Downhole flow monitoring and evaluation using distributed acoustic sensing and acoustic noise logging

Abstract

Systems and techniques of the present disclosure may first use a fiber optic cable as a distributed acoustic sensor or as a sensor that senses temperatures along the fiber optic cable that is deployed in a wellbore. These systems and techniques may also control the deployment of an acoustic sensing tool in the wellbore that has greater resolution than the fiber optic cable. Data collected via the fiber optic cable may be used to identify locations where the acoustic sensing tool should be deployed such that noise sources can be accurately characterized based on data collected by the acoustic sensing tool. As such, the fiber optic cable may be used to identify a general location of a sound of interest after which the acoustic sensing tool may be used to collect data such that wellbore defects or subterranean flows may be more accurately characterized.

Description

TECHNICAL FIELD

[0001] The present disclosure is directed to making evaluations using data sensed by sensors deployed in a wellbore. More specifically, the present disclosure is directed to making determinations based on data sensed by different types of sensors.BACKGROUND

[0002] Acoustic or sonic logging tools are often employed in wellbore environments for a variety of purposes. In some instances, acoustic sensors may be deployed in a wellbore when evaluations regarding well integrity and flow profiles of the wellbore are performed. Noises associated with leaking fluids in a wellbore environment may be indicative of a defect in the wellbore that could render the wellbore unsuitable for a given task. Other noises may be associated with fluids flowing through subterranean strata.BRIEF DESCRIPTION OF THE DRAWINGS

[0003] In order to describe the manner in which the above-recited and other advantages and features of the disclosure can be obtained, a more particular description of the principles briefly described above will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. Understanding that these drawings depict only exemplary embodiments of the disclosure and are not therefore to be considered to be limiting of its scope, the principles herein are described and explained with additional specificity and detail through the use of the accompanying drawings in which:

[0004] FIG. 1A illustrates an example schematic diagram of a system for performing distributed measurements along a wellbore using distributed strain sensing with a fiber optic cable when the cable may be permanently installed in a wellbore.

[0005] FIG. 1B is a schematic diagram of an example of wireline, slickline, coil, tubing, or other in a downhole environment having tubulars, in accordance with various aspects of the subject technology.

[0006] FIG. 2 illustrates a schematic diagram of assemblies that may be used in a wellbore for collecting acoustic data from inside the wellbore, in accordance with various aspects of the subject technology.

[0007] FIG. 3 illustrates two different sound sources that emit noises that may be detected by three different acoustic sensors, in accordance with various aspects of the subject technology.

[0008] FIG. 4 illustrates a series of actions that may be performed when fluid flows in subterranean strata or wellbore defects are characterized, in accordance with various aspects of the subject technology.

[0009] FIG. 5A illustrates a mapping of data collected based on operation of a fiber optic cable deployed in a wellbore, in accordance with various aspects of the subject technology.

[0010] FIG. 5B illustrates a mapping made from data collected by a set of acoustic sensors, in accordance with various aspects of the subject technology.

[0011] FIG. 6 illustrates another series of actions that may be performed when fluid flows in subterranean strata or wellbore defects are characterized, in accordance with various aspects of the subject technology.

[0012] FIG. 7 illustrates an example architecture of a computing device which can implement the various technologies and techniques described herein.DETAILED DESCRIPTION

[0013] As discussed in greater detail herein, the present disclosure provides systems, methods, and computer-readable media for identifying locations of a wellbore where sensors of a particular type may be deployed to identify the size or scope of wellbore defects more accurately and that may allow for more accurate determinations be made as to flow rates of fluids in a subterranean environment. Apparatus and methods of the present disclosure may be referred to as systems and techniques that address challenges of monitoring downhole flows in real-time or that may be used to perform high-quality flow evaluation and high-precision leak localization.

[0014] Systems and techniques of the present disclosure may first use a fiber optic cable as a distributed acoustic sensor or as a sensor that senses temperatures along the fiber optic cable that is deployed in a wellbore. These systems and techniques may also control the deployment of an acoustic sensing tool in the wellbore that has greater resolution than the fiber optic cable. Data collected via the fiber optic cable may be used to identify locations where the acoustic sensing tool should be deployed such that noise sources can be accurately characterized based on data collected by the acoustic sensing tool. As such, the fiber optic cable may be used to identify a general location of a sound of interest after which the acoustic sensing tool may be used to collect data such that wellbore defects or subterranean flows may be more accurately characterized.

[0015] The fiber optic cable mentioned above may be part of a distributed acoustic sensing (DAS) system that may be used to continuously monitor abnormal acoustic signals along a wellbore. In an instance when a leak occurs at a set of tubing or in a wellbore casing, acoustic signals generated by the flows associated with the leak may be detected in real-time. An acoustic noise logging tool may then be deployed in the wellbore to target depth intervals. Data sensed by the noise logging tool may be recorded and analyzed such that determinations regarding the size (e.g., orifice size and / or volume) an actual location of fluid movement may be identified more accurately than possible by analyzing data received from the fiber optic cable alone. Furthermore, by combining DAS and acoustic noise logging, real-time flows may be identified quickly, reliably, and more accurately than before.

[0016] While acoustic noise logging may be used for wellbore leak detection and localization and downhole flow evaluation (e.g., channel flows, fracture flows, and formation flows), fiber optics combined with controlled deployment of a hydrophone array is one unique aspect of the present disclosure. Techniques of the present disclosure may use beamforming technology to identify leaks can be accurately localized both radially and vertically. Furthermore, the flowrate of leakage can be estimated from an acoustic data recorded by an acoustic noise logging tool. In certain instances, the phase of the leakage flow can be classified according to the spectra of the recorded signals. The success of acoustic noise logging tools may be limited because noise events are not always continuous. This means that noise events may be transitory and could occur when the tool is not close to a noise source.

[0017] Another limitation to using acoustic noise logging tools in isolation relates to the fact that collecting such acoustic data can be time consuming. This means that deploying acoustic sensor arrays like a hydrophone for a time does not guarantee that a leak will be detected. In worst case scenarios, not timely detecting a leak could end in catastrophic blowouts in the downhole environment. When a fiber optic cable is used as part of a DAS system, acoustic signals / sounds may be identified along the entire wellbore where the fiber optic cable is deployed. Since a fiber optic cable may be used to collect data continuously in real-time along the wellbore, downhole flows can be monitored and leaks can be detected upon occurrence. Since, however, the resolution of DAS is typically in the order of feet, DAS may not be able to accurately detect the precise location and size of a wellbore defect.

[0018] The vertical resolution of the acoustic modern noise logging tools (e.g., sensors of a hydrophone) are in inches. Furthermore, acoustic noise logging can provide frequency / spectra analysis, radial localization of noise sources and flow evaluation. This means that while a DAS system is used to provide general information regarding sounds of interest. The use of a sensor array (e.g., sensors of a hydrophone array) may be used to profile wellbore defects and subterranean flows in a manner not possible with a DAS system.

[0019] By incorporating the technologies together (DAS and acoustic noise logging) techniques of the present disclosure, techniques of the present disclosure can generate a base log with DAS after which an interval for collecting data with an acoustic noise logging tool may be identified based on the data collected by the DAS system at selected depths. By running the stationary noise logging with only a few chosen intervals, amounts of time required to collect data with sufficient resolution can be achieved more efficiently. The same may be true for characterizing of fluid flows through subterranean strata.

[0020] Generally, a work flow of the present disclosure may include a series of actions that include: *Deploying a fiber optic cable of a distributed acoustic sensing (DAS) system downhole: *Logging strain changes along the wellbore based on data collected via the fiber optic cable: *Monitoring downhole flows based on strain changes associated with subterranean noise sources and / or temperature changes: *Deploying an acoustic logging tool downhole in the vicinity of a sound of interest; and *Evaluating data collected by the DAS system and the acoustic noise logging tool to identify, locate, and characterize downhole flows that may be associated wellbore defects and / or flows of fluids through subterranean strata.

[0021] FIG. 1A illustrates an example schematic diagram of a system for performing distributed measurements along a wellbore using distributed strain sensing with a fiber optic cable when the cable may be permanently installed in a wellbore. The system 100 can include a wellbore 102 with a casing string 104 extending from the surface 106 through the wellbore 102. A blowout preventer 107 (“BOP”) can be positioned above a wellhead 109 at the surface 106. The wellbore 102 extends through various earth strata and may have a substantially vertical section 108. In some aspects, the wellbore 102 can also include a substantially horizontal section. The casing string 104 can include multiple casing tubes 110 coupled together end-to-end by casing collars 112. In some aspects, the casing tubes 110 are approximately thirty feet in length. The substantially vertical section 108 may extend / through a rock or hydrocarbon bearing subterranean formation 114.

[0022] A tool can be positioned downhole as part of casing string 104. The tool can be coupled to a locator device, such as magnetic pickup coil 118, which can generate a voltage in response to a change in a surrounding magnetic field. In one example, the locator device can be a magnetic pickup coil 118. In other examples, a piezoelectric sensor or other suitable locator device can be used by the system 100. The magnetic pickup coil 118 can include a permanent magnet with a coil wrapped around it. The casing tubes 110 can each emit a magnetic field. Each casing collar 112 can emit a magnetic field that is different from the magnetic field emitted by the casing tubes 110, which can be joined by the casing collar 112. The change in the magnetic field between the casing collars 112 and the casing tubes 110 can be detected by the magnetic pickup coil 118 of the system 100. The magnetic pickup coil 118 of the system 100 can generate a voltage in response to the change in the surrounding magnetic field when the magnetic pickup coil 118 passes a casing collar 112. The voltage generated by the magnetic pickup coil 118 can be in proportion to the velocity of the magnetic pickup coil 118 as the magnetic pickup coil 118 travels past the casing collar 112. In some aspects, the magnetic pickup coil 118 of the system 100 can travel between approximately 10 feet per second and approximately 30 feet per second.

[0023] The magnetic pickup coil 118 of the system 100 can be coupled to a light source, for example a light emitting diode (LED) 120. The voltage generated by the magnetic pickup coil 118 can momentarily energize the LED 120, which can be coupled to the magnetic pickup coil 118. The LED 120 can emit a pulse of light (e.g., an optical signal) in response to the voltage generated by the pickup coil 118. The LED 120 of the system 100 can transmit the pulse of light to a receiver 124 positioned at the surface 106. In some aspects, the LED 120 can operate at a 1300 nm wavelength and can minimize Rayleigh transmission losses and hydrogen-induced and coil bend-induced optical power losses. In some aspects, a high speed laser diode or other optical sources can be used in place of the LED 120 and various other optical wavelengths can be used. For example, wavelengths from about 850 nm to 2100 nm can make use of the optical low-transmission wavelength bands in ordinary fused silica multimode and single mode fibers.

[0024] In another example, the system 100 may include a light source that may be a laser 113 positioned at the surface 106 proximate to the BOP 107. The laser 113 can be coupled to the fiber optic cable 122, which can be dispensed at an end by the upper reel 132. The upper reel 132 can be positioned at the surface 106 proximate to the BOP 107. In some aspects, the laser 113 and the upper reel 132 can be positioned elsewhere at the surface 106 or within the wellbore 102.

[0025] The laser 113 of the system 100 can be a high repetition pulse laser or other suitable light source. The laser 113 of the system 100 can also generate an optical signal, for example, a series of light pulses that are transmitted by the fiber optic cable 122. The tool of the system 100 can be coupled to the reel 138 and the magnetic pickup coil 118. In some aspects, a piezoelectric sensor or another suitable modulation device can be used to modulate the optical signal of the laser 113. In some aspects, the modulation device can modulate, for example but not limited to, the frequency, amplitude, phase, or other suitable characteristic of the optical signal. The optical signal generated by the laser 113 can travel the length of the fiber optic cable 122 and reach a lower end of the fiber optic cable 122 proximate to the lower reel 138.

[0026] The receiver 124 of the system 100 can be communicatively coupled to a computing device 128 located away from the wellbore 102 by a communication link 130. The communication link 130 may be a wireless communication link. The communication link 130 can include wireless interfaces such as IEEE 802.11, Bluetooth, or radio interfaces for accessing cellular telephone networks (e.g., transceiver / antenna for accessing a CDMA, GSM, UMTS, or other mobile communications network). In some aspects the communication link 130 may be wired. A wired communication link can include interfaces such as Ethernet, USB, IEEE 1394, or a fiber optic interface. The receiver 124 of the system 100 can transmit information related to the optical signal, for example but not limited to the light pulse count, the time the light pulse arrived, or other information, to the computing device 128. In some aspects, the receiver 124 of the system 100 can be coupled to a transmitter that communicates with the computing device 128.

[0027] Strain value based on the distributed measurement pressure data from the communication link 130 may be received by a computing device 128 via a network interface with a compatible communication link 130. In some aspects, the computing device 128 of the system 100 may use the interface to communicate with one or more networks, such as local area network (LAN) and / or wide area network (WAN), such as the Internet. The computing device 128 of the system 100 may also include a processor for processing the received the distributed measurement pressure data. The processor may be embodied, without limitation, as a microprocessor, application-specific integrated circuit (ASIC), digital signal processor (DSP), field-programmable gate array (FPGA) or the like. The processor may execute instructions stored in a storage device to perform aspects of the methods described herein. The storage device may also be used to store one or more logs, which may be embodied as any suitable data structure(s) for representing received and / or processed data. In one aspect, the computing device 128 may further include a user interface, such as a graphics card, for displaying graphics and / or text on a display device, such as a computer monitor. The user interface may display pressure and temperature based on the determined strain value.

[0028] The fiber optic cable 122 of the system 100 that transmits the light pulse to / from the LED 120 to the receiver 124 can be an unarmored fiber. The unarmored fiber can include a fiber core and cladding and a thin primary buffer coating but no outer jacket or secondary tight buffer to minimize fiber diameter for increased fiber length capacity of a given payout bobbin or reel. In some aspects, the fiber optic cable 122 of the system 100 can be an armored fiber. The armored fiber can include a fiber core, a cladding, a thin primary buffer coating an outer jacket or secondary tight buffer. The inclusion of the outer jacket or secondary tight buffer can increase the diameter of the fiber optic cable 122. The fiber optic cable 122 can be a multi-mode or single-mode optical fiber. The fiber optic cable 122 can include one or more optical fibers. The fiber optic cable 122 can be a sacrificial cable that is not retrieved from the wellbore 102 but instead remains in the wellbore 102 until it is destroyed. For example, the fiber optic cable 122 can be destroyed during stimulation of the wellbore 102.

[0029] The fiber optic cable 122 of the system 100 can also be dispensed from an upper bobbin or reel 132 positioned within the wellbore 102 proximate to the surface. In some aspects, the upper reel 132 can be positioned at the surface 106, for example the upper reel 132 can be positioned proximate to the blowout preventer 107. The upper reel 132 can be secured within the wellbore 102 by a securing device, for example by spring loaded camming feet 136 or other suitable securing mechanisms. The upper reel 132 of the system 100 can have a near-zero tension payout force that can allow dispensing of the fiber optic cable 122 when there is a tension in the fiber optic cable 122.

[0030] The fiber optic cable 122 of the system 100 can further be tensioned by and pulled along with the displacement fluid that is injected into the casing string 104 to move the tool. The upper reel 132 of the system 100 can dispense additional lengths of the fiber optic cable 122 as the fiber optic cable 122 is tensioned by the displacement fluid injected into the wellbore 102. In some aspects, the fiber optic cable 122 of the system 100 can spool off the upper reel 132 at the same rate as the flow of the displacement fluid. The upper reel 132 can prevent the fiber optic cable 122 from breaking or otherwise becoming damaged as the fiber optic cable 122 travels downhole.

[0031] The fiber optic cable 122 of the system 100 can also be spooled on and dispensed from a lower bobbin or reel 138 positioned proximate to the magnetic pickup coil 118. The lower reel 138 can include a drag device 139. The drag device 139 can allow the lower reel 138 to dispense the fiber optic cable 122 only when a pre-set tension in the fiber optic cable 122 is reached. The lower reel 138 payout can prevent the fiber optic cable 122 from breaking or otherwise becoming damaged as the fiber optic cable 122 and the cement plug 116 travel downhole. The upper reel 132 and the lower reel 138 can store greater lengths of unarmored fiber optic cable than armored fiber optic cable. While FIG. 3 depicts the lower reel 138 positioned below the LED 120 and the magnetic pickup coil 118, in some aspects, the lower reel 138 can be positioned elsewhere with respect to the LED 120 and the magnetic pickup coil 118 of the system 100.

[0032] Referring to FIG. 1A, the system 100 may further include permanently installed sensors. The sensors may include fiber optic cables 122 that may be cemented in place in the annular space between the casing string 104 and formation 114, or fiber optic cables 122 may be positioned within casing string 104 as shown in FIG. 1A. Fiber optic cables 122 can also include fiber optic lines, fiber optic tubes, waveguides, optical waveguides, or any other fiber suitable for the intended purpose and understood by a person of ordinary skill in the art. Other types of permanent sensors may include surface and down-hole pressure sensors, where the pressure sensors may be capable of collecting data at rates up to 2,000 Hz or even higher.

