Three-component seismic data processing and hydraulic fracturing seismic interpretation method

Abstract

Systems and methods include a computer-implemented method for presenting an interpretation result of synchronized seismic data and fracturing treatment time. A standard format seismic data set of sensor readings obtained from three-component sensors is generated. Coordinates and recording times corresponding to the sensor readings are added to the standard format seismic data set. Synchronized seismic data is generated from the standard format seismic data set by synchronizing the seismic recording times with the fracturing treatment time. Quality-controlled synchronized seismic data is generated by removing dead traces and abnormal data samples from the synchronized seismic data. A time-frequency analysis is performed on the quality-controlled synchronized seismic data, including performing a short-time Fourier transform to analyze changes in Fourier spectra over time. Based on the time-frequency analysis, a resonance frequency is extracted from each spectrum at different time samples. An interpretation result based on the resonance frequency is presented to a user.

Description

[0001] CLAIM OF PRIORITY

[0002] This application claims priority to U.S. Patent Application No. 16 / 840,903, filed April 6, 2020, the entirety of which is incorporated herein by reference. BACKGROUND

[0003] The present disclosure is applicable to techniques for monitoring a fracturing (or fracking) process.

[0004] Seismic While Fracking (SWF) is a seismic technique used to assess the quality of hydraulic fractures during hydraulic fracturing. Conventional SWF techniques can include microseismic monitoring methods, which can require many sensors. Conventional techniques can also require significant processing time and computing resources, and can be labor intensive. SUMMARY

[0005] The present disclosure describes techniques that can be used to generate an interpretation based on synchronized seismic data and fracturing treatment time.

[0006] In some implementations, a computer-implemented method includes the following. A set of seismic data in a standard format of sensor readings obtained from three-component sensors is generated. Coordinates and recording times corresponding to the sensor readings are added to the set of seismic data in the standard format. Synchronized seismic data is generated from the set of seismic data in the standard format by synchronizing seismic recording times with fracturing treatment time. Quality-controlled synchronized seismic data is generated by removing dead traces and abnormal data samples from the synchronized seismic data. A time-frequency analysis is performed on the quality-controlled synchronized seismic data, including performing a short-time Fourier transform to analyze changes in Fourier spectra over time. Based on the time-frequency analysis, resonant frequencies are extracted from each frequency spectrum at different time samples. An interpretation based on the resonant frequencies is presented to a user.

[0007] The implementations described in the preceding can be implemented using: a computer- implemented method; a non-transitory computer-readable medium storing computer-readable instructions for performing the computer-implemented method; and a computer-implemented system comprising a computer memory interoperably coupled with a hardware processor, the hardware processor configured to perform the computer-implemented method / instructions stored on the non-transitory computer-readable medium.

[0008] The subject matter described in this specification can be implemented in particular implementations to realize one or more of the following advantages. First, the techniques described in this disclosure can provide improvements over conventional techniques that use body waves scattered from a fracture. Body waves tend to be weak, so a wide azimuth and dense receiver array can be needed to reconstruct the wavefield. In contrast, the techniques described in this disclosure can instead use tube waves, which propagate with less energy dissipation within the wellbore, so fewer receivers are needed. Second, one or several three-component sensors can be determined to effectively record reflected tube waves. Third, the techniques of this disclosure can reduce computing, labor, and transportation costs. Fourth, the techniques of this disclosure can use reflected tube waves to provide efficient and reliable assessment of fracture quality.

[0009] The details of one or more implementations of the subject matter of this specification are set forth in the specific embodiments, drawings, and claims. Other features, aspects, and advantages of the subject matter will become apparent from the description, the claims, and the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0010] Figure 1 is a geometry of a well trajectory for a seismic while fracturing test according to some embodiments of the present disclosure.

[0011] Figure 2A and Figure 2B is a plot showing raw data recorded by a sensor according to some embodiments of the present disclosure.

[0012] Figure 3A and Figure 3B is a plot showing a time-frequency analysis performed on seismic data according to some embodiments of the present disclosure.

[0013] Figures 4A to 4C is a plot showing an interpretation of seismic data acquired at a 15thfracturing stage according to some embodiments of the present disclosure.

[0014] Figure 5 is a flowchart of an example of a method for generating an interpretation result based on synchronized seismic data and fracturing treatment time according to some embodiments of the present disclosure.

[0015] Figure 6 is a block diagram illustrating an example computer system for providing computational functionality associated with the described algorithms, methods, functions, processes, flows, and procedures as described in the present disclosure, according to some embodiments of the present disclosure.

[0016] Like reference numbers and designations in different drawings represent like elements. DETAILED DESCRIPTION

[0017] The following DETAILED DESCRIPTION describes techniques for generating an interpretation result based on synchronized seismic data and fracturing treatment times. Various modifications, changes, and substitutions can be made to the disclosed embodiments without departing from the general principles of the defined general principles can be applied to other embodiments and applications, without departing from the scope of the disclosure. In some instances, details unnecessary to obtain an understanding of the described subject matter can be omitted so as not to unnecessarily obscure one or more described embodiments, and because such details are within the skill of the art. The present disclosure is not intended to be limited to the described or illustrated embodiments, but rather is to be accorded the widest scope consistent with the described principles and features.

