
bleed for Run 3 (e.g., after placement of second and third well barrier
elements WBE2/3) of
Example 1.
100271 Figure 14A is a schematic of the DAS logs for Run 1 (e.g., prior to
placement of first
well barrier element WBE1), including one hour averaged comparisons for the
baseline, the B
bleed, and the C bleed of Example 1.
[0028] Figure 14B is a schematic of the DAS logs for the baseline corrected C
bleed (e.g., the
C bleed minus the baseline) of Run 1 (e.g., prior to placement of first well
barrier element
WBE I) and a baseline smoothed log of the C bleed of Run I of Example 1.
100291 Figure 15A is a schematic of the DAS logs for Run 3 (e.g., after
placement of the
second and third well barrier elements WBE2/3), including one hour averaged
comparisons for
the baseline, the B bleed, and the C bleed of Example 1.
[0030] Figure 15B is a schematic of the DAS logs for the baseline corrected C
bleed (e.g., the
C bleed minus the baseline) of Run 3 (i.e., after placement of second and
third well barrier
elements WBE2/3) and a baseline smoothed log of the C bleed of Run 3 of
Example I.
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100311 Figure 16 is a schematic of the DAS logs of the baseline smoothed C
bleeds of Run I
(e.g., prior to placement of first well barrier element WBE I) and Run 3
(i.e., after placement of
second and third well barrier elements WBE2/3) of Example 1.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
100321 Unless otherwise specified, any use of any form of the terms "connect,"
"engage,"
"couple," "attach," or any other term describing an interaction between
elements is not meant
to limit the interaction to direct interaction between the elements and may
also include
indirect interaction between the elements described. In the following
discussion and in the
claims, the terms "including" and "comprising" are used in an open-ended
fashion, and thus
should be interpreted to mean "including, but not limited to. . . ". Reference
to up or down
will be made for purposes of description with "up," "upper," "upward,"
"upstream," or
"above" meaning toward the surface of the wellbore and with "down," "lower,"
"downward,"
"downstream," or "below" meaning toward the terminal end of the well,
regardless of the
wellbore orientation. Reference to inner or outer will be made for purposes of
description
with "in," "inner," or "inward" meaning towards the central longitudinal axis
of the wellbore
and/or wellbore tubular, and "out," "outer," or "outward" meaning towards the
wellbore wall.
As used herein, the term "longitudinal" or "longitudinally" refers to an axis
substantially
aligned with the central axis of the wellbore tubular, and "radial" or
"radially" refer to a
direction perpendicular to the longitudinal axis. The various characteristics
mentioned above,
as well as other features and characteristics described in more detail below,
will be readily
apparent to those skilled in the art with the aid of this disclosure upon
reading the following
detailed description of the embodiments, and by referring to the accompanying
drawings.
10033] Disclosed herein is a real time signal processing architecture that
allows for the
identification of the presence, location, rate, and flow mechanism of various
downhole fluid
flows (fluid flow refers to fluid inflow, fluid flow within the wellbore,
within an annulus, or
any combination thereof, which may be indicative of a "leak"), whereby one or
more well
barriers can be positioned at or above the one or more fluid flow locations
during plugging
and abandonment (P&A) operations. The signal processing architecture can be
utilized to
identify one or more fluid flow events including fluid flow detection,
pressure source
identification, flow path identification, and phase detection of an flow fluid
in the wellbore
(within a casing, within an annulus, etc.), the formation (e.g., overburden
monitoring, etc.), or
moving between the formation and wellbore. As used herein, the term "fluid
flow
mechanism" can refer to the fluid flow pathway, source, and/or flow type or
phase of a
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flowing fluid. As used herein, the term "real time" refers to a time that
takes into account
various communication and latency delays within a system, and can include
actions taken
within about ten seconds, within about thirty seconds, within about a minute,
within about
five minutes, or within about ten minutes of the action occurring.
10034] In general, zonal isolation and well integrity management are concerns
not only from
the standpoint of operational risk and requirements, but also from an
environmental impact
perspective. Fluid flow detection techniques can include the use of
temperature sensors,
pressure sensors, casing collar locators, multi-finger calipers, spinners, and
sometimes,
density measurement tools deployed in well using intervention technologies, as
well as other
non-invasive evaluation / assessment techniques for detecting flow behind
casing (e.g.,
temperature loping, ultrasonic imaging, oxygen activation (for detection of
water flow
behind casing) with neutrons, and the like).
10035] While one or .a combination of these tools may help provide a
qualitative, and
sometimes quantitative, estimates of fluid flow locations between the
production tubing and
the production casing, these methods suffer from being 'point' measurement
tools (i.e,, tools
that can only transduce a single physical parameter at a certain discrete
location / depth at any
one instance in time). This means that the fluid flows/leaks may not be
captured accurately or
captured at all unless the tools are positioned at the right location at the
right time and/or
unless the fluid flow or leak is large enough to generate a transdueable
signal. This typically
results in longer data acquisition times and limited representations, which
can often impede
decision making and support. None of these tools offer the capability to
monitor the flow of
hydrocarbons behind multiple barriers, for example, in the casing-casing
annuli, and this
presents a challenge in maintaining well integrity. Multi-finger calipers are
also often used to
investigate any diameter variations along the tubing but this process does not
quantify the
extent, rate, or phase of leaking fluid. This also only provides an indication
of potential fluid
flow location based on mechanical assessment of the tubing. Each of these
methods generally'
only provide an indication of a fluid flow location and do not provide the
means to assess
changes in fluid flow rate or fluid flow mechanism (e.g., changes in fluid
flow pathways,
sources, flow types, etc.).
[0036] As described in more detail herein, distributed fibre optic (NO)
sensors for well
integrity assessment use the. fibre to monitor properties along the. length of
a wellbore.
Similarly, distributed temperature sensing systems (DTS) can be used to
measure the
temperature along the wellbore. The main advantage of these DFO sensors is
that the
measurement can be made along the entire length of the wellbore over long
periods of time as
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the entire deployed fibre cable is the sensor. This can avoid the need to move
the tool and aid
in more economical operations. The full wellbore coverage would also enable
studies of fluid
flow evolution through time and depth, consequently enabling precise
identification of when
and where fluid flows occur, rather than piecing together the picture from
various steps in the
logging operation. The use of DTS for leak detection however, brings a few
limitations
including: 1) the use of thermal profiles alone for leak identification often
results in
inconclusive results, and 2) it is difficult to achieve controlled shut in
versus flowing
conditions outside of casing to compare and determine leak locations from
baseline thermal
profiles.
100371 As disclosed herein, a new approach to plugging and abandoning a well
is described
using Distributed Acoustic Sensors (DAS) as the primary data input. This type
of system
offers not only identification of leaks and fluid flow behind casing, but also
enables
categorization of these events in real time or near real time. A data
processing architecture is
also described that processes voluminous DAS data in near real time (e.g.,
within a second,
within ten seconds, etc.) to identify and classify leaks and other "fluid flow
events" indicative
of well barrier performance with a single fibre optic cable deployed in well.
In embodiments,
the data can also be used in conjunction with surface and peripheral sensor
data to enable
semi-quantitative assessments of fluid flow rates.
100381 As further disclosed herein, the DAS data can be used with additional
sensor data
such as pressure data as the primary sensor inputs for determining in-well and
near wellbore
fluid flows. The processing methodology uses a fluid flow event detection
algorithm that
detects and captures acoustic events that are then processed in real-time
using a spectral
descriptor framework for signature recognition and identification of fluid
flow. In
embodiments, the outputs of the fluid flow event detection algorithm can then
be correlated
in time with the additional sensor data (e.g., the pressure gauge
measurements). The
correlation of the signals can enable identification of a pressure source, a
location of a leak, a
flow rate of the leak, a leak flow path, and/or a predominant phase of a
flowing fluid, and
thus be utilized to determine where to set a barrier for well abandonment
and/or determine
whether or not well barrier placement has successfully plugged the well (e.g.,
that placement
of one or more well barriers has reduced or eliminated fluid flow at one or
more identified
fluid flow locations).
100391 The method may also allow for monitoring fluid flows behind multiple
barriers which
are usually not detected using conventional leak detection diagnostics tools.
This ability
enables monitoring of hydrocarbon migration up pathways adjacent to wellbores
to shallower
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zones (cross-flow) and/or into well annuli, thereby enabling real time
monitoring of fluid
movements in the formation and/or annuli and evaluating how to best plug such
fluid flows
for well abandonment,
100401 As described in more detail herein, the system comprises a DAS
interrogator
connected to the fibre optic cable deployed in the well. Various sensors
(e.g., the distributed
fibre optic acoustic sensors, etc.) can be used to obtain an acoustic sampling
at various points
along the wellbore. The acoustic sample can then be processed using signal
processing
architecture with various feature extraction techniques (e.g., spectral
feature extraction
techniques) to obtain a measure of one or more frequency domain features that
enable
selectively extracting the acoustic signals of interest from background noise
and consequently
aiding in improving the accuracy of the identification of the movement of
fluids and/or solids
(e.g., liquid ingress locations, gas influx locations, constricted fluid flow
locations, etc.) in
real time. As used herein, various frequency domain features can be obtained
from the
acoustic signal. In some contexts the frequency domain features can also be
referred to as
spectral features or spectral descriptors. The signal processing techniques
described herein
can also help to address the big-data problem through intelligent extraction
of data (rather
than crude decimation techniques) to considerably reduce real time data -
volutnes at the
collection and processing site (e.g., by over 100 times, over 500 times, or
over 1000 times, or
over 10,000 times reduction).
100411 The acoustic signal can be obtained in a manner that allows for a
signal to be obtained
along the entire wellbore or a portion of interest. Fibre optic distributed
acoustic sensors
(DAS) capture acoustic signals resulting from downhole events such as gas
influx, liquid
influx, fluid flow past restrictions, and the like as well as other background
acoustics as well,
This mandates the need for a robust signal processing procedure that
distinguishes acoustic
signals resulting from events of interest from other noise sources to avoid
false positives in
the results. This in turn results in a need for a clearer understanding of the
acoustic fingerprint
of in-well event of interest (e.g,, fluid flow detection, leak detection,
etc.) in order to he able
to segregate a noise resulting from an event of interest from other ambient
acoustic
background noise. As used herein, the resulting acoustic fingerprint of a
particular event can
also be referred to as a spectral signature. The spectral signature can be
defined by a plurality
of different frequency domain features and/or combination and modifications
thereof, and
corresponding thresholds or ranges for the plurality of different frequency
domain features
and/or combination and modifications thereof', as described in more detail
herein.
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[0042] The ability to identify various fluid flow events in the wellbore may
allow for
appropriate actions to be taken in order to plug the leaks and prepare the
well for
abandonment. For example, a barrier can be positioned at or above one or more
identified
fluid flow locations, and the DAS system utilized to determine whether or not
the barrier is
successful at reducing or eliminating the fluid flow at the one or more fluid
flow locations.
As described herein, frequency domain features (e.g., also referred to as
spectral descriptors)
can be used with DAS acoustic data processing in real time to provide various
downhole
surveillance applications. More specifically, the data processing techniques
can be applied for
various downhole fluid profiling such as events including fluid flow / inflow
/ outflow
detection, fluid phase segregation, well integrity monitoring, in-well leak
detection (e.g.,
downhole casing and tubing leak detection, leaking fluid phase identification,
etc.), annular
fluid flow detection, overburden monitoring, fluid flow detection behind a
casing, fluid
induced hydraulic fracture detection in the overburden, and the like, and can
thus be utilized
to determine a degree of success in blocking fluid flow(s) at one or more
identified fluid flow
locations via the setting of one or more well barriers. Such events may be
referred to herein
as "fluid flow" events.
100431 In addition to the use of DAS data, additional sensor data such as
pressure sensors
and/or flow sensors can be used to obtain data within the wellbore. As an
example, a flow
sensor or pressure sensor can be used to detect fluid flow within the wellbore
and/or an
annulus within the wellbore. The sensors can be used with controlled shut-in
and/or flow
conditions to correlate in time the resulting pressure and/or flow conditions
with the
processed DAS data. The resulting correlation can then be used to determine a
presence (or
absence) and/or location of fluid flow.
100441 Referring now to Figure 1, an example of a wellbore operating
environment 100 is
shown. As will be described in more detail below, embodiments of completion
assemblies
comprising distributed acoustic sensor (DAS) system in accordance with the
principles
described herein can be positioned in environment 100.