[0033] The fiber optic cable 122 of the system 100 may house one or several optical fibers and the optical fibers may be single mode fibers, multi-mode fibers or a combination of single mode and multi-mode optical fibers. The system connected to the optical fibers may include Distributed Temperature Sensing (DTS) systems, Distributed Acoustic Sensing (DAS) Systems, Distributed Strain Sensing (DSS) Systems, quasi-distributed sensing systems where multiple single point sensors are distributed along an optical fiber / cable, or single point sensing systems where the sensors are located at the end of the cable. For each of the optical fibers 122, Raman scattering and coherent Rayleigh measurement(s) may be performed on the ground surface, and a comparison of Raman signal intensities to derive temperature and Rayleigh or enhanced backscatter based interferometric phase shift for acoustic signal may be performed. From these measurements of Raman comparison and Rayleigh-based interferometric phase shift, distributions of pressure, temperature, and strain along the fiber optic cable 122 can be determined simultaneously. Operation of a DTS, DAS, or DSS system or combination thereof may be used to identify temperatures of interest, sounds of intertest, or stresses of interest that may be associated with a wellbore defect.

[0034] The system 100 may operate using various sensing principles. One example includes a DTS system based on inelastic Raman scattering with comparison of Stokes and Antistokes signal intensities to derive localized fiber temperature. Another example includes an optical phase change sensing-based system, such as a DAS system, which is based on interferometric sensing principles using a highly coherent laser and homodyne or heterodyne detection techniques, where the system may sense optical signal phase and / or intensity changes due to constructive or destructive interference along said fibers, due to changes in optical path length from temperature or strain perturbations. Another example includes a strain sensing system, such as a DSS using integrated dynamic strain measurements based on interferometric sensors or static strain sensing measurements using Brillouin scattering. Brillouin-based DSS systems sense both strain and temperature via inelastic scattering, where an acoustic phonon vibration is generated near 11 GHz in silica optical fiber and can be demodulated to measure phonon frequency shift, which is a function of strain and / or temperature. Another example includes quasi-distributed sensors based on Fiber Bragg Gratings (FBGs) where a wavelength shift is detected or multiple FBGs or multiple fibers are used to form Fabry-Perot, Mach-Zehnder, Michelson, or Sagnac type interferometric sensors for phase based sensing, or single point fiber optic sensors based on Fabry-Perot or FBG or intensity-based sensors.

[0035] FIG. 1B is a schematic diagram of an example of wireline, slickline, coil, tubing, or other in a downhole environment having tubulars. In this example, an example system 140 is depicted for conducting downhole measurements after at least a portion of a wellbore has been drilled and the drill string removed from the well. An imager tool (not shown) can be operated in the example system 140 shown in FIG. 1B to log the wellbore. A downhole tool is shown having a tool body 146 in order to carry out logging and / or other operations. For example, instead of or in addition to using the casing string 104 of FIG. 1A to lower the downhole tool, which can contain sensors and / or other instrumentation for detecting and logging nearby characteristics and conditions of the wellbore 116 and surrounding formations, a wireline conveyance 144 can be used. The tool body 146 can be lowered into the wellbore 116 by wireline conveyance 144. The wireline conveyance 144 can be anchored in drill rig 142 or by a portable means such as a truck 145. The wireline conveyance 144 can include one or more wires, slicklines, cables, and / or the like, as well as tubular conveyances such as coiled tubing, joint tubing, or other tubulars. The downhole tool can include an applicable tool for collecting measurements in a drilling scenario, such as the imager tools described herein.

[0036] The illustrated wireline conveyance 144 provides power and support for the tool, as well as enabling communication between data processors 148A, 148B, through 148N (148A-N) on the surface. In some examples, wireline conveyance 144 can include electrical and / or fiber optic cabling for carrying out communications. The wireline conveyance 144 is sufficiently strong and flexible to tether the tool body 146 through the wellbore 116, while also permitting communication through the wireline conveyance 144 to one or more of the processors 148A-N, which can include local and / or remote processors. The processors 148A-N can be integrated as part of an applicable computing system, such as the computing device architectures described herein. Moreover, power can be supplied via wireline conveyance 144 to meet power requirements of the tool. For slickline or coiled tubing configurations, power can be supplied downhole with a battery or via a downhole generator.

[0037] The scope of the present disclosure is not limited to the environment shown in FIGS. 1A and 1B as methods of the present disclosure may be applied in other environments. Methods and apparatus of the present disclosure may process acoustic data that was received from one or more microphones, hydrophones, piezoelectric sensors, or other equipment that may be capable of sensing acoustic signals, such as sub-sonic, sonic, or ultrasonic signals. This processing may include performing evaluations that allow portions of received acoustic data to be identified based on characteristics known to be representative of specific types of sound sources. Characteristics that may be associated with a sound source include yet are not limited to one or more frequencies emitted by the sound source and / or information that can be used to identify a location of the sound source. Additionally, or alternatively, acoustic noise characteristic of a sound source may be associated with a sound amplitude, a power, or a power spectral density of the noise emitted by the sound source.

[0038] Techniques used to evaluate noises in an environment may include a technique referred to as beamforming where signals from different receiving elements of a sensing array (e.g., an array of different hydrophones) may be delayed by different times. This may result in signals being combined constructively to generate a resultant signal that is of greater magnitude than any signal received by a particular sensing element. This may include multiplying signals received from different sensing elements with different gains or weighting factors. In certain instances, the addition of these signals may be performed in the frequency domain. Alternatively or additionally, techniques of the present disclosure may perform a form of signal analysis referred to as independent component analysis (ICA), where matrix math operations are performed to associate particular sounds with specific sound sources.

[0039] Other types of separation techniques may be used to evaluate signals from different types of sources include extracting sound from a single object in an environment that includes multiple objects emitting sounds that are superimposed over each other. This may include separating sounds that have multivariate data from other sounds using statistical methods or statistical characteristics. For example, samples of a person's voice may be collected and analyzed to identify characteristics of tone, dynamic range, and / or intonation. Once identified, these samples may be compared with sound information received from a sensor array and characteristics that match the characteristics of the person's voice may be interpreted as coming from that person. This may include comparing sets of voice data from the person with newly acquired data and performing a statistical analysis. Sounds that match characteristics in the set of voice data to at least a threshold level by the statistical analysis may be attributed as being spoken by the person. Sounds that do not match the characteristics in the set of voice data may be filtered out.

[0040] Specific types of sound sources may produce sounds that can be collected and analyzed to identify a type of sound source from which a particular sound was emitted. For example, a crack, hole, or other orifice in tubing of wellbore that is producing oil may emit an acoustic noise that could be classified as a whistle sound that has spectral characteristics that include a base frequency, one or more harmonic frequencies, and potentially other frequencies. In such an instance, the base frequency may be a frequency of 110 Hertz (Hz) and the one or more harmonic frequencies may be integer multiples of the base 110 Hz frequency (e.g., 220 Hz or 330 Hz). Other frequencies emitted by this wellbore crack or orifice may be a function of factors such a thickness of the tubing, a space between the tubing and other parts of the wellbore, a hydrocarbon flow rate, densities of hydrocarbons or other substances moving through the wellbore, or other factors. These other factors may also be a combination of a base frequency that is offset based on factors such as the tubing thickness, the space between the tubing and other parts of the wellbore, the hydrocarbon flow rate, material density, or other factors.

[0041] In an instance, when a sensor or sensor array senses sounds from two different sound sources, for example, a first sound source that has characteristics consistent with a whistle and second sound source that has characteristics consistent with a vibrating string, the two different sounds may be distinguished from each other even though they may have frequency components that overlap. For example, this can include a comparison of the sound of a flute to the sound of a violin. Here the flute sound would have frequency components that correspond to a volume circumscribed by the flute, keys of the flute that are depressed, and materials from which the flute is made. This may be the case when all of these factors affect the current resonance frequency of the flute. Similarly, the violin sound is a function of string length, string thickness, string tightness, materials that the violin is made of, and other applicable factors. In the context of a wellbore, a flute or whistle sound may be characteristic of a crack in wellbore tubing and the violin or string sound may be characteristic of materials moving between a wellbore casing and wellbore tubing. Other noises may be associated with production materials that move past equipment deployed in the wellbore. For example, a string or cable used to deploy wellbore equipment may make noise.

[0042] FIG. 2 illustrates a schematic diagram of assemblies that may be used in a wellbore for collecting acoustic data from inside the wellbore. FIG. 2 includes casing 220 that may be cemented in place into wellbore 210. Wellbore 210 may have been drilled using drilling equipment known in the art and casing 220 may have been fabricated by screwing tubular sections of pipe together after which cement may have been applied between an outer surface of casing 220 and an inner surface of wellbore 210. Tubing 230 may have been inserted into casing 220 after completion of a wellbore cementing process. Because of this, casing 220 may be used to maintain or form a physical isolation barrier between portions of wellbore 210 and an internal portion 290 of casing 220.

[0043] While FIG. 2 illustrates fiber optic cable 205 that is inserted in tube 230, fiber optic cable 205 may be inserted in casing 220. Fiber optic cable 205 may be inserted into wellbore 210 at any stage of operation and may remain in the wellbore for the lifespan of wellbore 210. In certain instances, fiber optic cable 205 may be cemented into place when casing 220 is cemented in place in wellbore 210. As such fiber optic cable 205 may be deployed within or next to any wellbore feature.

[0044] After tubing 230 has been inserted into casing 220 of wellbore 210, sensing array 240 may be lowered into casing 220. Sensing assembly 240 may be used to collect acoustic data throughout the lifespan of wellbore 210—when a wellbore is made, during a wellbore production phase, and / or after the wellbore has been placed out of service. While not illustrated in FIG. 2, sensing assembly may be deployed in wellbore 210 before tubing 230 is inserted into the wellbore. Techniques of the present disclosure may be performed such that a certificate of compliance may be generated, and such a certificate may allow a wellbore to be placed into service or retired from service based on sets of wellbore management rules or regulations.

[0045] After wellbore 210 is placed into operation, substances may flow through tubing 230 during a production process. Such a production process may relate to hydrocarbon extraction, hydraulic fracturing, or carbon dioxide sequestration. Sensing assembly 240 may be lowered into tubing 230 using string 250. Sensing assembly 240 includes multiple acoustic sensing elements 260 disposed along a length of sensing assembly 240. Each of sensing elements 260 may include one or more acoustic sensors that may be capable of sensing acoustic noise in one or more directions, for example, using directional sensors, omni-directional sensors, multidirectional sensors, or combination of different types of sensors. Hydrophones, microphones, and piezoelectric sensors are examples of sensor types that may be used when methods of the present disclosure are implemented. In certain instances, string 250 may include a fiber optic cable.

[0046] The tubing 230 shown in FIG. 2 includes an opening in tubing 230 that may be referred to as an orifice. Orifice 270 may be any defect, for example, a crack, hole, orifice, or other defect. Techniques of the present disclosure may be used to identify tubing defects, tubing leaks, tubing related flows, defects in cement, damaged cement related flows, casing leaks, or other leaks associated with a particular wellbore. These techniques may also identify sounds from another wellbore or a formation near a current wellbore, this may include sounds of a flow of another wellbore, a leak in another wellbore, a flow in a fracture of a formation, or a flow in a permeable matrix of a formation. Materials moving along an inside area 280 of tubing 230 may generate noise as those materials move through, past, or around orifice 270. When a production flow includes providing materials via tubing 230 to some portion of wellbore 210 (not illustrated in FIG. 2), those materials may flow down tubing 230 and through and past orifice 270. When a production flow injected into the portion of the wellbore is carbon dioxide or a fracturing fluid, portions of that fluid may flow through or past orifice 270. The sounds generated by that fluid motion may vary based on a size of orifice 270, a density of the fluid, a pressure of the fluid, a fluid flow rate, or other factors. In certain instances, orifices of different sizes may have similar yet not necessarily identical characteristics. For example, an orifice of a first size may generate noise that includes a base frequency and harmonics of that base frequency. This noise may also include sounds generated as a function of the thickness or type of material (e.g., a type of tubing 230). These noises may also include sounds associated with the motion of the fluid between tubing 230 and casing 220 in area 290 of FIG. 2. Similar factors may be associated with noises generated when fluids (e.g., oil, gas, or water) are extracted from a formation that wellbore 210 is drilled into.

[0047] An orifice of a first size may generate noise at frequencies that are a function of the size of the orifice and an intensity of that noise may vary based on operating conditions (e.g., pressure or flow rate) and proximity. An orifice of a larger size may generate noise at different frequencies than the noises generated by a orifice of the smaller size for a given set of conditions. In such instances, other characteristics associated with fluids moving through orifices of different sizes may correspond to each other. For example, frequencies associated with a orifice of the first size may include a base (resonant) frequency of 110 Hz and harmonics of 220 Hz and 330 Hz. An orifice of a second size may include a base frequency of 200 Hz and harmonics of 400 Hz and 600 Hz.

[0048] In another example, analysis may include identifying the shape of a spectrum of frequencies from a type of sound source. A type of sound source may generate noises that have a specific spectral signature. A spectrum associated with a casing leak may have high amplitudes of low frequency signals and low amplitudes of higher frequency signals that results in a characteristic curve that fits a pattern. One such pattern could be plotted in a frequency domain map that shows frequencies of sounds and respective amplitudes. A first curve attributed to a particular type of sound source may include sounds at 10 Hz, 25 Hz, and 50 Hz that reduce according to a parabolic function and a second curve attributed to that same particular type of sound source may include sounds at 20 Hz, 50 Hz, and 100 Hz that fit the same parabolic function with different coefficients. Mappings used to identify a type of sound source may use different mathematical functions that are associated with different portions of the frequency spectrum. For example, a type of sound source may have a first portion where spectral magnitudes correspond to an open downward shaped parabola and may have a second portion that corresponds to an open upward shaped parabola. Data collected from two different sound sources that generate noise at different frequencies may both be identified as being emitted from a same type of sound source when mappings of their respective spectral content and magnitude correspond to a same set of functions that have different coefficient values.

[0049] Noises associated with orifice 270 may include primary sounds and secondary sounds. Primary sounds may be a function of an orifice size and secondary sounds may be a function of other factors, for example, types of materials or material thickness associated with the noise source. These various factors may result in noises being generated that have a same pattern of respective frequencies as included in the example above where noises generated by the orifice of the smaller size and the larger size correspond to each other based on a base resonant frequency one or more harmonics of the base resonant frequency. Relative amplitudes of these different frequencies may also be associated with a pattern that is characteristic of a orifice 270 in tubing 230. Such relative amplitudes associated with each respective orifice size may correspond to each other based on linear or logarithmic functions. This may be similar to the way the pitch of a piano changes with each respective key as other sound characteristics of a piano may not change even though the pitch of the sound changes.

[0050] In certain instances, multiple conditions must be met to identify a type of sound source creating a particular sound. A set of harmonic matching criteria may be necessary yet not sufficient to identify that a particular sound was generated by a crack in a wellbore tube. For example, a sound generated by a type of tubing material and / or a tubing thickness may also be required to identify whether the sound source should be classified as a crack in the tubing. Cracks or other orifices in a type of tubing may be associated with sounds generated by deformation or movement in a portion of the tubing. The orifice 270 in tubing 230 may result in the tube 230 vibrating as fluid leaks from area 280 inside of tubing 230 to area 290 located between an outer surface of tubing 230 and an inner surface of casing 220. In such instances, the harmonic criteria may be associated with a first set of matching criteria and the sounds associated with deformation or movement of the tubing may be associated with a second set of matching criteria. A determination that a particular sound was generated by a crack in wellbore tubing may require both sets of criteria to correspond to sounds that are characteristic of a tubing crack.

[0051] Similar determinations may be made to distinguish between sounds made by a violin and sounds made by a piano. Sounds made by the violin and the piano may share some criteria (e.g., the presence of a base frequency and specific harmonics) yet have other sounds that can be used to differentiate a piano sound from a violin sound. For example, the violin sound may include noises associated with a size of resonance chamber in the violin or noises associated with a type of wood that the violin is made of. In contrast, the piano may have a resonance chamber that is larger than the violin's resonance chamber and materials used to make the piano may make sounds that are not characteristic of the violin.

[0052] Magnitudes of noises detected by sensing array 240 may vary based on operating conditions and a distance that separates orifice 270 from sensing elements 260 of sensing array 240. A set of magnitudes of acoustic power of one or more frequencies included in a set of sensed data that are associated with a particular sound source may be referred to as a power spectral density of the sound source. Characteristics of a type of sound source may include different frequencies of acoustic noise that each have their own magnitude or power relative to each other. Different noise sources may emit frequencies of a same frequency. Because of this, filtering techniques of the present disclosure may filter sets of sensed data in ways that remove only remove portions of acoustic energy of a particular frequency.