[0018] Some conventional hydraulic impedance tests or similar techniques can use water hammer signals. However, these techniques can be limited to wellhead pressure time series sampled at a frequency not exceeding 1 Hertz (Hz). In the context of wellbore acoustics, other techniques can be used to analyze wave reflections from a fracture. High frequency signals (e.g., signals above 1 kilohertz (kHz)) generated by wellbore logging tools can be used to image fractures and porous layers. In contrast, the techniques described in the present disclosure can use low frequency signals less than about 10 Hz. Conventional techniques for inferring hydraulic fracture conductivity can rely on installing a single component sensor on the surface. The sensor can be installed near, at, or in contact with the fluid within the wellhead to acquire tube waves. In some embodiments, a three-component sensor can be installed in contact with the outside of the wellhead. Since tube waves are guided waves that propagate along the wellbore, the wave motion includes x, y, and z components. These components can be fully captured by one or more three-component sensors. Thus, the techniques described in the present disclosure can utilize more comprehensive data to more accurately and robustly infer subsurface fracture information compared to conventional acquisition techniques that use single component sensors.

[0019] In some embodiments, a variety of techniques can be used to infer fracture connectivity using tube waves reflected from a hydraulic fracture during a fracturing treatment. For example, these techniques only require processing and interpreting a few seismic data channels recorded by a three-component sensor in contact with the outside of the wellhead. Results of the interpretation can be shown to provide a good match to fracturing treatment curves. These techniques can be used for real-time monitoring of hydraulic fracturing. The term “real-time” can correspond to events that occur within a specified time period (e.g., within hours, minutes, or seconds).

[0020] A primary goal of a hydraulic fracturing seismic (SWF) system is to provide real-time hydraulic fracture information during the hydraulic fracturing process to aid in decision making. During a conventional hydraulic fracturing operation, engineers can rely primarily on previous hydraulic fracturing information, ongoing hydraulic fracturing measurements, and well logs obtained during intervals of different hydraulic fracturing stages. This type of information cannot be obtained in real-time, which can leave engineers unable to make timely decisions. A typical microseismic monitoring method can require many sensors, which can greatly increase the cost, time, and labor required to process and interpret the data. The present disclosure presents cost-effective techniques for processing and interpreting seismic data collected, for example, by a single three-component sensor in contact with the exterior of a wellhead. The output of these techniques can include real-time flow conductivity parameters of a hydraulic fracture.

[0021] Data acquisition

[0022] Figure 1 is a geometry 100 of a well trajectory for a seismic while fracturing test according to some embodiments of the present disclosure. To obtain the geometry 100, a single three-component sensor can be placed on the surface in contact with the exterior of a wellhead 102. The sensor can be connected with a data storage device and a battery. Since the sensor has only three channels, the amount of data can be small even if the data recording can last for several days. In this way, data processing and interpretation can be part of real-time monitoring of a hydraulic fracture. Figure 1 The geometry 100 depicted in the middle can be with respect to x, y, and z components given, for example, by an east direction 104, a north direction 106, and a depth direction 108. The geometry 100 can include 26 segments 110 with a geometric midpoint 112. In one example, the geometric midpoint 112 can be between the 13th segment and the 14th segment of the 26 segments 110.

[0023] The three-component sensor can be designed to be sensitive to wideband. Incident tube waves can be excited by pressure pulses in the wellbore, microseismic events, or significant rapid fluid flow rate changes such as water hammer. For example, water hammer can be caused by rapid injection or release of large amounts of fluid, or sudden flow. The resulting excited tube waves can propagate as guided waves (e.g., Stoneley waves) in the wellbore. When these waves encounter the boundaries of the wellbore and the fracture, the guided waves can convert to a Croccoletis wave. Inside the fracture, the Croccoletis wave can reflect back and forth along the main fracture junction, forming a low-attenuation standing wave. The Croccoletis wave can convert back to a guided wave within the wellbore. Finally, the guided wave can reflect back to the surface and be recorded by the surface sensor.

[0024] Figure 2A and Figure 2Bis a plot showing raw data 200 recorded by a sensor according to some embodiments of the present disclosure. Figure 2A Three-component time series of raw data are shown, including traces from x-component 200a, y-component 200b, and z-component 200c, respectively. Components 200a-200c show Figure 2A A signal is shown plotted against amplitude 202 and time 204, where the signal corresponds to a continuous portion 206 of a wellbore (e.g., corresponding to portion 110).

