well and overload monitoring with the use of distributed acoustic sensors

专利摘要:
a method for detecting a leak event within a well bore may include inducing a pressure differential within a well bore comprising a fluid, obtaining a sample data set representative of the acoustic signal across a frequency spectrum while induces the pressure differential, determine a plurality of frequency domain resources from the sample data set, determine a presence of a leak event at one or more depths within the well bore based on the determination that the plurality of resources frequency domain corresponds to a leak event signature, correlate the leak event with the induced pressure differential, and determine the presence and location of a leak within the well bore based on the presence of the leak event and the correlation of the leakage event with the induced pressure differential.
公开号:BR112019020125A2
申请号:R112019020125
申请日:2018-03-29
公开日:2020-05-05
发明作者:Thiruvenkatanathan Pradyumna；Langnes Tommy
申请人:Bp Exploration Operating Company Limited；
IPC主号:

专利说明:

WELL AND OVERLOAD MONITORING WITH THE USE OF DISTRIBUTED ACOUSTIC SENSORS
CROSS REFERENCE TO RELATED ORDERS [0001] 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 well bore. Fluid production can result in the movement of fluids in various downhole regions, including within the underground formation, the formation into the wellbore, and within the wellbore itself.
BRIEF SUMMARY OF THE REVELATION [0003] In one embodiment, a method for detecting a leak event within a well bore comprises inducing a pressure differential within a well bore comprising a fluid, obtaining a sample data set while induces the pressure differential, determine a plurality of frequency domain resources from the sample data set, determine a presence of a leak event at one or more depths within the well bore based on the determination that the plurality of resources frequency domain corresponds to a leak event signature, correlate the leak event with the induced pressure differential and determine a presence and location of a leak within the well bore based on the presence of the leak event and the correlation of the event of leakage with the induced pressure differential. The sample data set is a sample of an acoustic signal that originates within the well bore and the sample data set is representative of the acoustic signal across a frequency spectrum.
[0004] In one embodiment, a system for detecting a leak event within a well bore comprises a receiving unit comprising a processor and a memory. The receiving unit is configured to
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2/63 receive a first signal from a sensor arranged in a well hole. A processing application is stored in memory, and the processing application, when run on the processor, configures the processor to: receive the first signal from the sensor, where the signal comprises an indication of an acoustic signal received at one or more depths within the borehole, receive a second signal comprising an indication of a pressure differential within the borehole, determine a plurality of acoustic signal frequency domain resources across the frequency spectrum and purchase the plurality of acoustic domain resources frequency with a leak event signature, determine a presence of a leak event at one or more depths within the well hole based on the plurality of frequency domain resources corresponding to the leak event signature at one or more depths in the borehole, correlate the leakage event with the induced pressure differential, determine a presence and location of a leak inside the well bore based on the presence of the leak event and on the correlation of the leak event with the induced pressure differential and generate an exit indication of the presence and location of the leak. The signal is indicative of the acoustic signal through a frequency spectrum.
[0005] In one embodiment, a method for detecting a leak in a borehole comprises detecting a baseline condition within the borehole, the borehole comprises one or more tubular columns and one or more annulus arranged between at least minus one of: i) two
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3/63 tubular columns adjacent to one or more tubular columns, ii) a tubular column of one or more tubular columns and a formation, or iii) both i and ii. The method also includes inducing a pressure differential relative to the baseline condition within a first annulus of one or more annuli, receiving an acoustic signal from one or more depths within the well bore while inducing the pressure differential, detecting a flow condition within the borehole based on a plurality of frequency domain resources of the acoustic signal across the frequency spectrum, correlate the flow condition with the baseline condition and pressure differential, determine a depth and flow condition and based on correlation and determine an annulus of the one or more annulus with the flow condition based on correlation. [0006] In one embodiment, a system for detecting a leak event within a well bore comprises a receiving unit comprising a processor and a memory. The receiving unit is configured to receive a first signal from a sensor arranged in a well hole. A processing application is stored in memory, and the processing application, when run on the processor, configures the processor to: receive the first signal from the sensor, where the signal comprises an indication of an acoustic signal received at one or more depths within from the well bore, receive a second signal comprising an indication of a pressure or flow within the well bore, determine a plurality of frequency domain resources of the acoustic signal across the frequency spectrum, purchase the plurality of
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4/63 frequency domain resources with an overload event subscription, determining the presence of an overload event at one or more depths within the well hole based on the plurality of frequency domain resources corresponding to the overhead event subscription overload at one or more depths in the well hole, correlate the overload event with pressure or flow, determine a presence and location of the overload event within the well hole based on the presence of the overload event and the correlation of the overflow event overload with pressure or flow, and generate an output indication of the presence and location of the overload event. The signal is indicative of the acoustic signal through a frequency spectrum.
[0007] These and other resources will be more clearly understood from the following detailed description taken in conjunction with the attached drawings and claims.
[0008] The modalities described in this document comprise a combination of resources and advantages designed to solve several disadvantages associated with certain devices, systems and previous methods. The aforementioned outlined the features and technical advantages of the invention in a very broad way so that the following detailed description of the invention can be better understood. The various features described above, as well as other resources, will be readily apparent to those skilled in the art by reading the following detailed description, and by reference to the accompanying drawings. It should be noted by those skilled in the art that the specific design and modalities revealed can
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5/63 readily used as a basis for modifying or designing other structures to carry out the same purposes as the invention. It should also be noted by those skilled in the art that such equivalent constructions do not depart from the spirit and scope of the invention as presented in the appended claims.
BRIEF DESCRIPTION OF THE DRAWINGS [0009] For a detailed description of the preferred embodiments of the invention, reference will now be made to the accompanying drawings in which:
[0010] Figure 1 is a schematic cross-sectional illustration of a well-bottomed well hole environment according to a modality.
[0011] Figure 2 is a schematic view of an embodiment of a well-bore tubular with fluid inlet according to an embodiment.
[0012] Figures 3A and 3B are seen in schematic cross section of modalities of a well with a tubular well-hole that has an optical fiber associated with it.
[0013] Figure 4 illustrates a modality of a schematic processing flow for an acoustic signal.
[0014] Figures 5A and 5B illustrate exemplary acoustic time-depth block graphics.
[0015] Figures 6A, 6B and 6C illustrate exemplary filtered acoustic time-depth graphs.
[0016] Figure 7 illustrates an exemplary leak record according to a modality.
[0017] Figure 8 schematically illustrates a computer that can be used to perform various steps according to
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6/63 with some modalities.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS [0018] Otherwise, unless otherwise specified, any use of any form of the terms connect, engage, dock, fix or any other term that describes an interaction between elements is not intended to limit the interaction to drive interaction between the elements and can 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 manner and thus must be interpreted to mean including, but not limited to. . . . Reference to ascending or descending will be made for the purposes of description with ascending, upper, upward, upstream or above that mean towards the surface of the well hole and with descending, lower, downward, downstream or below that mean in towards the terminal end of the well, regardless of the well hole orientation. Reference to internal or external will be made for purposes of description with inside, internal or inward which mean towards the central longitudinal geometric axis of the well hole and / or tubular well hole, and outside, external or outward meaning towards the borehole wall. As used herein, the term longitudinal or longitudinally refers to a geometric axis substantially aligned with the central geometric axis of the wellbore tubular, and radially or radially refers to a direction perpendicular to the longitudinal geometric axis. The various characteristics
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7/63 mentioned above, as well as other features and characteristics described in greater detail below, will be readily apparent to those skilled in the art with the aid of the present disclosure by reading the following detailed description of the modalities, and by reference to the attached drawings.
[0019] This document reveals a real-time signal processing architecture that allows the identification of several downhole events including leak detection, pressure source identification, flow path identification and phase detection of a leakage fluid in the well bore (inside an enclosure, inside an annulus, etc.), the formation (eg, overload monitoring, etc.) or movement between the formation and the well bore. As used in this document, the term real time refers to a time that takes into account various latency and communication delays within a system, and can include actions taken in about ten seconds, in about thirty seconds, in about one minute, in about five minutes or in about ten minutes of the action that takes place. In general, zonal isolation and well integrity management are concerns, not only from the point of view of operational risk and improved production efficiencies, but also from an environmental impact perspective. Leak detection techniques can include the use of temperature sensors, pressure sensors, casing collar locators, multi-finger calipers, rotators and sometimes density measurement tools implanted in the well with the use of
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8/63 intervention, as well as other non-invasive assessment / analysis techniques to detect the flow behind the enclosure (eg temperature recording, ultrasonic imaging, oxygen activation (for detecting water flow behind the enclosure) with neutrons and the like).
[0020] While one or a combination of these tools can help provide qualitative and sometimes quantitative estimates of the fluid flow between the production pipeline and the production enclosure, these methods suffer from being point measurement tools (ie , tools that can only transduce a single physical parameter in a certain discrete location / depth in any occurrence in time). This means that leaks may not be captured precisely or simply do not need to be captured, unless the tools are positioned in the correct location at the right time and / or unless the leak is large enough to generate a transducible signal. This typically results in longer data acquisition times and limited representations, which can often hamper support and decision making. None of these tools offers the ability to monitor the flow of hydrocarbons behind multiple barriers, for example, in the casing-annulus, and this presents a challenge in maintaining well integrity. Multi-finger calipers are also often used to investigate any variations in diameter along the pipeline, however, this process does not quantify the extent, rate or phase of leakage fluid.
