Classifications

• • E—FIXED CONSTRUCTIONS
  • E21—EARTH OR ROCK DRILLING; MINING
  • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
  • E21B47/00—Survey of boreholes or wells
  • E21B47/10—Locating fluid leaks, intrusions or movements
  • E21B47/107—Locating fluid leaks, intrusions or movements using acoustic means

Definitions

• 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 itseif.
• plugs are positioned in a well to be abandoned in order to prevent leaks of fluid from the well.
• 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
• a system for abandoning a wellbore 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 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
• 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, w-herein the second baseline sample data set is a sample of an a
• a system for of comparing acoustic signals obtained between different acoustic sensor operations in a wellbore 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
• 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 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
• a system for abandoning a wellbore 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
• 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 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.
• Figure 1 is a schematic, cross-sectional illustration of a downhole wellbore environment according to embodiments of this disclosure.
• Figure 2 is a schematic, cross-sectional illustration of another downhole wellbore environment according to embodiments of this disclosure.
• Figure 3 A is a schematic view of a wellbore environment 100B prior to placement of well barriers.
• Figure 3B is a schematic view of a wellbore environment 100C after placement of well barriers.
• Figure 4A is a schematic, cross-sectional view of an embodiment of a well with a wellbore tubular having an optical fibre associated therewith.
• Figure 4B is a schematic, cross-sectional view of another embodiment of a well with a wellbore tubular having an optical fibre associated therewith.
• Figure 5 illustrates an embodiment of a schematic processing flow for an acoustic signal.
• Figures 6A and 6B illustrate exemplary acoustic depth-time block graphs.
• Figures 7A, 7B, and 7C illustrate exemplary filtered acoustic depth-time graphs.
• Figure 8 illustrates an exemplary fluid flow log according to embodiments of this disclosure.
• Figure 9 schematically illustrates a computer that can be used to carry out various steps according to some embodiments of this disclosure.
• 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 WBEI, referred to in Figure 10 as“Pre WBE1 placement; Run 2 after placement of first well barrier element WBEI, 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.”
• Figure 11 is 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 1.
• DAS logs e.g., the acoustic logs
• Run 3 e.g., after setting of second and third well barrier elements WBE2/3 of Example 1.
• 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 WBE1) and Run 3 (e.g., after placement of second and third well barrier elements WBE2/3) of Example 1.
• 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.
• 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.
• 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 1 ) and a baseline smoothed log of the C bleed of Run 1 of Example 1.
• 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 dements WBE2/3) and a baseline smoothed log of the C bleed of Run 3 of Example 1.
• Figure 16 is a schematic of the DAS logs of the baseline smoothed C bleeds of Run 1 (e.g., prior to placement of first well barrier element WBE1) and Run 3 (i.e., after placement of second and third well barrier elements WBE2/3) of Example 1.
• 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.
• the terms“including” and“comprising” are used in an open-ended fashion, and thus should be interpreted to mean“including, but not limited to . . .
• references 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.
• 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.
• 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.
• P&A plugging and abandonment
• 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.
• fluid flow mechanism can refer to the fluid flow pathway, source, and/or flow type or phase of a flowing fluid
• 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.
• 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 logging, ultrasonic imaging, oxygen activation (for detection of water flow behind casing) with neutrons, and the like).
• 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.).
• DFO distributed fibre optic
• DTS distributed temperature sensing systems
• 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 the entire deployed fibre cable is the sensor. This can avoid the need to move the too! 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.
• DTS leak detection
• DAS Distributed Acoustic Sensors
• 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.
• the data can also be used in conjunction with surface and peripheral sensor data to enable semi -quantitative assessments of fluid flow rates.
• 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.
• 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 ieak 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).
• 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 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,
• 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.
• acoustic sampling at various points aiong 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.
• 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 volumes 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).
• 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 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.
• 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.
• 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.
• frequency domain features e.g., also referred to as spectral descriptors
• spectral descriptors can be used with DAS acoustic data processing in real time to provide various downhole surveillance applications.
• 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 seting of one or more well barriers.
• events may be referred to herein as“fluid flow” events.
• additional sensor data such as pressure sensors and/or flow sensors can be used to obtain data within the wellbore.
• 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 he used to determine a presence (or absence) and/or location of fluid flow.
• FIG. 1 an example of a wellbore operating environment 100 is shown.