[0053] FIG. 3 illustrates two different sound sources that emit noises that may be detected by three different acoustic sensors. FIG. 3 includes sound sources 310 and 320 and acoustic sensors 330, 340, and 350. Acoustic sensor 330 is located at a distance D1 from sound source 310 and is located at a distance D2 from sound source 320. Acoustic sensor 340 is located at a distance D3 from sound source 310 and is located at a distance D4 from sound source 320. Acoustic sensor 350 is located a distance D5 from sound source 310 and is located a distance D6 from sound source 320. Depending on specific types of acoustic sensors used, noises detected by acoustic sensors 330, 340 and 350 may be directional to some degree. In other instances, noises detected by acoustic sensors 330, 340, and 350 may be omni-directional. The medium in which given sets of frequencies move may also affect sounds that reach certain sensors. This is because sounds of some frequencies may be more directional than other frequencies. Furthermore, reflections of sounds off different surfaces may make it difficult to identify a specific location from which a specific sound emanated from. Sounds traveling through water or that echo off surfaces may interfere with the ability of a sensing array to distinguish a location from which those sounds emanate.

[0054] Acoustic energy is transmitted through fluids (e.g., air, carbon dioxide, hydrocarbon streams, or water) in a manner that is consistent with the inverse square law and the speed of sound through the fluid. This means that as an acoustic sensor is moved away from a sound source, noise emitted from the sound source will tend to diminish according to the inverse square of the distance between the sound source and the acoustic sensor. Furthermore, noise emitted from a sound source travels at a speed in many directions. This means that noise leaving sound source 310 at a particular moment in time will reach acoustic sensor 330 that is closer to sound source 310 before that noise reaches acoustic sensor 340 that is farther from sound source 310. In other words, noises emitted from sound source 310 will reach acoustic sensor 330 before reaching acoustic sensor 340 because distance D1 is less than distance D3. Furthermore, the magnitudes of the noise emitted from sound source 310 that is received by acoustic sensor 330 will be larger than magnitudes of the noise emitted from sound source 310 and that is received by acoustic sensor 340 because the noise magnitude varies based on distance according to the inverse square law. Noises emitted from sound sources 310 and 320 will be received at different times and different amplitudes by respective acoustic sensors 330, 340, and 350 because distances that separate each respective sound source and each respective acoustic sensor is different.

[0055] This means that locations of particular sound sources relative to locations where specific acoustic sensors are located may be identified in different ways. A location of a sound source may be identified using several different directional acoustic sensors. When several different directional acoustic sensors receive noise from a same sound source, the location where the sound source is located may be identified using triangulation. By knowing relative locations of each respective acoustic sensor and knowing angles at which each respective acoustic sensor is pointed, vectors along those angles may be projected from each respective acoustic sensor to a point where those vectors intersect. Note that in FIG. 3, acoustic sensor 330 is located at a distance D7 from acoustic sensor 340 and that acoustic sensor 340 is located at distance D7 from acoustic sensor 350. As such, by knowing the distance D7 and by knowing vectors that point along lines D1, D3, and D5, the location of sound source 310 can often be identified. Note also that acoustic sensor 330 is located at a distance of two times distance D7 which equals 2D7.

[0056] In an instance when the three acoustic sensors 330, 340, and 350 receive noise from sound sources 310 and 320, the times at which the different sensors receive noise from each respective sound source will be different. Noise emitted by sound source 320 will reach acoustic sensor 350 at a first time T1, reach acoustic sensor 340 at a second time T2, and will then reach acoustic sensor 350 at a third time T3. A beamforming technique may be performed to identify where sound source 320 is located. This may include delaying noise signals received at respective sensors by different amounts of time. When these different amounts of time correspond to respective delay times (i.e., a first set of delay times) of noise from sound source 320 is received by each respective acoustic sensor, a sum of these three different noise signals will reach a peak magnitude. Such a peak magnitude may be referred to as a high energy peak of delayed noise. This first set of delay times will include a first difference in time ΔT1 that equals time T3 minus time T1 and a second difference in time ΔT2 that equals time T3 minus time T2. These time differences and the speed of sound may be used to perform calculations that identify a location of sound source 320. This is because the location of sound source 320 corresponds to distances associated with the respective delay times (time T3 minus time T1; and T3 minus time T2) as well as distances D7 and 2D7 that separate the respective acoustic sensors.

[0057] Noises from sound source 310 when summed using delays from this first set of delay times will not result in a peak magnitude because distances that separate sound source 310 from acoustic sensors 330, 340, and 350 are different from distances that separate sound source 320 from acoustic sensors 330, 340 and 350. This is because distances D2, D4, and D6 between sound source 320 and respective acoustic sensors 330, 340, and 350 are different than distances D1, D3, and D5 between sound source 310 and the respective acoustic sensors 330, 340, and 350. As such, a set of delay times that characterize relative timing of noise received from sound source 310 at acoustic sensors 330, 340, and 350 will be different than delay times included in the first set of delay times. A set of evaluations could be performed to identify delay times that result in a peak sum of sounds associated with sound source 310 and based on this, a location of sound source 310 may be identified.

[0058] As mentioned above, a form of independent component analysis (ICA) may alternatively or additionally, be performed to associate particular sounds with particular sound sources. For example, sounds from two different sound sources may be combined into a dataset that linearly combines sounds from these two sources into a combined matrix of source sound waveforms X, where X=AS. As such the matrix X may include waveforms of sounds recorded by two different hydrophones as functions of time X1(t) and X2(t), A is a matrix that mixes the components of the sources, and S is a matrix that consists of waveforms of the two sources S1(t) and S2(t). In order to obtain the source matrix S, a mathematical function of S=A−1 or S=WS may be performed. Here A−1 and W represent an inverse matrix of A. An estimate of source matrix S or S would then consist of two estimated source waveforms Ŝ1(t) and Ŝ2(t). By assuming that the two sources are independent, a matrix W can be found that minimizes the sum of entropies associated with waveforms Ŝ1(t) and Ŝ2 (t). Calculations that estimate entropy, for example calculations consistent with Shannon's theorem may then be performed to identify these sums of entropies using the entropy equations below.H⁢1⁢(Sˆ⁢1)=-∑i=1nSˆ⁢1⁢(ti)⁢ log2⁢ Sˆ⁢1⁢(ti)H⁢2⁢(Sˆ⁢2)=-∑i=1nSˆ⁢2⁢(ti)⁢ log2⁢ Sˆ⁢2⁢(ti)Sum⁢ of⁢ Entropy⁢ Equations

[0059] Here the equation H1 is used to calculate entropy to associate with a first sound source and the equation H2 is used to calculate entropy to associate with the second sound source as functions of time Ŝ1(ti) and Ŝ2(ti). These sums may be identified over a number of samples n. Once H1 and H2 are identified, they may be added together to calculate a total entropy E, where E=H1+H2. A plurality of different variations of Ŝ1(t) and Ŝ2(t) may be evaluated when generating different estimates of sums of entropies. A computer modeling inversion process may be performed to find a minimum value of matrix W that corresponds to a minimum value of H1+H2. Examples of inversion methods that may be used to identify matrix W are the Larangian Multiplier Method or Newtonian Iteration. By identifying the sum with a lowest (or minimum) value, sounds to associates with the first sound source and the second sound source may be discriminated from each other to a greater degree of probability as each of these waveforms will correspond to a greater degree of organization or negative entropy because a lowest sum of entropy will correspond to greater organization.

[0060] The locations of many different noise sources that surround a sensing array may be identified and maps may be generated that show where each of these different noise sources are located. Such mappings may be referred to as beamforming maps or sound source location maps. In certain instances, such mappings may be incorporated into visualizations that show respective locations of each different respective noise source in two dimensions or in three dimensions. Such mappings may be useful in identify conditions of the wellbore. For example, a first set of noises may be characteristic of fluids moving through an Earth formation and a second set of noises may be characteristic of defects in a set of wellbore tubing, a wellbore casing, or some other wellbore defect.

[0061] A second way that could be used to identify a location of a sound source, at least in part, is by comparing magnitudes of noise energy that is received by several different acoustic sensors. For example, in an instance when two different acoustic sensors are located at a same distance from a sound source and a third acoustic sensor is located at some other distance from the sound source, magnitudes of noise received by the first two acoustic sensors may be expected to be the same and a magnitude of noise received by the third acoustic sensor will have some other value. This information should be enough to identify a set of potential locations where the sound source can be located, when plotted on a graph, this set of point would include all points equal distant from each of the first two acoustic sensors while being more distant from the third acoustic sensor. This information is enough to identify locations where the sound source is located based on the inverse square law. While FIG. 3 shows two sound sources, methods the present disclosure may perform similar evaluations on more than two sound sources. While FIG. 3 shows three acoustic sensors, some degree of triangulation could be performed using as few as two acoustic sensors. The more acoustic sensors included in a sensor array may tend to increase the accuracy of determinations made as compared to sensor arrays that used fewer acoustic sensors. In other words, evaluations performed on data collected from N+1 sensors will yield higher resolution location accuracy as compared to evaluations performed on data collected using N sensors.

[0062] In instances when an acoustic array includes more than three acoustic sensors, these additional sensors may be located at different distances and relative magnitudes of noise energy received may be used to identify a location of the sound source by solving a set of equations. In such instances, known distances between respective acoustic sensors and measured differences in sensed acoustic energy from each of those respective acoustic sensors may be used to identify the location of the sound source.

[0063] A third way that a location of the sound source could be identified is by identifying differences in time when specific noise signals are received at specific acoustic sensors. These differences in time may be used to identify a set of possible locations where the acoustic sensor is located. Here again the more sensors used may help identify the location of the sound source based on the speed that noise travels from the sound source to the respective acoustic sensors.

[0064] FIG. 4 illustrates a series of actions that may be performed when fluid flows in subterranean strata or wellbore defects are characterized. At block 410 data may be extracted from light signals received via a fiber optic cable deployed in a wellbore. This fiber optic cable may be part of a distributed acoustic sensing (DAS) system, a distributed strain sensing system (DSS) system, a distributed temperature sensing (DTS) system, or a system that senses a combination of acoustic sensing, strain sensing, and temperature sensing along the length of the fiber optic cable. As mentioned above, techniques to measure sound, cable strain, and / or temperature along the fiber optic cable may use various techniques (e.g., Rayleigh measurement Raman comparison or other techniques).

[0065] Once the data is extracted at block 410, an evaluation may be performed at determination block 420 to identify whether a sound of interest has been identified by the sensing system (e.g., a DAS system). When the sound of interest has not been identified, program flow may move back to block 410 where additional data is received from the fiber optic cable. When a sound of interest has been identified at block 420, program flow may move to block 430 where a wellbore location to associate with that sound of interest is identified. The identification that the sound of interest exists that was made at block 420 and the wellbore location identified at block 430 may have been performed based on an analysis of the data received at block 410.

[0066] At block 440, a set of acoustic sensors may be deployed in the wellbore such that additional data regarding the sound of interest may be collected. This set of sensors may be in the form of a hydrophone array like the array discussed in respect to FIG. 2. Since such hydrophone arrays may include many sensors, one or more of which may be directional sensors, data collected from the set of acoustic sensors may be richer (higher resolution of inches as compared to meters) than data collected from the light signals of the fiber optic cable. As such, at block 450 a span or radial and / or vertical locations to associate with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0067] FIG. 5A illustrates a mapping of data collected based on the operation of a fiber optic cable deployed in a wellbore. Mapping 500 of FIG. 5A includes a vertical axis of depth or length (in meters) and includes a horizontal axis of time (in days, March 1 through March 9). Horizontal line 510 in mapping 500 represents a sound of interest that was detected on March 6 (3-6) and that continued through March 9 (3-9). The sound of interest represented by line 510 was not observed before March 6. Note that the sound of interest is located at about 2500 meters of wellbore depth (or length). The term wellbore depth may refer to a distance or length from a location where the wellbore begins (e.g., a surface location) to a location in the wellbore. For various reasons, a wellbore depth may not actually be a depth below the surface location where the wellbore begins. For example, when a wellbore is drilled vertically downward for 500 meters and then turns horizontally over a distance of 50 meters to and end point, the overall “wellbore depth” may be said to be 550 meters, even though the wellbore goes no “deeper” than 500 meters below the surface where the wellbore begins. Because of this, a given wellbore depth may be measured based on a distance between the surface where the wellbore begins and some location within the wellbore. As such, the location of a place in the wellbore may be specified as a distance from the surface that may be referred to as a “wellbore depth.”

[0068] FIG. 5B illustrates a mapping made from data collected by a set of acoustic sensors. Mapping 550 of FIG. 5B includes a vertical axis of “wellbore depth” and a horizontal axis of radial distance. This radial distance may be a distance from a center point of a set of acoustic sensors, for example. In such an instance and when the set of acoustic sensors is placed in the center of a casing, the radial distance of mapping 550 may be drawn relative to the center of the casing. The vertical dashed lines of FIG. 5B may show where the casing is located in mapping 550. In such an instance, the distance separating the dashed lines may correspond to the thickness of the casing. Here the casing may have an inner diameter of 3.5 inches and a thickness of about 0.5 inches.

[0069] After a sound the sound of interest located at “wellbore depth” of about 2500 meters is observed, the set of acoustic sensors may be deployed in the wellbore at that depth. In such instances, data extracted from light signals received via the fiber optic cable may identify an approximate depth of the sound of interest. Because of this, the set of sensors (e.g., sensors of a hydrophone) may be deployed at the 2500 meter “wellbore depth” and data may be collected using the set of sensors. At this time the set of sensors may be moved uphole or downhole to identify a more precise location of the sound of interest. Note that mapping 550 may depict the sound of interest relative to a zero depth or length as shown by the placement of the “0” point of the vertical axis.

[0070] Mapping 550 includes a vertical and radial mapping associated with sound of interest 560. Here sound of interest 560 may be a sound that is created by fluids leaking from through a defect (e.g., a crack) in the casing. As such, techniques of the present disclosure may be used to identify a general location of a sound of interest based on sounds sensed using data collected from a fiber optic cable after which acoustic sensors or sensors of a hydrophone may be used to identify the location of a defect more accurately. Once a crack or other wellbore defect is identified, a repair of that defect may be initiated.

[0071] FIG. 6 illustrates another series of actions that may be performed when fluid flows in subterranean strata or wellbore defects are characterized. At block 610 data may be extracted from light signals received via a fiber optic cable deployed in a wellbore. At block 620 the location / depth of a sound of interest may be identified based on an analysis of the data received from fiber optic cable at block 620. Since in some instances, sounds of interest may be intermittent, a determination may be made a block 630 that the sound of interest has disappeared. At block 640, an analysis may be performed on data extracted from light signals that traveled along the fiber optic cable. Metrics may then be identified at block 650 based on the analysis performed at block 640. These metrics may identify an approximate location of a wellbore defect or a subterranean fluid flow based on temperature changes identified by the analysis performed at block 640 and 650.

[0072] At block 660, a set of acoustic sensors may be deployed at a depth where a temperature change or temperature gradient has been observed. In some instances, the acoustic sensors may be deployed until the sound of interest reappears. In other instances (e.g., at block 670), one or more changes to the operation of the wellbore may be changed when the set of acoustic sensors is deployed in the vicinity where the temperature changes were observed. Such changes to the wellbore operation may include changing a how a hardware device operates. For example, such a change may be related to changing a valve setting (e.g., opening or closing a valve, such as a wellhead choke valve) or turning a pump on or off. These changes may stimulate the reappearance of the sound of interest, and this may lead to a sensing system identifying that the sound of interest has reappeared at block 680. As such, at block 690 a span or radial and / or vertical locations to associate with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0073] Systems and techniques of the present disclosure may generate temperature logs and acoustic logs based on data sensed by operation of a DAS / DTS system. By combining DAS / DTS and / or arrays of acoustic sensors, techniques of the present disclosure may more accurately map leak events that happened and that then stopped happening. In instances when a sound emitted from a noise source is not continuous, acoustic tools may not be able to characterize source of the noise. Even so, temperatures effects of the noise may still be observable even after the noise is no longer present. Based on the fact that temperature events tend to have memory and based on the fact that it takes time for these temperature events to fade away, temperature gradients detectable by operation of a DTS system may allow for a general location of a leak or the noise source to be identified. Based on this, operations of the wellbore may be changed after an acoustic sensing tool with greater resolution (e.g., a hydrophone sensing array) has been deployed to the general location of the noise source. As mentioned above, one more valves may be opened or closed or pumps may be turned on or off in an effort to stimulate the reemergence of the noise. Operation of a DTS, DAS, or DSS system or combination thereof may be used to identify temperatures of interest, sounds of intertest, or stresses that may be associated with a wellbore defect. Analysis of collected data may identify characteristics of potential defects and as such a temperature of interest, a sound of interest, or a stress of interest may include or may correspond to a span of radial locations, a span of vertical locations, an acoustic amplitude, an acoustic pattern, a temperature, or a change in temperatures (e.g., a temperature gradient).

[0074] FIG. 7 illustrates an example architecture 700 of a computing device which can implement the various technologies and techniques described herein. The various implementations will be apparent to those of ordinary skill in the art when practicing the present technology. Persons of ordinary skill in the art will also readily appreciate that other system implementations or examples are possible. The components of the computing device architecture 700 are shown in electrical communication with each other using a connection 705, such as a bus. The example computing device architecture 700 includes a processing unit (CPU or processor) 710 and a computing device connection 705 that couples various computing device components including the computing device memory 715, such as read only memory (ROM) 720 and random-access memory (RAM) 725, to the processor 710.