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9/63
This also provides only an indication of the location of potential leak based on the mechanical analysis of the pipeline.
[0021] As described in more detail in this document, distributed fiber optic (DFO) sensors for well integrity analysis use the fiber to monitor properties along the length of a well hole. Similarly, distributed temperature detection systems (DTS) can be used to measure the temperature along the well bore. The main advantage of these DFO sensors is that the measurement can be carried out over the entire length of the well hole for long periods of time, since the entire fiber cable implanted is the sensor. This can avoid the need to move the tool and assist in more economical operations. Full well hole coverage would also enable studies of leak evolution over time and depth, thereby enabling accurate identification of when and where leaks occur, rather than assuming from several steps in the logging operation. The use of DTS for leak detection, however, generates some limitations including: 1) the use of separate thermal profiles for leak identification often results in inconclusive results, and 2) it is difficult to achieve controlled shutdown versus out-of-flow conditions casing to compare and determine leak locations from baseline thermal profiles.
[0022] As revealed in this document, a new approach to well and overhead monitoring is
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10/63 described with the use of Distributed Acoustic Sensors (DAS) as the primary data entered. This type of system offers not only identification of leaks and fluid flow behind the enclosure, but also allows the categorization of these events in real time or almost in real time. Also described is a data processing architecture that processes bulky DAS data almost in real time (for example, in up to one second, in up to ten seconds, etc.) to identify and classify leaks and other events indicative of barrier anomalies. well with a single fiber optic cable implanted in the well. The data can also be used in conjunction with surface and peripheral sensor data to enable semi-quantitative leak rate analysis.
[0023] As further disclosed in this document, DAS data can be used with additional sensor data such as surface meter pressure data as the primary sensor inputs to determine well and near-well leakage. The processing methodology uses an event detection algorithm that detects and captures acoustic events, which are then processed in real time using a spectral descriptor structure for signature recognition and leak identification. The outputs of the event detection algorithm can then be correlated in time with additional sensor data (for example, surface pressure gauge measurements). The correlation of the signals can make it possible to identify: a pressure source, a leak location, a trajectory
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11/63 leakage flow and / or a predominant phase of a leakage fluid.
[0024] The method can also allow the monitoring of fluid leaks behind multiple barriers that are generally not detected with the use of conventional leak detection diagnostic tools. This ability makes it possible to monitor hydrocarbon migration above trajectories adjacent to well holes to shallower areas (cross flow) and / or in well rings, thus enabling real-time monitoring of fluid movements in the overload and the evaluation of well barrier degradation mechanisms that can eventually lead to well collapses and zonal isolation device failures.
[0025] As described in more detail in this document, the system comprises a DAS interrogator connected to the fiber optic cable implanted in the well. Various sensors (for example, distributed optical fiber acoustic sensors, etc.) can be used to obtain acoustic sampling at various points along the well bore. The acoustic sample can then be processed using signal processing architecture with various resource extraction techniques (for example, spectral resource extraction techniques) to obtain a measure of one or more frequency domain resources that make it possible to selectively extract the acoustic signals of interest from background noise and consequently assist in improving the accuracy of the identification of the movement of fluids and / or solids (for example, locations of liquid ingress, locations of
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12/63 gas inflow, restricted fluid flow locations, etc.) in real time. As used in this document, several frequency domain resources can be obtained from the acoustic signal. In some contexts, frequency domain resources can also be called spectral resources or spectral descriptors. The signal processing techniques described in this document can also help to solve the problem of big data through intelligent data extraction (instead of crude decimation techniques) to considerably reduce real-time data volumes at the collection site and processing (eg reduction by more than 100 times, more than 500 times, or more than 1,000 times, or more than 10,000 times).
[0026] The acoustic signal can be obtained in a way that allows a signal to be obtained over the entire well hole or a portion of interest. Acoustic sensors distributed by optical fiber (DAS) capture acoustic signals resulting from downhole events such as gas inflow, liquid inflow, fluid flow beyond restrictions and the like as well as other background acoustics as well. This forces 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 from the results. This, in turn, results in a need for a clearer understanding of the acoustic fingerprint of an event of interest in the well (for example, leak detection, etc.) so that noise resulting from an event of interest can be segregated.
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13/63 other ambient acoustic background noise. As used in this document, the acoustic fingerprint resulting from a particular event can also be called a spectral signature, as described in more detail in this document.
[0027] In terms of data processing and loads, DAS acquisition units produce large volumes of data (typically around 1 TB / hour) creating complexities in data handling, data transfer, data processing and storage. There is currently no method for intelligently extracting useful information to reduce data volumes in real time for immediate decision support. This imposes complexity in real-time data transmission to the coast and data integration for existing IT platforms due to data bandwidth limitations and the data needs to be stored on hard drives that are sent back to the coast for interpretation and analysis. In addition, this increases the turnaround time for interpretation (typically, a few weeks to months) before any remediation efforts can be carried out, resulting in deferred production.
[0028] The ability to identify multiple events at the well hole can allow multiple actions to be taken in response to the events. For example, a well can be deactivated, production can be increased or decreased and / or palliative measures can be taken at the well bore, as appropriate based on the identified event (or events). An effective response, when needed, benefits, not from a binary yes / no output from a
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14/63 identification of events in the well, but also of a measure of the relative amount of fluids (for example, amount of gas inflow, amount of fluid flow in addition to a restriction, etc.) from each of the identified zones, so that one can act first through the zones that contribute to the largest amounts of fluid and / or solid to improve or optimize production. For example, when a leak is detected in addition to a constraint, a relative flow rate of the leak may allow identification of the timing at work to plug the leak (for example, small leaks may not need to be corrected, larger leaks may need to be corrected. high priority, etc.).
[0029] As described in this document, spectral descriptors can be used with real-time acoustic DAS data processing to provide various downhole surveillance applications. More specifically, data processing techniques can be applied for various downhole fluid profiling such as fluid infusion / effluent detection, fluid phase segregation, well integrity monitoring, well leak detection (eg example, leak detection of pipeline and downhole casing, leakage phase identification, etc.), annular fluid flow detection, overload monitoring, fluid flow detection behind an enclosure, fluid-induced hydraulic fracture at overload and the like.
[0030] In addition to using DAS data, additional sensor data such as pressure sensors and / or flow sensors
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15/63 can be used to obtain data inside the well bore. As an example, a flow sensor or pressure sensor can be used to detect fluid flow within the well bore and / or an annulus within the well bore. The sensors can be used with controlled conditions of deactivation and / or flow to correlate in time the conditions resulting from pressure and / or flow with the processed DAS data. The resulting correlation can then be used to determine the presence and location of a leak. [0031] Now with reference to Figure 1, an example of a well-hole 100 operating environment is shown. As will be described in greater detail below, the modalities of
sets completion who understand system of sensor acoustic distributed (DAS) of wake up with the Principles described in the present document can be positioned on environment 100.[0032] As shown in Figure 1, O environment exemplifi captive 100 includes a hole in well 114 that through a formation underground 102, enclosure 112 that cover at least one portion dc j hole in well 114 and one
tubular 120 extending through well bore 114 and casing 112. A plurality of spaced screen elements or assemblies 118 are provided along tubular 120. Additionally, a plurality of spaced zonal isolation devices 117 and gravel packages 122 they are provided between the tubular 120 and the side wall of the well bore 114. In some embodiments, the operating environment 100 includes a reconditioning and / or drilling probe positioned on the surface and extending over the well bore 114.
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16/63 [0033] In general, well bore 114 can be drilled in underground formation 102 using any suitable drilling technique. The borehole 114 may extend substantially vertically from the surface of the earth over a vertical portion of the borehole, deviate from the vertical portion with respect to the surface of the earth over a deviated portion of the borehole and / or transition to a horizontal portion of a borehole. In general, the whole or portions of a well bore can be vertical, offset at any suitable angle, horizontal and / or curved. In addition, well bore 114 can be a new borehole, an existing borehole, a straight borehole, an extended borehole bore, an offset borehole, a multilateral borehole, and other types of well holes for drilling and completing one or more production zones. As illustrated, well bore 114 includes a substantially vertical production section 150, which is an open hole completion (for example, housing 112 does not extend through production section 150). Although section 150 is illustrated as a vertical open hole portion of well bore 114 in Figure 1, the modalities disclosed in this document can be employed in well bore sections that have any orientation, and in open or casing sections. of well holes. The housing 112 extends into the well bore 114 from the surface and is cemented into the well bore 114 with cement 111.
[0034] The tubular 120 can be lowered into the well bore 114 to perform an operation such as drilling, completion, reconditioning, treatment and / or production processes.