• DAS distributed acoustic sensor
• exemplary environment 100 includes a wellbore 114 traversing a subterranean formation 102, casing 1 12 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.
• a plurality of spaced zonal isolation devices 117 and gravel packs 122 can he provided between tubular 120 and the sidewall of wellbore 114.
• the operating environment 100 includes a workover and/or drilling rig positioned at the surface and extending over the wellbore 114.
• the wellbore 114 can be a new wellbore, an existing wellbore, a straight wellbore, an extended reach wellbore, a sidetracked wellbore, a multilateral wellbore, and other types of wellbores for drilling and completing one or more production zones.
• 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).
• 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.
• Tubular 120 can be lowered into wellbore 114 for performing an operation such as drilling, completion, workover, treatment, and/or production processes.
• the tubular 120 is a completion assembly string including a distributed acoustic sensor (DAS) sensor coupled thereto.
• DAS distributed acoustic sensor
• 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.
• the tubular 120 may operate in any portion of the wellbore 1 14 (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.
• the DAS fibre 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.
• 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.
• 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.
• 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.
• zonal isolation devices 117 are used to isolate the various zones within the wellbore 114.
• each zonal isolation device 1 17 can be a packer (e.g., production packer, gravel pack packer, frac-pac packer, etc.).
• the zonal isolation devices 1 17 can be positioned between the screen assemblies 1 18, for example, to isolate different gravel pack zones or intervals along the wellbore 1 14 from each other. In general, the space between each pair of adjacent zonal isolation devices 117 defines a production interval.
• the screen assemblies 118 provide sand control capability.
• the sand control screen dements 1 18, 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.
• 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.
• 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.
• 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 1 14.
• 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.
• the flow of the various fluids into the wellbore 114 and/or through the w'ellbore 1 14 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.
• the event or acoustic signature can comprise thresholds or ranges for a plurality of different frequency domain features, combinations of frequency domain features, or modifications of a plurality of frequency domain features,
• 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 along 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,
• 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 1 14, to detect downhole acoustic signals/vibration perturbations.
• the DAS system can span a portion of the wellbore between a lower zona! isolation device (e.g., a plug, etc.) and a zone desired to be isolated as part of the abandonment process
• 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 optica! fibre 162, The resulting backseatered 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.
• 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
• An acquisition device 160 can be coupled to one end of the optical fibre 162.
• the light source 166 can generate the light (e.g., one or more light pulses), and the sensor 164 can collect and analyze the backseattered light returning up the optical fibre 162.
• the acquisition device 160 including the light source 166 and the sensor 164 can be referred to as an interrogator.
• 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.
• any suitable acoustic signal acquisition system can be used with the processing steps disclosed herein.
• 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,
• 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 easing 1 12 is illustrated in Figure 1, multiple annuli can be present.
• 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, (is) a tubular string of the one or more tubular strings and the formation 102, or (iii) both (i) and (ii).
• 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 1 12B, third casing 112C, and fourth casing 1 12D.
• 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 119B, or third annulus 119C), or a location of flow between annuli formed between a plurality of tubular strings in the wellbore 1 14 (e.g., between first annulus 119A and second annulus 119B or between second annulus 119B and third annulus 119C).
• 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, and/or within the first 100 m, within the first 150 m, within the first 200 m, or within about the first 300 m along the wellbore as measured from ground level.
• 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.
• 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.
• 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.
• 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 RMS energy, spectral flatness, , spectral scope, spectral kurtosis, a spectra! flux, spectral entropy, and a spectral autocorrelation function.
• RMS root mean square
• 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.
• S In order to compute the spectral spread, S, one has to take the deviation of the spectrum from the computed cen troid as per the following equation (all other terms defined above);
• the total RMS energy of the acoustic 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.
• 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-lntersection, and the max and media regression error may be used as features.
• the spectral kurtosis provides a measure of the flatness of a distribution around the mean value.
• 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.
• the acoustic sample data can be converted to the frequency domain.
• 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
• 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.
• the acoustic sample will be in the frequency domain in order to determine the spectral centroid and the spectral spread.
• the processor 168 can he configured to perform the conversion of the raw acoustic data and/or the acoustic sample data 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 reai time or near real time.
• 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.
• 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.
• a fluid flow' event or location e.g., depth
• 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.
• 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.
• 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.
• 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
• 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.