[0025] Figure 2B Corresponding Fourier spectra of sensor recordings are shown for x-component, y-component, and z-component 200a-200c, respectively, at three channels. These spectra include features of equidistant spectra aligned at a frequency 208 of 150 Hz. The data can show consistent patterns at different stages after time windows of superimposed fracturing stages. Plots of x-component, y-component, and z-component 200a-200c are plotted against amplitude 202, time 204 (hours), frequency 208 (Hz), and amplitude 210.

[0026] Data processing workflow

[0027] To estimate fracture conductivity from reflected tube waves, raw data can be analyzed and processed. In some embodiments, a data processing workflow for estimating fracture conductivity can include the following. First, in a field data decoding step, raw data can be downloaded from a sensor and converted to a standard format, such as Society of Exploration Geophysicists (SEG) Y (SEGY) format. Second, in a SEGY trace header editing step, SEGY trace headers including coordinates and recording times can be added to the SEGY file. Third, in a time synchronization step, seismic recording times can be synchronized with fracturing treatment times. Fourth, in a data quality control step, dead traces and abnormal data samples can be removed. Fifth, in a time-frequency analysis step, a short-time Fourier transform can be used to analyze changes in Fourier spectra over time. Sixth, a resonance frequency extraction step can be performed. For example, at each time sample, resonance frequencies can be extracted from spectra by stacking spectra of different frequency intervals. Resonance frequencies are frequency intervals that produce the strongest stacked power.

[0028] Figure 3A and Figure 3B are plots 300a and 300b showing time-frequency analysis of seismic data according to some embodiments of the present disclosure. For example, data processing results are shown for seismic data acquired at the 13th fracturing stage. Figure 3AThree-component data is shown plotted against an amplitude axis 302 and a time axis 304, including data for the x-component, y-component, and z-component at the 13th hydraulic fracturing stage. Plot 300a can be obtained, for example, by applying a short-time Fourier transform to the three-component data and stacking their Fourier spectra. Plot 300 includes amplitudes for the x-component 306, y-component 308, and z-component 310. Figure 3B A final time-frequency spectrum is shown plotted against a frequency axis 312 and a time axis 304. Information can be recorded at high speed, but analysis can focus on signals less than 10 Hz.

[0029] Data interpretation

[0030] Figures 4A to 4C is a plot showing an interpretation of seismic data acquired at the 15th fracturing stage, according to some embodiments of the present disclosure. Figure 4A A time-frequency spectrum 400 is shown, including a plot showing the results of data interpretation. The behavior of the resonant frequency 404 (e.g., in Hz) plotted against a time axis 402 can be consistent with a pressure curve. As newly generated fractures release stress in the rock formation, the generation of fractures can be indicated by a pressure curve in which the pressure drops rapidly as the steady injection of slurry progresses. From the time-frequency spectrum, it can be determined that new fluid-filled fractures can generate new resonant frequencies. The reason for this is that the resonance arises from the back-and-forth reflections of the Krauklis wave within the space trapped by the perforation points and the fracture tips.

[0031] Figure 4B A plot of the results of interpretation 406 is shown against a time axis 408 and a fracture conductivity 410. For example, the resonant frequency can be extracted from the time spectrum, and a histogram of fracture conductivities can be computed, as shown in Figure 4B

[0032] Figure 4C A plot of the fracturing treatment curve 412 is shown. The trend of the histogram included in the fracturing treatment curve 412 is consistent with a pressure curve. To elaborate on this interpretation, the 15th fracturing stage can be divided into three periods.

[0033] During a perforation stage 414 (from time A 416 to time B 418), a slurry with low sand concentration can be pumped into the coiled tubing. Sand can be injected through nozzles into the target reservoir. In this period, the formation is dominated by natural fractures, and the fracture conductivities are low.

[0034] ​During the fracturing period 420 (from time B 418 to time C 422), the fracturing treatment can start at time B 418 and the pressure can increase as the slurry is injected. When some fractures are created, the pressure starts to decrease. To create more fractures, typically multiple rounds of slurry injection are required. In this example, there are five injections. The interpreted results demonstrate that the fracture conductivity gradually increases with the injection procedure.

[0035] During the fracturing period 424 (from time C 422 to time D 426), the flow rate and the connection pipe pressure decrease, while the sand concentration increases. The interpreted results show that, although the sand-laden fluid is injected gradually, the hydraulic fractures in the formation gradually decrease as the fracturing pressure decreases. Finally, as more and more proppant is injected into the formation, the fracture conductivity tends to stabilize.

[0036] The fracturing treatment curve 412 includes plots of the connection pipe pressure 428, the annulus pressure 430, the slurry rate 432, the sand concentration 434, and the liquid added 436. For example, pressures, such as the connection pipe pressure 428 and the annulus pressure 430, can be measured in megaPascals (MPa). For example, slurry rates, such as the slurry rate 432, can be measured in cubic meters per minute (m 3 / min). For example, sand concentrations, such as the sand concentration 434, can be measured in kilograms per cubic meter (kg / m 3 ). For example, the liquid added 436 can be measured in liters per minute (L / min). The plots 428, 430, 432, 434, and 436 are plotted relative to their own units.