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In the embodiment shown in Figure 1, the tubular 120 is a completion set column that includes a distributed acoustic sensor (DAS) coupled to it. However, in general, tubular modalities 120 may function as a different type of structure in a well bore including, without limitation, as a drill string, casing, liner, joint tubing and / or coiled tubing. In addition, the tubular 120 can operate in any portion of the well bore 114 (e.g., vertical, offset, horizontal and / or curved section of the well bore 114). The DAS system modalities described in this document can be coupled to the exterior of the tubular 120 or, in some embodiments, arranged within an interior of the tubular 120, as shown in Figures 3A and 3B. When the DAS fiber is attached to the outside of the tubular 120, the DAS can be positioned within a control line, control channel or recess in the tubular 120. In some embodiments, a sand control system may include an external blanket for contain the tubular 120 and protect the system during installation. A control line or channel can be formed on the blanket and the DAS system can be placed on the control line or channel.
[0035] The tubular 120 extends from the surface to the production zones and generally provides a conduit for fluids to move from formation 102 to the surface. A completion kit including tubular 120 may include a variety of other downhole tools or equipment to facilitate the production of forming fluids from production areas. For example, 117 zonal isolation devices are used to isolate
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18/63 the various zones within the well bore 114. In this embodiment, each zonal isolation device 117 may be an obstructor (for example, production obstructor, gravel pack obstructor, weak-pac type obstructor, etc.). The zonal isolation devices 117 can be positioned between the screen assemblies 118, for example, to isolate different zones or gravel packet intervals along the well bore 114 from each other. In general, the space between each pair of adjacent zonal isolation devices 117 defines a production interval.
[0036] Screen sets 118 provide sand control capability. In particular, the sand control screen elements 118, or other filter means associated with the wellbore tubular 120 can be designed to allow fluids to flow through them, however, restrict and / or prevent particulate matter of sufficient size to flow through. In some embodiments, the gravel bundles 122 can be formed at the annulus 119 between the web elements 118 (or tubular 120) and the side wall of the well bore 114 in an open hole completion. In general, the gravel packages 122 comprise relatively coarse granular material placed in the annulus to form a rough canvas against the ingress of sand into the well hole while also supporting the well hole wall. The gravel package 122 is optional and may not be present in all conclusions.
[0037] The fluid flowing into the tubular 120 may comprise more than one fluid component. The components
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Typical 19/63 include natural gas, oil, water, steam and / or carbon dioxide. The relative proportions of these components can vary over time based on conditions within formation 102 and well bore 114. Similarly, the composition of the fluid that flows into the sections of tubular 120 along the length of the entire production column can vary significantly from section to section at any given time.
[0038] As the fluid is produced for the well bore 114 and the completion set column, the flow of the various fluids to the well bore 114 and / or through the well bore 114 can create acoustic sounds that can be detected using the acoustic sensor as the DAS system. Each type of event like the different fluid flows and fluid flow locations can produce an acoustic signature with unique frequency domain features. For example, a leak that represents the flow of fluid beyond a restriction, through an annulus and / or through the formation can create unique sound profiles through a frequency domain, so that each event can have a unique acoustic signature with based on a plurality of frequency domain resources.
[0039] In Figure 1, the DAS comprises an optical fiber 162 based on the acoustic detection system that uses the optical backscatter component of light injected into the optical fiber to detect vibration / acoustic disturbances (for example, dynamic effort) when along the length of the fiber 162. The light can be generated by a generator or light source 166 like a laser, which can guarantee pulses of light. THE
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20/63 optical fiber 162 acts as the sensor element without addition transducers in the optical path, and measurements can be taken along the entire length of the optical fiber 162. The measurements can then be detected by an optical receiver such as the sensor 164 and selectively filtered to obtain measurements from a given point or depth range, thus providing a distributed measurement that has selective data for a plurality of zones along the optical fiber 162 at any given time. In this way, optical fiber 162 functions effectively as a distributed array of acoustic sensors spread over the entire length of optical fiber 162, which typically spans at least the production area 150 of well bore 114 to detect vibration disturbances / downhole acoustic signals.
[0040] Light reflected back up from optical fiber 162, as a result of backscattering, can travel back to the source, where the signal can be collected by a sensor 164 and processed (for example, using of a 168 processor). In general, the time it takes the light to return to the collection point is proportional to the distance shifted along the optical fiber 162. The resulting backscattered light that appears along the length of the optical fiber 162 can be used to characterize the environment around around optical fiber 162. The use of a controlled light source 166 (for example, which has a controlled spectral width and frequency) can allow backscattering to be collected and any disturbances along the length of optical fiber 162 to be analyzed. In general, any dynamic stress disturbances or
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21/63 acoustics along the length of the optical fiber 162 can result in a change in the properties of the backscattered light, allowing for a distributed measurement of the acoustic magnitude, frequency and, in some cases, the relative phase of the disturbance.
[0041] An acquisition device 160 can be coupled to one end of the optical fiber 162. As discussed in this document, the light source 166 can generate light (e.g., one or more light pulses), and the sensor 164 it can collect and analyze the backscattered light that returns upward from the optical fiber 162. In some contexts, the acquisition device 160 including the light source 166 and the sensor 164 can be called an interrogator. In addition to the light source 166 and sensor 164, the acquisition device 160 generally comprises a processor 168 in signal communication with sensor 164 to perform various stages of analysis described in greater detail in the present document. Although shown as being inside the acquisition device 160, the processor can also be located outside the acquisition device 160 including being located remotely in relation to the acquisition device 160. Sensor 164 can be used to obtain data at various rates and can obtain data at a rate sufficient to detect the acoustic signals of interest with sufficient bandwidth. In one embodiment, the depth resolution ranges between about 1 meter and about 10 meters can be reached.
[0042] Although the system 100 described in this document can be used with a DAS system to acquire an acoustic signal for a location range or
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22/63 depth in the well bore 114, in general, any suitable acoustic signal acquisition system can be used with the processing steps disclosed in this document. For example, several microphones or other sensors can be used to provide an acoustic signal at a given location based on the acoustic signal processing described in this document. The benefit of using the DAS system is that an acoustic signal can be obtained through a plurality of locations and / or through a continuous length of the well bore 114 instead of distinct locations.
[0043] In addition to the DAS system, a surface sensor or sensor system 152 can be used to obtain additional data for the well hole. The surface sensor system 152 may comprise one or more sensors such as pressure sensors, flow sensors, temperature sensors and the like. The sensors can detect conditions within the tubular 120 and / or in one or more annuli such as annuli 119. Although only a single annulus between the tubular 120 and the enclosure 112 is illustrated in Figure 1, multiple annuli can be present. For example, more than one casing column can often be defined on or near the surface of the well hole during drilling, which can result in two or more annuli (for example, an annulus between the tubular 120 and the casing 112, a annulus between a first casing 112 and a second casing, an annulus between a casing column and the borehole wall, etc.). As used in this document, the reference to the term surface can refer to a location above or at the wellhead (for example,
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23/63 example, in Kelly's bushing, rig floor, etc.), close to ground level and / or in the first 100 m, in the first 150 m, in the first 200 m or in about the first 300 m along the well bore as measured from ground level.
[0044] The specific spectral signatures can be determined for each event considering one or more frequency domain resources. The resulting spectral signatures can then be used in conjunction with the processed beep data to determine whether an event is occurring at a depth range of interest. Spectral signatures can be determined by considering the different types of movement and flow that occur in a well bore and by characterizing the frequency domain resources for each type of movement.
[0045] As an example, the fluid, which may contain particles or sand, can be considered as an example of an event that generates an acoustic signal. As illustrated schematically in Figure 2 and shown in the cross-sectional illustrations in Figures 3A and 3B, a fluid, which may contain sand 202, can flow from formation 102 to well bore 114 and then to tubular 120. As far as wherein the fluid flows into the tubular 120, sand 202 may collide against the inner surface 204 of the tubular 120, and with the fiber itself in cases where the fiber is placed inside the tubular, in a random manner. The resulting random impacts can produce a random broadband acoustic signal that can be captured in optical fiber 162 attached (for example, attached) to tubular 120. Sand 202
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24/63 entering well bore 114 can be transported within a transport fluid 20 6, and transport fluid 206 can also generate high-intensity acoustic background noise when entering well bore 114 due to turbulence associated with fluid flowing into the tubular 120. That background noise generated by the turbulent fluid flow is generally expected to be predominantly in a lower frequency region. For example, the acoustic signals of fluid inflow can be between about 0 Hz and about 500 Hz, or alternatively between about 0 Hz and about 200 Hz. An increased power intensity can be expected at low frequencies resulting from turbulence increased transport fluid flow. Background noise can be detected as signals superimposed on the broadband acoustic signals produced by sand 202 when sand ingress occurs.
[0046] Numerous acoustic signal sources can also be considered together with the types of acoustic signals that these sources generate. In general, a variety of signal sources can be considered including fluid flow with or without sand through formation 102, fluid flow with or without sand 202 through a gravel pack 122, fluid flow with or without sand inside or through tubular 120 and / or sand screen 118, fluid flow with sand 202 inside or through tubular 120 and / or sand screen 118, fluid flow without sand 202 in tubular 120 and / or sand screen 118 , gas / liquid inflow, hydraulic fracture, fluid leaks beyond restrictions (e.g. gas leaks, liquid leaks, etc.)