[0075] The computing device architecture 700 can include a cache of high-speed memory connected directly with, in close proximity to, or integrated as part of the processor 710. The computing device architecture 700 can copy data from the memory 715 and / or the storage device 730 to the cache 712 for quick access by the processor 710. In this way, the cache can provide a performance boost that avoids processor 710 delays while waiting for data. These and other modules can control or be configured to control the processor 710 to perform various actions. Other computing device memory 715 may be available for use as well. The memory 715 can include multiple different types of memory with different performance characteristics. The processor 710 can include any general-purpose processor / multi-processor and a hardware or software service, such as service 1 732, service 2 734, and service 3 736 stored in storage device 730, configured to control the processor 710 as well as a special-purpose processor where software instructions are incorporated into the processor design. The processor 710 may be a self-contained system, containing multiple cores or processors, a bus, memory controller, cache, etc. A multi-core processor may be symmetric or asymmetric.

[0076] To enable user interaction with the computing device architecture 700, an input device 745 can represent any number of input mechanisms, such as a microphone for speech, a touch-sensitive screen for gesture input, keyboard, mouse, motion input, speech and so forth. An output device 735 can also be one or more of a number of output mechanisms known to those of skill in the art, such as a display, projector, television, speaker device, etc. In some instances, multimodal computing devices can enable a user to provide multiple types of input to communicate with the computing device architecture 700. The communications interface 740 can generally govern and manage the user input and computing device output. There is no restriction on operating on any particular hardware arrangement and therefore the basic features here may easily be substituted for improved hardware or firmware arrangements as they are developed.

[0077] Storage device 730 is a non-volatile memory and can be a hard disk or other types of computer readable media which can store data that are accessible by a computer, such as magnetic cassettes, flash memory cards, solid state memory devices, digital versatile disks, cartridges, random access memories (RAMs) 725, read only memory (ROM) 720, and hybrids thereof. The storage device 730 can include services 732, 734, 736 for controlling the processor 710. Other hardware or software modules are contemplated. The storage device 730 can be connected to the computing device connection 705. In one aspect, a hardware module that performs a particular function can include the software component stored in a computer-readable medium in connection with the necessary hardware components, such as the processor 710, connection 705, output device 735, and so forth, to carry out the function.

[0078] For clarity of explanation, in some instances the present technology may be presented as including individual functional blocks including functional blocks comprising devices, device components, steps or routines in a method embodied in software, or combinations of hardware and software.

[0079] In some instances the computer-readable storage devices, mediums, and memories can include a cable or wireless signal containing a bit stream and the like. However, when mentioned, non-transitory computer-readable storage media expressly exclude media such as energy, carrier signals, electromagnetic waves, and signals per se.

[0080] Methods according to the above-described examples can be implemented using computer-executable instructions that are stored or otherwise available from computer readable media. Such instructions can include, for example, instructions and data which cause or otherwise configure a general-purpose computer, special purpose computer, or a processing device to perform a certain function or group of functions. Portions of computer resources used can be accessible over a network. The computer executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, firmware, source code, etc. Examples of computer-readable media that may be used to store instructions, information used, and / or information created during methods according to described examples include magnetic or optical disks, flash memory, USB devices provided with non-volatile memory, networked storage devices, and so on.

[0081] Devices implementing methods according to these disclosures can include hardware, firmware and / or software, and can take any of a variety of form factors. Typical examples of such form factors include laptops, smart phones, small form factor personal computers, personal digital assistants, rackmount devices, standalone devices, and so on. Functionality described herein also can be embodied in peripherals or add-in cards. Such functionality can also be implemented on a circuit board among different chips or different processes executing in a single device, by way of further example.

[0082] The instructions, media for conveying such instructions, computing resources for executing them, and other structures for supporting such computing resources are example means for providing the functions described in the disclosure.

[0083] In the foregoing description, aspects of the application are described with reference to specific embodiments thereof, but those skilled in the art will recognize that the application is not limited thereto. Thus, while illustrative embodiments of the application have been described in detail herein, it is to be understood that the disclosed concepts may be otherwise variously embodied and employed, and that the appended claims are intended to be construed to include such variations, except as limited by the prior art. Various features and aspects of the above-described subject matter may be used individually or jointly. Further, embodiments can be utilized in any number of environments and applications beyond those described herein without departing from the broader spirit and scope of the specification. The specification and drawings are, accordingly, to be regarded as illustrative rather than restrictive. For the purposes of illustration, methods were described in a particular order. It should be appreciated that in alternate embodiments, the methods may be performed in a different order than that described.

[0084] Where components are described as being “configured to” perform certain operations, such configuration can be accomplished, for example, by designing electronic circuits or other hardware to perform the operation, by programming programmable electronic circuits (e.g., microprocessors, or other suitable electronic circuits) to perform the operation, or any combination thereof.

[0085] The various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the examples disclosed herein may be implemented as electronic hardware, computer software, firmware, or combinations thereof. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0086] The techniques described herein may also be implemented in electronic hardware, computer software, firmware, or any combination thereof. Such techniques may be implemented in any of a variety of devices such as general purposes computers, wireless communication device handsets, or integrated circuit devices having multiple uses including application in wireless communication device handsets and other devices. Any features described as modules or components may be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques may be realized at least in part by a computer-readable data storage medium comprising program code including instructions that, when executed, performs one or more of the method, algorithms, and / or operations described above. The computer-readable data storage medium may form part of a computer program product, which may include packaging materials.

[0087] The computer-readable medium may include memory or data storage media, such as random-access memory (RAM) such as synchronous dynamic random access memory (SDRAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), FLASH memory, magnetic or optical data storage media, and the like. The techniques additionally, or alternatively, may be realized at least in part by a computer-readable communication medium that carries or communicates program code in the form of instructions or data structures and that can be accessed, read, and / or executed by a computer, such as propagated signals or waves.

[0088] Other embodiments of the disclosure may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. Embodiments may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination thereof) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0089] The various embodiments described above are provided by way of illustration only and should not be construed to limit the scope of the disclosure. For example, the principles herein apply equally to optimization as well as general improvements. Various modifications and changes may be made to the principles described herein without following the example embodiments and applications illustrated and described herein, and without departing from the spirit and scope of the disclosure. Claim language reciting “at least one of” a set indicates that one member of the set or multiple members of the set satisfy the claim.Aspects of the Disclosure:

[0090] Aspect 1: A method comprising: receiving data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed acoustic sensing (DAS) system; identifying a sound of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable; deploying a set of acoustic sensors at the wellbore depth; sensing acoustic data by the set of acoustic sensors at the wellbore depth; and identifying characteristics associated with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0091] Aspect 2: The method of Aspect 1, wherein the deployment of the set acoustic sensors at the wellbore depth includes moving the set of acoustic sensors over a range of wellbore depths that include the wellbore depth.

[0092] Aspect 3: The method of Aspect 1 or 2, further comprising: collecting additional data from the fiber optic cable based on operation of the (DAS) being continued when the set of acoustic data sense the acoustic data.

[0093] Aspect 4: The method of any of Aspects 1 through 3, further comprising: identifying that the sound of interest has stopped; initiating one or more changes to operation of the wellbore to stimulate the sound of interest; and identifying that the sound of interest has been stimulated by the one or more changes to the operation of the wellbore.

[0094] Aspect 5: The method of any of Aspects 1 through 4, wherein the characteristics associated with the sound of interest include one or more of a span of radial locations a span of vertical locations, an acoustic amplitude, and an acoustic pattern to associate with the sound of interest and wherein the evaluation associated with the sound of interest includes analyzing data sensed by each sensor of the set of sensors based on one or more of distances that separate each respective sensor of the set of sensors, relative radial positions of each of the respective sensors of the set of sensors, and arrival times of the sound of interest at each of the respective sensors of the set of sensors.

[0095] Aspect 6: A non-transitory computer-readable storage medium having embodied thereon instructions that when executed by one or more processors cause the one or more processors to: receive data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed acoustic sensing (DAS) system; identify a sound of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable; control deployment of a set of acoustic sensors at the wellbore depth; receive acoustic data sensed by the set of acoustic sensors at the wellbore depth; and identify characteristics associated with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0096] Aspect 7: The non-transitory computer-readable storage medium of Aspect 6, wherein the deployment of the set acoustic sensors at the wellbore depth includes moving the set of acoustic sensors over a range of wellbore depths that include the wellbore depth.

[0097] Aspect 8: The non-transitory computer-readable storage medium of Aspect 6 or 7, wherein the one or more processors execute the instructions to: collect additional data from the fiber optic cable based on operation of the (DAS) system being continued when the set of acoustic data sense the acoustic data.

[0098] Aspect 9: The non-transitory computer-readable storage medium of any of Aspects 6 through 8, wherein the one or more processors execute the instructions to: identify that the sound of interest has stopped; initiate one or more changes to operation of the wellbore to stimulate the sound of interest; and identify that the sound of interest has been stimulated by the one or more changes to the operation of the wellbore.

[0099] Aspect 10: The non-transitory computer-readable storage medium of any of Aspects 6 through 9, wherein the one or more processors execute the instructions to: identify a temperature at the wellbore depth based on additional data collected from the fiber optic cable.

[0100] Aspect 11: The non-transitory computer-readable storage medium of any of Aspects 6 through 10, wherein the characteristics associated with the sound of interest include one or more of a span of radial locations, a span of vertical locations, an acoustic amplitude, and an acoustic pattern to associate with the sound of interest, and wherein the evaluation associated with the sound of interest includes analyzing data sensed by each sensor of the set of sensors based on one or more of: distances that separate each respective sensor of the set of sensors, relative radial positions of each of the respective sensors of the set of sensors, and arrival times of the sound of interest at each of the respective sensors of the set of sensors.

[0101] Aspect 12. A system comprising: a fiber optic cable deployed at a wellbore when the fiber optic cable is part of a distributed acoustic sensing (DAS) system; a set of acoustic sensors; a memory; and one or more processors that execute instructions out of the memory to: identify a sound of interest at a wellbore depth based on an analysis of data received from the fiber optic cable, control deployment of the set of acoustic sensors to the wellbore depth, receive acoustic data sensed by the set of acoustic sensors at the wellbore depth; and identify characteristics associated with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0102] Aspect 13: The system of Aspect 12, wherein the deployment of the set acoustic sensors at the wellbore depth includes moving the set of acoustic sensors over a range of wellbore depths that include the wellbore depth.

[0103] Aspect 14: The system of Aspect 12 or 13, wherein the one or more processors execute the instructions to: collect additional data from the fiber optic cable based on operation of the (DAS) system being continued when the set of acoustic data sense the acoustic data.

[0104] Aspect 15: The system of any of Aspects 12 through 14, wherein the one or more processors execute the instructions to: identify that the sound of interest has stopped; initiate one or more changes to operation of the wellbore to stimulate the sound of interest; and identify that the sound of interest has been stimulated by the one or more changes to the operation of the wellbore.

[0105] Aspect 16: A method comprising: receiving data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed temperature sensing (DTS) system; identifying a temperature of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable; deploying a set of acoustic sensors at the wellbore depth based on the temperature of interest being identified at the wellbore depth; sensing acoustic data by the set of acoustic sensors at the wellbore depth; and identifying characteristics associated with the sensed acoustic data based on an evaluation of the data collected by the set of acoustic sensors.

[0106] Aspect 17: The method of Aspect 16, further comprising: identifying one or more additional temperatures within a threshold distance from the wellbore depth; and performing an analysis that identifies a temperature gradient associated with the temperature.

[0107] Aspect 18: The method of Aspect 16 or 17, further comprising: identifying a range of wellbore depths to sense the acoustic data by the set of acoustic sensors based on the temperature gradient.

[0108] Aspect 19: A non-transitory computer-readable storage medium having embodied thereon instructions that when executed by one or more processors cause the one or more processors to: receive data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed temperature sensing (DTS) system; identify a temperature of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable; deploy a set of acoustic sensors at the wellbore depth based on the temperature being identified at the wellbore depth; sense acoustic data by the set of acoustic sensors at the wellbore depth; and identify characteristics associated with the sensed acoustic data based on an evaluation of the data collected by the set of acoustic sensors.

[0109] Aspect 20: A system comprising: a fiber optic cable deployed at a wellbore when the fiber optic cable is part of a distributed acoustic temperature sensing (DAS) system; a set of acoustic sensors; a memory; and one or more processors that execute instructions out of the memory to: receive data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed temperature sensing (DTS) system, identify a temperature of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable, deploy a set of acoustic sensors at the wellbore depth based on the temperature of interest being identified at the wellbore depth, sense acoustic data by the set of acoustic sensors at the wellbore depth, and identify characteristics associated with the sensed acoustic data based on an evaluation of the data collected by the set of acoustic sensors.

Examples

Embodiment Construction

[0013]As discussed in greater detail herein, the present disclosure provides systems, methods, and computer-readable media for identifying locations of a wellbore where sensors of a particular type may be deployed to identify the size or scope of wellbore defects more accurately and that may allow for more accurate determinations be made as to flow rates of fluids in a subterranean environment. Apparatus and methods of the present disclosure may be referred to as systems and techniques that address challenges of monitoring downhole flows in real-time or that may be used to perform high-quality flow evaluation and high-precision leak localization.

[0014]Systems and techniques of the present disclosure may first use a fiber optic cable as a distributed acoustic sensor or as a sensor that senses temperatures along the fiber optic cable that is deployed in a wellbore. These systems and techniques may also control the deployment of an acoustic sensing tool in the wellbore that has greater...

TECHNICAL FIELD

[0001] The present disclosure is directed to making evaluations using data sensed by sensors deployed in a wellbore. More specifically, the present disclosure is directed to making determinations based on data sensed by different types of sensors.BACKGROUND

[0002] Acoustic or sonic logging tools are often employed in wellbore environments for a variety of purposes. In some instances, acoustic sensors may be deployed in a wellbore when evaluations regarding well integrity and flow profiles of the wellbore are performed. Noises associated with leaking fluids in a wellbore environment may be indicative of a defect in the wellbore that could render the wellbore unsuitable for a given task. Other noises may be associated with fluids flowing through subterranean strata.BRIEF DESCRIPTION OF THE DRAWINGS

[0003] In order to describe the manner in which the above-recited and other advantages and features of the disclosure can be obtained, a more particular description of the principles briefly described above will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. Understanding that these drawings depict only exemplary embodiments of the disclosure and are not therefore to be considered to be limiting of its scope, the principles herein are described and explained with additional specificity and detail through the use of the accompanying drawings in which:

[0004] FIG. 1A illustrates an example schematic diagram of a system for performing distributed measurements along a wellbore using distributed strain sensing with a fiber optic cable when the cable may be permanently installed in a wellbore.

[0005] FIG. 1B is a schematic diagram of an example of wireline, slickline, coil, tubing, or other in a downhole environment having tubulars, in accordance with various aspects of the subject technology.

[0006] FIG. 2 illustrates a schematic diagram of assemblies that may be used in a wellbore for collecting acoustic data from inside the wellbore, in accordance with various aspects of the subject technology.

[0007] FIG. 3 illustrates two different sound sources that emit noises that may be detected by three different acoustic sensors, in accordance with various aspects of the subject technology.

[0008] FIG. 4 illustrates a series of actions that may be performed when fluid flows in subterranean strata or wellbore defects are characterized, in accordance with various aspects of the subject technology.

[0009] FIG. 5A illustrates a mapping of data collected based on operation of a fiber optic cable deployed in a wellbore, in accordance with various aspects of the subject technology.

[0010] FIG. 5B illustrates a mapping made from data collected by a set of acoustic sensors, in accordance with various aspects of the subject technology.

[0011] FIG. 6 illustrates another series of actions that may be performed when fluid flows in subterranean strata or wellbore defects are characterized, in accordance with various aspects of the subject technology.

[0012] FIG. 7 illustrates an example architecture of a computing device which can implement the various technologies and techniques described herein.DETAILED DESCRIPTION

[0013] As discussed in greater detail herein, the present disclosure provides systems, methods, and computer-readable media for identifying locations of a wellbore where sensors of a particular type may be deployed to identify the size or scope of wellbore defects more accurately and that may allow for more accurate determinations be made as to flow rates of fluids in a subterranean environment. Apparatus and methods of the present disclosure may be referred to as systems and techniques that address challenges of monitoring downhole flows in real-time or that may be used to perform high-quality flow evaluation and high-precision leak localization.

[0014] Systems and techniques of the present disclosure may first use a fiber optic cable as a distributed acoustic sensor or as a sensor that senses temperatures along the fiber optic cable that is deployed in a wellbore. These systems and techniques may also control the deployment of an acoustic sensing tool in the wellbore that has greater resolution than the fiber optic cable. Data collected via the fiber optic cable may be used to identify locations where the acoustic sensing tool should be deployed such that noise sources can be accurately characterized based on data collected by the acoustic sensing tool. As such, the fiber optic cable may be used to identify a general location of a sound of interest after which the acoustic sensing tool may be used to collect data such that wellbore defects or subterranean flows may be more accurately characterized.