• 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 131A and the second cement plug 130B, and/or the third well barrier comprising the second bridge plug 131B and the third cement plug 130C.
• 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 131 A and the second cement plug 130B, and/or the third well barrier comprising the second bridge plug 13 IB and the third cement plug 130C has reduced or eliminated fluid flow.
• any number of well barriers can he 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.
• 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
• 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
• 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.
• 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.
• ASIC application specific integrated circuit
• 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.
• 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.
• CPU 782 itself, and the CPU 782 may then execute instructions that the application is comprised of.
• 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.
• an application may load instructions into the CPU 782, for example load some of the instructions of the application into a cache of the CPU 782,
• 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.
• the CPU 782 becomes a specific purpose computer or a specific purpose machine.
• ROM 786 and RAM 788 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,
• 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 (WLAN) 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 (LTE), 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.
• CDMA code division multiple access
• GSM global system for mobile communications
• LTE long-term evolution
• WiMAX worldwide interoperability for microwave access
• NFC near field communications
• RFID radio frequency identity
• These network connectivity devices 792 may enable the processor 782 to communicate with the Internet or one or more intranets.
• 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.
• information which is often represented as a sequence of instructions to be executed using processor 782, may he received from and outputted to the network, for example, in the form of a computer data signal embodied in a carrier wave.
• 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 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.
• the computer system 780 may comprise two or more computers in communication with each other that collaborate to perform a task.
• an application may be partitioned in such a way as to permit concurrent and/or parallel processing of the instructions of the application.
• 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.
• 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.
• 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 resources owned and operated by the enterprise as well as cloud computing resources hired and/or leased from a third party provider.
• 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 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.
• the processor 782 may comprise an internal
• RAM random access memory
• ROM read-only memory
• cache memory temporary storage media
• non-transitory storage blocks, sections, or components that may he referred to in some contexts as non-transitory computer readable media or computer readable storage media
• FIG. 10 is a schematic showing baseline logs for 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 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.
• WBE1 first well barrier element
• 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
• 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.
• 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.
• FIG. 1 1 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 1 1, 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.
• TOC top of the cement
• FIG. 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 WBE2/3). As seen in Figure 12, litle to no acoustic noise is captured in the zone above the TOC of WBE2/3.
• Figure 13 is a schematic showing the DAS iogs 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,
• 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.
• 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).
• the baseline corrected C bleed e.g., the C bleed minus the baseline
• 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 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.
• 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.
• the baseline corrected C bleed e.g., the C bleed minus the baseline
• Figure 16 is a schematic of the DAS logs of the baseline smoothed C bleeds of Run 1 (e.g., prior to placement of WBE 1) and Run 3 (e.g., after placement of WBE2/3).
• a reduction in the baseline smoothed flow noise observed in Runs 1 and 3 evidences a drop in overall flow noise at shallower depths during the bleed, indicating successful barrier placement and performance.
• R L R L +k*(R u -R. L ), wherein k is a variable ranging from 1 percent to 100 percent with a 1 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.
• any numerical range defined by two R numbers as defined in the above is also specifically disclosed.
• compositions and methods are described in broader terms of “having”,“comprising,” “containing,” or “including” various components or steps, the compositions and methods can also “consist essentially of’ or “consist of” 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 .
• Embodiments disclosed herein include:
• a method of abandoning a wellbore 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; seting 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 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.
• a system for abandoning a wellbore 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 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
• [00135] 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 acous
• a system for of comparing acoustic signals obtained between different acoustic sensor operations in a wellbore 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
• a method of abandoning a wellbore comprising: 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 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
• a system for abandoning a wellbore 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;
• Each of embodiments A, B, C, D, E, and F may have one or more of the following additional elements: Element 1 : further 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 differentia!
• 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.
• El ement 5 wherein the baseline acoustic signal data set is a time averaged acoustic data set.
• the barrier e.g., the first barrier, the second barrier, or both the first barrier and the second harrier
• the barrier comprise a bridge plug, a packer, a cement plug, or a combination thereof.
• 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 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 1 1 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
• 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.
• 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.
• inducing the first pressure differential and/or inducing the second pressure 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.
• 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.
• 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.
• 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.
• 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.
• 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 band 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.

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• 2019
  • 2019-06-25 EP EP19765548.3A patent/EP3990747A1/de not_active Withdrawn
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