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25/63 mechanical instrumentation and geophysical acoustic noise and potential point reflection noise within the fiber caused by cracks in the optical fiber / conduit cable under investigation.
[0047] For gas flow in the well bore, proximity to optical fiber 162 can result in a high probability that any acoustic signals generated will be detected by optical fiber 162. The flow of a gas into the well bore would likely result in a turbulent flow over a wide frequency range. For example, acoustic inflow 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 can occur between about 300 Hz and about 500 Hz of increased turbulence in the gas flow. An example of the acoustic signal resulting from the inflow of gas into the well bore may include acoustic intensity filtered by frequency 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 2,000 Hz and 2,000 Hz to 5,000 Hz. The acoustic intensity in the first three bins can have frequency ranges up to about 500 Hz, with an almost undetectable acoustic intensity in the frequency range above 500 Hz. At least a portion of the frequency domain resources may not be present above 500 Hz, which may help to define the signature of the inflow of gas.
[0048] For the hydraulic fracture, the self-induced fracture of the underground formation due to various conditions of
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26/63 formation can create an acoustic signal. The intensity of such a signal can be detected by optical fiber 162 depending on the distance between the fracture and optical fiber 162. The resulting fracture can be expected to produce a wide band response that has the acoustic energy present in a frequency band between about 0 Hz to about 400 Hz. Some amount of spectral energy can be expected up to about 1,000 Hz. Furthermore, the distinct nature of fracture events can be seen as an almost instantaneous high-energy broadband event followed by a signal low energy low frequency fluid flow acoustic resulting from fluid flow in response to fracture.
[0049] For the flow of a fluid behind a casing in the well bore, the proximity of the fluid flow to the optical fiber 162 can result in the acoustic signal being detected. The flow behind the enclosure can generally be characterized by a flow of fluid through one or more constraints based on a generally narrow or small leakage path that is present. The flow through such a restriction can 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 from about 0 Hz to about 100 Hz, or between about 0 Hz and about 70 Hz.
[0050] For the acoustic signals generated by mechanical instrumentation and geophysical acoustic noise, sounds can be detected by optical fiber 162 in some instances depending on the distance between the sound generation and the portion of optical fiber 162 being used to detect the sounds. Several mechanical noises are expected to have
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27/63 low frequency. For example, several motors can operate in the range of 50 Hz to 60 Hz, and the resulting acoustic signal is expected to have spectral energy in a narrow band. It can also be expected that several mechanical instrumentation noises may be the loudest on or near the surface of the well bore. Various geophysical sounds can have even lower frequencies. As a result, it is expected that sounds from mechanical instrumentation and geophysical sources can be removed by filtration based on a low pass frequency filter.
[0051] For point reflection type noises, these are generally broadband in nature, however, they can occur at spatially confined depths and generally do not cover the expected spatial resolution of the interrogator. These can be removed as part of the pre-processing steps by calculating spatial averages or median filtering the data across the entire fiber depth.
[0052] Based on the sound characteristics expected from the potential acoustic signal sources, the acoustic signature of each event can be defined in relation to the background noise contributions. Again with reference to Figure 1, processor 168 within the acquisition device 160 can be configured to perform processing of various data to detect the presence of one or more events along the length of the well bore 114. The acquisition device 160 can understand a memory 170 configured to store an application or program to perform data analysis. Although it is shown to be contained within the
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28/63 acquisition device 160, memory 170 may comprise one or more memories, any of which may be external to acquisition device 160. In one embodiment, processor 168 may execute the program, which may configure processor 168 to filter the acoustic data set spatially, determine one or more frequency domain resources of the acoustic signal, compare the resulting frequency domain resource values with the acoustic signatures, and determine whether an event is occurring at the selected location based on the analysis and comparison. The analysis can be repeated through several locations along the length of the well bore 114 to determine the occurrence of one or more events and / or event locations along the length of the well bore 114.
[0053] At the same time, one or more well hole parameters can be measured with the sensor system 152. For example, sensors can be used to detect pressure (pressures), flow rate (flow rates), temperature (temperatures) and the like at one or more locations on or near the well hole surface. 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 correlated by time after processing the acoustic signal.
[0054] When the acoustic sensor comprises a DAS system, the optical fiber 162 can return raw optical data in real time or almost in real time to the unit of
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29/63 acquisition 160. In one embodiment, raw data can be stored in memory 170 for various subsequent uses. Sensor 164 can be configured to convert the raw optical data into an acoustic data set. Depending on the type of DAS system employed, optical data may or may not be coherent in phase and may be pre-processed to improve signal quality (for example, for normalizing optoelectronic noise / removing reflection noise from single point not biased through the use of median filtration techniques or even through the use of average computations of spatial movement with defined averaging windows for the spatial resolution of the acquisition unit, etc.).
[0055] As shown schematically in Figure 4, an embodiment of a system for detecting various event conditions such as leak detection may comprise a data extraction unit 402, a processing unit 404, a sensor data correlation unit peripheral 408 and / or an output or display unit 406. The system comprises a DAS 160 interrogator connected to the fiber optic cable 162 implanted in the well bore. DAS interrogator data is transmitted in real time to a data processing unit 402 which 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 one embodiment, the acoustic sample may be non-biased noise. Variable acoustic data of non-biased noise can be subjected to
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30/63 an optional spatial filtration step after the pre-processing steps, if present. This is an optional step and helps to focus mainly on a range of interest in the well bore. For example, the spatial filtration step can be used to focus on a production interval, where there is a maximum likelihood of a leak when a leak event is being examined. In one embodiment, spatial filtration can narrow the analysis focus to a reservoir section and still allow a reduction in data typically of the order of ten times, thus simplifying data analysis operations. The resulting data set produced by converting the raw optical data can be called acoustic sample data.
[0056] This type of filtration can provide several advantages in addition to reducing the size of the data set. Regardless of whether the set of acoustic data 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 through a defined depth (for example, the entire length optical fiber, some portion thereof or a point source in well bore 114). In some embodiments, the acoustic data set may comprise a plurality of acoustic samples resulting from spatial filtration to provide data across numerous depth ranges. In some embodiments, the acoustic sample may contain acoustic data across a range of depth sufficient to capture multiple points of interest. In some modalities, the sample data
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31/63 acoustics contain information over the entire frequency range at the depth represented by the sample. This means that the various filtration steps, including spatial filtration, do not remove the frequency information from the acoustic sample data.
[0057] Processing unit 402 can also be used to generate and extract acoustic descriptors (for example, also called frequency domain resources in this document) from the acoustic data set. In one embodiment, the data extraction unit 402 can obtain the optical data and perform the initial pre-processing steps to obtain the initial acoustic information of the signal returned from the well hole. Various analyzes can be performed including the extraction of frequency domain resources, extraction of frequency bands, analysis and / or transformation of frequency, calculation of intensity and / or energy and / or determination of one or more resources of frequency domain of acoustic data. To obtain the frequency domain resources, the data processing unit 402 can be additionally configured to perform discrete Fourier transforms (DFT) or a short time Fourier transform (STFT) of the acoustic variable time domain data measured in each depth section along the fiber or a section of it to spectrally check the conformity of the acoustic sample data for one or more acoustic signatures. The spectral compliance check can be used to determine whether the expected signature of an event is present in the acoustic sample data. The extraction of spectral resources over time
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32/63 and space can be used to determine spectral compliance and determine whether an acoustic signature (for example, a fingerprint of sand ingress, gas inflow, hydraulic fracture signature, etc.) is present in the acoustic sample. In this process, several frequency domain resources can be calculated for the acoustic sample data.
[0058] The use of frequency domain resources to identify one or more events has numerous advantages. First, the use of frequency domain resources results in significant data reduction compared to the DAS raw data stream. Thus, numerous frequency domain resources can be calculated to allow event identification while the remaining data can be discarded or otherwise stored, while the remaining analysis can be performed using frequency domain resources. Even when the raw DAS data is stored, the remaining processing power is significantly reduced through the use of frequency domain resources instead of the raw acoustic data itself. Furthermore, the use of frequency domain resources provides a concise quantitative measure of the spectral character or the acoustic signature of specific sounds relevant to the monitoring of downhole fluid and other applications that can be directly used for application-specific signal processing In real time.
[0059] Although numerous frequency domain resources can be determined for the acoustic sample data, not every frequency domain resource can be used in
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33/63 characterization of each acoustic signature. The frequency domain features represent specific properties or characteristics of the acoustic signals. There are a number of factors that can affect the frequency domain resource selection for each event. For example, a selected descriptor must remain relatively unaffected by the influences of interference from the environment such as interference noise from electronic / optical devices, disturbances of competing acoustic sounds in the transmission channel and the like. In general, electronic / instrumentation noise is present in the acoustic signals captured in the DAS or any other electronic meter, and is generally an unwanted component that interferes with the signal. Thermal noise is introduced during signal capture and processing by analog devices that form a part of the instrumentation (for example, electronic amplifiers and other analog circuit systems). This is mainly due to the thermal movement of cargo conveyors. In digital systems, additional noise can be introduced through sampling and quantization. Frequency domain resources must avoid any interference from these sources.