[0037] The interpreted results can demonstrate that the fracture conductivity extracted from the resonant frequency has a high correlation with the fracturing treatment curve, which can provide valuable information about the quality of the fracturing in real time. In addition, the 13-part fracturing build-up time can be performed in a very short time. Throughout the fracturing treatment, the conductivity factor calculated from the resonant frequency can show a stable fracture distribution. The conductivity histograms of different stages can also be compared to evaluate the fracturing quality during the entire hydraulic fracture treatment.

[0038] In some implementations, the treatment can be modified to account for contamination issues. For example, during data collection, the reflected tube waves can be contaminated by environmental noise, such as traffic noise, human activity, and pump noise. These contaminations can be accounted for in the calculations and the resulting plots.

[0039] Figure 5is a flowchart of an example of a method 500 for generating an interpretation result based on synchronized seismic data and fracturing treatment time according to some embodiments of the present disclosure. For clarity of presentation, the description that follows generally describes the method 500 in the context of other figures in this description. However, it will be appreciated that the method 500 can be performed, where appropriate, by any suitable system, environment, software, and hardware, or a combination of these, for example. In some embodiments, various steps of the method 500 can be performed in parallel, combined, looped, or in any order.

[0040] At 502, a standard format seismic dataset of sensor readings obtained from a three-component sensor is generated. For example, the sensor readings obtained from the three-component sensor include signals that can be less than 10 hertz. The three-component sensor can be located outside of a wellhead, such as the wellhead 102. The sensor readings can be obtained according to a geometry of a well trajectory 100 of a fracturing seismic test during a fracturing that occurs in a well. Generating the standard format seismic dataset can include, for example, receiving raw data corresponding to the sensor readings obtained by the three-component sensor, and generating the standard format seismic dataset by converting the raw data corresponding to the sensor readings into the standard format. For example, the standard format can be a Society of Exploration Geophysicists (SEG) Y (SEGY) format. The method 500 proceeds from 502 to 504.

[0041] At 504, coordinates and recording times corresponding to the sensor readings are added to the standard format seismic dataset. As an example, adding the coordinates and recording times can include updating a SEGY header of the standard format seismic dataset with the coordinates and recording times. The method 500 proceeds from 504 to 506.

[0042] At 506, synchronized seismic data is generated from the standard format seismic dataset by synchronizing the seismic recording times with the fracturing treatment times. Since the sensor is placed on the surface, the synchronization process is simple and can be performed by setting both the recording times and the fracturing times to GPS (Global Positioning System) times. The method 500 proceeds from 506 to 508.

[0043] At 508, quality-controlled synchronized seismic data is generated by removing dead traces and abnormal data samples from the synchronized seismic data. The abnormal data can be automatically detected according to their statistical properties, including but not limited to mean, variance, skewness, and kurtosis. The method 500 proceeds from 508 to 510.

[0044] At 510, a time-frequency analysis is performed on the quality-controlled simultaneous seismic data, including performing a short-time Fourier transform to analyze the variation of the Fourier spectrum with time. The procedure to compute the short-time Fourier transform is to divide a longer time signal into equal-length shorter segments, and then compute the Fourier transform separately on each shorter segment. Other time-frequency analysis tools can be used, such as the Gabor transform and the S-transform. The method 500 proceeds from 510 to 512.

[0045] At 512, based on the time-frequency analysis, a resonance frequency is extracted from the time-frequency spectrum at each time sample. For each time sample, the procedure includes applying automatic gain control (AGC) to the spectrum, stacking the spectrum with different intervals, and finally picking the frequency interval with the highest stacked energy as the estimated resonance frequency, where the AGC is applied to increase the amplitude of weak frequency components using a sliding frequency window. The procedure is performed for all time samples. The method 500 proceeds from 512 to 514.

[0046] At 514, the interpreted results based on the extraction are presented to a user. For example, presenting the interpreted results based on the extraction can include generating a histogram of the fracture conductivity. This information can be displayed to a user (e.g., an engineer associated with a hydraulic fracturing operation) in a user interface. After 514, the method 500 can stop.

[0047] Figure 6 FIG. 6 is a block diagram of an example computer system 600 for providing computing functionality associated with the described algorithms, methods, functions, processes, flows, and procedures described in the present disclosure, in accordance with some embodiments of the present disclosure. The illustrated computer 602 is intended to encompass any computing device such as a server, desktop computer, laptop / notebook computer, wireless data port, smart phone, personal data assistant (PDA), tablet computing device, or one or more processors of any of these devices, including physical instances, virtual instances, or both. The computer 602 can include input devices, such as a small keyboard, keyboard, and touchscreen, that can accept user information. Also, the computer 602 can include output devices that can present information associated with the operation of the computer 602. This information can include digital data, visual data, audio information, or a combination of information. The information can be presented in a graphical user interface (UI) (or GUI).