100451 As shown in Figure 1, exemplary environment 100 includes a wellbore 114
traversing
a subterranean formation 102, casing 112 lining at least a portion of wellbore
114, and a
tubular 120 extending through wellbore 114 and casing 112. A plurality of
spaced screen
elements or assemblies 118 are provided along tubular 120. In addition, a
plurality of spaced
zonal isolation devices 117 and gravel packs 122 can be provided between
tubular 120 and
the sidewall of wellbore 114. In some embodiments, the operating environment
100 includes
a workover and/or drilling rig positioned at the surface and extending over
the wellbore 114.
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100461 In general, the wellbore 114 can be drilled into the subterranean
formation 102 using
any suitable drilling technique. The wellbore 114 can extend substantially
vertically from the
earth's surface over a vertical wellbore portion, deviate from vertical
relative to the earth's
surface over a deviated wellbore portion, and/or transition to a horizontal
wellbore portion.
In general, all or portions of a wellbore may be vertical, deviated at any
suitable angle,
horizontal, and/or curved. In addition, the wellbore 114 can be a new
wellbore, an existing
wellbore, a straight wellbore, an extended reach wellbore, a sidetracked
wellbore, a multi-
lateral wellbore, and other types of wellbores for drilling and completing one
or more
production zones. As illustrated, the wellbore 114 includes a substantially
vertical producing
section 150, which is an open hole completion (e.g., casing 112 does not
extend through
producing section 150). Although section 150 is illustrated as a vertical and
open hole
portion of wellbore 114 in Figure 1, embodiments disclosed herein can be
employed in
sections of wellbores having any orientation, and in open or cased sections of
wellbores. The
casing 112 extends into the wellbore 114 from the surface 113 and is cemented
within the
wellbore 114 with cement 111.
[00471 Tubular 120 can be lowered into wellbore 114 for performing an
operation such as
drilling, completion, workover, treatment, and/or production processes. In the
embodiment
shown in Figure 1, the tubular 120 is a completion assembly string including a
distributed
acoustic sensor (DAS) sensor coupled thereto. However, in general, embodiments
of the
tubular 120 can function as a different type of structure in a wellbore
including, without
limitation, as a drill string, casing, liner, jointed tubing, and/or coiled
tubing. Further, the
tubular 120 may operate in any portion of the wellbore 114 (e.g.. vertical,
deviated,
horizontal, and/or curved section of wellbore 114). Embodiments of DAS systems
described
herein can be coupled to the exterior of the tubular 120, as depicted in
Figure 4B, or in some
embodiments, disposed within an interior of the tubular 120, as shown in
Figure 4A. When
the DAS fibre is coupled to the exterior of the tubular 120, as depicted in
Figure 4B, the DAS
can be positioned within a control line, control channel, or recess in the
tubular 120. In some
embodiments, a sand control system can include an outer shroud to contain the
tubular 120
and protect the system during installation. A control line or channel can be
formed in the
shroud and the DAS system can be placed in the control line or channel. In
some
embodiments, the tubular and/or the DAS fiber can be removed prior to or
subsequent
utilization of the DAS system as described herein to identify a (first) fluid
flow location,
followed by removal prior to setting a barrier at or above the identified
(first) fluid flow
location.
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[0048] The tubular 120 extends from the surface to the producing zones and
generally
provides a conduit for fluids to travel from the formation 102 to the surface.
A completion
assembly including the tubular 120 can include a variety of other equipment or
downhole
tools to facilitate the production of the formation fluids from the production
zones. For
example, zonal isolation devices 117 are used to isolate the various zones
within the wellbore
114. In this embodiment, each zonal isolation device 117 can be a packer
(e.g., production
packer, gravel pack packer, frac-pac packer, etc.). The zonal isolation
devices 117 can be
positioned between the screen assemblies 118, for example, to isolate
different gravel pack
zones or intervals along the wellbore 114 from each other. In general, the
space between
each pair of adjacent zonal isolation devices 117 defines a production
interval.
[0049] The screen assemblies 118 provide sand control capability. In
particular, the sand
control screen elements 118, or other filter media associated with wellbore
tubular 120, can
be designed to allow fluids to flow therethrough but restrict and/or prevent
particulate matter
of sufficient size from flowing therethrough. In some embodiments, gravel
packs 122 can be
formed in the annulus 119 between the screen elements 118 (or tubular 120) and
the sidewall
of the wellbore 114 in an open hole completion. In general, the gravel packs
122 comprise
relatively coarse granular material placed in the annulus to form a rough
screen against the
ingress of sand into the wellbore while also supporting the wellbore wall. The
gravel pack
122 is optional and may not be present in all completions.
[0050] The fluid flowing into the tubular 120 may comprise more than one fluid
component.
Typical components include natural gas, oil, water, steam, and/or carbon
dioxide. The
relative proportions of these components can vary over time based on
conditions within the
formation 102 and the wellbore 114. Likewise, the composition of the fluid
flowing into the
tubular 120 sections throughout the length of the entire production string can
vary
significantly from section to section at any given time.
[0051] As fluid flows into the wellbore 114 and into the completion assembly
string, the flow
of the various fluids into the wellbore 114 and/or through the wellbore 114
can create
acoustic sounds that can be detected using the acoustic sensor such as the DAS
system. Each
type of fluid flow event such as the different fluid flows and fluid flow
locations can produce
an acoustic signature with unique frequency domain features. For example, a
fluid flow or
"leak" representing fluid flow past a restriction, through an annulus, and/or
through the
formation can create unique sound profiles over a frequency domain such that
each event
may have a unique acoustic signature based on a plurality of frequency domain
features. In
some embodiments, the event or acoustic signature can comprise thresholds or
ranges for a
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plurality of different frequency domain features, combinations of frequency
domain features,
or modifications of a plurality of frequency domain features.
[0052] In Figure 1, the DAS comprises an optical fibre 162 based acoustic
sensing system
that uses the optical backscatter component of light injected into the optical
fibre for
detecting acoustic/vibration perturbations (e.g., dynamic strain) along the
length of the fibre
162. The light can be generated by a light generator or source 166 such as a
laser, which can
generate light pulses. The optical -fibre 162 acts as the sensor element with
no addition
transducers in the optical path, and measurements can be taken alone the
length of the entire
optical fibre 162. The measurements can then be detected by an optical
receiver such as
sensor 164 and selectively filtered to obtain measurements from a given depth
point or range,
thereby providing for a distributed measurement that has selective data for a
plurality of
zones along the optical fibre 162 at any given time. In this manner, the
optical fibre 162
effectively functions as a distributed array of acoustic sensors spread over
the entire length of
the optical fibre 162, which typically spans at least a portion of the
production zone 150 of
the wellbore 114, to detect downhole acoustic signals/vibration perturbations.
When used in
an abandonment system, the DAS system can span a portion of the wellbore
between a lower
zonal isolation device (e.g., a plug, etc.) and a zone desired to be isolated
as part of the
abandonment process.
[0053] The light reflected back up the optical fibre 162 as a result of the
backscatter can
travel back to the source, where the signal can be collected by a sensor 164
and processed
(e.g., using a processor 168). In general, the time the light takes to return
to the collection
point is proportional to the distance traveled along the optical fibre 162.
The resulting
backscattered light arising along the length of the optical fibre 162 can be
used to
characterize the environment around the optical fibre 162. The use of a
controlled light
source 166 (e.g., having a controlled spectral width and frequency) may allow
the backscatter
to be collected and any disturbances along the length of the optical fibre 162
to be analyzed.
In general, any acoustic or dynamic strain disturbances along the length of
the optical fibre
162 can result in a change in the properties of the backscattered light,
allowing for a
distributed measurement of both the acoustic magnitude, frequency and in some
cases of the
relative phase of the disturbance.
[0054] An acquisition device 160 can be coupled to one end of the optical
fibre 162. As
discussed herein, the light source 166 can generate the light (e.g., one or
more light pulses),
and the sensor 164 can collect and analyze the backscattered light returning
up the optical
fibre 162. In some contexts, the acquisition device 160 including the light
source 166 and the
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sensor 164 can be referred to as an interrogator. In addition to the light
source 166 and the
sensor 164, the acquisition device 160 generally comprises a processor 168 in
signal
communication with the sensor 164 to perform various analysis steps described
in more detail
herein. While shown as being within the acquisition device 160, the processor
can also be
located outside of the acquisition device 160 including being located remotely
from the
acquisition device 160. The sensor 164 can be used to obtain data at various
rates and may
obtain data at a sufficient rate to detect the acoustic signals of interest
with sufficient
bandwidth. In an embodiment, depth resolution ranges of between about I meter
and about
meters can be achieved.
100551 While the system 100 described herein can be used with a DAS system to
acquire an
acoustic signal for a location or depth range in the wellbore 114, in general,
any suitable
acoustic signal acquisition system can be used with the processing steps
disclosed herein.
For example, various microphones or other sensors can be used to provide an
acoustic signal
at a given location based on the acoustic signal processing described herein.
The benefit of
the use of the DAS system is that an acoustic signal can be obtained across a
plurality of
locations and/or across a continuous length along the wellbore 114 rather than
at discrete
locations.
100561 In addition to the DAS system, a surface sensor or sensor system 152
can be used to
obtain additional data for the wellbore. The surface sensor system 152 can
comprise one or
more sensors such as pressure sensors, flow sensors, temperature sensors, and
the like. The
sensors can detect the conditions within the tubular 120 and/or in one or more
annuli such as
annuli 119. While only a single annulus between the tubular 120 and the casing
112 is
illustrated in Figure 1, multiple annuli can be present. For example, more
than one casing
string (also referred to herein as a tubular string or casing) can often be
set at or near the
surface of the wellbore during drilling, which can result in two or more
annuli (e.g., an
annulus between the tubular 120 and the casing 112, an annulus between a first
casing 112
and a second casing, an annulus between a casing string and the wellbore wall,
etc.).
[0057] In embodiments, the wellbore comprises one or more tubular strings and
one or more
annuli disposed between: (i) two adjacent tubular strings of the one or more
tubular strings,
(ii) a tubular string of the one or more tubular strings and the formation
102, or (iii) both (i)
and (ii). For example, as depicted in Figure 2, which is a schematic, cross-
sectional
illustration of another downhole wellbore environment 100A according to
embodiments of
this disclosure, wellbore environment 100A comprises wellbore 114, tubular
120, and first
casing 112A, second casing 112B, third casing 112C, and fourth casing 112D. As
depicted in
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Figure 2, a first annulus I 19A is positioned between wellbore 114 and first
casing 112A and
second casing 112B. A second annulus 119B is positioned between second casing
112B and
third casing 112C. A third annulus 119C is positioned between third casing
112C and fourth
casing 1121). in embodiments, identifying a fluid flow location comprises
determining an
annulus of the one or more annuli and a depth at which the fluid flow location
is present. The
'fluid flow locations identified according to this disclosure can comprise,
for example, a
location of fluid flow from the formation 102 into the wellbore 114, a
location of flow
between the formation 102 and an annulus between a tubular string or casing
and the
wellbore wall (e.g., between the formation 102 and first annulus 119A, second
annulus 11913,
or third annulus 119C), or a location of -flow between annuli formed between a
plurality of
tubular strings in the wellbore 114 (e.g., between first annulus 119A and
second annulus
119B or between second annulus 119B and third annulus 119C).
[00581 As used herein, reference to the term "surface" (113) can refer to a
location above or
at the well head (e.g., at the Kelly bushing, rig floor, etc.), near the
ground level, amilor
within the first 100 m, within the first 150 m, within the first 200 rn, or
within about the first
300 m along the wellbore as measured from ground level.
100591 Specific spectral signatures can be determined for each fluid flow
event by
considering one or more frequency domain features. The resulting spectral
signatures can
-then be used along with processed acoustic signal data to determine if a
fluid flow event is
occurring at a depth range of interest. The spectral signatures can be
determined by
considering the different types of movement and flow occurring within a
wellbore and
characterizing the frequency domain features for each type of movement.
[0060] For the flow of gas into the wellbore, the proximity to the optical
fibre 162 can result
in a high likelihood that any acoustic signals generated would be detected by
the optical fibre
162. The flow of a gas into the 1,vellbore would likely result in a turbulent
flow over a broad
frequency range. For example, the gas flow acoustic signals can be between
about 0 Hz and
about 1000 Hz, or alternatively between about 0 Hz and about 500 Hz. An
increased power
intensity may occur between about 300 Hz and about 500 Hz from increased
turbulence in
the gas flow. An example of the acoustic signal resulting from the influx of
gas into the
wellbore can include frequency filtered acoustic intensity in depth versus
time graphs for five
frequency bins. The five frequency bins represent 5 Hz to 50 Hz, 50 Hz to 100
Hz, 100 Hz to
500 Hz, 500 Hz to 2000 Hz, and 2000 Hz to 5000 Hz, The acoustic intensity in
the first three
bins can have frequency ranges up to about 500 Hz, with a nearly undetectable
acoustic
intensity in the frequency range above 500 Hz. At least a portion of the
frequency domain
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features may not be present above 500 Hz, which can help to define the
signature of the
influx of gas.