[0015] The fiber optic cable mentioned above may be part of a distributed acoustic sensing (DAS) system that may be used to continuously monitor abnormal acoustic signals along a wellbore. In an instance when a leak occurs at a set of tubing or in a wellbore casing, acoustic signals generated by the flows associated with the leak may be detected in real-time. An acoustic noise logging tool may then be deployed in the wellbore to target depth intervals. Data sensed by the noise logging tool may be recorded and analyzed such that determinations regarding the size (e.g., orifice size and / or volume) an actual location of fluid movement may be identified more accurately than possible by analyzing data received from the fiber optic cable alone. Furthermore, by combining DAS and acoustic noise logging, real-time flows may be identified quickly, reliably, and more accurately than before.

[0016] While acoustic noise logging may be used for wellbore leak detection and localization and downhole flow evaluation (e.g., channel flows, fracture flows, and formation flows), fiber optics combined with controlled deployment of a hydrophone array is one unique aspect of the present disclosure. Techniques of the present disclosure may use beamforming technology to identify leaks can be accurately localized both radially and vertically. Furthermore, the flowrate of leakage can be estimated from an acoustic data recorded by an acoustic noise logging tool. In certain instances, the phase of the leakage flow can be classified according to the spectra of the recorded signals. The success of acoustic noise logging tools may be limited because noise events are not always continuous. This means that noise events may be transitory and could occur when the tool is not close to a noise source.

[0017] Another limitation to using acoustic noise logging tools in isolation relates to the fact that collecting such acoustic data can be time consuming. This means that deploying acoustic sensor arrays like a hydrophone for a time does not guarantee that a leak will be detected. In worst case scenarios, not timely detecting a leak could end in catastrophic blowouts in the downhole environment. When a fiber optic cable is used as part of a DAS system, acoustic signals / sounds may be identified along the entire wellbore where the fiber optic cable is deployed. Since a fiber optic cable may be used to collect data continuously in real-time along the wellbore, downhole flows can be monitored and leaks can be detected upon occurrence. Since, however, the resolution of DAS is typically in the order of feet, DAS may not be able to accurately detect the precise location and size of a wellbore defect.

[0018] The vertical resolution of the acoustic modern noise logging tools (e.g., sensors of a hydrophone) are in inches. Furthermore, acoustic noise logging can provide frequency / spectra analysis, radial localization of noise sources and flow evaluation. This means that while a DAS system is used to provide general information regarding sounds of interest. The use of a sensor array (e.g., sensors of a hydrophone array) may be used to profile wellbore defects and subterranean flows in a manner not possible with a DAS system.

[0019] By incorporating the technologies together (DAS and acoustic noise logging) techniques of the present disclosure, techniques of the present disclosure can generate a base log with DAS after which an interval for collecting data with an acoustic noise logging tool may be identified based on the data collected by the DAS system at selected depths. By running the stationary noise logging with only a few chosen intervals, amounts of time required to collect data with sufficient resolution can be achieved more efficiently. The same may be true for characterizing of fluid flows through subterranean strata.

[0020] Generally, a work flow of the present disclosure may include a series of actions that include: *Deploying a fiber optic cable of a distributed acoustic sensing (DAS) system downhole: *Logging strain changes along the wellbore based on data collected via the fiber optic cable: *Monitoring downhole flows based on strain changes associated with subterranean noise sources and / or temperature changes: *Deploying an acoustic logging tool downhole in the vicinity of a sound of interest; and *Evaluating data collected by the DAS system and the acoustic noise logging tool to identify, locate, and characterize downhole flows that may be associated wellbore defects and / or flows of fluids through subterranean strata.

[0021] FIG. 1A illustrates an example schematic diagram of a system for performing distributed measurements along a wellbore using distributed strain sensing with a fiber optic cable when the cable may be permanently installed in a wellbore. The system 100 can include a wellbore 102 with a casing string 104 extending from the surface 106 through the wellbore 102. A blowout preventer 107 (“BOP”) can be positioned above a wellhead 109 at the surface 106. The wellbore 102 extends through various earth strata and may have a substantially vertical section 108. In some aspects, the wellbore 102 can also include a substantially horizontal section. The casing string 104 can include multiple casing tubes 110 coupled together end-to-end by casing collars 112. In some aspects, the casing tubes 110 are approximately thirty feet in length. The substantially vertical section 108 may extend / through a rock or hydrocarbon bearing subterranean formation 114.

[0022] A tool can be positioned downhole as part of casing string 104. The tool can be coupled to a locator device, such as magnetic pickup coil 118, which can generate a voltage in response to a change in a surrounding magnetic field. In one example, the locator device can be a magnetic pickup coil 118. In other examples, a piezoelectric sensor or other suitable locator device can be used by the system 100. The magnetic pickup coil 118 can include a permanent magnet with a coil wrapped around it. The casing tubes 110 can each emit a magnetic field. Each casing collar 112 can emit a magnetic field that is different from the magnetic field emitted by the casing tubes 110, which can be joined by the casing collar 112. The change in the magnetic field between the casing collars 112 and the casing tubes 110 can be detected by the magnetic pickup coil 118 of the system 100. The magnetic pickup coil 118 of the system 100 can generate a voltage in response to the change in the surrounding magnetic field when the magnetic pickup coil 118 passes a casing collar 112. The voltage generated by the magnetic pickup coil 118 can be in proportion to the velocity of the magnetic pickup coil 118 as the magnetic pickup coil 118 travels past the casing collar 112. In some aspects, the magnetic pickup coil 118 of the system 100 can travel between approximately 10 feet per second and approximately 30 feet per second.

[0023] The magnetic pickup coil 118 of the system 100 can be coupled to a light source, for example a light emitting diode (LED) 120. The voltage generated by the magnetic pickup coil 118 can momentarily energize the LED 120, which can be coupled to the magnetic pickup coil 118. The LED 120 can emit a pulse of light (e.g., an optical signal) in response to the voltage generated by the pickup coil 118. The LED 120 of the system 100 can transmit the pulse of light to a receiver 124 positioned at the surface 106. In some aspects, the LED 120 can operate at a 1300 nm wavelength and can minimize Rayleigh transmission losses and hydrogen-induced and coil bend-induced optical power losses. In some aspects, a high speed laser diode or other optical sources can be used in place of the LED 120 and various other optical wavelengths can be used. For example, wavelengths from about 850 nm to 2100 nm can make use of the optical low-transmission wavelength bands in ordinary fused silica multimode and single mode fibers.

[0024] In another example, the system 100 may include a light source that may be a laser 113 positioned at the surface 106 proximate to the BOP 107. The laser 113 can be coupled to the fiber optic cable 122, which can be dispensed at an end by the upper reel 132. The upper reel 132 can be positioned at the surface 106 proximate to the BOP 107. In some aspects, the laser 113 and the upper reel 132 can be positioned elsewhere at the surface 106 or within the wellbore 102.

[0025] The laser 113 of the system 100 can be a high repetition pulse laser or other suitable light source. The laser 113 of the system 100 can also generate an optical signal, for example, a series of light pulses that are transmitted by the fiber optic cable 122. The tool of the system 100 can be coupled to the reel 138 and the magnetic pickup coil 118. In some aspects, a piezoelectric sensor or another suitable modulation device can be used to modulate the optical signal of the laser 113. In some aspects, the modulation device can modulate, for example but not limited to, the frequency, amplitude, phase, or other suitable characteristic of the optical signal. The optical signal generated by the laser 113 can travel the length of the fiber optic cable 122 and reach a lower end of the fiber optic cable 122 proximate to the lower reel 138.

[0026] The receiver 124 of the system 100 can be communicatively coupled to a computing device 128 located away from the wellbore 102 by a communication link 130. The communication link 130 may be a wireless communication link. The communication link 130 can include wireless interfaces such as IEEE 802.11, Bluetooth, or radio interfaces for accessing cellular telephone networks (e.g., transceiver / antenna for accessing a CDMA, GSM, UMTS, or other mobile communications network). In some aspects the communication link 130 may be wired. A wired communication link can include interfaces such as Ethernet, USB, IEEE 1394, or a fiber optic interface. The receiver 124 of the system 100 can transmit information related to the optical signal, for example but not limited to the light pulse count, the time the light pulse arrived, or other information, to the computing device 128. In some aspects, the receiver 124 of the system 100 can be coupled to a transmitter that communicates with the computing device 128.

[0027] Strain value based on the distributed measurement pressure data from the communication link 130 may be received by a computing device 128 via a network interface with a compatible communication link 130. In some aspects, the computing device 128 of the system 100 may use the interface to communicate with one or more networks, such as local area network (LAN) and / or wide area network (WAN), such as the Internet. The computing device 128 of the system 100 may also include a processor for processing the received the distributed measurement pressure data. The processor may be embodied, without limitation, as a microprocessor, application-specific integrated circuit (ASIC), digital signal processor (DSP), field-programmable gate array (FPGA) or the like. The processor may execute instructions stored in a storage device to perform aspects of the methods described herein. The storage device may also be used to store one or more logs, which may be embodied as any suitable data structure(s) for representing received and / or processed data. In one aspect, the computing device 128 may further include a user interface, such as a graphics card, for displaying graphics and / or text on a display device, such as a computer monitor. The user interface may display pressure and temperature based on the determined strain value.

[0028] The fiber optic cable 122 of the system 100 that transmits the light pulse to / from the LED 120 to the receiver 124 can be an unarmored fiber. The unarmored fiber can include a fiber core and cladding and a thin primary buffer coating but no outer jacket or secondary tight buffer to minimize fiber diameter for increased fiber length capacity of a given payout bobbin or reel. In some aspects, the fiber optic cable 122 of the system 100 can be an armored fiber. The armored fiber can include a fiber core, a cladding, a thin primary buffer coating an outer jacket or secondary tight buffer. The inclusion of the outer jacket or secondary tight buffer can increase the diameter of the fiber optic cable 122. The fiber optic cable 122 can be a multi-mode or single-mode optical fiber. The fiber optic cable 122 can include one or more optical fibers. The fiber optic cable 122 can be a sacrificial cable that is not retrieved from the wellbore 102 but instead remains in the wellbore 102 until it is destroyed. For example, the fiber optic cable 122 can be destroyed during stimulation of the wellbore 102.

[0029] The fiber optic cable 122 of the system 100 can also be dispensed from an upper bobbin or reel 132 positioned within the wellbore 102 proximate to the surface. In some aspects, the upper reel 132 can be positioned at the surface 106, for example the upper reel 132 can be positioned proximate to the blowout preventer 107. The upper reel 132 can be secured within the wellbore 102 by a securing device, for example by spring loaded camming feet 136 or other suitable securing mechanisms. The upper reel 132 of the system 100 can have a near-zero tension payout force that can allow dispensing of the fiber optic cable 122 when there is a tension in the fiber optic cable 122.

[0030] The fiber optic cable 122 of the system 100 can further be tensioned by and pulled along with the displacement fluid that is injected into the casing string 104 to move the tool. The upper reel 132 of the system 100 can dispense additional lengths of the fiber optic cable 122 as the fiber optic cable 122 is tensioned by the displacement fluid injected into the wellbore 102. In some aspects, the fiber optic cable 122 of the system 100 can spool off the upper reel 132 at the same rate as the flow of the displacement fluid. The upper reel 132 can prevent the fiber optic cable 122 from breaking or otherwise becoming damaged as the fiber optic cable 122 travels downhole.

[0031] The fiber optic cable 122 of the system 100 can also be spooled on and dispensed from a lower bobbin or reel 138 positioned proximate to the magnetic pickup coil 118. The lower reel 138 can include a drag device 139. The drag device 139 can allow the lower reel 138 to dispense the fiber optic cable 122 only when a pre-set tension in the fiber optic cable 122 is reached. The lower reel 138 payout can prevent the fiber optic cable 122 from breaking or otherwise becoming damaged as the fiber optic cable 122 and the cement plug 116 travel downhole. The upper reel 132 and the lower reel 138 can store greater lengths of unarmored fiber optic cable than armored fiber optic cable. While FIG. 3 depicts the lower reel 138 positioned below the LED 120 and the magnetic pickup coil 118, in some aspects, the lower reel 138 can be positioned elsewhere with respect to the LED 120 and the magnetic pickup coil 118 of the system 100.

[0032] Referring to FIG. 1A, the system 100 may further include permanently installed sensors. The sensors may include fiber optic cables 122 that may be cemented in place in the annular space between the casing string 104 and formation 114, or fiber optic cables 122 may be positioned within casing string 104 as shown in FIG. 1A. Fiber optic cables 122 can also include fiber optic lines, fiber optic tubes, waveguides, optical waveguides, or any other fiber suitable for the intended purpose and understood by a person of ordinary skill in the art. Other types of permanent sensors may include surface and down-hole pressure sensors, where the pressure sensors may be capable of collecting data at rates up to 2,000 Hz or even higher.

[0033] The fiber optic cable 122 of the system 100 may house one or several optical fibers and the optical fibers may be single mode fibers, multi-mode fibers or a combination of single mode and multi-mode optical fibers. The system connected to the optical fibers may include Distributed Temperature Sensing (DTS) systems, Distributed Acoustic Sensing (DAS) Systems, Distributed Strain Sensing (DSS) Systems, quasi-distributed sensing systems where multiple single point sensors are distributed along an optical fiber / cable, or single point sensing systems where the sensors are located at the end of the cable. For each of the optical fibers 122, Raman scattering and coherent Rayleigh measurement(s) may be performed on the ground surface, and a comparison of Raman signal intensities to derive temperature and Rayleigh or enhanced backscatter based interferometric phase shift for acoustic signal may be performed. From these measurements of Raman comparison and Rayleigh-based interferometric phase shift, distributions of pressure, temperature, and strain along the fiber optic cable 122 can be determined simultaneously. Operation of a DTS, DAS, or DSS system or combination thereof may be used to identify temperatures of interest, sounds of intertest, or stresses of interest that may be associated with a wellbore defect.

[0034] The system 100 may operate using various sensing principles. One example includes a DTS system based on inelastic Raman scattering with comparison of Stokes and Antistokes signal intensities to derive localized fiber temperature. Another example includes an optical phase change sensing-based system, such as a DAS system, which is based on interferometric sensing principles using a highly coherent laser and homodyne or heterodyne detection techniques, where the system may sense optical signal phase and / or intensity changes due to constructive or destructive interference along said fibers, due to changes in optical path length from temperature or strain perturbations. Another example includes a strain sensing system, such as a DSS using integrated dynamic strain measurements based on interferometric sensors or static strain sensing measurements using Brillouin scattering. Brillouin-based DSS systems sense both strain and temperature via inelastic scattering, where an acoustic phonon vibration is generated near 11 GHz in silica optical fiber and can be demodulated to measure phonon frequency shift, which is a function of strain and / or temperature. Another example includes quasi-distributed sensors based on Fiber Bragg Gratings (FBGs) where a wavelength shift is detected or multiple FBGs or multiple fibers are used to form Fabry-Perot, Mach-Zehnder, Michelson, or Sagnac type interferometric sensors for phase based sensing, or single point fiber optic sensors based on Fabry-Perot or FBG or intensity-based sensors.

[0035] FIG. 1B is a schematic diagram of an example of wireline, slickline, coil, tubing, or other in a downhole environment having tubulars. In this example, an example system 140 is depicted for conducting downhole measurements after at least a portion of a wellbore has been drilled and the drill string removed from the well. An imager tool (not shown) can be operated in the example system 140 shown in FIG. 1B to log the wellbore. A downhole tool is shown having a tool body 146 in order to carry out logging and / or other operations. For example, instead of or in addition to using the casing string 104 of FIG. 1A to lower the downhole tool, which can contain sensors and / or other instrumentation for detecting and logging nearby characteristics and conditions of the wellbore 116 and surrounding formations, a wireline conveyance 144 can be used. The tool body 146 can be lowered into the wellbore 116 by wireline conveyance 144. The wireline conveyance 144 can be anchored in drill rig 142 or by a portable means such as a truck 145. The wireline conveyance 144 can include one or more wires, slicklines, cables, and / or the like, as well as tubular conveyances such as coiled tubing, joint tubing, or other tubulars. The downhole tool can include an applicable tool for collecting measurements in a drilling scenario, such as the imager tools described herein.

[0036] The illustrated wireline conveyance 144 provides power and support for the tool, as well as enabling communication between data processors 148A, 148B, through 148N (148A-N) on the surface. In some examples, wireline conveyance 144 can include electrical and / or fiber optic cabling for carrying out communications. The wireline conveyance 144 is sufficiently strong and flexible to tether the tool body 146 through the wellbore 116, while also permitting communication through the wireline conveyance 144 to one or more of the processors 148A-N, which can include local and / or remote processors. The processors 148A-N can be integrated as part of an applicable computing system, such as the computing device architectures described herein. Moreover, power can be supplied via wireline conveyance 144 to meet power requirements of the tool. For slickline or coiled tubing configurations, power can be supplied downhole with a battery or via a downhole generator.

[0037] The scope of the present disclosure is not limited to the environment shown in FIGS. 1A and 1B as methods of the present disclosure may be applied in other environments. Methods and apparatus of the present disclosure may process acoustic data that was received from one or more microphones, hydrophones, piezoelectric sensors, or other equipment that may be capable of sensing acoustic signals, such as sub-sonic, sonic, or ultrasonic signals. This processing may include performing evaluations that allow portions of received acoustic data to be identified based on characteristics known to be representative of specific types of sound sources. Characteristics that may be associated with a sound source include yet are not limited to one or more frequencies emitted by the sound source and / or information that can be used to identify a location of the sound source. Additionally, or alternatively, acoustic noise characteristic of a sound source may be associated with a sound amplitude, a power, or a power spectral density of the noise emitted by the sound source.