[0060] As an additional consideration in selecting the frequency domain resource (or resources) for an event, the dimensionality of the frequency domain resource must be compact. A compact representation is desired to decrease the computational complexity of subsequent calculations. The frequency domain resource must also have discriminating power. For example, for
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34/63 different types of audio signals, the selected set of descriptors must provide altogether different values. A measure of a resource's discriminating power is the variance of the resulting resource vectors for a set of relevant input signals. Considering different classes of similar signs, a discriminatory descriptor must have low variance within each class and high variance across different classes. The frequency domain resource must also be able to completely cover the range of property values it describes. As an example, the chosen frequency domain resource set must be able to completely and exclusively identify the signatures of each of the acoustic signals belonging to a downhole surveillance application or selected event as described in this document. Such frequency domain features may include, but are not limited to, the spectral centroid, spectral spreading, spectral attenuation, spectral obliquity, mean square root band (RMS) energy (or subband energy ratios / normalized band energy), a total RMS height or energy, spectral flattening, spectral slope, spectral kurtosis, a spectral flow, spectral entropy and a spectral autocorrelation function.
[0061] The spectral centroid denotes the brightness of the sound captured by the optical fiber 162 and indicates the center of gravity of the frequency spectrum in the acoustic sample. The spectral centroid can be calculated as the weighted average of the frequencies present in the signal, where the magnitudes of the present frequencies can be used as
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35/63 their weightings in some modalities. The value of the spectral centroid, Ci, of the 1st frame of the acoustic signal captured at a spatial location in the fiber can be written as:
_ _(Eq . _1}
Σ ^ _{= 1} Χι (.κ) magnitude of the short-time Fourier transform of the frame, in which it denotes the frequency coefficient or binary index, N denotes the total number of bins and f (k) denotes the central frequency of the bin. The computed spectral centroid can be scaled to a value between 0 and 1. Upper spectral centroides 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 with a threshold or spectral centroid range for a given event, and when the spectral centroid meets or exceeds the threshold, the event of interest may be present.
[0062] The absolute magnitudes of the computed spectral centroides can be scaled to read a value between zero and one. The turbulent noise generated by other sources like fluid flow and inflow can typically be at the lowest frequencies (for example, under about 100 Hz) and centroid computing can produce lower values, for example, around or below 0.1 after rescheduling. The introduction of fluid or fluid that carries sand can trigger broader frequencies of sounds (for example, a broadband response) that can extend in spectral content to higher frequencies (for example,
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36/63 example, up to and beyond 5,000 Hz). This can produce centroides of higher values (for example, between about 0.2 and about 0.7 or between about 0.3 and about 0.5), and the magnitude of change would remain considerably independent of the concentration general sand assuming that there is a good signal-to-noise ratio in the measurement assuming a traditional electronic noise floor (for example, white noise with intermittent noise imposed at lower frequencies).
[0063] The spectral spread can also be determined for the acoustic sample. Spectral spread is a measure of the shape of the spectrum and helps to measure how the spectrum is distributed around the spectral centroid. To compute the spectral spread, Si, it is necessary to take the deviation of the spectrum from the computed centroid according to the following equation (all other terms defined above):
(Eq. 2)
The lowest values of the spectral spread correspond to signals whose spectra are tightly concentrated around the spectral centroid. The higher values represent a wider spread of the magnitudes and provide an indication of the presence of a broadband 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.
[0064] Spectral attenuation is a measure of the width of
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37/63 band of the audio signal. The spectral attenuation of the 1st 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% to 95%) of the general sum of magnitudes of the spectrum.
Σί, χΙΥΜΙ = ^ Σ.ιΙΥΜΙ (Eg. 3)
Where c = 85 or 95. The result of the spectral attenuation calculation is a binary index and makes it possible to distinguish acoustic events based on dominant energy contributions in the frequency domain, (for example, between gas inflow and fluid flow, etc.) [0065] The spectral obliquity measures the symmetry of the distribution of the spectral magnitude values around its arithmetic mean.
[0066] The RMS band energy provides a measure of the signal energy within the defined frequency bins which can then be used for the signal amplitude population. The selection of bandwidths can be based on the characteristics of the captured acoustic signal. In some embodiments, a subband energy ratio that represents the ratio of the upper frequency in the selected band to the lower frequency in the selected band can vary from about 1.5: 1 to about 3: 1. In some embodiments, the subband energy ratio may vary from about 2.5: 1 to about 1.8: 1, or alternatively be about 2: 1. In some embodiment, frequency bands selected for a signal with a 5,000 Hz Nyquist acquisition bandwidth may 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, one
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38/63 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 1,280 Hz, an eighth bin with a frequency range between 1,280 Hz and 2,500 Hz and a ninth bin with a frequency range between 2,500 Hz and 5,000 Hz. Although certain frequency ranges for each bin are listed in this document, they are used only as examples, and other values in an equal or different number of frequency range bins can also be used. In some embodiments, the RMS band energies can also be expressed as a ratiometric measure by computing the ratio of the RMS signal energy within the defined frequency bins to the total RMS energy across the acquisition bandwidth ( Nyquist). This can help to reduce or remove dependencies on noise and any momentary variations in broadband sound.
[0067] The total RMS energy of the acoustic waveform calculated in the time domain can indicate the height of the acoustic signal. In some embodiments, the total RMS energy can also be extracted from the temporal domain after filtering the signal for noise.
[0068] Spectral flattening is a measure of the noise / tone of an acoustic spectrum. The same can be computed by the ratio of the geometric mean to the arithmetic mean of the energy spectrum value and can be used with an alternative approach to detect the signals
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39/63 submitted to broadband (for example, those caused by the ingress of sand). For tonal signals, the spectral flatness can be close to 0 and for broadband signals, it can be closer to 1.
[0069] The spectral slope provides a basic approximation of the spectrum format by a linearly regressed line. The spectral slope represents the decrease in spectral amplitudes from low to high frequencies (for example, a spectral slope). The slope, the y-intersection and the max and mean regression errors can be used as resources.
[0070] Spectral kurtosis provides a measure of the flatness of a distribution around the mean value.
[0071] The spectral flow is a measure of instantaneous changes in the magnitude of a spectrum. It even provides a measure of the quadratic difference from frame to frame of the spectral magnitude vector plus across all frequencies or a selected portion of the spectrum. Signals with slowly varying (or almost constant) spectral properties (for example, noise) have a low spectral flow, while signals with abrupt spectral changes have a high spectral flow. The spectral flow can allow a direct measurement of the rate of change of spectral location and consequently serves as an event detection scheme that could be used to capture the onset of acoustic events that can then be further analyzed using the defined resource above to uniquely identify and classify the acoustic signal.
[0072] The spectral autocorrelation function provides a
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40/63 method in which the signal is displaced, and for each signal displacement (latency) the correlation or similarity of the displaced signal with the original is computed. This makes it possible to compute the fundamental period by selecting the latency, for which the signal is most similar to itself, for example, in which the autocorrelation is maximized. This can be useful in the analysis of explanatory signature / even for anomaly detection to monitor well integrity through specific depths in which all the barrier elements to be monitored are positioned.
[0073] Any of these frequency domain features, or any combination of these frequency domain features, can be used to provide an acoustic signature for a rock bottom event. In one embodiment, a selected set of features can be used to provide the acoustic signature for each event, and / or all the frequency domain resources that are calculated can be used as a group to characterize the acoustic signature for an event. The specific values for the frequency domain resources that are calculated may vary depending on the specific attributes of the acoustic signal acquisition system, so that the absolute value of each frequency domain resource can be changed between systems. In some embodiments, the frequency domain resources can be calculated for each event based on the system that is used to capture the acoustic signal and / or the differences between systems can be taken into account when determining the domain domain resource values.
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41/63 frequency for each signature between the systems used to determine the values and systems used to capture the acoustic signal being evaluated.
[0074] To obtain the frequency domain resources, the acoustic sample data can be converted into the frequency domain. In one embodiment, the raw optical data may contain or represent acoustic data in the time domain. A domain representation of the data frequency can be obtained using a Fourier Transform. Various algorithms can be used as known in the art. In some modalities, a Short Time Fourier Transform technique or a Discrete Fourier Transform can be used. The resulting sample of data, then, can be represented by a range of frequencies in relation to their power levels at which they are present. The raw optical data can be transformed in the frequency domain before or after the application of the spatial filter. In general, the acoustic sample will be in the frequency domain to determine the spectral centroid and the spectral spread. In one embodiment, processor 168 can be configured to convert raw acoustic data and / or acoustic sample data from the time domain to the frequency domain. In the process of converting the signal into the frequency domain, the power across all frequencies in the acoustic sample can be analyzed. Using processor 168 to perform the transformation can provide the frequency domain data in real time or near real time.
[0075] The data processing unit 402 can then be used to analyze the acoustic sample data
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42/63 in the frequency domain to obtain one or more of the frequency domain resources and provide an output with the determined frequency domain resources for further processing. In some modalities, the output of the frequency domain resources may include resources that are not used to determine the presence of each event.