[0061] For the 'flow of a fluid behind a casing in the wellbore, the proximity
of the =fluid flow
to the optical fibre 162 can result in the acoustic signal being detected. The
flow behind the
casing can generally be characterized by a flow of fluid through one or more
restrictions
based on a generally narrow or small leak path being present. The flow through
such a
restriction may be characterized by an increase in spectral power in a
frequency range
between about 0 Hz to about 300 Hz with a main energy contribution in the
range of about 0
Hz to about 100 Hz, or between about 0 Hz and about 70 Hz.
100621 Based on the expected sound characteristics from the potential acoustic
signal
sources, the acoustic signature of each fluid flow event can be defined
relative to background
noise contributions. Referring again to Figure 1, the processor 168 within the
acquisition
device 160 can be configured to perform various data processing to detect the
presence of one
or more fluid flow events along a length of the wellbore 114, The acquisition
device 160 can
comprise a memory 170 configured to store an application or program to perform
the data
analysis. While shown as being contained within the acquisition device 160,
the memory 170
can comprise one or more memories, any of which can be external to the
acquisition device
160. In an embodiment, the processor 168 can execute the program, which can
configure the
processor 168 to filter the acoustic data set spatially, determine one or more
frequency
domain features of the acoustic signal, compare the resulting frequency domain
feature
values to the acoustic signatures, and determine whether or not a fluid flow
event is occurring
at the selected location based on the analysis and comparison. The analysis
can be repeated
across various locations along the length of the wellbore 114 to determine the
occurrence of
one or more fluid flow events and/or fluid flow event locations along the
length of the
we llbore 114.
100631 At the same time, one or more wellbore parameters can be measured with
the sensor
system 152. For example, the sensors can be used to detect the pressure(s),
flow rate(s),
temperature(s), and the like at one or more locations at or near the surface
of the wellbore
and/or within the welibore. For example, a pressure in the tubular, and one or
more annuli
can be monitored over time. The measurements can be stored with a time stamp
and/or
stored with the acquired acoustic data set so that the two data sets can be
time correlated after
processing the acoustic signal.
[0064] When the acoustic sensor comprises a DAS system, the optical fibre 162
can return
raw optical data in real time or near real time to the acquisition unit 160.
In an embodiment,
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the raw data can be stored in the memory 170 for various subsequent uses. The
sensor 164
can be configured to convert the raw optical data into an acoustic data set.
Depending on the
type of DAS system employed, the optical data may or may not be phase coherent
and may
be pre-processed to improve the signal quality (e.g., for opto-electronic
noise normalization /
de-trending single point-reflection noise removal through the use of median
filtering
techniques or even through the use of spatial moving average computations with
averaging
windows set to the spatial resolution of the acquisition unit, etc.).
[0065] As shown schematically in Figure 5, an embodiment of a system for
detecting various
-fluid flow event conditions such as a leak detection can comprise a data
extraction unit 402, a
processing unit 404, a peripheral sensor data correlation unit 408, and/or an
output or
visualization unit 406. The system comprises of a DAS interroeator 160
connected to the
fibre optic cable 162 deployed in the wellbore. The data from the DAS
interrogator is
transmitted in real time to a data processing unit 402 that receives and
processes the data in
real time. The data processing unit 402 can perform a variety of processing
steps on the
acoustic sample data. In an embodiment, the acoustic sample can be noise de-
trended. The
noise de-trended acoustic variant data can be subjected to an optional spatial
filtering step
following the pre-processing steps, if present. This is an optional step and
helps focus
primarily on an interval of interest in the wellbore. For example, the spatial
filtering step can
be used to focus on an interval where there is maximum likelihood of fluid
flow when a fluid
flow event is being examined. In an embodiment, the spatial -filtering can
narrow the focus of
the analysis to a reservoir section and also allow a reduction in data
typically of the order of
ten times, thereby simplifying the data analysis operations. The resulting
data set produced
through the conversion of the raw optical data can be referred to as the
acoustic sample data.
100661 This type of filtering can provide several advantages in addition to
the data set size
reduction. Whether or not the acoustic data set is spatially filtered, the
resulting data, for
example the acoustic sample data, used for the next step of the analysis can
be indicative of
an acoustic sample over a defined depth (e.g., the entire length of the
optical fibre, some
portion thereof, or a point source in the wellbore 114). In some embodiments,
the acoustic
data set can comprise a plurality of acoustic samples resulting from the
spatial filtering to
provide data over a number of depth ranges. In some embodiments, the acoustic
sample may
contain acoustic data over a depth range sufficient to capture multiple points
of interest. In
some embodiments, the acoustic sample data contains information over the
entire frequency
range at the depth represented ,by the sample. This is to say that the various
filtering steps,
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including the spatial filtering, do not remove the frequency information from
the acoustic
sample data.
100671 The processing unit 402 can also be used to generate and extract
acoustic descriptors
(e.g., also referred to as frequency domain features herein) from the acoustic
data set. In an
embodiment, the data extraction unit 402 can obtain the optical data and
perform the initial
pre-processing steps to obtain the initial acoustic information from the
signal returned from
the sensor in the wellbore. Various analyses can be performed including
frequency domain
feature extraction, frequency band extraction, frequency analysis and/or
transformation,
intensity and/or energy calculations, and/or determination of one or more
frequency domain
features of the acoustic data. In order to obtain the frequency domain
features, the data
processing unit 402 can be further configured to perform Discrete Fourier
transformations
(DFT) or a short time Fourier transform (STFT) of the acoustic variant time
domain data
measured at each depth section along the fibre or a section thereof to
spectrally check the
conformance of the acoustic sample data to one or more acoustic signatures.
The spectral
conformance check can be used to determine if the expected signature of an
event is present
in the acoustic sample data. Spectral feature extraction through time and
space can be used to
determine the spectral conformance and determine if an acoustic signature
(e.g., a gas influx
signature, fluid flow signature, etc.) is present in the acoustic sample in
order to classify the
events within the acoustic signal. Within this process, various frequency
domain features can
be calculated for the acoustic sample data.
100681 The frequency domain features represent specific properties or
characteristics of the
acoustic signals. While a number of frequency domain features can be
determined for the
acoustic sample data, not every frequency domain feature may be used in the
characterization
of each acoustic signature. In some embodiments, the frequency domain features
that are
calculated can be a plurality of different frequency domain features. Some
frequency domain
features can represent transformed or modified frequency domain features,
including
combinations or mathematical modifications (e.g., ratios, multiplications,
formula, etc.) of a
plurality of frequency domain features. The term "frequency domain features"
is used here to
refer to not only the frequency domain features obtained from the acoustic
signal, but also
any combinations or modifications thereof
[00691 The use of the frequency domain features to identify one or more fluid
flow events
has a number of advantages. First, the use of the frequency domain features
results in
significant data reduction relative to the raw DAS data stream. Thus, a number
of frequency
domain features can be calculated to allow for event identification while the
remaining data
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can be discarded or otherwise stored, while the remaining analysis can
performed using the
frequency domain features. Even when the raw DAS data is stored, the remaining
processing
power is significantly reduced through the use of the frequency domain
features rather than
the raw acoustic data itself. Further, the use of the frequency domain
features provides a
concise, quantitative measure of the spectral character or acoustic signature
of specific
sounds pertinent to downhole fluid surveillance and other applications that
may directly be
used for real-time, application-specific signal processing.
100701 As a further consideration in selecting the frequency domain feature(s)
for an event,
the dimensionality of the frequency domain feature should be compact. A
compact
representation is desired to decrease the computational complexity of
subsequent
calculations. The frequency domain feature should also have discriminant
power. For
example, for different types of audio signals, the selected set of descriptors
should provide
altogether different values. A measure for the discriminant power of a feature
is the variance
of the resulting feature vectors for a set of relevant input signals. Given
different classes of
similar signals, a discriminatory descriptor should have low variance inside
each class and
high variance over different classes. The frequency domain feature should also
be able to
completely cover the range of values of the property it describes. As an
example, the chosen
set of frequency domain features should be able to completely and uniquely
identify the
signatures of each of the acoustic signals pertaining to a selected downhole
surveillance
application or event as described herein. Such frequency domain features can
include, but are
not limited to, the spectral centroid, the spectral spread, the spectral roll-
off, the spectral
skewness, the root mean square (RMS) band energy (or the normalized subband
energies /
band energy ratios), a loudness or total RIMS energy, spectral flatnessõ
spectral scope,
spectral kurtosis, a spectral flux, spectral entropy, and a spectral
autoeorrelation function. In
embodiments, a single frequency domain feature is utilized to determine the
presence (or
absence) of a fluid flow event and identifY a fluid flow location of the -
fluid flow event, which
information is subsequently utilized to locate one or more well barriers
during plugging and
abandonment operations and/or determine whether or not such plugging
operations have been
successful at reducing or eliminating the fluid flow at the identified fluid
flow location. In
alternative embodiments, a plurality (e.g,, at least two) of different
frequency domain features
are utilized to determine the presence (or absence) of the fluid flow event
and identify the
fluid flow location of the fluid flow event, which information is subsequently
utilized to
lobate one or more well barriers during plugging and abandonment operations
and/or
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determine whether or not such plugging operations have been successful at
reducing or
eliminating the fluid flow at the identified fluid flow location,
100711 The spectral centroid denotes the "brightness" of the sound captured by
the optical
fibre 162 and indicates the center of gravity of the frequency spectrum in the
acoustic sample.
The spectral centroid can be calculated as the weighted mean of the
frequencies present in the
signal, where the magnitudes of the frequencies present can be used as their
weights in some
embodiments. The value of the spectral centroid. Ci, of the ith frame of the
acoustic signal
captured at a spatial location on the fibre, may be written as:
f(k)x=Ve)
Li = = r (Eq. 1)
LIZY:-1.4.(10
Where X (k), is the magnitude of the short time Fourier transform of the ith
frame where '
denotes the frequency coefficient or bin index, N denotes the total number of
bins and f (k)
denotes the centre frequency of the bin. The computed spectral centroid may be
scaled to
value between 0 and 1. Higher spectral centroids typically indicate the
presence of higher
frequency acoustics and help provide an immediate indication of the presence
of high
frequency noise. The calculated spectral centroid can be compared to a
spectral centroid
threshold or range for a given event, and when the spectral centroid meets or
exceeds the
threshold, the event of interest may be present.
[0072] The absolute magnitudes of the computed spectral eentroids can be
sealed to read a
value between zero and one. The turbulent noise generated by other sources
such as fluid
flow and flow may typically be in the lower frequencies (e.g., under about 100
Hz) and the
centroid computation can produce lower values, for example, around or under
0.1 post
resealing. The introduction of fluid or fluid carrying sand can trigger
broader frequencies of
sounds (e.g., a broad band response) that can extend in spectral content to
higher frequencies
(e.g., up to and beyond 5,000 Hz), This can produce eentroids of higher values
(e.g.`, between
about 0.2 and about 0.7, or between about 0.3 and about 0.5), and the
magnitude of change
would remain fairly independent of the overall concentration of sanding
assuming there is a
good signal to noise ratio in the measurement assuming a traditional
electronic noise floor
(e.g., white noise with imposed flicker noise at lower frequencies).
[0073] The spectral spread can also be determined for the acoustic sample. The
spectral
spread is a measure of the shape of the spectrum and helps measure how the
spectrum is
distributed around the spectral centroid. In order to compute the spectral
spread, Si, one has to
take the deviation of the spectrum from the computed centroid as per the
following equation
(all other terms defined above):
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S1
= liEkl\c,...1(f(k)¨Ci)2Xi(k)
EPtt_i ______________________________________ (Eq. 2)
Lower values of the spectral spread correspond to signals whose spectra are
tightly
concentrated around the spectral centroid. Higher values represent a wider
spread of the
spectral magnitudes and provide an indication of the presence of a broad band
spectral
response. The calculated spectral spread can be compared to a spectral spread
threshold or
range, and when the spectral spread meets or exceeds the threshold or falls
within the range,
the event of interest may be present.
100741 The spectral roll-off is a measure of the bandwidth of the audio
signal. The Spectral
roll-off of the ith frame, is defined as the frequency bin 'y' below which the
accumulated
magnitudes of the short-time Fourier transform reach a certain percentage
value (usually
between 85% - 95%) of the overall sum of magnitudes of the spectrum.
Vic12.11Xi (k)I = -c Ef_ilXi(k) I ................... (Eq. 3)
100 ¨
Where c = 85 or 95. The result of the spectral roll-off calculation is a bin
index and enables
distinguishing acoustic events based on dominant energy contributions in the
frequency
domain. (e.g., between gas influx and fluid flow, etc.)