[0038] Techniques used to evaluate noises in an environment may include a technique referred to as beamforming where signals from different receiving elements of a sensing array (e.g., an array of different hydrophones) may be delayed by different times. This may result in signals being combined constructively to generate a resultant signal that is of greater magnitude than any signal received by a particular sensing element. This may include multiplying signals received from different sensing elements with different gains or weighting factors. In certain instances, the addition of these signals may be performed in the frequency domain. Alternatively or additionally, techniques of the present disclosure may perform a form of signal analysis referred to as independent component analysis (ICA), where matrix math operations are performed to associate particular sounds with specific sound sources.

[0039] Other types of separation techniques may be used to evaluate signals from different types of sources include extracting sound from a single object in an environment that includes multiple objects emitting sounds that are superimposed over each other. This may include separating sounds that have multivariate data from other sounds using statistical methods or statistical characteristics. For example, samples of a person's voice may be collected and analyzed to identify characteristics of tone, dynamic range, and / or intonation. Once identified, these samples may be compared with sound information received from a sensor array and characteristics that match the characteristics of the person's voice may be interpreted as coming from that person. This may include comparing sets of voice data from the person with newly acquired data and performing a statistical analysis. Sounds that match characteristics in the set of voice data to at least a threshold level by the statistical analysis may be attributed as being spoken by the person. Sounds that do not match the characteristics in the set of voice data may be filtered out.

[0040] Specific types of sound sources may produce sounds that can be collected and analyzed to identify a type of sound source from which a particular sound was emitted. For example, a crack, hole, or other orifice in tubing of wellbore that is producing oil may emit an acoustic noise that could be classified as a whistle sound that has spectral characteristics that include a base frequency, one or more harmonic frequencies, and potentially other frequencies. In such an instance, the base frequency may be a frequency of 110 Hertz (Hz) and the one or more harmonic frequencies may be integer multiples of the base 110 Hz frequency (e.g., 220 Hz or 330 Hz). Other frequencies emitted by this wellbore crack or orifice may be a function of factors such a thickness of the tubing, a space between the tubing and other parts of the wellbore, a hydrocarbon flow rate, densities of hydrocarbons or other substances moving through the wellbore, or other factors. These other factors may also be a combination of a base frequency that is offset based on factors such as the tubing thickness, the space between the tubing and other parts of the wellbore, the hydrocarbon flow rate, material density, or other factors.

[0041] In an instance, when a sensor or sensor array senses sounds from two different sound sources, for example, a first sound source that has characteristics consistent with a whistle and second sound source that has characteristics consistent with a vibrating string, the two different sounds may be distinguished from each other even though they may have frequency components that overlap. For example, this can include a comparison of the sound of a flute to the sound of a violin. Here the flute sound would have frequency components that correspond to a volume circumscribed by the flute, keys of the flute that are depressed, and materials from which the flute is made. This may be the case when all of these factors affect the current resonance frequency of the flute. Similarly, the violin sound is a function of string length, string thickness, string tightness, materials that the violin is made of, and other applicable factors. In the context of a wellbore, a flute or whistle sound may be characteristic of a crack in wellbore tubing and the violin or string sound may be characteristic of materials moving between a wellbore casing and wellbore tubing. Other noises may be associated with production materials that move past equipment deployed in the wellbore. For example, a string or cable used to deploy wellbore equipment may make noise.

[0042] FIG. 2 illustrates a schematic diagram of assemblies that may be used in a wellbore for collecting acoustic data from inside the wellbore. FIG. 2 includes casing 220 that may be cemented in place into wellbore 210. Wellbore 210 may have been drilled using drilling equipment known in the art and casing 220 may have been fabricated by screwing tubular sections of pipe together after which cement may have been applied between an outer surface of casing 220 and an inner surface of wellbore 210. Tubing 230 may have been inserted into casing 220 after completion of a wellbore cementing process. Because of this, casing 220 may be used to maintain or form a physical isolation barrier between portions of wellbore 210 and an internal portion 290 of casing 220.

[0043] While FIG. 2 illustrates fiber optic cable 205 that is inserted in tube 230, fiber optic cable 205 may be inserted in casing 220. Fiber optic cable 205 may be inserted into wellbore 210 at any stage of operation and may remain in the wellbore for the lifespan of wellbore 210. In certain instances, fiber optic cable 205 may be cemented into place when casing 220 is cemented in place in wellbore 210. As such fiber optic cable 205 may be deployed within or next to any wellbore feature.

[0044] After tubing 230 has been inserted into casing 220 of wellbore 210, sensing array 240 may be lowered into casing 220. Sensing assembly 240 may be used to collect acoustic data throughout the lifespan of wellbore 210—when a wellbore is made, during a wellbore production phase, and / or after the wellbore has been placed out of service. While not illustrated in FIG. 2, sensing assembly may be deployed in wellbore 210 before tubing 230 is inserted into the wellbore. Techniques of the present disclosure may be performed such that a certificate of compliance may be generated, and such a certificate may allow a wellbore to be placed into service or retired from service based on sets of wellbore management rules or regulations.

[0045] After wellbore 210 is placed into operation, substances may flow through tubing 230 during a production process. Such a production process may relate to hydrocarbon extraction, hydraulic fracturing, or carbon dioxide sequestration. Sensing assembly 240 may be lowered into tubing 230 using string 250. Sensing assembly 240 includes multiple acoustic sensing elements 260 disposed along a length of sensing assembly 240. Each of sensing elements 260 may include one or more acoustic sensors that may be capable of sensing acoustic noise in one or more directions, for example, using directional sensors, omni-directional sensors, multidirectional sensors, or combination of different types of sensors. Hydrophones, microphones, and piezoelectric sensors are examples of sensor types that may be used when methods of the present disclosure are implemented. In certain instances, string 250 may include a fiber optic cable.

[0046] The tubing 230 shown in FIG. 2 includes an opening in tubing 230 that may be referred to as an orifice. Orifice 270 may be any defect, for example, a crack, hole, orifice, or other defect. Techniques of the present disclosure may be used to identify tubing defects, tubing leaks, tubing related flows, defects in cement, damaged cement related flows, casing leaks, or other leaks associated with a particular wellbore. These techniques may also identify sounds from another wellbore or a formation near a current wellbore, this may include sounds of a flow of another wellbore, a leak in another wellbore, a flow in a fracture of a formation, or a flow in a permeable matrix of a formation. Materials moving along an inside area 280 of tubing 230 may generate noise as those materials move through, past, or around orifice 270. When a production flow includes providing materials via tubing 230 to some portion of wellbore 210 (not illustrated in FIG. 2), those materials may flow down tubing 230 and through and past orifice 270. When a production flow injected into the portion of the wellbore is carbon dioxide or a fracturing fluid, portions of that fluid may flow through or past orifice 270. The sounds generated by that fluid motion may vary based on a size of orifice 270, a density of the fluid, a pressure of the fluid, a fluid flow rate, or other factors. In certain instances, orifices of different sizes may have similar yet not necessarily identical characteristics. For example, an orifice of a first size may generate noise that includes a base frequency and harmonics of that base frequency. This noise may also include sounds generated as a function of the thickness or type of material (e.g., a type of tubing 230). These noises may also include sounds associated with the motion of the fluid between tubing 230 and casing 220 in area 290 of FIG. 2. Similar factors may be associated with noises generated when fluids (e.g., oil, gas, or water) are extracted from a formation that wellbore 210 is drilled into.

[0047] An orifice of a first size may generate noise at frequencies that are a function of the size of the orifice and an intensity of that noise may vary based on operating conditions (e.g., pressure or flow rate) and proximity. An orifice of a larger size may generate noise at different frequencies than the noises generated by a orifice of the smaller size for a given set of conditions. In such instances, other characteristics associated with fluids moving through orifices of different sizes may correspond to each other. For example, frequencies associated with a orifice of the first size may include a base (resonant) frequency of 110 Hz and harmonics of 220 Hz and 330 Hz. An orifice of a second size may include a base frequency of 200 Hz and harmonics of 400 Hz and 600 Hz.

[0048] In another example, analysis may include identifying the shape of a spectrum of frequencies from a type of sound source. A type of sound source may generate noises that have a specific spectral signature. A spectrum associated with a casing leak may have high amplitudes of low frequency signals and low amplitudes of higher frequency signals that results in a characteristic curve that fits a pattern. One such pattern could be plotted in a frequency domain map that shows frequencies of sounds and respective amplitudes. A first curve attributed to a particular type of sound source may include sounds at 10 Hz, 25 Hz, and 50 Hz that reduce according to a parabolic function and a second curve attributed to that same particular type of sound source may include sounds at 20 Hz, 50 Hz, and 100 Hz that fit the same parabolic function with different coefficients. Mappings used to identify a type of sound source may use different mathematical functions that are associated with different portions of the frequency spectrum. For example, a type of sound source may have a first portion where spectral magnitudes correspond to an open downward shaped parabola and may have a second portion that corresponds to an open upward shaped parabola. Data collected from two different sound sources that generate noise at different frequencies may both be identified as being emitted from a same type of sound source when mappings of their respective spectral content and magnitude correspond to a same set of functions that have different coefficient values.

[0049] Noises associated with orifice 270 may include primary sounds and secondary sounds. Primary sounds may be a function of an orifice size and secondary sounds may be a function of other factors, for example, types of materials or material thickness associated with the noise source. These various factors may result in noises being generated that have a same pattern of respective frequencies as included in the example above where noises generated by the orifice of the smaller size and the larger size correspond to each other based on a base resonant frequency one or more harmonics of the base resonant frequency. Relative amplitudes of these different frequencies may also be associated with a pattern that is characteristic of a orifice 270 in tubing 230. Such relative amplitudes associated with each respective orifice size may correspond to each other based on linear or logarithmic functions. This may be similar to the way the pitch of a piano changes with each respective key as other sound characteristics of a piano may not change even though the pitch of the sound changes.

[0050] In certain instances, multiple conditions must be met to identify a type of sound source creating a particular sound. A set of harmonic matching criteria may be necessary yet not sufficient to identify that a particular sound was generated by a crack in a wellbore tube. For example, a sound generated by a type of tubing material and / or a tubing thickness may also be required to identify whether the sound source should be classified as a crack in the tubing. Cracks or other orifices in a type of tubing may be associated with sounds generated by deformation or movement in a portion of the tubing. The orifice 270 in tubing 230 may result in the tube 230 vibrating as fluid leaks from area 280 inside of tubing 230 to area 290 located between an outer surface of tubing 230 and an inner surface of casing 220. In such instances, the harmonic criteria may be associated with a first set of matching criteria and the sounds associated with deformation or movement of the tubing may be associated with a second set of matching criteria. A determination that a particular sound was generated by a crack in wellbore tubing may require both sets of criteria to correspond to sounds that are characteristic of a tubing crack.

[0051] Similar determinations may be made to distinguish between sounds made by a violin and sounds made by a piano. Sounds made by the violin and the piano may share some criteria (e.g., the presence of a base frequency and specific harmonics) yet have other sounds that can be used to differentiate a piano sound from a violin sound. For example, the violin sound may include noises associated with a size of resonance chamber in the violin or noises associated with a type of wood that the violin is made of. In contrast, the piano may have a resonance chamber that is larger than the violin's resonance chamber and materials used to make the piano may make sounds that are not characteristic of the violin.

[0052] Magnitudes of noises detected by sensing array 240 may vary based on operating conditions and a distance that separates orifice 270 from sensing elements 260 of sensing array 240. A set of magnitudes of acoustic power of one or more frequencies included in a set of sensed data that are associated with a particular sound source may be referred to as a power spectral density of the sound source. Characteristics of a type of sound source may include different frequencies of acoustic noise that each have their own magnitude or power relative to each other. Different noise sources may emit frequencies of a same frequency. Because of this, filtering techniques of the present disclosure may filter sets of sensed data in ways that remove only remove portions of acoustic energy of a particular frequency.

[0053] FIG. 3 illustrates two different sound sources that emit noises that may be detected by three different acoustic sensors. FIG. 3 includes sound sources 310 and 320 and acoustic sensors 330, 340, and 350. Acoustic sensor 330 is located at a distance D1 from sound source 310 and is located at a distance D2 from sound source 320. Acoustic sensor 340 is located at a distance D3 from sound source 310 and is located at a distance D4 from sound source 320. Acoustic sensor 350 is located a distance D5 from sound source 310 and is located a distance D6 from sound source 320. Depending on specific types of acoustic sensors used, noises detected by acoustic sensors 330, 340 and 350 may be directional to some degree. In other instances, noises detected by acoustic sensors 330, 340, and 350 may be omni-directional. The medium in which given sets of frequencies move may also affect sounds that reach certain sensors. This is because sounds of some frequencies may be more directional than other frequencies. Furthermore, reflections of sounds off different surfaces may make it difficult to identify a specific location from which a specific sound emanated from. Sounds traveling through water or that echo off surfaces may interfere with the ability of a sensing array to distinguish a location from which those sounds emanate.

[0054] Acoustic energy is transmitted through fluids (e.g., air, carbon dioxide, hydrocarbon streams, or water) in a manner that is consistent with the inverse square law and the speed of sound through the fluid. This means that as an acoustic sensor is moved away from a sound source, noise emitted from the sound source will tend to diminish according to the inverse square of the distance between the sound source and the acoustic sensor. Furthermore, noise emitted from a sound source travels at a speed in many directions. This means that noise leaving sound source 310 at a particular moment in time will reach acoustic sensor 330 that is closer to sound source 310 before that noise reaches acoustic sensor 340 that is farther from sound source 310. In other words, noises emitted from sound source 310 will reach acoustic sensor 330 before reaching acoustic sensor 340 because distance D1 is less than distance D3. Furthermore, the magnitudes of the noise emitted from sound source 310 that is received by acoustic sensor 330 will be larger than magnitudes of the noise emitted from sound source 310 and that is received by acoustic sensor 340 because the noise magnitude varies based on distance according to the inverse square law. Noises emitted from sound sources 310 and 320 will be received at different times and different amplitudes by respective acoustic sensors 330, 340, and 350 because distances that separate each respective sound source and each respective acoustic sensor is different.

[0055] This means that locations of particular sound sources relative to locations where specific acoustic sensors are located may be identified in different ways. A location of a sound source may be identified using several different directional acoustic sensors. When several different directional acoustic sensors receive noise from a same sound source, the location where the sound source is located may be identified using triangulation. By knowing relative locations of each respective acoustic sensor and knowing angles at which each respective acoustic sensor is pointed, vectors along those angles may be projected from each respective acoustic sensor to a point where those vectors intersect. Note that in FIG. 3, acoustic sensor 330 is located at a distance D7 from acoustic sensor 340 and that acoustic sensor 340 is located at distance D7 from acoustic sensor 350. As such, by knowing the distance D7 and by knowing vectors that point along lines D1, D3, and D5, the location of sound source 310 can often be identified. Note also that acoustic sensor 330 is located at a distance of two times distance D7 which equals 2D7.

[0056] In an instance when the three acoustic sensors 330, 340, and 350 receive noise from sound sources 310 and 320, the times at which the different sensors receive noise from each respective sound source will be different. Noise emitted by sound source 320 will reach acoustic sensor 350 at a first time T1, reach acoustic sensor 340 at a second time T2, and will then reach acoustic sensor 350 at a third time T3. A beamforming technique may be performed to identify where sound source 320 is located. This may include delaying noise signals received at respective sensors by different amounts of time. When these different amounts of time correspond to respective delay times (i.e., a first set of delay times) of noise from sound source 320 is received by each respective acoustic sensor, a sum of these three different noise signals will reach a peak magnitude. Such a peak magnitude may be referred to as a high energy peak of delayed noise. This first set of delay times will include a first difference in time ΔT1 that equals time T3 minus time T1 and a second difference in time ΔT2 that equals time T3 minus time T2. These time differences and the speed of sound may be used to perform calculations that identify a location of sound source 320. This is because the location of sound source 320 corresponds to distances associated with the respective delay times (time T3 minus time T1; and T3 minus time T2) as well as distances D7 and 2D7 that separate the respective acoustic sensors.

[0057] Noises from sound source 310 when summed using delays from this first set of delay times will not result in a peak magnitude because distances that separate sound source 310 from acoustic sensors 330, 340, and 350 are different from distances that separate sound source 320 from acoustic sensors 330, 340 and 350. This is because distances D2, D4, and D6 between sound source 320 and respective acoustic sensors 330, 340, and 350 are different than distances D1, D3, and D5 between sound source 310 and the respective acoustic sensors 330, 340, and 350. As such, a set of delay times that characterize relative timing of noise received from sound source 310 at acoustic sensors 330, 340, and 350 will be different than delay times included in the first set of delay times. A set of evaluations could be performed to identify delay times that result in a peak sum of sounds associated with sound source 310 and based on this, a location of sound source 310 may be identified.