[0048] The computer 602 can act as a client, a network component, a server, a database, a persistence, or a component of a computer system for performing the subject matter described in the present disclosure. The illustrated computer 602 is communicatively coupled with a network 630. In some embodiments, one or more components of the computer 602 can be configured to operate within different environments, including cloud-computing based environments, local environments, global environments, and combinations of environments.

[0049] At the highest level, the computer 602 is an electronic computing device operable to receive, transmit, process, store, and manage data and information associated with the described subject matter. According to some implementations, the computer 602 can also include, be communicably coupled to, or operate in association with an application server, an email server, a web server, a caching server, a streaming data server, or a combination of servers.

[0050] The computer 602 can receive requests from client applications (executing on another computer 602, for example), across a network 630. The computer 602 can respond to the received requests by processing the requests using software applications. Requests can also be sent to the computer 602 from internal users (e.g., from a command console), external (or third) parties, automated applications, entities, individuals, systems, and computers.

[0051] Each of the components of the computer 602 can communicate using the system bus 603. In some implementations, any or all of the components of the computer 602, including hardware or software components, can interface with each other or the interface 604 (or a combination thereof) over the system bus 603. The interface can use an application programming interface (API) 612, a service layer 613, or a combination of the API 612 and the service layer 613. The API 612 can include specifications for routines, data structures, and object classes. The API 612 can be computer language-independent or dependent. The API 612 can refer to a complete interface, a single function, or a group of APIs.

[0052] The service layer 613 can provide software services to the computer 602 and other components that can be communicably coupled to the computer 602, whether illustrated or not. All software services provided by the service layer 613 can be accessible through defined interfaces. For example, the interfaces can be software that enables a software consumer to access and use the defined functionality of the accessible software provider to exchange information. For example, the interface can be software written in JAVA, C++, or a language that provides data in extensible markup language (XML) format. Although illustrated as an integrated component of the computer 602, in alternative implementations, the API 612 or the service layer 613 can be separate from the computer 602 and able to communicate with the computer 602 and other components over a network, as desired. Moreover, any or all parts of the API 612 or the service layer 613 can be implemented as child or sub-modules of another software module, enterprise application, or hardware module without departing from the scope of this disclosure.

[0053] The computer 602 includes the interface 604. Although illustrated as an Figure 6The interface 604, while shown as a single interface 604, can use two or more interfaces 604, depending on particular needs, desires, or particular embodiments of the computer 602 and the described functionality. The interface 604 can be used by the computer 602 for communicating internal commands between components of the computer 602 and for communicating with other systems (not shown or illustrated) that are connected to the network 630 in a distributed environment. In general, the interface 604 can include or use logic that is encoded in software or hardware (or a combination of software and hardware) operable to communicate with the network 630, or use logic that is implemented using the same. More specifically, the interface 604 can include software that supports one or more communication protocols associated with the communication. Thus, the network 630 or the hardware of the interface can be operable to communicate physical signals internally and externally to the computer 602.

[0054] The computer 602 includes a processor 605. While one processor 605 is shown in the computer 602, two or more processors 605 can be used according to the particular needs, desires, or particular embodiments of the computer 602 and the described functionality. Figure 6 The processor 605, while shown as a single processor 605, can comprise two or more processors 605, depending on the particular needs, desires, or particular embodiments of the computer 602 and the described functionality. In general, the processor 605 can execute instructions and can manipulate data stored in the computer 602, including using algorithms, methods, functions, processes, flows, and procedures as described in the present disclosure.

[0055] The computer 602 also includes a database 606 that can hold data for the computer 602 and other components (not shown or illustrated) that are connected to the network 630. For example, the database 606 can be an in-memory, conventional, or a database that stores data consistent with the present disclosure. In some embodiments, the database 606 can be a combination of two or more different database types (e.g., a hybrid in-memory database and conventional database) according to the particular needs, desires, or particular embodiments of the computer 602 and the described functionality. Figure 6 The database 606, while shown as a single database 606, can use two or more databases (of the same type, different types, or a combination of types) according to the particular needs, desires, or particular embodiments of the computer 602 and the described functionality. While the database 606 is shown as an internal component of the computer 602, in alternate embodiments, the database 606 can be external to the computer 602.

[0056] The computer 602 also includes a memory 607 that can hold data for the computer 602 or a combination of components (not shown or illustrated) that are connected to the network 630. The memory 607 can store any data consistent with the present disclosure. In some embodiments, the memory 607 can be a combination of two or more different memory types (e.g., a combination of semiconductor memory and magnetic storage) according to the particular needs, desires, or particular embodiments of the computer 602 and the described functionality. Figure 6The memory 607, which can be single or a combination of memories 607, can be used to store instructions executable by the processor 603, as well as data files generated or used by the processor 603, in accordance with the particular needs, desires, or particular implementations of the computer 602, and the described functionality. Although illustrated as a single memory 607 in the computer 602, the memory 607 can be distributed across several components if desired. For example, some application data, one or more operating systems, and the like can be stored on the computer 602, while other application data can be stored on a storage device 609.