[0075] The spectral skewness measures the symmetry of the distribution of the
spectral
magnitude values around their arithmetic mean.
[0076] The RMS band energy provides a measure of the signal energy within
defined
frequency bins that may then be used for signal amplitude population. The
selection of the
bandwidths can be based on the characteristics of the captured acoustic
signal. In some
embodiments, a sub-band energy ratio representing the ratio of the upper
frequency in the
selected band to the lower frequency in the selected band can range between
about 1.5:1 to
about 3:1. In some embodiments, the sub-band energy ratio can range from about
2.5:1 to
about 1.8:1, or alternatively be about 2:1. In some embodiment, selected
frequency ranges
for a signal with a 5,000 Hz Nyquist acquisition bandwidth can include: a
first bin with a
frequency range between 0 Hz and 20 Hz, a second bin with a frequency range
between 20
Hz and 40 Hz, a third bin with a frequency range between 40 Hz and 80 Hz, a
fourth bin with
a frequency range between 80 Hz and 160 Hz, a fifth bin with a frequency range
between 160
Hz and 320 Hz, a sixth bin with a frequency range between 320 Hz and 640 Hz, a
seventh bin
with a frequency range between 640 Hz and 1280 Hz, an eighth bin with a
frequency range
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between 1280 Hz and 2500 Hz, and a ninth bin with a -frequency range between
2500 Hz and
5000 Hz. While certain frequency ranges thr each bin are listed herein, they
are used as
examples only, and other values in the same or a different number of frequency
range bins
can also be used. In some embodiments, the RMS band energies may also be
expressed as a
ratiornetric measure by computing the ratio of the RMS signal energy within
the defined
frequency bins relative to the total RMS energy across the acquisition
(Nyquist) bandwidth.
This may help to reduce or remove the dependencies on the noise and any
momentary
variations in the broadband sound.
[00771 The total RMS enemy of the =MIS& waveform calculated in the time domain
can
indicate the loudness of the acoustic signal. In some embodiments, the total
RMS energy can
also be extracted from the temporal domain after filing the signal for noise.
100781 The spectral flatness is a measure of the noisiness/ tonality of an
acoustic spectrum. It
can be computed by the ratio of the geometric mean to the arithmetic mean of
the enemy
spectrum value and may he used as an alternative approach to detect
broadbancled signals
(e.g., such as those caused by sand ingress). For tonal signals, the spectral
flatness can be
close to 0 and for broader band signals it can be closer to I.
100791 The spectral slope provides a basic approximation of the spectrum shape
by a linearly
regressed line. The spectral slope represents the decrease of the spectral
amplitudes from low
to high frequencies (e.g., a spectral tilt), The slope, the y-intersection,
and the max and media
regression error may be used as features.
100801 The spectral kurtosis provides a measure of the flatness of a
distribution around the
mean value.
100811 The spectral flux is a measure of instantaneous changes in the
magnitude of a
spectrum. It provides a measure of the frame-to-frame squared difference of
the spectral
magnitude vector summed across all frequencies or a selected portion of the
spectrum.
Signals with slowly varying (or nearly constant) spectral properties (e.g.:
noise) have a low
spectral flux, while signals with abrupt spectral changes have a high spectral
flux. The
spectral flux can allow for a direct measure of the local spectral rate of
change and
consequently serves as an event detection scheme that could be used to pick up
the onset of
acoustic events that may then be further analyzed using the feature set above
to identify and
uniquely classify the acoustic signal.
[00821 The spectral autocorrelation function provides a method in which the
signal is shifted,
and for each signal shift (lag) the correlation or the resemblance of the
shifted signal with the
original one is computed. This enables computation of the fundamental period
by choosing
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the lag, for which the signal best resembles itself, for example, where the
autocorrelation is
maximized. This can be useful in exploratory signature analysis / even fbr
event detection for
well integrity monitoring across specific depths where well barrier elements
to be monitored
are positioned.
10083] Any of these frequency domain features, or any combination of these
frequency
domain features, can be used to provide an acoustic signature for a fluid flow
event. In
embodiments, a selected set of characteristics can be used to provide the
acoustic signature
for each fluid -flow event, and/or all of the frequency domain features that
are calculated can
be used as a group in characterizing the acoustic signature for a fluid flow
event. The
specific values for the frequency domain features that are calculated can vary
depending on
the specific attributes of the acoustic signal acquisition system, such that
the absolute value of
each frequency domain feature can change between systems. In some embodiments,
the
frequency domain features can be calculated for each event based on the system
being used to
capture the acoustic signal and/or the differences between systems can be
taken into account
in determining the frequency domain feature values for each signature between
the systems
used to determine the values and the systems used to capture the acoustic
signal being
evaluated. In embodiments, subtraction of a baseline acoustic signal, as
described in
Example 1, from a 'flowing acoustic signal can be utilized to decoupie optical
parameter
variations, for example, allowing direct comparison (i.e., "like for like"
comparison) of
difference logs (e.g., allowing comparison of sample data sets comprising the
flowing
acoustic signal from which the baseline acoustic signal has been subtracted).
In this Tnanner,
a scaling can be effected without the need for an autocalibration each time
the DAS sensor is
removed and redeployed within the wellbore.
[0084] in order to obtain the frequency domain features, the acoustic sample
data can be
converted to the frequency domain. In an embodiment, the raw optical data may
contain or
represent acoustic data in the time domain. A frequency domain representation
of the data
can be obtained using a Fourier Transform. Various algorithms can be used as
known in the
art. In some embodiments, a Short Time Fourier Transform technique or a
Discrete Time
Fourier transform can be used. The resulting data sample may then be
represented by a range
of frequencies relative to their power levels at which they are present. The
raw optical data
can be transformed into the frequency domain prior to or after the application
of the spatial
filter. In general, the acoustic sample will be in the frequency' domain in
order to determine
the spectral centroicl and the spectral spread. In an embodiment, the
processor 168 can be
configured to perform the conversion of the raw acoustic data and/or the
acoustic sample data
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from the time domain into the frequency domain. In the process of converting
the signal to
the frequency domain, the power across all frequencies within the acoustic
sample can he
analyzed. The use of the processor 168 to perform the transformation may
provide the
frequency domain data in real time or near real time.
[00851 The data processing unit 402 can then be used to analyze the acoustic
sample data in
the frequency domain to obtain one or more of the frequency domain features
and provide an
output with the determined frequency domain features for further processing.
In some
embodiments, the output of the frequency domain features can include features
that are not
used to determine the presence of every event.
100861 The output of the processor with the frequency domain features for the
acoustic
sample data can then be used to determine the presence of one or more fluid
flow events at
one or more locations in the wellbore corresponding to depth intervals over
which the
acoustic data is acquired or filtered. In some embodiments, the detet __
mination of the presence
of one or more fluid flow events can include comparing the frequency domain
features with
the frequency domain feature thresholds or ranges in each fluid flow event
signature. When
the frequency domain features in the acoustic sample data match one or more of
the fluid
flow event signatures, the event can be identified as having occurred during
the sample data
measurement period, which can be in real time. Various outputs can be
generated to display
or indicate the presence (or absence) of the one or more fluid flow events.
[0087] The processed acoustic data (Le., the frequency domain features), which
can have a
significantly smaller file size (typically over 1000 X smaller) can then be
written into a file
(e.g., an ASCII file) in a memory at certain intervals (e.g., every second,
every ten seconds,
etc.), which can then he retrieved and transmitted through network using a
data collection and
transmission software. This process can be executed in real time or near real
time for
transmission of data.
[00881 The data transmitted from the DAS interrogator (which can include the
frequency
domain feature data) can then be further processed using a sequence of data
processing steps
as shown in the processing sequence 404 in Figure 5. The processing sequence
404 can
comprise a series of steps including an event detection step, a signature
extraction step, an
event classification step, a leak or fluid flow identification step, and an
output step. The
descriptor data are first processed using an event-detection algorithm to
determine the
presence of any anomalous acoustic response(s) that may be triggered by a
fluid leak/flow.
While there are several ways to implement the event detection algorithm,
amplitude
thresholding of the data relative to surface noise captured by the DAS on the
fibre optic cable
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dispersed at or near the surface (e.g., within the first 100 meters) of the
well head can be
used. As an example of amplitude thresholding, an acoustic intensity over the
entire
bandwidth can be averaged over the surface or near surface measurements (e.g.,
in the first
300 in of acoustic data) acquisitions to provide an estimate of the average
surface acoustic
noise. A threshold can then be taken as a percentage of this average. For
example, the
amplitude threshold can be between about 90% and about 95% of the average. The
presence
of the signal within the wellbore can be detected when the amplitude of the
acoustic event
captured exceeds the threshold value. The frequency and amplitude
characteristics of the
surface noise may also be used to suppress and/or reduce the background noise
within the
selected window to identify presence of signals at the surface, if needed.
This enables a zero
point depth recognition, helps to reduce or eliminate surface noise
contributions, helps to
reduce or eliminate the DAS interrogator noise contributions, allows for the
capture of
acoustic events and renders the captured events in a format ready for
signature recognition,
and uses processed data (as compared to raw DAS data) as the primary feed to
the processing
sequence. While amplitude thresholding is used, other time based digital
processing
approaches could also be used.
[0089] Once the data is initially processed, the anomalous events can be
recognized (e.g., as
events having amplitudes over the thresholds), and the corresponding data from
the portion of
the acoustic sample can be extracted as a depth-time event block. Figure 6A
illustrates an
example of a depth-time event block show depth versus amplitude. Once the
depth-time
blocks are amplitude thresholded, the corresponding data may appear as shown
in Figure 6B,
with the surface noise filtered out and the anomalous events highlighted,
100901 In the second step 412 of the processing sequence 404, the acoustic
event blocks can
be further analyzed by extracting the frequency domain features at the event
depths and times
identified by the anomalous event detection step and comparing the extracted
frequency
domain features to the fluid flow event signatures to match the frequency
domain features for
each identified event with an appropriate signature. The extraction of the
frequency domain
features can be performed prior to the data being sent to the processing
sequence such that the
extraction of the frequency domain features involves filtering the received
frequency domain
features for the depth and times identified by the anomalous event detection,
or the extraction
of the frequency domain features can be performed only after the anomalous
depth-time
blocks have been identified.
100911 In either case, the resulting frequency domain features can be compared
with one or
more fluid flow event signatures to identify if integrity fluid flow event has
occurred in the
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event classification step 414. In some embodiments, the fluid flow event
signatures can
include frequency domain signatures for a liquid leak/flow, a gas leak/flow,
or another such
event (e.g., an unrecognized event category or other non-flow signature, which
can be used
for comparison).
[0092] The event classification step 414 can be executed at each depth
location along the
fibre and may depend on the acoustic signatures captured at the locations
identified to have
an anomalous event. Once classified into the appropriate category, the
intensities of the
events can he determined using the normalized RIOS values within the
appropriate frequency
bands extracted on site (e.g., which can already be one of the descriptors
obtained in the
extracted frequency domain features) from the raw acoustic data. The
descriptor data can then
be transformed and re-written as an event matrix. These steps can be executed
in near real
time at the data integration server, and the transformed decision ready well
integrity event
data can be stored along with some or all of the acoustic descriptor data. The
classified event
data may also be visualized as a three dimensional depth versus time versus
event type
intensity plot as shown in Figure 7A and Figure 7B to illustrate fluid flow
events as a
function of depth and time.
100931 The fluid flow event matrix may be further filtered to highlight and
visualize certain
types of fluid flow events as shown in Figure 7C. These may also be aligned in
depth to the
well completion schematic and / or the geological maps (e.g., discrete
pressure zones) to
ascertain the source of the leaking fluid in case of liquid leaks. In
embodiments, a fluid flow
event or location (e.g., depth) is correlated with one or more structural
features within the
wellbore, and a source of the fluid flow determined based on the correlating
of the one or
more fluid flow events or locations (e.g., depths) with the one or more
structural features.
[0094] Accordingly, in embodiments of this disclosure, subsequent to detection
of a leak
(e.g., a fluid flow) utilizing the feature extraction and the event signatures
as described
hereinabove, a flow log can be determined using a feature that is
representative of the
turbulent noise caused by the leak. Such a feature representative of the
turbulent noise can
comprise, for example, acoustic power, spectral intensity, and the like in the
frequency bands
identified for the fluid flow. For example, in embodiments, the leak detection
and
identification step 416, the event matrix may also be processed further to
obtain semi-
quantitative leak assessment by filtering the event matrix to extract the
events correlating to
gas or liquid leaks/flows and then integrating the filtered intensity data
through time to
provide fluid flow logs, an example of which is shown in Figure 8.