[0076] The processor output with frequency domain capabilities for the acoustic sample data can then be used to determine the presence of one or more events at one or more locations in the well hole corresponding to depth intervals at the over which acoustic data is acquired or filtered. In some embodiments, determining the presence of one or more events may include comparing the frequency domain resources with the frequency domain resource thresholds or ranges in each event subscription. When the frequency domain resources in the acoustic sample data correspond to one or more of the event signatures, the event can be identified as having occurred during the sample data measurement period, which can be in real time. Several outputs can be generated to display or indicate the presence of one or more events.
[0077] Processed acoustic data (ie frequency domain resources), which can have a significantly smaller file size (typically more than 1,000X smaller), then can be recorded in a file (for example, an ASCII file ) in a memory at certain intervals (for example, every second, every ten seconds, etc.), which can then be retrieved and
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43/63 transmitted over the network using data collection and transmission software. This process can be performed in real time or almost in real time for data transmission.
[0078] The data transmitted from the DAS interrogator (which includes the frequency domain resource data) can then be further processed using a sequence of data processing steps as shown in the processing sequence 404 in Figure 4. The 404 processing sequence may comprise a series of steps including an anomaly detection step, a signature extraction step, an event classification step, a leak identification step and an exit step. The descriptor data is first processed using an anomaly detection algorithm (for example, an event detection) to determine the presence of any anomalous acoustic response (or responses) that may be triggered by a fluid leak. Although there are several ways to implement the event detection algorithm, the data amplitude threshold in relation to the surface noise captured by the DAS in the fiber optic cable dispersed on or near the surface (for example, in the first 100 meters) of the head well can be used. As an example of the amplitude threshold, an acoustic intensity over the entire bandwidth can be averaged through the acquisition of surface or near surface measurements (for example, in the first 300 m of acoustic data) to provide a estimate of average surface acoustic noise. A threshold, then, can be taken as a
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44/63 percentage of that average. For example, the amplitude threshold can be between about 90% and about 95% of the average. The presence of the signal inside the well hole can be detected when the amplitude of the captured acoustic event exceeds the threshold value. The frequency and amplitude characteristics of the surface noise can also be used to suppress and / or reduce background noise within the selected window to identify the presence of signals on the surface, if necessary. This enables zero-point depth recognition, helps to reduce or eliminate contributions of surface noise, helps to reduce or eliminate DAS interrogator noise contributions, allows the capture of acoustic events and renders captured events in a ready format for signature recognition and uses processed data (as compared to raw DAS data) as the primary feed for the processing sequence. Although the amplitude threshold is used, other time-based digital processing approaches could also be used.
[0079] Once the data is initially processed, anomalous events can be recognized (for example, as events that have amplitudes above thresholds), and the corresponding data from the acoustic sample portion can be extracted as an event block. depth-time. Figure 5A illustrates an example of a depth-time event block that shows depth versus amplitude. Since the depth-time blocks have limited amplitude, the corresponding data can appear as shown in Figure 5B, with the surface noise removed by filtration and the
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45/63 outstanding anomalous events.
[0080] In the second step 412 of the processing sequence 404, the acoustic event blocks can be further analyzed by extracting the frequency domain resources at the event depths and times identified by the anomalous event detection step and comparing the frequency domain resources extracted with event subscriptions to match frequency domain resources for each event identified with an appropriate subscription. The extraction of frequency domain resources can be performed before data is sent to the processing sequence so that the extraction of frequency domain resources involves filtering the received frequency domain resources to the depth and times identified by anomalous event detection, or the extraction of frequency domain resources can be performed only after the anomalous depth-time blocks have been identified.
[0081] In any case, the resulting frequency domain resources can be compared with one or more event subscriptions to identify whether an integrity event occurred in event classification step 414. In some embodiments, event subscriptions may include frequency domain signatures for a liquid leak, a gas leak, a self-induced hydraulic fracture, a shear reactivation or other such event (for example, an unrecognized event category or other non-leak signatures, which can be used To compare).
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46/63 [0082] The event classification step 414 can be performed at each depth location along the fiber and may depend on the acoustic signatures captured at the identified locations to have an anomalous event. Once classified in the appropriate category, the intensities of the events can be determined using the normalized RMS values within the appropriate frequency bands extracted from the site (for example, which may already be one of the descriptors obtained in the extracted domain resources) ) of raw acoustic data. The descriptor data can then be transformed and rewritten as an event matrix. These steps can be performed almost in real time on the data integration server, and transform decision-ready well health event data can be stored together with some or all of the acoustic descriptor data. Classified event data can also be viewed as a three-dimensional depth versus time versus event type intensity plot as shown in Figure 6A and Figure 6B to illustrate well integrity events as a function of depth and time, where the type of event can be represented using different colors for different types of event.
[0083] The event matrix can be further filtered to highlight and view certain types of well integrity events as shown in Figure 6C. These can also be aligned in depth with respect to the well completion scheme and / or geological maps (for example, separate pressure zones) to determine the source of the leakage fluid in the event of leaks
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47/63 liquids.
[0084] In the stage of identification and detection of leakage
416, the matrix in event can also to be processed additionally for get evaluation in leak semi-quantitative per filtration of the matrix in event for
extract events related to gas leaks or
liquids θ / So, integrate the data from intensity filtered to long time to to provide records in leak in fluid, an example of which is shown at Figure 7. [0085] At production of a record fluid leak
For visualization, the spectral energy of RMS for depth sections that do not exhibit spectral compliance for specific overload and well integrity events can be set to zero. This allows those points or zones of depth that have one or more frequency domain resources greater than the thresholds to be easily observed. Figure 7 represents an example of a modality of a fluid leak record that shows the acoustic intensity against depth. This figure illustrates locations that have fluid leaks as spikes in acoustic intensity. The acoustic intensity and its visualization in the fluid leak record, therefore, can be used to identify the relative contribution of fluid leaks at different points along the well bore. For example, it may be possible to determine which zone contributes the largest proportion of fluid leaks, which zone contributes the second largest portion of fluid leaks, and so on. This can also allow for correlation of one or more
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48/63 zonal isolation devices, potential leak locations and / or fluid flow through formation along the length of the well hole.
[0086] The use of processing sequence 404 may result in an adequate identification of fluid leaks within the well bore. In an optional processing step on the secondary (ie, peripheral) data correlation unit 408, the resulting processed data can be correlated with external sensor data such as that provided by a sensor system on or near the surface of the hole well. This processing sequence can be used with the DAS system to determine the flow path for leaks, especially in cases where there are multiple casing columns or leak paths at or near a specified depth to have a leak. The process can also be used to provide a semi-quantitative estimate of the fluid volumes associated with the leak when combined with surface measurements (for example, bleed rate measurements, surface pressure gauge data, etc.).
[0087] The correlation process can generally comprise the use of variable surface measurement data as a comparison with the identified event process. For example, variable pressure or flow data on the surface can be used as a correlation with leakage identification data. It can be expected that, as the leak occurs, a deactivated annulus may have a pressure rise and / or an increased flow rate (for example, a flow rate of
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49/63 bleed). When multiple voids or leak paths are present, the use of pressure or flow data can help identify which leak path (or path) is specifically experiencing the leaks, while the leak depth would be known from the leak detection sequence. event. Although described in this document as a leak path, numerous potential paths are available for fluid flow within the well bore. For example, a leak can occur beyond a restriction or barrier at one or more annulus, between a shell and the formation, and / or within the formation or a hydrocarbon zone and, potentially, in a production assembly. For example, the flow of fluid within a hydrocarbon zone in the formation can be monitored using any of the methods and systems described in this document.
[0088] In one modality, a correlation process can start by deactivating a well. This can allow a base reading to be taken from both the surface sensor data and the frequency domain resources in the well bore without fluid flow. Once 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 pressure, which can potentially induce fluid flow in such an annulus if there is a leak in fluid communication with the selected annulus. This can create a pressure differential between the selected annulus and the neighboring annulus or annuli. The pressure differential can be
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50/63 determined to analyze fluid flow potentials. Once a 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 remains active during the induced flow process to monitor for leaks and determine the phase or phases of the leakage fluid.
[0089] Since the data is obtained from the sensors and the DAS system, which can include the event data determined from the 404 processing sequence to determine the presence or absence of any events, the data can be correlated through time to determine a leak location and leak path. For example, filtered leakage acoustic intensities obtained from the 404 processing sequence can be integrated over time at each depth location to obtain leak data (for example, which can be viewed as leak records) for the leakage path trigger stages (for example, the annular pressure bleeding process). These data can then be aligned over time with pressures, pressure differentials, flow data, etc. for each drive operation to determine leak points and flow paths. For example, it can be determined that a given leak trajectory only triggers a leak at a given depth rather than over numerous depths. From these data, the records of
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51/63 leakage can be determined for each tubular, enclosure column or the like.
[0090] In some modalities, all the surface sensor data can be used in this process. Pressure data, including induced pressure differentials, can be used to determine leak trajectories and leak locations. Bleeding rates can be used to provide a quantitative analysis of leak rates for each leak path. This data can then be stored and / or issued and used in the future for additional leak identification and quantification.