[0057] The application 608 can be an algorithmic software engine providing functionality in accordance with the particular needs, desires, or particular implementations of the computer 602 and the described functionality. For example, the application 608 can be used as one or more components, modules, or applications. Further, although illustrated as a single application 608, the application 608 can be implemented as multiple applications 608 on the computer 602. Additionally, although illustrated as internal to the computer 602, in alternative implementations, the application 608 can be external to the computer 602.

[0058] The computer 602 can also include a power supply 614. The power supply 614 can include a rechargeable or non-rechargeable battery that can be configured to be either user- or non-user-replaceable. In some implementations, the power supply 614 can include power-conversion and management circuits including recharging, standby, and power-management functionality. In some implementations, the power supply 614 can include a power plug to allow the computer 602 to be plugged into a wall socket or power supply to, for example, power the computer 602 or charge a rechargeable battery.

[0059] There can be any number of computers 602 associated with or external to the computer system containing the computer 602, with each computer 602 communicating over the network 630. Further, the terms "client," "user," and other appropriate terminology can be used interchangeably as appropriate, without departing from the scope of the present disclosure. Additionally, the present disclosure contemplates that many users can use one computer 602 and that one user can use multiple computers 602.

[0060] The described subject matter implementations can include one or more features alone or in combination.

[0061] For example, in a first implementation, a computer-implemented method includes the following. A standard format seismic dataset of sensor readings obtained from a three-component sensor is generated. Coordinates and recording times corresponding to the sensor readings are added to the standard format seismic dataset. Synchronized seismic data is generated from the standard format seismic dataset by synchronizing the recording times of the seismic data with the time of a fracturing treatment. Quality-controlled synchronized seismic data is generated by removing dead traces and abnormal data samples from the synchronized seismic data. A time-frequency analysis is performed on the quality-controlled synchronized seismic data, including performing a short-time Fourier transform to analyze changes in Fourier spectra over time. Based on the time-frequency analysis, a resonance frequency is extracted from each frequency spectrum at different time samples. An interpretation result based on the extraction is presented to a user.

[0062] The foregoing and other described implementations can each include one or more of the following features:

[0063] A first feature, combinable with any of the above or below features, wherein the three-component sensor is located outside of a wellhead.

[0064] A second feature, combinable with any of the above or below features, wherein generating the standard format seismic dataset includes: receiving raw data corresponding to the sensor readings obtained by the three-component sensor; and generating the standard format seismic dataset by converting the raw data corresponding to the sensor readings into the standard format.

[0065] A third feature, combinable with any of the above or below features, wherein the standard format is Society of Exploration Geophysicists (SEG) Y (SEGY) format.

[0066] A fourth feature, combinable with any of the above or below features, wherein adding the coordinates and the recording times includes updating SEGY headers of the standard format seismic dataset with the coordinates and the recording times.

[0067] A fifth feature, combinable with any of the above or below features, wherein presenting the interpretation result based on the extraction includes generating a fracture conductivity histogram.

[0068] A sixth feature, combinable with any of the above or below features, wherein the sensor readings obtained from the three-component sensor include signals less than 10 Hertz.

[0069] In a second implementation, a non-transitory computer-readable medium stores one or more instructions executable by a computer system to perform operations including generating a standard format seismic data set of sensor readings obtained from a three-component sensor. Adding coordinates and recording times corresponding to the sensor readings to the standard format seismic data set. Generating synchronized seismic data from the standard format seismic data by synchronizing the seismic recording times with a fracturing treatment time. Generating quality-controlled synchronized seismic data by removing dead traces and abnormal data samples from the synchronized seismic data. Performing a time-frequency analysis on the quality-controlled synchronized seismic data, including performing a short-time Fourier transform to analyze changes in Fourier spectra over time. Extracting a resonance frequency from each frequency spectrum at different time samples based on the time-frequency analysis. Presenting an interpretation result based on the extracting to a user.

[0070] The foregoing and other described implementations can each include one or more of the following features:

[0071] A first feature, combinable with any of the above or below features, wherein the three-component sensor is located outside a wellhead.

[0072] A second feature, combinable with any of the above or below features, wherein generating the standard format seismic data set includes receiving raw data corresponding to the sensor readings obtained by the three-component sensor, and generating the standard format seismic data set by converting the raw data corresponding to the sensor readings to the standard format.

[0073] A third feature, combinable with any of the above or below features, wherein the standard format is a Society of Exploration Geophysicists (SEG) Y (SEGY) format.

[0074] A fourth feature, combinable with any of the above or below features, wherein adding the coordinates and the recording times includes updating SEGY headers of the standard format seismic data set with the coordinates and the recording times.