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100951 In producing a visualization fluid flow log, the RIMS spectral energy -
for depth
sections that do not exhibit the spectral conformance to specific fluid flow
events can be set
to zero. This allows those depth points or zones having one or more frequency
domain
features greater than the thresholds to be easily observed. Figure 8
represents an example of
an embodiment of a fluid flow log showing acoustic intensity against depth.
This figure
illustrates the locations having fluid flow as peaks in the acoustic
intensity. The acoustic
intensity and its visualization on the fluid flow log can therefore be used to
identify the
relative contribution of the fluid flows at different points along the
wellbore. For example, it
may be possible to determine which zone is contributing the greatest
proportion of the fluid
flows, which zone contributes the second greatest portion of the fluid flows,
and so on. This
may also allow for correlation of one or more zonal isolation devices,
potential leak/flow
locations, and/or fluid -flow through the formation along the length of the
wellbore.
[00961 The use of the processing sequence 404 can result in a suitable
identification of the
fluid flows within the welibore to be plugged and abandoned. In an optional
processing step
in the peripheral sensor data correlation unit 408, the resulting processed
data can be
correlated with external sensor data such as that provided by a sensor system
at or near the
surface of the wellbore. This processing sequence may be used with the DAS
system to
determine the flow path for the leaks, especially in eases where there are
multiple casing
strings or leak paths at or near a depth determined to have a fluid flow, The
process may also
be used to provide a semi-quantitative estimate of the volumes of fluid
associated with the
fluid flow when combined with surface measurements (e.g., bleed off rate
measurements,
surface pressure gauge data, etc.).
[0097] The correlation process can generally comprise the use of changing
surface
measurement data as a comparison with the identified -fluid flow event
process. For example,
changing pressure or flow data at the surface can be used as a correlation
with the fluid flow
identification data. It may be expected that as the fluid flow occurs, a shut
in annulus may
have a pressure rise and/or an increased flow rate (e.g., a bleed off flow
rate). When multiple
annuli or leak paths are present, the use of the pressure or flow data can
help to identify
which leak path(s) are specifically experiencing the fluid flows, while the
fluid flow depth
would be known from the fluid flow event detection sequence. While described
herein as a
leak or fluid flow path, a number of potential paths are available for fluid
flow within the
wellbore. For example, a leak can occur past a restriction or barrier in one
or more annuli,
between a casing and the formation, and/or within the formation or a
hydrocarbon zone, and
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potentially, into a production assembly. For example, fluid flow within a
hydrocarbon zone
in the formation can be monitored using any of the methods and systems
described herein.
100981 In an embodiment, a correlation process may begin by shutting in a
well. This may
allow a base reading to be taken of both the surface sensor data and the
frequency domain
features of the wellbore without fluid flow. Once the baseline readings have
been obtained, a
leak path can be triggered to potentially induce a fluid flow. For example, an
annulus can be
opened to bleed off pressure (e.g., induce a pressure differential), which can
potentially
induce fluid flow within that annulus if there is a leak in fluid
communication with the
selected annulus. This may create a pressure differential between the selected
annulus and a
neighboring annulus or annuli. The pressure differential can be determined to
assess the fluid
flow potentials. Once one leak path has been tested, it can be closed and
another leak path
can be triggered. This sequence can continue until all of the desired leak
paths that are to be
tested are triggered. The DAS monitoring system can remain active during the
induced flow
process to monitor for leaks and ascertain the leaking fluid phase or phases.
Inducing the
differential (e.g., inducing a first pressure differential prior for
determination of a first fluid
flow location prior to setting of a well barrier at or above the first fluid
flow location and/or
inducing a second pressure differential subsequent setting of the first well
barrier at or above
the first fluid flow location) can comprise, for example, opening a flow valve
within an
annulus of the one or more annuli; and inducing a fluid flow based on opening
of the flow
valve.
[0099] In embodiments, a sample data set (e.g., a first sample data set that
is a sample of the
acoustic signal originating in the wellbore) is obtained within the wellbore
by obtaining the
baseline acoustic signal data set while the wellbote is shut in, inducing the
pressure
differential within the wellbore, as described above, obtaining a flowing
acoustic sample data
set while inducing the pressure differential, and subtracting the baseline
acoustic signal data
set from the flowing acoustic signal data set to provide the sample data set
from which the
plurality of frequency domain features are determined and utilized as
described herein to
identify the fluid flow location within the wellbore.
[00100j Once the
data is obtained from the sensors and the DAS system, which can
include the fluid flow event data determined from the processing sequence 404
to determine
the presence of absence of any fluid flow events, the data can be correlated
through time to
determine a fluid flow location and fluid flow path. For example, the filtered
fluid flow
acoustic intensities obtained from the processing sequence 404 can be
integrated through time
at each depth location to obtain fluid flow data (e.g., which can be
visualized as fluid flow
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logs) for the stages of the fluid flow path triggering (e.g., the annular
pressure bleed process).
This data can then be aligned in time with the pressures, pressure
differentials, flow data, etc.
for each trigger operation to determine the fluid flow points and flow paths.
For example, it
may be determined that a given fluid flow path only triggers a fluid flow at a
given depth
rather than over a number of depths. From this data, the fluid flow logs can
be determined
for each tubular, casing string, or the like.
[001011 In some
embodiments, all of the surface sensor data can be used in this
process. The pressure data, including the induced pressure differentials, may
be used to
determine the fluid flow paths and fluid flow locations. In embodiments, the
bleed off rates
can be used to provide a quantitative assessment of the leak rates from each
fluid flow path.
This data can then be stored and/or outputted and used in the future for
further fluid flow
identification, comparison, and/or quantification.
[00102] Once a
first fluid flow event in a first depth interval (e.g., the entire length of
the wellbore or a portion thereof) has been confirmed and the location of the
first fluid flow
event determined, one or more first well barriers can be set in an attempt to
plug the well.
Any barriers known to those of skill in the art and with the help of this
disclosure can be
utilized. By way of non-limiting examples, the one or more well barriers can
comprise
bridge plugs, packers, cement plugs or columns, or combinations thereof, and
the like. The
acoustic sensor can be removed from the wellbore 114 prior to the setting of
the one or more
first well barriers employed in an attempt to plug the first fluid flow at the
first fluid flow
location.
[001031
Subsequent to the setting of the first well barrier(s), the fluid flow
detection
process can be repeated. That is, the acoustic sensor can be re-deployed into
the well within
a second depth interval overlapping the first depth interval (e.g., generally,
a depth interval
comprising at least a portion of the first depth interval and above a
location(s) at which the
one or more first well barriers have been positioned).. When the acoustic
sensor is
redeployed, the well barrier can block the ability to deploy the fiber below
the well barrier.
As a result, the acoustic sensor can be deployed to extend between a point at
or near the well
barrier towards the surface of the wellbore. Once redeployed, a second sample
data set can
be obtained and utilized as described hereinabove to identify whether or not a
fluid flow rate
or mechanism was reduced or eliminated and/or to determine a second fluid flow
location. If
a second fluid flow presence and a second fluid flow location are determined,
one or more
second well barriers can be set in an attempt to plug the fluid flow at the
second fluid flow
location. Again, the acoustic sensor can be removed from the wellbore prior to
the setting of
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the one or more second well barriers employed in the attempt to plug the
second fluid flow at
the second fluid flow location. The process can be repeated as necessary to
prepare the well
for abandonment. Accordingly, in embodiments of this disclosure, fluid flow
logs can be
compared ("like for like"), and the effectiveness of a flow barrier validated.
That is, a barrier
that is placed can be validated based on the identified reduction or
elimination of the fluid.
flow rate and/or the -fluid flow mechanism at the first fluid flow location.
In embodiments, an
effective barrier is one that reduces the fluid inflow at the fluid inflow
location such that a
flow rate of the/any remaining fluid flow at the inflow location being blocked
by the barrier is
less than 80, 85, 90, 95, 96, 97, 98, 99, or 100% of the original flow rate of
the leak (e.g., the
original fluid flow rate), or that the fluid flow rate is zero or
substantially zero after
placement of the barrier.
[001041 For
example, as depicted in Figures 3A and 3B, which are schematics of a
wellbore environment 10013 prior to placement of well barriers, and a wellbore
environment
100C after placement of well barriers, respectively, tubular 120 can be
removed from the
wellbore 114 and one or more well barriers set, at a fluid flow location
determined with the
use of the D.AS system as described herein, to plug the well for abandonment.
in some
embodiments, a baseline acoustic signal can be obtained and the first well
barrier can be set
on the basis of the producing zone within the wellbore such that the well
barrier will
generally extend through and above the producing zone. Thus, the DAS system
can be
utilized s described herein to determine one or more locations of fluid flow
at or above which
one or more well barriers can be positioned.
1001051 The DAS
system can also be utilized to determine whether or not the fluid
flow has been reduced or eliminated by the setting of the one or more well
barriers. By way
of example, in the embodiment of Figure 313, a first barrier comprising a
first cement plug
130A has been set at a first location in the wellbore, wherein the first
location is within first
casing 112A, a second barrier comprising a first bridge plug 131A and a second
cement plug
13013 is positioned at a second location in the wellbore, wherein the second
location is above
the first location and within second casing 112B, and a third barrier
comprising a second
bridge plug 13113 and a third cement plug 130 C has been set at a third
location in the
wellbore, wherein the third location is above the second location and within
third casing
112C. The DAS system can be utilized as described herein to determine a
location at or
above which to set the first well barrier comprising the first cement plug
130A, the second
well barrier comprising the first bridge plug 131 A and the second cement plug
13013, and/or
the third well barrier comprising the second bridge plug 13113 and the third
cement plug
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130C. Alternatively or additionally, the DAS system can be utilized as
described herein to
determine if the setting of the first well barrier comprising the first cement
plug 130A, the
second well barrier comprising the first bridge plug 131A and the second
cement plug 130B,
and/or the third well barrier comprising the second bridge plug 1318 and the
third cement
plug 130C has reduced or eliminated fluid flow. In aspects, any number of well
barriers can
be positioned within the wellbore environment, with one or more of the well
barriers
positioned at or above a fluid flow location determined via the DAS system as
described
herein.
[00106] In some
embodiments, the fluid flow can be a leak path behind a casing or
within an annulus (e.g., between casing strings and/or between a casing string
and a wellbore
wall). The identification of the location of the fluid flow may be allow for a
separate
procedure to be identified and performed to stop the fluid -flow. For example,
a fluid flow
behind a casing can be addressed through the use of a repair process
comprising perforating
the casing and injecting cement behind the casing (e.g., a squeeze cement
procedure). This
may be in addition to setting a well barrier within the 1,vellbore,
[00107] Also
provided herein is a method of comparing acoustic signals obtained
between different acoustic sensor operations or deployments in a wellbore. For
example, the
method can allow for the comparison between a first acoustic signal from a
first deployment
of the fiber and a second acoustic signal from a second deployment of the
fiber after a well
barrier has been placed in the wellbore. While described in the context of
being redeployed
after a well bander has been placed in the wellbore, the method can allow for
a comparison
between acoustic signals obtained between any deployments of the fiber,
regardless of
whether or not there are changes made within the wellbore or not.
100108] The
method comprises obtaining a first baseline sample data set over a first
depth interval within a -wellbore, as described herein. The first baseline
data set can be a
sample of an acoustic signal originating within the wellbore. In some
embodiments, the
baseline data set can be obtained when the wellbore is shut-in and/or when a
stable pressure
is maintained within the wellbore. At least one frequency domain feature of
the first baseline
sample data set can be determined. A first pressure differential can be
induced within the
wellbore, as described herein, to provide for a fluid flow. A first acoustic
data set can be
obtained over the first depth interval within the wellbore while inducing the
first pressure
differential, as described herein. At least one frequency domain feature of
the first acoustic
data set can then be determined. The at least one frequency domain feature of
the first
baseline sample data set can be subtracted from the at least one frequency
domain feature of
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the first acoustic data set to obtain a first sample data set over the first
depth interval. A
second baseline sample data set can be obtained over a second depth interval
within the
wellbore, as described herein. The second baseline sample data set can be a
sample of an
acoustic signal originating within the wellbore, and the second depth interval
can overlap
with the first depth interval. At least one frequency domain feature of the
second baseline
sample data set can be determined, as described herein. A second pressure
differential can be
induced within the wellhore, as described herein, and a second acoustic data
set can be
obtained over the second depth interval within the wellbore while inducing the
second
pressure differential, as described herein. At least one frequency domain
feature of the
second acoustic data set can be determined, as described herein, and the at
least one
frequency domain feature of the second baseline sample data set can be
subtracted from the at
least one frequency domain feature of the second acoustic data set to obtain a
second sample
data set over the second depth interval. The second sample data set can be
compared to the
first sample data set over the second depth interval. In some embodiments, a
fluid flow
reduction can be determined at a fluid flow location based on comparing the
second sample
data set to the first sample data set. As noted hereinabove, the first
baseline sample data set
and the first acoustic data set can be obtained with an acoustic sensor
disposed in the
wellbore within the first depth interval, and the second baseline sample data
set and the
second acoustic data set can be obtained with the acoustic sensor disposed in
the wellbore
within the second depth interval. The method can thus further comprise
removing the
acoustic sensor from the wellbore between obtaining the -first baseline sample
data set and
obtaining the second baseline sample data set (e.g., the acoustic sensor 164
can be removed
from the wellbore 114 prior to setting a well barrier element (e.g., a cement
plug
130A/130B/130C and/or a bridge plug 131A/131B) and/or performing a workover
procedure
to reduce the fluid flow in an attempt to plug fluid flow at an identified
fluid flow location,
and redeployed in the wellbore 114 subsequent the setting of the well barrier
element).