[0058] As mentioned above, a form of independent component analysis (ICA) may alternatively or additionally, be performed to associate particular sounds with particular sound sources. For example, sounds from two different sound sources may be combined into a dataset that linearly combines sounds from these two sources into a combined matrix of source sound waveforms X, where X=AS. As such the matrix X may include waveforms of sounds recorded by two different hydrophones as functions of time X1(t) and X2(t), A is a matrix that mixes the components of the sources, and S is a matrix that consists of waveforms of the two sources S1(t) and S2(t). In order to obtain the source matrix S, a mathematical function of S=A−1 or S=WS may be performed. Here A−1 and W represent an inverse matrix of A. An estimate of source matrix S or S would then consist of two estimated source waveforms Ŝ1(t) and Ŝ2(t). By assuming that the two sources are independent, a matrix W can be found that minimizes the sum of entropies associated with waveforms Ŝ1(t) and Ŝ2 (t). Calculations that estimate entropy, for example calculations consistent with Shannon's theorem may then be performed to identify these sums of entropies using the entropy equations below.H⁢1⁢(Sˆ⁢1)=-∑i=1nSˆ⁢1⁢(ti)⁢ log2⁢ Sˆ⁢1⁢(ti)H⁢2⁢(Sˆ⁢2)=-∑i=1nSˆ⁢2⁢(ti)⁢ log2⁢ Sˆ⁢2⁢(ti)Sum⁢ of⁢ Entropy⁢ Equations

[0059] Here the equation H1 is used to calculate entropy to associate with a first sound source and the equation H2 is used to calculate entropy to associate with the second sound source as functions of time Ŝ1(ti) and Ŝ2(ti). These sums may be identified over a number of samples n. Once H1 and H2 are identified, they may be added together to calculate a total entropy E, where E=H1+H2. A plurality of different variations of Ŝ1(t) and Ŝ2(t) may be evaluated when generating different estimates of sums of entropies. A computer modeling inversion process may be performed to find a minimum value of matrix W that corresponds to a minimum value of H1+H2. Examples of inversion methods that may be used to identify matrix W are the Larangian Multiplier Method or Newtonian Iteration. By identifying the sum with a lowest (or minimum) value, sounds to associates with the first sound source and the second sound source may be discriminated from each other to a greater degree of probability as each of these waveforms will correspond to a greater degree of organization or negative entropy because a lowest sum of entropy will correspond to greater organization.

[0060] The locations of many different noise sources that surround a sensing array may be identified and maps may be generated that show where each of these different noise sources are located. Such mappings may be referred to as beamforming maps or sound source location maps. In certain instances, such mappings may be incorporated into visualizations that show respective locations of each different respective noise source in two dimensions or in three dimensions. Such mappings may be useful in identify conditions of the wellbore. For example, a first set of noises may be characteristic of fluids moving through an Earth formation and a second set of noises may be characteristic of defects in a set of wellbore tubing, a wellbore casing, or some other wellbore defect.

[0061] A second way that could be used to identify a location of a sound source, at least in part, is by comparing magnitudes of noise energy that is received by several different acoustic sensors. For example, in an instance when two different acoustic sensors are located at a same distance from a sound source and a third acoustic sensor is located at some other distance from the sound source, magnitudes of noise received by the first two acoustic sensors may be expected to be the same and a magnitude of noise received by the third acoustic sensor will have some other value. This information should be enough to identify a set of potential locations where the sound source can be located, when plotted on a graph, this set of point would include all points equal distant from each of the first two acoustic sensors while being more distant from the third acoustic sensor. This information is enough to identify locations where the sound source is located based on the inverse square law. While FIG. 3 shows two sound sources, methods the present disclosure may perform similar evaluations on more than two sound sources. While FIG. 3 shows three acoustic sensors, some degree of triangulation could be performed using as few as two acoustic sensors. The more acoustic sensors included in a sensor array may tend to increase the accuracy of determinations made as compared to sensor arrays that used fewer acoustic sensors. In other words, evaluations performed on data collected from N+1 sensors will yield higher resolution location accuracy as compared to evaluations performed on data collected using N sensors.

[0062] In instances when an acoustic array includes more than three acoustic sensors, these additional sensors may be located at different distances and relative magnitudes of noise energy received may be used to identify a location of the sound source by solving a set of equations. In such instances, known distances between respective acoustic sensors and measured differences in sensed acoustic energy from each of those respective acoustic sensors may be used to identify the location of the sound source.

[0063] A third way that a location of the sound source could be identified is by identifying differences in time when specific noise signals are received at specific acoustic sensors. These differences in time may be used to identify a set of possible locations where the acoustic sensor is located. Here again the more sensors used may help identify the location of the sound source based on the speed that noise travels from the sound source to the respective acoustic sensors.

[0064] FIG. 4 illustrates a series of actions that may be performed when fluid flows in subterranean strata or wellbore defects are characterized. At block 410 data may be extracted from light signals received via a fiber optic cable deployed in a wellbore. This fiber optic cable may be part of a distributed acoustic sensing (DAS) system, a distributed strain sensing system (DSS) system, a distributed temperature sensing (DTS) system, or a system that senses a combination of acoustic sensing, strain sensing, and temperature sensing along the length of the fiber optic cable. As mentioned above, techniques to measure sound, cable strain, and / or temperature along the fiber optic cable may use various techniques (e.g., Rayleigh measurement Raman comparison or other techniques).

[0065] Once the data is extracted at block 410, an evaluation may be performed at determination block 420 to identify whether a sound of interest has been identified by the sensing system (e.g., a DAS system). When the sound of interest has not been identified, program flow may move back to block 410 where additional data is received from the fiber optic cable. When a sound of interest has been identified at block 420, program flow may move to block 430 where a wellbore location to associate with that sound of interest is identified. The identification that the sound of interest exists that was made at block 420 and the wellbore location identified at block 430 may have been performed based on an analysis of the data received at block 410.

[0066] At block 440, a set of acoustic sensors may be deployed in the wellbore such that additional data regarding the sound of interest may be collected. This set of sensors may be in the form of a hydrophone array like the array discussed in respect to FIG. 2. Since such hydrophone arrays may include many sensors, one or more of which may be directional sensors, data collected from the set of acoustic sensors may be richer (higher resolution of inches as compared to meters) than data collected from the light signals of the fiber optic cable. As such, at block 450 a span or radial and / or vertical locations to associate with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0067] FIG. 5A illustrates a mapping of data collected based on the operation of a fiber optic cable deployed in a wellbore. Mapping 500 of FIG. 5A includes a vertical axis of depth or length (in meters) and includes a horizontal axis of time (in days, March 1 through March 9). Horizontal line 510 in mapping 500 represents a sound of interest that was detected on March 6 (3-6) and that continued through March 9 (3-9). The sound of interest represented by line 510 was not observed before March 6. Note that the sound of interest is located at about 2500 meters of wellbore depth (or length). The term wellbore depth may refer to a distance or length from a location where the wellbore begins (e.g., a surface location) to a location in the wellbore. For various reasons, a wellbore depth may not actually be a depth below the surface location where the wellbore begins. For example, when a wellbore is drilled vertically downward for 500 meters and then turns horizontally over a distance of 50 meters to and end point, the overall “wellbore depth” may be said to be 550 meters, even though the wellbore goes no “deeper” than 500 meters below the surface where the wellbore begins. Because of this, a given wellbore depth may be measured based on a distance between the surface where the wellbore begins and some location within the wellbore. As such, the location of a place in the wellbore may be specified as a distance from the surface that may be referred to as a “wellbore depth.”

[0068] FIG. 5B illustrates a mapping made from data collected by a set of acoustic sensors. Mapping 550 of FIG. 5B includes a vertical axis of “wellbore depth” and a horizontal axis of radial distance. This radial distance may be a distance from a center point of a set of acoustic sensors, for example. In such an instance and when the set of acoustic sensors is placed in the center of a casing, the radial distance of mapping 550 may be drawn relative to the center of the casing. The vertical dashed lines of FIG. 5B may show where the casing is located in mapping 550. In such an instance, the distance separating the dashed lines may correspond to the thickness of the casing. Here the casing may have an inner diameter of 3.5 inches and a thickness of about 0.5 inches.

[0069] After a sound the sound of interest located at “wellbore depth” of about 2500 meters is observed, the set of acoustic sensors may be deployed in the wellbore at that depth. In such instances, data extracted from light signals received via the fiber optic cable may identify an approximate depth of the sound of interest. Because of this, the set of sensors (e.g., sensors of a hydrophone) may be deployed at the 2500 meter “wellbore depth” and data may be collected using the set of sensors. At this time the set of sensors may be moved uphole or downhole to identify a more precise location of the sound of interest. Note that mapping 550 may depict the sound of interest relative to a zero depth or length as shown by the placement of the “0” point of the vertical axis.

[0070] Mapping 550 includes a vertical and radial mapping associated with sound of interest 560. Here sound of interest 560 may be a sound that is created by fluids leaking from through a defect (e.g., a crack) in the casing. As such, techniques of the present disclosure may be used to identify a general location of a sound of interest based on sounds sensed using data collected from a fiber optic cable after which acoustic sensors or sensors of a hydrophone may be used to identify the location of a defect more accurately. Once a crack or other wellbore defect is identified, a repair of that defect may be initiated.

[0071] FIG. 6 illustrates another series of actions that may be performed when fluid flows in subterranean strata or wellbore defects are characterized. At block 610 data may be extracted from light signals received via a fiber optic cable deployed in a wellbore. At block 620 the location / depth of a sound of interest may be identified based on an analysis of the data received from fiber optic cable at block 620. Since in some instances, sounds of interest may be intermittent, a determination may be made a block 630 that the sound of interest has disappeared. At block 640, an analysis may be performed on data extracted from light signals that traveled along the fiber optic cable. Metrics may then be identified at block 650 based on the analysis performed at block 640. These metrics may identify an approximate location of a wellbore defect or a subterranean fluid flow based on temperature changes identified by the analysis performed at block 640 and 650.

[0072] At block 660, a set of acoustic sensors may be deployed at a depth where a temperature change or temperature gradient has been observed. In some instances, the acoustic sensors may be deployed until the sound of interest reappears. In other instances (e.g., at block 670), one or more changes to the operation of the wellbore may be changed when the set of acoustic sensors is deployed in the vicinity where the temperature changes were observed. Such changes to the wellbore operation may include changing a how a hardware device operates. For example, such a change may be related to changing a valve setting (e.g., opening or closing a valve, such as a wellhead choke valve) or turning a pump on or off. These changes may stimulate the reappearance of the sound of interest, and this may lead to a sensing system identifying that the sound of interest has reappeared at block 680. As such, at block 690 a span or radial and / or vertical locations to associate with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0073] Systems and techniques of the present disclosure may generate temperature logs and acoustic logs based on data sensed by operation of a DAS / DTS system. By combining DAS / DTS and / or arrays of acoustic sensors, techniques of the present disclosure may more accurately map leak events that happened and that then stopped happening. In instances when a sound emitted from a noise source is not continuous, acoustic tools may not be able to characterize source of the noise. Even so, temperatures effects of the noise may still be observable even after the noise is no longer present. Based on the fact that temperature events tend to have memory and based on the fact that it takes time for these temperature events to fade away, temperature gradients detectable by operation of a DTS system may allow for a general location of a leak or the noise source to be identified. Based on this, operations of the wellbore may be changed after an acoustic sensing tool with greater resolution (e.g., a hydrophone sensing array) has been deployed to the general location of the noise source. As mentioned above, one more valves may be opened or closed or pumps may be turned on or off in an effort to stimulate the reemergence of the noise. Operation of a DTS, DAS, or DSS system or combination thereof may be used to identify temperatures of interest, sounds of intertest, or stresses that may be associated with a wellbore defect. Analysis of collected data may identify characteristics of potential defects and as such a temperature of interest, a sound of interest, or a stress of interest may include or may correspond to a span of radial locations, a span of vertical locations, an acoustic amplitude, an acoustic pattern, a temperature, or a change in temperatures (e.g., a temperature gradient).

[0074] FIG. 7 illustrates an example architecture 700 of a computing device which can implement the various technologies and techniques described herein. The various implementations will be apparent to those of ordinary skill in the art when practicing the present technology. Persons of ordinary skill in the art will also readily appreciate that other system implementations or examples are possible. The components of the computing device architecture 700 are shown in electrical communication with each other using a connection 705, such as a bus. The example computing device architecture 700 includes a processing unit (CPU or processor) 710 and a computing device connection 705 that couples various computing device components including the computing device memory 715, such as read only memory (ROM) 720 and random-access memory (RAM) 725, to the processor 710.

[0075] The computing device architecture 700 can include a cache of high-speed memory connected directly with, in close proximity to, or integrated as part of the processor 710. The computing device architecture 700 can copy data from the memory 715 and / or the storage device 730 to the cache 712 for quick access by the processor 710. In this way, the cache can provide a performance boost that avoids processor 710 delays while waiting for data. These and other modules can control or be configured to control the processor 710 to perform various actions. Other computing device memory 715 may be available for use as well. The memory 715 can include multiple different types of memory with different performance characteristics. The processor 710 can include any general-purpose processor / multi-processor and a hardware or software service, such as service 1 732, service 2 734, and service 3 736 stored in storage device 730, configured to control the processor 710 as well as a special-purpose processor where software instructions are incorporated into the processor design. The processor 710 may be a self-contained system, containing multiple cores or processors, a bus, memory controller, cache, etc. A multi-core processor may be symmetric or asymmetric.

[0076] To enable user interaction with the computing device architecture 700, an input device 745 can represent any number of input mechanisms, such as a microphone for speech, a touch-sensitive screen for gesture input, keyboard, mouse, motion input, speech and so forth. An output device 735 can also be one or more of a number of output mechanisms known to those of skill in the art, such as a display, projector, television, speaker device, etc. In some instances, multimodal computing devices can enable a user to provide multiple types of input to communicate with the computing device architecture 700. The communications interface 740 can generally govern and manage the user input and computing device output. There is no restriction on operating on any particular hardware arrangement and therefore the basic features here may easily be substituted for improved hardware or firmware arrangements as they are developed.

[0077] Storage device 730 is a non-volatile memory and can be a hard disk or other types of computer readable media which can store data that are accessible by a computer, such as magnetic cassettes, flash memory cards, solid state memory devices, digital versatile disks, cartridges, random access memories (RAMs) 725, read only memory (ROM) 720, and hybrids thereof. The storage device 730 can include services 732, 734, 736 for controlling the processor 710. Other hardware or software modules are contemplated. The storage device 730 can be connected to the computing device connection 705. In one aspect, a hardware module that performs a particular function can include the software component stored in a computer-readable medium in connection with the necessary hardware components, such as the processor 710, connection 705, output device 735, and so forth, to carry out the function.

[0078] For clarity of explanation, in some instances the present technology may be presented as including individual functional blocks including functional blocks comprising devices, device components, steps or routines in a method embodied in software, or combinations of hardware and software.

[0079] In some instances the computer-readable storage devices, mediums, and memories can include a cable or wireless signal containing a bit stream and the like. However, when mentioned, non-transitory computer-readable storage media expressly exclude media such as energy, carrier signals, electromagnetic waves, and signals per se.

[0080] Methods according to the above-described examples can be implemented using computer-executable instructions that are stored or otherwise available from computer readable media. Such instructions can include, for example, instructions and data which cause or otherwise configure a general-purpose computer, special purpose computer, or a processing device to perform a certain function or group of functions. Portions of computer resources used can be accessible over a network. The computer executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, firmware, source code, etc. Examples of computer-readable media that may be used to store instructions, information used, and / or information created during methods according to described examples include magnetic or optical disks, flash memory, USB devices provided with non-volatile memory, networked storage devices, and so on.

[0081] Devices implementing methods according to these disclosures can include hardware, firmware and / or software, and can take any of a variety of form factors. Typical examples of such form factors include laptops, smart phones, small form factor personal computers, personal digital assistants, rackmount devices, standalone devices, and so on. Functionality described herein also can be embodied in peripherals or add-in cards. Such functionality can also be implemented on a circuit board among different chips or different processes executing in a single device, by way of further example.

[0082] The instructions, media for conveying such instructions, computing resources for executing them, and other structures for supporting such computing resources are example means for providing the functions described in the disclosure.

[0083] In the foregoing description, aspects of the application are described with reference to specific embodiments thereof, but those skilled in the art will recognize that the application is not limited thereto. Thus, while illustrative embodiments of the application have been described in detail herein, it is to be understood that the disclosed concepts may be otherwise variously embodied and employed, and that the appended claims are intended to be construed to include such variations, except as limited by the prior art. Various features and aspects of the above-described subject matter may be used individually or jointly. Further, embodiments can be utilized in any number of environments and applications beyond those described herein without departing from the broader spirit and scope of the specification. The specification and drawings are, accordingly, to be regarded as illustrative rather than restrictive. For the purposes of illustration, methods were described in a particular order. It should be appreciated that in alternate embodiments, the methods may be performed in a different order than that described.

[0084] Where components are described as being “configured to” perform certain operations, such configuration can be accomplished, for example, by designing electronic circuits or other hardware to perform the operation, by programming programmable electronic circuits (e.g., microprocessors, or other suitable electronic circuits) to perform the operation, or any combination thereof.