[0075] A fifth feature, combinable with any of the above or below features, wherein presenting the interpretation result based on the extracting includes generating a fracture conductivity histogram.

[0076] A sixth feature, combinable with any of the above or below features, wherein the sensor readings obtained from the three-component sensor include signals less than 10 hertz.

[0077] In a third implementation, a computer-implemented system includes one or more processors and a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors. The programming instructions instruct the one or more processors to perform operations including generating a standard format seismic dataset of sensor readings obtained from a three-component sensor. Adding coordinates and recording times corresponding to the sensor readings to the standard format seismic dataset. Generating synchronized seismic data from the standard format seismic dataset by synchronizing seismic recording times with fracturing treatment times. Generating quality-controlled synchronized seismic data by removing dead traces and abnormal data samples from the synchronized seismic data. Performing time-frequency analysis on the quality-controlled synchronized seismic data, including performing a short-time Fourier transform to analyze changes in Fourier spectra over time. Extracting a resonant frequency from each frequency spectrum at different time samples based on the time-frequency analysis. Presenting an interpretation result based on the extracting to a user.

[0078] The foregoing and other described implementations can each include one or more of the following features:

[0079] A first feature, combinable with any of the above or below features, wherein the three-component sensor is located outside a wellhead.

[0080] A second feature, combinable with any of the above or below features, wherein generating the standard format seismic dataset includes receiving raw data corresponding to the sensor readings obtained by the three-component sensor, and generating the standard format seismic dataset by converting the raw data corresponding to the sensor readings to the standard format.

[0081] A third feature, combinable with any of the above or below features, wherein the standard format is Society of Exploration Geophysicists (SEG) Y (SEGY) format.

[0082] A fourth feature, combinable with any of the above or below features, wherein adding the coordinates and the recording times includes updating SEGY headers of the standard format seismic dataset with the coordinates and the recording times.

[0083] A fifth feature, combinable with any of the above or below features, wherein presenting the interpretation result based on the extracting includes generating a fracture conductivity histogram.

[0084] Embodiments of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, in tangibly-embodied computer software or firmware, in computer hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Software implementations of the described subject matter can be implemented as one or more computer programs. Each computer program can include one or more modules of computer program instructions encoded on a tangible non-transitory computer- readable computer storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively or additionally, the program instructions can be encoded in / on an artificially generated propagated signal, for example, a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. The computer storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of computer storage mediums.

[0085] The terms“data processing apparatus,”“computer,” and“electronic computer device” (or equivalent as understood by one of ordinary skill in the art) refer to data processing hardware. For example, a data processing apparatus can include all kinds of apparatuses, devices, and machines for processing data, including by way of example a programmable processor, a computer, or multiple processors or computers. The apparatus can also include special purpose logic, for example, a central processing unit (CPU), a field programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). In some embodiments, a data processing apparatus or special purpose logic can be hardware-based (for example, a microprocessor, an ASIC, or a FPGA) or software-based (for example, a programmable processor or a computer) or a combination of both. The apparatus can optionally include code that creates an execution environment for computer programs, for example, code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of execution environments. The disclosure contemplates a data processing apparatus that has or accesses code that creates an execution environment for programs, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of execution environments.

[0086] A computer program, which can also be referred to or described as a program, software, a software application, a module, a software module, a script, or code, can be written in any form of programming language. The programming language can include, for example, a compiled language, an interpreted language, declarative language, or a procedural language. The program can be deployed in any form, including as a stand-alone program, a module, a component, a subroutine, or a

[0087] The methods, procedures, or logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform functions by operating on input data and generating output. The methods, procedures, or logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., a CPU, an FPGA, or an ASIC.

[0088] Computers suitable for the execution of a computer program can be based on one or more general and special purpose microprocessors and other kinds of CPUs. The elements of a computer are a CPU for executing instructions and one or more memory devices for storing instructions and data. Generally, a CPU can receive instructions and data from memory and write data to memory. A computer can also include, or be operatively coupled to, one or more mass storage devices for storing data. In some implementations, a computer can receive data from and transmit data to mass storage devices, including for example, a magnetic, magneto-optical or optical disk. Also, a computer can be embedded in another device, e.g., a mobile telephone, a PDA, a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a portable storage device (e.g., a universal serial bus (USB) flash drive).