[001091 Any of
the systems and methods disclosed herein can be carried out on a
computer or other device comprising a processor, such as the acquisition
device 160 of
Figure 1. Figure 9 illustrates a computer system 780 suitable for implementing
one or more
embodiments disclosed herein such as the acquisition device or any portion
thereof. The
computer system 780 includes a processor 782 (which may be referred to as a
central
processor unit or CPU) that is in communication with memory devices including
secondary
storage 784, read only memory (ROM) 786, random access memory (RAM) 788,
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input/output (i/0) devices 790, and network connectivity devices 792. The
processor 782
may be implemented as one or more CPU chips.
1001101 It is
understood that by programming and/or loading executable instructions
onto the computer system 780, at least one of the CPU 782, the RAM 788, and
the ROM 786
are changed, transforming the computer system 780 in part into a particular
machine or
apparatus having the novel functionality taught by the present disclosure. It
is fundamental to
the electrical engineering and software engineering arts that functionality
that can be
implemented by loading executable software into a computer can be converted to
a hardware
implementation by well-known design rules. Decisions between implementing a
concept in
software versus hardware typically hinge on considerations of stability of the
design and
numbers of units to be produced rather than any issues involved in translating
from the
software domain to the hardware domain. Generally, a design that is still
subject to frequent
change may be preferred to be implemented in software, because re-spinning a
hardware
implementation is more expensive than re-spinning a software design.
Generally, a design
that is stable that will be produced in large volume may be preferred to be
implemented in
hardware, for example in an application specific integrated circuit (ASIC),
because for large
production runs the hardware implementation may be less expensive than the
software
implementation. Often a design may be developed and tested in a software form
and later
transformed, by well-known design rules, to an equivalent hardware
implementation in an
application specific integrated circuit that hardwires the instructions of the
software. In the
same manner as a machine controlled by a new ASIC is a particular machine or
apparatus,
likewise a computer that has been programmed and/or loaded with executable
instructions
may be viewed as a particular machine or apparatus.
1001111
Additionally, after the system 780 is turned on or booted, the CPU 782 may
execute a computer program or application. For example, the CPU 782 may
execute software
or firmware stored in the ROM 786 or stored in the RAM 788. In some cases, on
boot and/or
when the application is initiated, the CPU 782 may copy the application or
portions of the
application from the secondary storage 784 to the RAM 788 or to memory space
within the
CPU 782 itself, and the CPU 782 may then execute instructions that the
application is
comprised of. in some cases, the CPU 782 may copy the application or portions
of the
application from memory accessed via the network connectivity devices 792 or
via the I/O
devices 790 to the RAM 788 or to memory space within the CPU 782, and the CPU
782 may
then execute instructions that the application is comprised of. During
execution, an
application may load instructions into the CPU 782, for example load some of
the
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instructions of the application into a cache of the CPU 782. In some contexts,
an application
that is executed may be said to configure the CPU 782 to do something, e.g.,
to configure the
CPU 782 to perform the function or functions promoted by the subject
application. When the
CPU 782 is configured in this way by the application, the CPU 782 becomes a
specific
purpose computer or a specific purpose machine.
[00112] The
secondary storage 784 is typically comprised of one or more disk drives
or tape drives and is used for non-volatile storage of data and as an over-
flow data storage
device if RAM 788 is not large enough to hold all working data. Secondary
storage 784 may
be used to store programs which are loaded into RAM 788 when such programs are
selected
for execution. The ROM 786 is used to store instructions and perhaps data
which are read
during program execution. ROM 786 is a non-volatile memory device which
typically has a
small memory capacity relative to the larger memory capacity of secondary
storage 784. The
RAM 788 is used to store volatile data and perhaps to store instructions.
Access to both
ROM 786 and RAM 788 is typically faster than to secondary storage 784. The
secondary
storage 784, the RAM 788, and/or the ROM 786 may be referred to in some
contexts as
computer readable storage media and/or non-transitory computer readable media.
1001131 I/O
devices 790 may include printers, video monitors, liquid crystal displays
(LCDs), touch screen displays, keyboards, keypads, switches, dials, mice,
track balls, voice
recognizers, card readers, paper tape readers, or other well-known input
devices.
1001141 The
network connectivity devices 792 may take the form of modems, modem
banks, Ethernet cards, universal serial bus (USB) interface cards, serial
interfaces, token ring
cards, fibre distributed data interface (FDDI) cards, wireless local area
network (MAN)
cards, radio transceiver cards that promote radio communications using
protocols such as
code division multiple access (CDMA), global system for mobile communications
(GSM),
long-term evolution (I,TE), worldwide interoperability for microwave access
(WiMAX), near
field communications (NFC), radio frequency identity (RFID), and/or other air
interface
protocol radio transceiver cards, and other well-known network devices. These
network
connectivity devices 792 may enable the processor 782 to communicate with the
Internet or
one or more intranets. With such a network connection, it is contemplated that
the processor
782 might receive information from the network, or might output information to
the network
(e.g., to an event database) in the course of performing the above-described
method steps.
Such information, which is often represented as a sequence of instructions to
be executed
using processor 782, may be received from and outputted to the network, for
example, in the
form of a computer data signal embodied in a carrier wave.
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1001151 Such
information, which may include data or instructions to be executed using
processor 782 for example, may be received from and outputted to the network,
for example,
in the form of a computer data baseband signal or signal embodied in a carrier
wave. The
baseband signal or signal embedded in the carrier wave, or other types of
signals currently
used or hereafter developed, may be generated according to several methods
well-known to
one skilled in the art. The baseband signal and/or signal embedded in the
carrier wave may
be referred to in some contexts as a transitory signal
[001161 The
processor 782 executes instructions, codes, computer programs, scripts
which it accesses from hard disk, floppy disk, optical disk (these various
disk based systems
may all be considered secondary storage 784), flash drive, ROM 786, RAM 788,
or the
network connectivity devices 792. While only one processor 782 is shown,
multiple
processors may be present. Thus, while instructions may be discussed as
executed by a
processor, the instructions may be executed simultaneously, serially, or
otherwise executed
by one or multiple processors. Instructions, codes, computer programs,
scripts, and/or data
that may be accessed from the secondary storage 784, for example, hard drives,
floppy disks,
optical disks, and/or other device, the ROM 786, and/or the RAM 788 may be
referred to in
some contexts as non-transitory instructions and/or non-transitory
information.
1001171 In an
embodiment, the computer system 780 may comprise two or more
computers in communication with each other that collaborate to perform a task.
For example,
but not by way of limitation, an application may be partitioned in such a way
as to permit
concurrent and/or parallel processing of the instructions of the application.
Alternatively, the
data processed by the application may be partitioned in such a way as to
permit concurrent
and/or parallel processing of different portions of a data set by the two or
more computers. In
an embodiment, virtualization software may be employed by the computer system
780 to
provide the functionality of a number of servers that is not directly bound to
the number of
computers in the computer system 780. For example, virtualization software may
provide
twenty virtual servers on four physical computers. In an embodiment, the
functionality
disclosed above may be provided by executing the application and/or
applications in a cloud
computing environment. Cloud computing may comprise providing computing
services via a
network connection using dynamically scalable computing resources. Cloud
computing may
be supported, at least in part, by virtualization software. A cloud computing
environment
may be established by an enterprise and/or may be hired on an as-needed basis
from a third
party provider. Some cloud computing environments may comprise cloud computing
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resources owned and operated by the enterprise as well as cloud computing
resources hired
and/or leased from a third party provider.
[00118] In an
embodiment, some or all of the functionality disclosed above may be
provided as a computer program product. The computer program product may
comprise one
or more computer readable storage medium having computer usable program code
embodied
therein to implement the functionality disclosed above. The computer program
product may
comprise data structures, executable instructions, and other computer usable
program code.
The computer program product may be embodied in removable computer storage
media
and/or non-removable computer storage media. The removable computer readable
storage
Medium may comprise, without limitation, a paper tape, a magnetic tape,
magnetic disk, an
optical disk, a solid state memory chip, for example analog magnetic tape,
compact disk read
only memory (CD-ROM) disks, floppy disks, jump drives, digital cards,
multimedia cards,
and others. The computer program product may be suitable for loading, by the
computer
system 780, at least portions of the contents of the computer program product
to the
secondary storage 784, to the ROM 786, to the RAM 788, and/or to other non-
volatile
memory and volatile memory of the computer system 780. The processor 782 may
process
the executable instructions and/or data structures in part by directly
accessing the computer
program product, for example by reading from a CD-ROM disk inserted into a
disk drive
peripheral of the computer system 780. Alternatively, the processor 782 may
process the
executable instructions and/or data structures by remotely accessing the
computer program
product, for example by downloading the executable instructions and/or data
structures from
a remote server through the network connectivity devices 792. The computer
program
product may comprise instructions that promote the loading and/or copying of
data, data
structures, files, and/or executable instructions to the secondary storage
784, to the ROM 786,
to the RAM 788, and/or to other non-volatile memory and volatile memory of the
computer
system 780.
(00119) In some
contexts, the secondary storage 784, the ROM 786, and the RAM 788
may be referred to as a non-transitory computer readable medium or a computer
readable
storage media. A dynamic RAM embodiment of the RAM 788, likewise, may be
referred to
as a non-transitory computer readable medium in that while the dynamic RAM
receives
electrical power and is operated in accordance with its design, for example
during a period of
time during which the computer system 780 is turned on and operational, the
dynamic RAM
stores information that is written to it. Similarly, the processor 782 may
comprise an internal
RAM, an internal ROM, a cache memory, and/or other internal non-transitory
storage blocks,
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sections, or components that may be referred to in some contexts as non-
transitory computer
readable media or computer readable storage media.
EXAMPLES
1001201 The
embodiments having been generally described, the following examples
are given as particular embodiments of the disclosure and to demonstrate the
practice and
advantages thereof. It is understood that the examples are given by way of
illustration and
are not intended to limit the specification or the claims in any manner.
Example 1
1001211 In this
Example, a DAS system as described herein was utilized to plug a well
for abandonment. Figure 10 is a schematic showing baseline logs for three
runs: Run 1 prior to
placement of a first mell barrier element (WBE1), referred to in Figure 10 as
"Pre WBE1
placement; Run 2 after placement of WBE1, referred to in Figure 10 as "Post
WBE1
placement"; and Run 3 after placement of second and third well barrier
elements (WBE2/3),
referred to in Figure 10 as "Post WBE2/3 placement." DAS logs were also
obtained while
inducing a first pressure by bleeding the B annulus for Run 2 after placement
of WBE1 and
Run 3 after placement of WBE2/3, and while inducing a second pressure
differential by
bleeding the C annulus for Run 2 after placement of WBE1 and for Run 3 after
placement of
WBE2/3.
1001221 Figure
10 is a schematic showing baseline logs for each of the three runs: Run 1
prior to placement of a first well barrier element (WBE1), referred to in
Figure 10 as "Pre
WBE1 placement; Run 2 after placement of WBE1, referred to in Figure 10 as
"Post VvI3E1
placement"; and Run 3 after placement of the second and third well barrier
elements
(WBE2/3), referred to in Figure 10 as "Post WBE2/3 placement." WBE1 was placed
at a first
depth of 9000 feet; WBE 2 was placed at a second depth of about 5500 feet; and
WBE 3 was
also placed at the second depth of about 5500 feet. As seen in Figure 10,
little to no acoustic
noise was captured in the baseline data in Run 3, after the placement of
WBE2/3, and, as
expected, similar behavior was observed in the acoustic response in Run 2 and
Run 3. The logs
indicate effective barrier performance. The baseline logs were obtained by
obtaining the signal
from the DAS sensor in the wellbore and averaging the relative acoustic
amplitude over time.