[0085] The various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the examples disclosed herein may be implemented as electronic hardware, computer software, firmware, or combinations thereof. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0086] The techniques described herein may also be implemented in electronic hardware, computer software, firmware, or any combination thereof. Such techniques may be implemented in any of a variety of devices such as general purposes computers, wireless communication device handsets, or integrated circuit devices having multiple uses including application in wireless communication device handsets and other devices. Any features described as modules or components may be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques may be realized at least in part by a computer-readable data storage medium comprising program code including instructions that, when executed, performs one or more of the method, algorithms, and / or operations described above. The computer-readable data storage medium may form part of a computer program product, which may include packaging materials.

[0087] The computer-readable medium may include memory or data storage media, such as random-access memory (RAM) such as synchronous dynamic random access memory (SDRAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), FLASH memory, magnetic or optical data storage media, and the like. The techniques additionally, or alternatively, may be realized at least in part by a computer-readable communication medium that carries or communicates program code in the form of instructions or data structures and that can be accessed, read, and / or executed by a computer, such as propagated signals or waves.

[0088] Other embodiments of the disclosure may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. Embodiments may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination thereof) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0089] The various embodiments described above are provided by way of illustration only and should not be construed to limit the scope of the disclosure. For example, the principles herein apply equally to optimization as well as general improvements. Various modifications and changes may be made to the principles described herein without following the example embodiments and applications illustrated and described herein, and without departing from the spirit and scope of the disclosure. Claim language reciting “at least one of” a set indicates that one member of the set or multiple members of the set satisfy the claim.Aspects of the Disclosure:

[0090] Aspect 1: A method comprising: receiving data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed acoustic sensing (DAS) system; identifying a sound of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable; deploying a set of acoustic sensors at the wellbore depth; sensing acoustic data by the set of acoustic sensors at the wellbore depth; and identifying characteristics associated with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0091] Aspect 2: The method of Aspect 1, wherein the deployment of the set acoustic sensors at the wellbore depth includes moving the set of acoustic sensors over a range of wellbore depths that include the wellbore depth.

[0092] Aspect 3: The method of Aspect 1 or 2, further comprising: collecting additional data from the fiber optic cable based on operation of the (DAS) being continued when the set of acoustic data sense the acoustic data.

[0093] Aspect 4: The method of any of Aspects 1 through 3, further comprising: identifying that the sound of interest has stopped; initiating one or more changes to operation of the wellbore to stimulate the sound of interest; and identifying that the sound of interest has been stimulated by the one or more changes to the operation of the wellbore.

[0094] Aspect 5: The method of any of Aspects 1 through 4, wherein the characteristics associated with the sound of interest include one or more of a span of radial locations a span of vertical locations, an acoustic amplitude, and an acoustic pattern to associate with the sound of interest and wherein the evaluation associated with the sound of interest includes analyzing data sensed by each sensor of the set of sensors based on one or more of distances that separate each respective sensor of the set of sensors, relative radial positions of each of the respective sensors of the set of sensors, and arrival times of the sound of interest at each of the respective sensors of the set of sensors.

[0095] Aspect 6: A non-transitory computer-readable storage medium having embodied thereon instructions that when executed by one or more processors cause the one or more processors to: receive data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed acoustic sensing (DAS) system; identify a sound of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable; control deployment of a set of acoustic sensors at the wellbore depth; receive acoustic data sensed by the set of acoustic sensors at the wellbore depth; and identify characteristics associated with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0096] Aspect 7: The non-transitory computer-readable storage medium of Aspect 6, wherein the deployment of the set acoustic sensors at the wellbore depth includes moving the set of acoustic sensors over a range of wellbore depths that include the wellbore depth.

[0097] Aspect 8: The non-transitory computer-readable storage medium of Aspect 6 or 7, wherein the one or more processors execute the instructions to: collect additional data from the fiber optic cable based on operation of the (DAS) system being continued when the set of acoustic data sense the acoustic data.

[0098] Aspect 9: The non-transitory computer-readable storage medium of any of Aspects 6 through 8, wherein the one or more processors execute the instructions to: identify that the sound of interest has stopped; initiate one or more changes to operation of the wellbore to stimulate the sound of interest; and identify that the sound of interest has been stimulated by the one or more changes to the operation of the wellbore.

[0099] Aspect 10: The non-transitory computer-readable storage medium of any of Aspects 6 through 9, wherein the one or more processors execute the instructions to: identify a temperature at the wellbore depth based on additional data collected from the fiber optic cable.

[0100] Aspect 11: The non-transitory computer-readable storage medium of any of Aspects 6 through 10, wherein the characteristics associated with the sound of interest include one or more of a span of radial locations, a span of vertical locations, an acoustic amplitude, and an acoustic pattern to associate with the sound of interest, and wherein the evaluation associated with the sound of interest includes analyzing data sensed by each sensor of the set of sensors based on one or more of: distances that separate each respective sensor of the set of sensors, relative radial positions of each of the respective sensors of the set of sensors, and arrival times of the sound of interest at each of the respective sensors of the set of sensors.

[0101] Aspect 12. A system comprising: a fiber optic cable deployed at a wellbore when the fiber optic cable is part of a distributed acoustic sensing (DAS) system; a set of acoustic sensors; a memory; and one or more processors that execute instructions out of the memory to: identify a sound of interest at a wellbore depth based on an analysis of data received from the fiber optic cable, control deployment of the set of acoustic sensors to the wellbore depth, receive acoustic data sensed by the set of acoustic sensors at the wellbore depth; and identify characteristics associated with the sound of interest based on an evaluation of the data collected by the set of acoustic sensors.

[0102] Aspect 13: The system of Aspect 12, wherein the deployment of the set acoustic sensors at the wellbore depth includes moving the set of acoustic sensors over a range of wellbore depths that include the wellbore depth.

[0103] Aspect 14: The system of Aspect 12 or 13, wherein the one or more processors execute the instructions to: collect additional data from the fiber optic cable based on operation of the (DAS) system being continued when the set of acoustic data sense the acoustic data.

[0104] Aspect 15: The system of any of Aspects 12 through 14, wherein the one or more processors execute the instructions to: identify that the sound of interest has stopped; initiate one or more changes to operation of the wellbore to stimulate the sound of interest; and identify that the sound of interest has been stimulated by the one or more changes to the operation of the wellbore.

[0105] Aspect 16: A method comprising: receiving data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed temperature sensing (DTS) system; identifying a temperature of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable; deploying a set of acoustic sensors at the wellbore depth based on the temperature of interest being identified at the wellbore depth; sensing acoustic data by the set of acoustic sensors at the wellbore depth; and identifying characteristics associated with the sensed acoustic data based on an evaluation of the data collected by the set of acoustic sensors.

[0106] Aspect 17: The method of Aspect 16, further comprising: identifying one or more additional temperatures within a threshold distance from the wellbore depth; and performing an analysis that identifies a temperature gradient associated with the temperature.

[0107] Aspect 18: The method of Aspect 16 or 17, further comprising: identifying a range of wellbore depths to sense the acoustic data by the set of acoustic sensors based on the temperature gradient.

[0108] Aspect 19: A non-transitory computer-readable storage medium having embodied thereon instructions that when executed by one or more processors cause the one or more processors to: receive data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed temperature sensing (DTS) system; identify a temperature of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable; deploy a set of acoustic sensors at the wellbore depth based on the temperature being identified at the wellbore depth; sense acoustic data by the set of acoustic sensors at the wellbore depth; and identify characteristics associated with the sensed acoustic data based on an evaluation of the data collected by the set of acoustic sensors.

[0109] Aspect 20: A system comprising: a fiber optic cable deployed at a wellbore when the fiber optic cable is part of a distributed acoustic temperature sensing (DAS) system; a set of acoustic sensors; a memory; and one or more processors that execute instructions out of the memory to: receive data from a fiber optic cable deployed at a wellbore based on the fiber optic cable being part of a distributed temperature sensing (DTS) system, identify a temperature of interest at a wellbore depth based on an analysis of the data received from the fiber optic cable, deploy a set of acoustic sensors at the wellbore depth based on the temperature of interest being identified at the wellbore depth, sense acoustic data by the set of acoustic sensors at the wellbore depth, and identify characteristics associated with the sensed acoustic data based on an evaluation of the data collected by the set of acoustic sensors.

Examples

Embodiment Construction

[0013]As discussed in greater detail herein, the present disclosure provides systems, methods, and computer-readable media for identifying locations of a wellbore where sensors of a particular type may be deployed to identify the size or scope of wellbore defects more accurately and that may allow for more accurate determinations be made as to flow rates of fluids in a subterranean environment. Apparatus and methods of the present disclosure may be referred to as systems and techniques that address challenges of monitoring downhole flows in real-time or that may be used to perform high-quality flow evaluation and high-precision leak localization.

[0014]Systems and techniques of the present disclosure may first use a fiber optic cable as a distributed acoustic sensor or as a sensor that senses temperatures along the fiber optic cable that is deployed in a wellbore. These systems and techniques may also control the deployment of an acoustic sensing tool in the wellbore that has greater...

Claims

1. A method comprising:deploying a fiber optic cable wellbore based on the fiber optic cable being part of a distributed acoustic sensing (DAS) system;receiving DAS data from the fiber optic cable deployed in a wellbore;identifying a sound of interest at a wellbore depth based on an analysis of the DAS data received from the fiber optic cable;deploying a noise logging tool at the wellbore depth based on the analysis of the DAS data received from the fiber optic cable;sensing acoustic data by the noise logging tool at the wellbore depth;identifying characteristics associated with the sound of interest based on an evaluation of the acoustic data collected by the noise logging tool, wherein the identified characteristics characterize the sound of interest as being indicative of a fluid flow downhole; andchanging a wellbore operation based on the identified characteristics by performing one or more remedial or control actions in the wellbore.

2. The method of claim 1, wherein the deployment of the noise logging tool at the wellbore depth includes moving the noise logging tool over a range of wellbore depths that includes the wellbore depth.

3. The method of claim 1, further comprising:collecting additional DAS data from the fiber optic cable based on operation of the DAS being continued when the set of acoustic data sense the acoustic data.

4. The method of claim 1, further comprising:identifying that the sound of interest has stopped;initiating one or more changes to operation of the wellbore to stimulate the sound of interest; andidentifying that the sound of interest has been stimulated by the one or more changes to the operation of the wellbore.

5. The method of claim 1, wherein the characteristics associated with the sound of interest include one or more of a span of radial locations, a span of vertical locations, an acoustic amplitude, and an acoustic pattern to associate with the sound of interest, and wherein the evaluation associated with the sound of interest includes analyzing data sensed by each sensor of a set of sensors based on one or more of:distances that separate each respective sensor of the set of sensors,relative radial positions of each of the respective sensors of the set of sensors, andarrival times of the sound of interest at each of the respective sensors of the set of sensors.

6. A non-transitory computer-readable storage medium having embodied thereon instructions that when executed by one or more processors cause the one or more processors to:receive distributed acoustic sensing (DAS) data from a fiber optic cable deployed in a wellbore;identify a sound of interest at a wellbore depth based on an analysis of the DAS data received from the fiber optic cable;control deployment of a noise logging tool at the wellbore depth based on the analysis of the DAS data received from the fiber optic cable;receive acoustic data sensed by the noise logging tool at the wellbore depth;identify characteristics associated with the sound of interest based on an evaluation of the acoustic data collected by the noise logging tool, wherein the identified characteristics characterize the sound of interest as being indicative of a fluid flow downhole defect; andchange a wellbore operation based on the identified characteristics by performing one or more remedial or control actions in the wellbore.

7. The non-transitory computer-readable storage medium of claim 6, wherein the deployment of the noise logging tool at the wellbore depth includes moving the noise logging tool over a range of wellbore depths that includes the wellbore depth.

8. The non-transitory computer-readable storage medium of claim 6, wherein the one or more processors execute the instructions to:collect additional DAS data from the fiber optic cable based on operation of the DAS system being continued when the set of acoustic data sense the acoustic data.

9. The non-transitory computer-readable storage medium of claim 6, wherein the one or more processors execute the instructions to:identify that the sound of interest has stopped;initiate one or more changes to operation of the wellbore to stimulate the sound of interest; andidentify that the sound of interest has been stimulated by the one or more changes to the operation of the wellbore.

10. The non-transitory computer-readable storage medium of claim 6, wherein the one or more processors execute the instructions to:identify a temperature at the wellbore depth based on additional DAS data collected from the fiber optic cable.

11. The non-transitory computer-readable storage medium of claim 6, wherein the characteristics associated with the sound of interest include one or more of a span of radial locations, a span of vertical locations, an acoustic amplitude, and an acoustic pattern to associate with the sound of interest, and wherein the evaluation associated with the sound of interest includes analyzing data sensed by each sensor of a set of sensors based on one or more of:distances that separate each respective sensor of the set of sensors,relative radial positions of each of the respective sensors of the set of sensors, and arrival times of the sound of interest at each of the respective sensors of the set of sensors.

12. A system comprising:a fiber optic cable deployed in a wellbore, wherein the fiber optic cable is part of a distributed acoustic sensing (DAS) system;a noise logging tool;a memory; andone or more processors that execute instructions out of the memory to:receive DAS data from the fiber optic cable;identify a sound of interest at a wellbore depth based on an analysis of DAS data received from the fiber optic cable deployed in the wellbore;control deployment of the noise logging tool to the wellbore depth based on the analysis of the DAS data received from the fiber optic cable,receive acoustic data sensed by the noise logging tool at the wellbore depth;identify characteristics associated with the sound of interest based on an evaluation of the acoustic data collected by the noise logging tool, wherein the identified characteristics characterize the sound of interest as being indicative of a fluid flow downhole; andchange a wellbore operation based on the identified characteristics by performing one or more remedial or control actions in the wellbore.

13. The system of claim 12, wherein the deployment of the noise logging tool at the wellbore depth includes moving the noise logging tool over a range of wellbore depths that includes the wellbore depth.

14. The system of claim 12, wherein the one or more processors execute the instructions to:collect additional data from the fiber optic cable based on operation of the DAS system being continued when the set of acoustic data sense the acoustic data.

15. The system of claim 12, wherein the one or more processors execute the instructions to:identify that the sound of interest has stopped;initiate one or more changes to operation of the wellbore to stimulate the sound of interest; andidentify that the sound of interest has been stimulated by the one or more changes to the operation of the wellbore.

16. A method comprising:deploying a fiber optic cable wellbore based on the fiber optic cable being part of a distributed temperature sensing (DTS) system;receiving DTS data from the fiber optic cable deployed in a wellbore;identifying a temperature of interest at a wellbore depth based on an analysis of the DTS data received from the fiber optic cable;deploying a noise logging tool at the wellbore depth based on the temperature of interest being identified at the wellbore depth;sensing acoustic data by the noise logging tool at the wellbore depth;identifying characteristics associated with the sensed acoustic data based on an evaluation of the acoustic data collected by the noise logging tool, wherein the identified characteristics characterize the sensed acoustic data as being indicative of a fluid flow downhole; andchanging a wellbore operation based on the identified characteristics by performing one or more remedial or control actions in the wellbore.

17. The method of claim 16, further comprising:identifying one or more additional temperatures within a threshold distance from the wellbore depth; andperforming an analysis that identifies a temperature gradient associated with the temperature.

18. The method of claim 17, further comprising:identifying a range of wellbore depths to sense the acoustic data by the noise logging tool based on the temperature gradient.

19. A non-transitory computer-readable storage medium having embodied thereon instructions that when executed by one or more processors cause the one or more processors to:receive distributed temperature sensing (DTS) data from a fiber optic cable deployed in a wellbore based on the fiber optic cable being part of a DTS system;identify a temperature of interest at a wellbore depth based on an analysis of the DTS data received from the fiber optic cable;deploy a noise logging tool at the wellbore depth based on the temperature being identified at the wellbore depth;sense acoustic data by the noise logging tool at the wellbore depth;identify characteristics associated with the sensed acoustic data based on an evaluation of the acoustic data collected by the noise logging tool, wherein the identified characteristics characterize the sense acoustic data as being indicative of a fluid flow downhole defect; andchange a wellbore operation based on the identified characteristics by performing one or more remedial or control actions in the wellbore.

20. A system comprising:a fiber optic cable deployed in a wellbore, wherein the fiber optic cable is part of a distributed acoustic temperature sensing (DTS) system;a noise logging tool;a memory; andone or more processors that execute instructions out of the memory to:receive DTS data from the fiber optic cable deployed in the wellbore based on the fiber optic cable being part of the DTS system;identify a temperature of interest at a wellbore depth based on an analysis of the DTS data received from the fiber optic cable;control deployment of the noise logging tool at the wellbore depth based on the temperature of interest being identified at the wellbore depth;receive acoustic data sensed by the noise logging tool at the wellbore depth;identify characteristics associated with the sensed acoustic data based on an evaluation of the acoustic data collected by the noise logging tool, wherein the identified characteristics characterize the sensed acoustic data as being indicative of a fluid flow downhole; andchange a wellbore operation based on the identified characteristics by performing one or more remedial or control actions in the wellbore.

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