[0091] In other modalities, the monitoring process can be used to monitor the detection of overload events. In general, this process can be similar to the one discussed above in relation to leak detection, and the 404 processing sequence can include event signatures for overload movements (for example, self-induced hydraulic fractures, etc.). Pressure and flow rate monitoring using surface sensors can also be used. When an overload event occurs, a change in the production rate (for example, an increase or decrease in some zones versus others) can occur. The pressure and / or flow rate of the production column and / or one or more production sets (if such sensors are available in the production sets) can be integrated with the event data to determine the presence and depth of the production event. overload. An increase, or decrease in flow rate, can be used to quantify the resulting change in
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52/63 any production area.
[0092] Any of the systems and methods disclosed in this document can be performed on a computer or other device comprising a processor, such as the acquisition device 160 of Figure 1. Figure 8 illustrates a computer system 780 suitable for implementing a or more modalities disclosed in this document as the acquisition device or any portion thereof. The computer system 780 includes a processor 782 (which can be called a central processor unit or CPU) that is communicating with memory devices including secondary storage 784, read-only memory (ROM) 786, random access memory (RAM) 788, input / output (I / O) devices 790 and network connectivity devices 792. Processor 782 can be implemented as one or more CPU chips.
[0093] It is understood that by programming and / or loading executable instructions in the computer system 780, at least one among CPU 782, RAM 788 and ROM 786 is altered, transforming computer system 780, in part, into a particular machine or device that has the innovative functionality taught by the present disclosure. It is critical for electrical engineering and software engineering techniques that the functionality that can be implemented by loading executable software on a computer can be converted into a hardware implementation by well-known design rules. Decisions between implementing a concept in software versus hardware typically depend on
Petition 870190096218, of 26/09/2019, p. 72/119
53/63 design stability considerations and numbers of units to be produced instead of any problems involved in translating the software domain to the hardware domain. In general, a project that is still subject to frequent changes may be preferred to be implemented in software, since performing a hardware implementation again is more expensive than performing a software project again. In general, a project that is stable that will be produced in high volume may be preferred to be implemented in hardware, for example, in an application-specific integrated circuit (ASIC), since, for large production cycles, the implementation of hardware can be less expensive than software implementation. Often a project can be developed and tested in a form of software and later transformed, by well-known design rules, into an equivalent hardware implementation on a specific integrated circuit in terms of
application what connect per wires as instructions of software. Of the same mane wrath that an machine controlled per a new ASIC is an machine or device particular, so
similarly, a computer that has been programmed and / or loaded with executable instructions can be viewed as a particular machine or device.
[0094] Additionally, after the 780 system is turned on or initialized, the 782 CPU can execute a computer program or application. For example, CPU 782 can run software or firmware stored in ROM 786 or stored in RAM 788. In some cases, at startup and / or when the application is started, CPU 782 can copy
Petition 870190096218, of 26/09/2019, p. 73/119
54/63 the application or portions of the application from secondary storage 784 to RAM 788 or to the memory space within CPU 782 itself, and CPU 782 can then execute instructions from which the application is understood. In some cases, the 782 CPU can copy the application or portions of the application from the memory accessed through network connectivity devices 792 or through I / O devices 790 to RAM 788 or into the memory space within of CPU 782, and CPU 782 can then execute instructions from which the application is understood. During execution, an application can load instructions on CPU 782, for example, load some of the application's instructions into a cache of CPU 782. In some contexts, an application that runs can be said to configure CPU 782 to do something, for example, to configure CPU 782 to perform the function or functions promoted by the present application. When CPU 782 is configured in this way by the application, CPU 782 becomes a special-purpose computer or a special-purpose machine.
[0095] Secondary storage 784 is typically comprised of one or more disk drives or tape drives and is used for non-volatile data storage and as an overflow data storage device if RAM 788 is not large enough to hold all functional data. Secondary storage 784 can be used to store programs that load into RAM 788 when such programs are selected for execution. ROM 786 is used to store instructions and, perhaps, data that is read during program execution.
Petition 870190096218, of 26/09/2019, p. 74/119
55/63
ROM 78 6 is a non-volatile memory device that typically has a small memory capacity compared to the larger memory capacity of secondary storage 784. 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 secondary storage 784. Secondary storage 784, RAM 788 and / or ROM 786 can be called, in some contexts, readable storage media by computer and / or computer-readable non-transitory means.
[0096] I / O devices 790 may include printers, video monitors, liquid crystal displays (LCDs), touch sensitive displays, keyboards, alpha-numeric keyboards, switches, displays, mouse, trackballs, speech recognizers, card readers, paper tape readers or other well-known input devices.
[0097] 792 network connectivity devices can take the form of modems, modem banks, Ethernet cards, universal serial bus (USB) interface cards, serial interfaces, token ring cards, distributed data interface cards fiber (FDDI), 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),
Petition 870190096218, of 26/09/2019, p. 75/119
56/63 radio frequency (RFID) and / or other radio interface protocol transceiver cards and other well-known network devices. These 792 network connectivity devices can enable the 782 processor to communicate with the Internet or one or more intranets. With such a network connection, it is contemplated that the 782 processor can receive information from the network, or can send information to the network (for example, to an event database) during the performance of the method steps described above. Such information, which is often represented as a sequence of instructions to be performed using the 782 processor, can be received from and sent to the network, for example, in the form of a computer data signal embedded in a carrier wave.
[0098] Such information, which may include data or instructions to be executed using the 782 processor, for example, may be received from and sent to the network, for example, in the form of a baseband signal. computer data or signal embedded in a carrier wave. The baseband signal or the signal embedded in the carrier wave, or other types of signals currently used or developed in the future, can be generated according to various methods well known to someone skilled in the art. The baseband signal and / or the signal embedded in the carrier wave may, in some contexts, be called a transient signal.
[0099] The 782 processor executes instructions, codes, computer programs, scripts that it accesses from the hard disk, floppy disk, optical disk (these
Petition 870190096218, of 26/09/2019, p. 76/119
57/63 several disk-based systems can all be considered secondary storage 784), flash drive, ROM 786, RAM 788 or network connectivity devices 792. Although only one processor 782 is shown, multiple processors can be present. Thus, although instructions can be discussed as executed by a processor, instructions can be executed simultaneously, in series or otherwise executed by one or multiple processors. Instructions, codes, computer programs, scripts and / or data that can be accessed from secondary storage 784, for example, hard disks, floppy disks, optical disks and / or other device, ROM 786, and / or RAM 788 may be called, in some contexts, non-transitory instructions and / or non-transitory information.
[0100] In one embodiment, the 780 computer system can comprise two or more computers in communication with each other, which collaborate to perform a task. For example, but not in a limiting way, an application can be partitioned in such a way that allows simultaneous and / or parallel processing of the application's instructions. Alternatively, the data processed by the application can be partitioned in such a way as to allow simultaneous and / or parallel processing of different portions of a data set by two or more computers. In one embodiment, virtualization software can be employed by the 780 computer system to provide the functionality of a number of servers that are not directly linked to the number of computers in the 780 computer system.
Petition 870190096218, of 26/09/2019, p. 77/119
58/63 virtualization can provide twenty virtual servers on four physical computers. In one embodiment, the functionality revealed above can be provided by running the application and / or applications in a cloud computing environment. Cloud computing can comprise providing computing services over a network connection using dynamically scalable computing resources. Cloud computing can be supported, at least in part, by virtualization software. A cloud computing environment can be established by a company and / or can be contracted as needed from a third party provider. Some cloud computing environments may comprise cloud computing resources owned and operated by the company, as well as cloud computing resources contracted and / or made available from a third party provider.
[0101] In one embodiment, some or all of the functionality revealed above can be provided as a computer program product. The computer program product may comprise one or more computer-readable storage media that have computer-usable program code incorporated into them to implement the functionality disclosed above. The computer program product may comprise data structures, executable instructions and other program code usable by computer. The computer program product can be incorporated into removable computer storage media and / or non-removable computer storage media. 0 readable storage medium
Petition 870190096218, of 26/09/2019, p. 78/119
59/63 by removable computer can comprise, without limitation, a paper tape, a magnetic tape, magnetic disk, an optical disk, a solid state memory chip, for example, analog magnetic tape, read-only memory disks compact disc (CD-ROM), floppy disks, jump drives, digital cards, multimedia cards and others. The computer program product may be suitable for loading, via computer system 780, at least portions of the contents of the computer program product to secondary storage 784, ROM 786, RAM 788 and / or other non-volatile memory and volatile memory of the 780 computer system. The 782 processor can process executable instructions and / or data structures in part by directly accessing the computer program product, for example, by reading from a CD disc -ROM inserted in a peripheral disk drive of the 780 computer system. Alternatively, the 782 processor can process executable instructions and / or data structures by remotely accessing the computer program product, for example, by downloading the instructions download executables and / or data structures from a remote server via network connectivity devices 7 92. The computer program product understand instructions that promote loading and / or copying of data, data structures, files and / or executable instructions for secondary storage 784, ROM 786, RAM 788 and / or other non-volatile and volatile memory of the 780 computer system.