Consistent behavior was observed throughout the baseline logging duration.
1001231 As noted
above, subsequent the placement of the second and third well barrier
elements WBE2/3, another baseline log (e.g., baseline for Run 3) was performed
by rerunning
the DAS sensor in the well to the second depth. A second pressure differential
was induced by
bleeding the C annulus (referred to in Figure 11 as "C Bleed"), and a DAS log
obtained during
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the C bleed of Run 3. Figure 11 is a schematic showing the DAS logs (e.g., the
acoustic logs)
for the baseline and C bleed of Run 3 after setting of WBE2/3. As can be seen
in Figure 11,
little to no acoustic noise is observed in the zone above the top of the
cement (TOC) of
WBE2/3, and similar behavior to the baseline is observed during the C bleed.
[001241 As noted
above, a first pressure differential was induced by performing a bleed
of the B annulus (referred to as "B Bleed" in the Figures). Figure 12 is a
schematic of the DAS
logs obtained during the B bleed of Run 2 (e.g., after placement of WBE1.) and
during the B
bleed of Run 3 (e.g., after placement of W11E2/3), As seen in Figure 12,
little to no acoustic
noise is captured in the zone above the TOC of WBE2/3.
1001251 Figure
13 is a schematic showing the DAS logs for the baseline, the B bleed and
the C bleed for Run 3 (e.g., after placement of the second and third well
barrier elements
WBE2/3). As seen in Figure 13, the trend remained the same in the B bleed and
no significant
noise zones were observed.
[00126] Figure
14A is a schematic of the DAS logs for Run I (e.g., prior to placement of
first well barrier element WBE1.), including one hour averaged comparisons for
the baseline,
the B bleed, and the C bleed. Figure 14B is a schematic of the DAS logs for
the baseline
corrected C bleed (e.g., the C bleed minus the baseline) of Run 1 and a
baseline smoothed log
of the C bleed of Run 1, which was obtained by subtracting the C bleed from
the baseline and
then smoothing (e.g., running a median filter or moving average). Figure 1.5A
is a schematic of
the DAS logs for Run 3 (e.g., after placement of the second and third well
barrier elements
WBE2/3), including one hour averaged comparisons for the baseline, the B
bleed, and the C
bleed. Figure 15B is a schematic of the DAS logs for the baseline corrected C
bleed (e.g., the C
bleed minus the baseline) of Run 3 and a baseline smoothed log of the C bleed
of Run 3.
[00127] Figure
16 is a schematic of the DAS logs of the baseline smoothed C bleeds of
Run I (e.g., prior to placement of WBE1) and Run 3 (e.g., after placement of
WBE2/3). As
seen in Figure 16, a reduction in the baseline smoothed flow noise observed in
Runs I and 3
evidences a drop in overall flow noise at shallower depths during the bleed,
indicating
successful barrier placement and performance,
[00128] While
various embodiments have been shown and described, modifications
thereof can be made by one skilled in the art without departing from the
spirit and teachings
of the disclosure. The embodiments described herein are exemplary only, and
are not
intended to be limiting. Many variations and modifications of the subject
matter disclosed
herein are possible and are within the scope of the disclosure. Where
numerical ranges or
limitations are expressly stated, such express ranges or limitations should be
understood to
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include iterative ranges or limitations of like magnitude falling within the
expressly stated
ranges or limitations (e.g., from about I to about 10 includes, 2, 3, 4, etc.;
greater than 0.10
includes 0.11, 0.12, 0.13, etc.). For example, whenever a numerical range with
a lower limit,
Ri and an upper limit, Ru is disclosed, any number falling within the range is
specifically
disclosed. In particular, the following numbers within the range are
specifically disclosed:
R=Rfei-k*(Ru-RL), wherein k is a variable ranging from 1 percent to 100
percent with a I
percent increment, i.e., k is 1 percent, 2 percent, 3 percent, 4 percent, 5
percent, 50 percent,
51 percent, 52 percent, ... , 95 percent, 96 percent, 97 percent, 98 percent,
99 percent, or 100
percent. Moreover, any numerical range defined by two R numbers as defined in
the above is
also specifically disclosed. Use of the term "optionally" with respect to any
element of a
claim is intended to mean that the subject element is required, or
alternatively, is not required.
Both alternatives are intended to be within the scope of the claim. Use of
broader terms such
as comprises, includes, having, etc. should be understood to provide support
for narrower
terms such as consisting of, consisting essentially a comprised substantially
of, etc.
[00129]
Accordingly, the scope of protection is not limited by the description set out
above but is only limited by the claims which follow, that scope including all
equivalents of
the subject matter of the claims. Each and every claim is incorporated into
the specification
as an embodiment of the present disclosure. Thus, the claims are a further
description and are
an addition to the embodiments of the present disclosure. The discussion of a
reference is not
an admission that it is prior art to the present disclosure, especially any
reference that may
have a publication date after the priority date of this application. The
disclosures of all
patents, patent applications, and publications cited herein are hereby
incorporated by
reference, to the extent that they provide exemplary, procedural, or other
details
supplementary to those set forth herein.
ADDITIONAL DESCRIPTION
[00130] The
particular embodiments disclosed above are illustrative only, as the
present disclosure may be modified and practiced in different but equivalent
manners
apparent to those skilled in the art having the benefit of the teachings
herein. Furthermore, no
limitations are intended to the details of construction or design herein
shown, other than as
described in the claims below. It is therefore evident that the particular
illustrative
embodiments disclosed above may be altered or modified and all such variations
are
considered within the scope and spirit of the present disclosure. Alternative
embodiments
that result from combining, integrating, and/or omitting features of the
embodiment(s) are
also within the scope of the disclosure. While compositions and methods are
described in
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broader terms of "having", "comprising," "containing," or "including" various
components or
steps, the compositions and methods can also "consist essentially or or
"consist or the
various components and steps. Use of the term "optionally" with respect to any
element of a
claim means that the element is required, or alternatively, the element is not
required, both
alternatives being within the scope of the claim.
[00131] Numbers and ranges disclosed above may vary by some amount.
Whenever a
numerical range with a lower limit and an upper limit is disclosed, any number
and any
included range falling within the range are specifically disclosed. In
particular, every range
of values (of the form, "from about a to about b," or, equivalently, "from
approximately a to
h," or, equivalently, "from approximately a-b") disclosed herein is to be
understood to set
forth every number and range encompassed within the broader range of values.
Also, the
terms in the claims have their plain, ordinary meaning unless otherwise
explicitly and clearly
defined by the patentee. Moreover, the indefinite articles "a" or "an", as
used in the claims,
are defined herein to mean one or more than one of the element that it
introduces. If there is
any conflict in the usages of a word or term in this specification and one or
more patent or
other documents, the definitions that are consistent with this specification
should be adopted.
[00132] Embodiments disclosed herein include:
[00133] A: A method of abandoning a wellhore, the method comprising:
obtaining a
first sample data set within a wellbore, wherein the first sample data set is
a sample of an
acoustic signal originating within the wellbore; determining a first plurality
of frequency
domain features of the -first sample data set; identifying a first fluid flow
location within the
wellbore using the first plurality of frequency domain features; setting a
first barrier at or
above the first fluid flow location; obtaining a second sample data set within
the wellhore
above the first barrier, wherein the second sample data set is a sample of an
acoustic signal
originating within the wellhore above the first barrier; determining a second
plurality of
frequency domain features of the second sample data set; and identifying that
a fluid flow
rate or fluid flow mechanism at the first fluid flow location has been reduced
or eliminated
and/or identifying a second fluid flow location within the wellbore using the
second plurality
of frequency domain features.
[00134] B: A system for abandoning a welibore, the system comprising; a
receiver
unit comprising a processor and a memory., wherein the receiver unit is
configured to receive
an acoustic signal from a sensor disposed in a wellbore, NA/herein a
processing application is
stored in the memory, and wherein the processing application, when executed on
the
processor, configures the processor to: receive a first baseline acoustic
signal data set from
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the sensor, wherein the first baseline acoustic signal data set comprises an
indication of the
acoustic signal received over a first depth interval while the wellbore is
shut in; receive a first
flowing acoustic signal data set, wherein the first flowing acoustic signal
data set comprises
an indication of the acoustic signal received over the first depth interval
while a first pressure
differential is induced within the wellbore; determine a baseline fluid flow
log using the first
baseline acoustic signal data set; determine a flowing fluid flow log using
the first flowing
acoustic signal data set; subtract the baseline fluid flow log from the
flowing fluid flow log to
provide a first sample data set; determine a first plurality of frequency
domain features of the
first sample data set; identify a first fluid flow location within the
1,vellbore using the first
plurality of frequency domain features; determine a change in a flow rate or
flow mechanism
at the first fluid flow location using the first sample data set; and generate
an output
indicative of the first fluid flow location and a change in the flow rate or
flow mechanism at
the first fluid flow location.
[00135.1 C: A
method of comparing acoustic signals obtained between different
acoustic sensor operations in a wellbore, the method comprising: obtaining a
first baseline
sample data set over a first depth interval within a wellbore, wherein the
first baseline data set
is a sample of an acoustic signal originating within the wellbore; determining
at least one
frequency domain feature of the first baseline sample data set; inducing a
first pressure
differential within the wellbore; obtaining a first acoustic data set over the
first depth interval
within the wellbore while inducing the first pressure differential;
determining at least one
frequency domain feature of the first acoustic data set; subtracting the at
least one frequency
domain feature of the first baseline sample data set from the at least one
frequency domain
feature of the first acoustic data set to obtain a first sample data set over
the first depth
interval; obtaining a second baseline sample data set over a second depth
interval within the
wellbore, wherein the second baseline sample data set is a sample of an
acoustic signal
originating within the wellbore, wherein the second depth interval overlaps
with the first
depth interval; determining at least one frequency domain feature of the
second baseline
sample data set; inducing a second pressure differential within the wellbore;
obtaining a
second acoustic data set over the second depth interval within the w-ellbore
while inducing the
second pressure differential; determining at least one frequency domain
feature of the second
acoustic data set; subtracting the at least one frequency domain feature of
the second baseline
sample data set from the at least one frequency domain feature of the second
acoustic data set
to obtain a second sample data set over the second depth interval; and
comparing the second
sample data set to the first sample data set over the second depth interval,
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[001361 D: A
system for of comparing acoustic signals obtained between different
acoustic sensor operations in a wellbore, the system comprising: a receiver
unit comprising a
processor and a memory, wherein the receiver unit is configured to receive an
acoustic signal
from a sensor disposed in a wellbore, wherein a processing application is
stored in the
memory, and wherein the processing application, when executed on the
processor, configures
the processor to: receive a first baseline sample data set over a first depth
interval within the
wellbore, wherein the first baseline data set is a sample of an acoustic
signal originating
within the wellbore; determine at least one frequency domain feature of the
first baseline
sample data set; receive a first acoustic data set over the first depth
interval within the
wellbore, wherein the first acoustic data sat is an acoustic signal obtained
while a first
pressure differential is induced within the wellbore; determine at least one
frequency domain
feature of the first acoustic data set; subtract the at least one frequency
domain feature of the
first baseline sample data set from the at least one frequency domain feature
of the first
acoustic data set to obtain a first sample data set over the first depth
interval; receive a second
baseline sample data set over a second depth interval within the wellbore,
wherein the second
baseline sample data set is a sample of an acoustic signal originating within
the wellbore,
wherein the second depth interval overlaps with the first depth interval;
determine at least one
frequency domain feature of the second baseline sample data set; receive a
second acoustic
data set over the second depth interval within the weilbore, wherein the
second acoustic data
sat is an acoustic signal obtained while a second pressure differential is
induced within the
wellbore; determine at least one frequency domain feature of the second
acoustic data set;
subtract the at least one frequency domain feature of the second baseline
sample data set from
the at least one frequency domain feature of the second acoustic data set to
obtain a second
sample data set over the second depth interval; and compare the second sample
data set to the
first sample data set over the second depth interval; and generate an output
indicative of the
comparison between the second sample data set and the first sample data set..
100137] E: A
method of abandoning a wellbore, the method comprising: obtaining a
first sample data set over a first depth interval within a ,,vellf.)ore,
wherein the first sample
data set comprises a first acoustic data set having a first baseline acoustic
sample data set
subtracted therefrom, wherein the first acoustic data set is obtained over the
first depth
interval while a first pressure differential is induced in the wellbore, and
wherein the first
baseline acoustic sample data set is obtained over the first depth interval
while the vvellbore is
shut in; identifying a fluid flow location within the first depth interval
using the first sample
data set; obtaining a second sample data set over a second depth interval
within a wellbore,
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wherein the second sample data set is obtained after a barrier is set at or
above the fluid flow
location, wherein the second sample data set comprises a second acoustic data
set having a
second baseline acoustic sample data set subtracted therefrom, wherein the
second acoustic
data set is obtained over the second depth interval while a second pressure
differential is
induced in the wellbore, wherein the second baseline acoustic sample data set
is obtained
over the second depth interval while the wellbore is shut in, and wherein the
second depth
interval is overlaps the first depth interval; comparing the first sample data
set to the second
sample data set; and determining whether or not fluid flow at the -fluid flow
location is
substantially blocked by the barrier.
1001381 F: A
system for abandoning a wellbore, the system comprising: a receiver
unit comprising a processor and a memory, wherein the receiver unit is
configured to receive
an acoustic signal from a sensor disposed in a wellbore, wherein a processing
application is
stored in the memory, and wherein the processing application, when executed on
the
processor, configures the processor to: receive a first baseline acoustic
sample data set and a
first acoustic data set from the sensor, wherein the first acoustic data set
is an acoustic signal
obtained over a -first depth interval while a first pressure differential is
induced in the
wellbore, and wherein the first baseline acoustic sample data set is an
acoustic signal
obtained over the first depth interval while the wellbore is shut in,
determine a first sample
data set over a first depth interval within the wellbore, wherein the first
sample data set
comprises the first acoustic data set having the first baseline acoustic
sample data set
subtracted therefrom; identify a fluid flow location within the first depth
interval using the
first sample data set; receive a second baseline acoustic sample data set and
a second acoustic
data set from the sensor, wherein the second acoustic data set is an acoustic
signal obtained
over a second depth interval while a second pressure differential is induced
in the wellbore
and after a barrier is set at or above the fluid flow location, and wherein
the second baseline
acoustic sample data set is an acoustic signal obtained over the second depth
interval while
the welibore is shut in and after the barrier is set at or above the fluid
flow location;
determine a second sample data set over the second depth interval within the
wellbore,
wherein the second sample data set comprises the second acoustic data set
having the second
baseline acoustic sample data set subtracted therefrom; compare the first
sample data set to
the second sample data set; determine whether or not fluid -flow at the fluid
flow location is
substantially blocked by the barrier; and generate an output indicative the
determination of
whether or not the fluid flow at the -fluid flow location is substantially
blocked by the barrier.
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Each of embodiments A, B, C, D, E, and F may have one or more of the following
additional
elements: Element 1: fiirther comprising: setting a second barrier at or above
the second
fluid flow location; and substantially blocking fluid flow from the first
fluid flow location and
the second fluid flow location using the first barrier and the second barrier.
Element 2:
wherein at least one of the first sample data set or the second sample data
set is representative
of the acoustic signal across a frequency spectrum. Element 3: wherein
obtaining the first
sample data set comprises: obtaining a baseline acoustic signal data set while
the wellbore is
shut in; obtaining a baseline fluid flow log using the baseline acoustic
signal data set;
inducing a pressure differential within the wellbore; obtaining a flowing
acoustic signal data
set while inducing the pressure differential; obtaining a flowing fluid flow
log using the
flowing acoustic signal data set; and subtracting the baseline fluid flow log
from the flowing
fluid flow log. Element 4: wherein the wellbore comprises one or more tubular
strings and
one or more annuli disposed between at least one of: i) two adjacent tubular
strings of the one
or more tubular strings, ii) a tubular string of the one or more tubular
strings and a formation,
or iii) both i and ii, and wherein inducing the pressure differential
comprises releasing a fluid
from an annulus of the one or more annuli. Element 5: wherein the baseline
acoustic signal
data set is a time averaged acoustic data set. Element 6: wherein the barrier
(e.g., the first
barrier, the second barrier, or both the first barrier and the second barrier)
comprise a bridge
plug, a packer, a cement plug, or a combination thereof. Element 7: wherein
the first fluid
flow location, the second fluid flow location, or both the first fluid flow
location and the
second fluid flow location comprise: a location of flow from a formation into
the wellbore, a
location of flow between the formation and an annulus between a tubular string
and the
wellbore wall, or a location of flow between annuli formed between a plurality
of tubular
strings in the wellbore. Element 8: wherein identifying the first fluid flow
location
comprises comparing the first plurality of frequency domain features with a
fluid flow event
signature, and/or wherein identifying the second fluid flow location comprises
comparing the
second plurality of frequency domain features with a fluid flow event
signature. Element 9:
further comprising: correlating the first fluid flow location with one or more
structural
features within the wellbore; and determining a source of the fluid flow at
the first fluid flow
location based on the correlating of the first fluid flow location with the
one or more
structural features. Element 10: wherein the wellbore comprises one or more
tubular strings
and one or more annuli disposed between at least one of: i) two adjacent
tubular strings of
the one or more tubular strings, ii) a tubular string of the one or more
tubular strings and a .
formation, or iii) both i and ii, and wherein identifying the first fluid flow
location or the
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second fluid flow location comprises determining an annulus of the one or more
annuli and a
depth at which the first fluid flow location or the second fluid flow location
is present.
Element 11: wherein the processing application, when executed on the
processor, further
configures the processor to: receive a second baseline acoustic signal data
set from within
the wellbore, wherein the second baseline acoustic signal data set comprises
an indication of
the acoustic signal received over a second depth interval of the wellbore
while the wellbore is
shut in, subsequent the setting of a barrier at or above the identified first
fluid flow location,
wherein the second depth interval overlaps the first depth interval; receive a
second flowing
acoustic signal data set, wherein the second flowing acoustic signal data set
comprises an
indication of the acoustic signal received over the second depth interval
while a second
pressure differential is induced within the wellbore, subsequent the setting
of the barrier at or
above the identified first fluid flow location; determine a second baseline
fluid flow log using
the second baseline acoustic signal data set; determine a second flowing fluid
flow log using
the second flowing acoustic signal data set; subtract the second baseline
fluid flow log from
the second flowing fluid flow log to provide a second sample data set;
determine a second
plurality of frequency domain features of the second sample data set;
determine that a fluid
flow rate or a fluid flow mechanism at the first fluid flow location within
the wellbore has
been reduced or eliminated and/or identify a second fluid flow location using
the second
plurality of frequency domain features; and generate an output indicative of
the identified
reduction or elimination of the fluid flow at the first fluid flow location
and/or indicative of
the second fluid flow location. Element 12: The system of claim 12 further
comprising:
validating the barrier based on the identified reduction or elimination of
fluid flow rate or the
fluid flow mechanism at the first fluid flow location. Element 13: further
comprising: the
sensor, wherein the sensor comprises a fibre optic cable disposed within the
wellbore; and an
optical generator coupled to the fibre optic cable, wherein the optical
generator is configured
to generate a light beam and pass the light beam into the fibre optic cable.
Element 14:
wherein the wellbore comprises one or more tubular strings and one or more
annuli disposed
between at least one of: i) two adjacent tubular strings of the one or more
tubular strings, ii) a
tubular string of the one or more tubular strings and a formation, or iii)
both i and ii, and
wherein where the first fluid flow location, the second fluid flow location,
or both comprise:
a location of flow from a formation into the wellbore, a location of flow
between the
formation and an annulus between a tubular string and the wellbore wall, or a
location of
flow between annuli formed between a plurality of tubular strings in the
wellbore. Element
15: wherein inducing the first pressure differential and/or inducing the
second pressure
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differential comprises: opening a flow valve within an annulus of the one or
more annuli;
and inducing a fluid flow based on opening of the flow valve. Element 16:
wherein the first
pressure differential and/or the second pressure differential is indicative of
a difference in
pressure between an annulus of the one or more annuli and an adjacent flow
path in the
wellbore. Element 17: wherein the processing application, when executed on the
processor,
further configures the processor to: integrate or time average an acoustic
intensity within
specified frequency bands for fluid flow in the wellbore, and determine a
relative fluid
flowrate for fluid flow based on the integrated acoustic intensity. Element
18: wherein the
output comprises a fluid flow log. Element 19: further comprising: determining
a fluid flow
reduction at a fluid flow location based on comparing the second sample data
set to the first
sample data set. Element 20: wherein the first baseline sample data set and
the first acoustic
data set are obtained with an acoustic sensor disposed in the wellbore within
the first depth
interval, wherein the second baseline sample data set and the second acoustic
data set are
obtained with the acoustic sensor disposed in the wellbore within the second
depth interval,
and wherein the method further comprises: removing the acoustic sensor from
the wellbore
between obtaining the first baseline sample data set and obtaining the second
baseline sample
data set. Element 21: wherein identifying the fluid flow location within the
first depth
interval using the first sample data set comprises determining a plurality of
frequency domain
features of the first sample data set. Element 22: wherein the plurality of
frequency domain
features of the first sample data set comprise at least two frequency domain
features selected
from the group consisting of a spectral centroid, a spectral spread, a
spectral roll-off, a
spectral skewness, an RMS hand energy, a total RMS energy, a spectral
_flatness, a spectral
slope, a spectral kurtosis, a spectral flux, spectral entropy, a spectral
autocorrelation function,
and combinations thereof.
[00139] While
various embodiments in accordance with the principles disclosed herein
have been shown and described above, modifications thereof may be made by one
skilled in
the art without departing from the spirit and .the teachings of the
disclosure. The
embodiments described herein are representative only and are not intended to
be limiting.
Many variations, combinations, and modifications are possible and are within
the scope of
the disclosure. Alternative embodiments that result from combining,
integrating, and/or
omitting features of the embodiment(s) are also within the scope of the
disclosure.
Accordingly, the scope of protection is not limited by the description set out
above, but is
defined by the claims which follow, that scope including all equivalents of
the subject matter
of the claims. Each and every claim is incorporated as further disclosure into
the
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specification and the claims are embodiment(s) of the present invention(s).
Furthermore, any
advantages and features described above may relate to specific embodiments,
but shall not
limit the application of such issued claims to processes and structures
accomplishing any or
all of the above advantages or having any or all of the above features.
[001401
Additionally, the section headings used herein are provided for consistency
with the suggestions under 37 C.F.R. 1.77 or to otherwise provide
organizational cues. These
headings shall not limit or characterize the invention(s) set out in any
claims that may issue
from this disclosure. Specifically and by way of example, although the
headings might refer
to a "Field," the claims should not be limited by the language chosen under
this heading to
describe the so-called field. Further, a description of a technology in the
"Background" is not
to be construed as an admission that certain technology is prior art to any
invention(s) in this
disclosure. Neither is the "Summary" to be considered as a limiting
characterization of the
invention(s) set forth in issued claims. Furthermore, any reference in this
disclosure to
"invention" in the singular should not be used to argue that there is only a
single point of
novelty in this disclosure. Multiple inventions may be set forth according to
the limitations
of the multiple claims issuing from this disclosure, and such claims
accordingly define the
invention(s), and their equivalents, that are protected thereby. In all
instances, the scope of
the claims shall be considered on their own merits in light of this
disclosure, but should not
be constrained by the headings set forth herein.
[001411 Use of
broader tehris such as comprises, includes, and having should be
understood to provide support for narrower terms such as consisting of,
consisting essentially
of, and comprised substantially of. Use of the term "optionally," "may,"
"might," "possibly,"
and the like with respect to any element of an embodiment means that the
element is not
required, or alternatively, the element is required, both alternatives being
within the scope of
the embodiment(s). Also, references to examples are merely provided for
illustrative
purposes, and are not intended to be exclusive.
[001421 While
preferred embodiments have been shown and described, modifications
thereof can be made by one skilled in the art without departing from the scope
or teachings
herein. The embodiments described herein are exemplary only and are not
limiting. Many
variations and modifications of the systems, apparatus, and processes
described, herein are
possible and are within the scope of the disclosure. For example, the relative
dimensions of
various parts, the materials from which the various parts are made, and other
parameters can
he varied. Accordingly, the scope of protection is not limited to the
embodiments described
herein, but is only limited by the claims that follow, the scope of which
shall include all
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equivalents of the subject matter of the claims. Unless expressly stated
otherwise, the steps
in a method claim may be performed in any order. The recitation of identifiers
such as (a),
(b), (c) or (1), (2), (3) before steps in a method claim are not intended to
and do not specify a
particular order to the steps, but rather are used to simplify subsequent
reference to such
steps.
[00143] Also,
techniques, systems, subsystems, and methods described and illustrated
in the various embodiments as discrete or separate may be combined or
integrated with other
systems, modules, techniques, or methods without departing from the scope of
the present
disclosure. Other items shown or discussed as directly coupled or
communicating with each
other may be indirectly coupled or communicating through some interface,
device, or
intermediate component, whether electrically, mechanically, or otherwise.
Other examples of
changes, substitutions, and alterations are ascertainable by one skilled in
the art and could be
made without departing from the spirit and scope disclosed herein.
49