[0102] In some contexts, secondary storage
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60/63
4, ROM 78 6 and RAM 788 may be referred to as a non-transitory computer-readable medium or computer-readable storage media. A dynamic RAM modality of RAM 788, similarly, can be called a non-transitory computer-readable medium, in the sense that, while a dynamic RAM receives electrical power and is operated according to its design, for example, during a period of time during which the 780 computer system is powered up and operational, dynamic RAM stores information that is written to it. Similarly, the 782 processor may comprise an internal RAM, an internal ROM, a cache memory and / or other internal blocks of non-transitory storage, sections or components that may be called, in some contexts, computer readable non-transitory media or computer-readable storage media. Although various modalities according to the principles revealed in this document have been shown and described above, modifications of them can be performed by someone skilled in the art without departing from the spirit and teachings of the revelation. The modalities described in this document are only representative and are not intended to be limiting. Many variations, combinations and modifications are possible and fall within the scope of the disclosure. The alternative modalities that result from the combination, integration and / or omission of resources of the modality (or modalities) are also covered by the scope of the disclosure. Consequently, the scope of protection is not limited by the description presented above, but, it is defined by the following claims, in which such scope
Petition 870190096218, of 26/09/2019, p. 80/119
61/63 includes all the subject matter equivalents of the claims. Each and every claim is incorporated as additional disclosure in the specification and the claims are embodiments of the present invention (or inventions). In addition, any advantages and resources described above may refer to specific modalities, but should not limit the application of such claims issued to processes and structures that achieve any and all of the above advantages or that have all or any of the above resources.
[0103] Additionally, the section headings used in this document are provided for consistency with the suggestions by means of 37 C.F.R. 1.77 or otherwise to provide organizational guidance. These headings should not limit or characterize the invention (or inventions) presented in any claims that may arise from the present disclosure. Specifically and by way of example, although the headings may refer to a Field, claims should not be limited by the language chosen under that heading to describe the so-called field. Furthermore, a description of a technology in the Background should not be interpreted as an admission that a certain technology consists of the prior art to any invention (or inventions) in the present disclosure. Nor should the Summary be considered a limiting characterization of the invention (or inventions) presented in the forwarded claims. Furthermore, any reference in the present disclosure to the invention in the singular should not be used to argue that there is only a single point of innovation in the present disclosure. Multiple
Petition 870190096218, of 26/09/2019, p. 81/119
62/63 inventions can be presented according to the limitations of the multiple claims issued from the present disclosure, and such claims, consequently, define the invention (or inventions) and their equivalents, which are therefore protected. In any case, the scope of the claims must be considered on its own merits in light of the present disclosure, however, it should not be interpreted by the headings presented in this document.
[0104] The use of broader terms as it comprises, includes and has to be understood in order to provide support for narrower terms as consisting of, consisting essentially of and substantially understood by. The use of the term optionally, may, possibly, and the like in relation to any element of a modality means that the element is not necessary or, alternatively, the element is necessary, in which both alternatives fall within the scope of the modality (or modalities). In addition, references to examples are provided for illustrative purposes only, and are not intended to be exclusive.
[0105] Although the preferred modalities have been shown and described, modifications of them can be made by an element versed in the technique without departing from the scope or the teachings in this document. The modalities described in this document are only exemplary and are not limiting. Many variations and modifications to the systems, apparatus and processes described in this document are possible and are covered by the
Petition 870190096218, of 26/09/2019, p. 82/119
63/63 scope of the disclosure. For example, the relative dimensions of various parts, the materials from which the various parts are produced and other parameters can be varied. Consequently, the scope of protection is not limited to the modalities described in this document, but is limited only by the following claims, the scope of which must include all the subject matter equivalents of the claims. Unless expressly stated otherwise, the steps in a method claim may be performed in any order. Mention of identifiers such as (a), (b), (c) or (1), (2), (3) before the steps in a method claim is not intended to and does not specify a particular order for the steps, but instead, it is used to simplify the subsequent reference to such steps.
[0106] In addition, the techniques, systems, subsystems and methods described and illustrated in the various modalities as distinct or separate can 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 in communication with each other may be indirectly coupled or in communication through some interface, device or intermediate component, electrically, mechanically or otherwise. Other examples of changes, substitutions and alterations are determinable by an element skilled in the art and can be carried out without departing from the spirit and scope revealed in this document.

权利要求:
Claims (5)
[1]
1. Method for detecting a leakage event inside a well bore, the method being characterized by comprising:
induce a pressure differential within a well bore that comprises a fluid;
obtain a sample data set while inducing the pressure differential, where the sample data set is a sample of an acoustic signal that originates within the well bore and where the sample data set is representative of the signal acoustic across a frequency spectrum;
determining a plurality of frequency domain resources from the sample data set, wherein each frequency domain resource of the plurality of frequency domain resources is derived across the frequency spectrum;
determining the presence of a leak event at one or more depths within the well bore based on the determination that the plurality of frequency domain resources correspond to a leak event signature;
correlate the leakage event with the induced pressure differential; and determining the presence and location of a leak within the well bore based on the presence of the leak event and the correlation of the leak event with the induced pressure differential.
Petition 870190096218, of 26/09/2019, p. 107/119
[2]
2/13
Method according to claim 1, characterized in that it further comprises:
obtain a set of surface acoustic data;
determine a surface amplitude threshold based on the acoustic surface data set; and filtering an acoustic data set based on the surface amplitude threshold to produce the sample data set, where the sample data set comprises acoustic data at one or more depths that have an amplitude above the amplitude threshold of surface.
[3]
3. Method, according to claim 2, characterized by the fact that the determination of the plurality of frequency domain resources from the sample data set comprises extracting the plurality of frequency domain resources in each one or more depths that have the amplitude above the surface amplitude threshold.
[4]
4. Method, according to any one of the preceding claims, characterized by the fact that determining the presence of the leakage event at one or more depths involves comparing the plurality of frequency domain resources in each of the one or more
more depths with the event subscription leak. 5. Method, in according to any one of claims 1 The 4, characterized by understand additionally:
calculate a normalized RMS energy within a defined frequency band for each event of
Petition 870190096218, of 26/09/2019, p. 108/119
3/13 leak at each of the one or more depths in the well bore, where the normalized RMS energy is indicative of a fluid flow rate for each leak event.
Method according to claim 5, characterized in that it further comprises:
integrate or calculate The average gives energy of RMS normalized to each event leakage to over time; and determine a rate of flow of relative fluid for each eventleak based at integration / calculation in average gives energy of RMS normalized for each event in leak. 7. Method, according with Any of them of
claims 1 to 6, characterized in that it further comprises:
correlate one or more depths within the well hole with leakage events with one or more structural features within the well hole; and determining a source of the leak based on the correlation of one or more depths with one or more structural features.
8. Method according to any one of claims 1 to 7, characterized in that the determination of the presence of the leakage event comprises
to determine The fluid phase of the leak through gives Comparation gives plurality in resources of domain in frequency with the signature in leakage event in an
or more depths.
Petition 870190096218, of 26/09/2019, p. 11/119
4/13
Method according to any one of claims 1 to 8, characterized in that the well bore comprises one or more tubular columns and one or more annulus arranged between at least one of: i) two adjacent tubular columns of the one or more tubular columns, ii) a tubular column of one or more tubular columns and a formation, or iii) both i and ii, and where determining a presence and location of the leak within the well bore comprises determining an annulus of the one or more rings and a depth at which the leak is present.
10. Method, according to claim 9, characterized by the fact that the induction of the pressure differential comprises releasing a fluid from a first annulus of one or more annulus, in which the method additionally comprises:
correlate a flow rate of the fluid released from the first annulus with the leakage event; and determining a leak rate at a depth based on the correlation of the flow rate of the fluid released from the first annulus with the leak event.
11. Method according to claim 10, characterized in that it further comprises: correlating the fluid flow rate and a phase measurement as measured on the surface while inducing the pressure differential with that obtained from the sample data set .
12. System to detect a leak event inside a well bore, the system being characterized by understanding
Petition 870190096218, of 26/09/2019, p. 110/119
[5]
5/13 a receiving unit comprising a processor and a memory, wherein the receiving unit is configured to receive a first signal from a sensor disposed in a well bore, in which a processing application is stored in memory, and where the processing application, when run on the processor, configures the processor to:
receiving the first signal from the sensor, where the signal comprises an indication of an acoustic signal received at one or more depths within the well bore, where the signal is indicative of the acoustic signal across a frequency spectrum, receiving a second signal comprising an indication of a pressure differential induced within the well bore, determining a plurality of frequency domain resources of the acoustic signal across the frequency spectrum, wherein each frequency domain resources of the plurality of frequency domain resources

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法律状态:
2021-10-19| B350| Update of information on the portal [chapter 15.35 patent gazette]|

优先权:

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申请号 | 申请日 | 专利标题

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US201762479873P| true| 2017-03-31|2017-03-31|

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PCT/EP2018/058174|WO2018178279A1|2017-03-31|2018-03-29|Well and overburden monitoring using distributed acoustic sensors|

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