[0089] Computer-readable media (transitory or non-transitory, as appropriate) suitable for storing computer program instructions and data includes all forms of permanent / non-permanent and volatile / non-volatile memory, media and memory devices. Computer-readable media can include, for example, semiconductor memory devices such as random access memory (RAM), read only memory (ROM), phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), erasable programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), and flash memory devices. Computer-readable media can also include, for example, magnetic devices such as tape, cartridges, cassettes, and internal / external disks. Computer-readable media can also include magneto-optical disks and optical memory devices and technologies, including, for example, digital video disk (DVD), CD-ROM, DVD+ / -R, DVD-RAM, DVD-ROM, HD-DVD, and Blu-ray. Memory can store various objects or data, including caches, classes, frameworks, applications, modules, backup data, jobs, web pages, web page templates, data structures, database tables, repositories, and dynamic information. Types of objects and data that can be stored in memory include parameters, variables, algorithms, instructions, rules, constraints, and references. Additionally, memory can include log files, policy files, security or access files, and reporting files. Processors and memory can be supplemented by, or incorporated into, special purpose logic circuitry.

[0090] Implementations of the subject matter described in this disclosure can be implemented on a computer having a display device for providing a user with a graphical user interface, including displaying information to the user (and receiving input from the user). Types of display devices can include, for example, cathode ray tubes (CRT), liquid crystal displays (LCD), light emitting diodes (LED), and plasma monitors. Display devices can include keyboards and pointing devices, including, for example, mice, track balls, or touch pads. User input can also be provided to the computer through the use of a touch screen, such as a tablet computer surface with pressure sensitivity or a multi-touch screen using capacitive or inductive sensing. Other kinds of devices can be used to provide for interaction with a user as well, including receiving user feedback including, for example, sensory feedback, including visual feedback, auditory feedback, or tactile feedback. Input from a user can be received in the form of acoustic, speech, or tactile inputs. Additionally, a computer can interact with a user by sending documents to and receiving documents from a device used by the user. For example, a computer can send web pages to a web browser on a user's client device in response to receiving requests from the web browser.

[0091] The term "graphical user interface" or "GUI" can be used in the singular or the plural to describe one or more graphical user interfaces and each of the displays of a particular graphical user interface. Therefore, a GUI can be an interface that processes information and efficiently presents the processed information to a user, including, but not limited to, a web browser, a touch screen, or a command line interface (CLI). Generally, a GUI can include a number of user interface (UI) elements, some or all of which can be associated with a web browser, such as interactive fields, drop-down lists, and buttons. These and other UI elements can be related to or represent the functionality of the web browser.

[0092] Implementations of the subject matter described in this specification can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having one or both of a graphical user interface or a web browser through which a user can interact with an implementation of the subject matter described in this specification, or a combination of one or more such computing systems. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network, such as a local area network (LAN) and a wide area network (WAN), but can be interconnected by any other communication medium. Examples of communication networks include a wired communication network, a wireless communication network, a metropolitan area network (MAN), a wide area network (WAN), a local area network (LAN), a telephone line network, a wireless personal area network (WPAN), a wide area file service (WAFS), a global area network (GAN), a content distribution network (CDN), the Internet, or a combination of networks. The network can communicate communication types such as Internet Protocol (IP) packets, frame relay frames, Asynchronous Transfer Mode (ATM) cells, voice, video, data, or a combination of these and other communication types.

[0093] The computing system can include clients and servers. A client and server can generally be remote from each other and typically interact through a communication network. The relationship of client and server can arise by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0094] The clustered file system can be any file system type that is accessible from multiple servers for reading and updating. Locking or consistency tracking can not be necessary as the locking of the swap file system can be done at the application layer. Additionally, the Unicode data files can be different from the non-Unicode data files.

[0095] While this specification contains many specific implementation details, these should not be construed as limitations on the scope of what can be claimed, but rather as descriptions of features that can be specific to particular embodiments. Certain features that are described in this specification in the context of separate embodiments can also combine in other embodiments. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features can be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination and the claimed combination can be directed to a subcombination or variation of a subcombination.

[0096] Particular embodiments of the subject matter have been described. Other embodiments, alterations, and permutations of the described embodiments are within the scope of the appended claims as will be apparent to those skilled in the art. While operations are depicted in the drawings or claims in a particular, chronological order, this should not be understood as requiring or implying that the order of the operations is anything other than as will be convenient, easy, or expedient for that process. In some cases, the processes described can be performed in an order different from the order described.

[0097] Furthermore, the separation or integration of various system modules and components in the previously described embodiments should not be understood as requiring such separation or integration in all embodiments. It will be appreciated that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0098] Accordingly, the previously described example embodiments do not define or limit the disclosure. Other changes, modifications, and alterations are also possible.

[0099] Moreover, any claimed embodiment is intended to be applicable to at least one computer-implemented method; a non-transitory computer-readable medium storing computer-readable instructions for performing the computer-implemented method; and a computer system comprising a computer memory interoperably coupled with a hardware processor, the hardware processor being configured to perform the computer-implemented method or the instructions stored on the non-transitory computer-readable medium.

Claims

1. A computer-implemented method comprising: generating a seismic data set in a standard format of sensor readings obtained from a three-component sensor, the seismic data set including x-component, y-component, and z-component of a wave motion of a guided wave propagating along the wellbore; Adding the x, y, z coordinates and recording times corresponding to these sensor readings to the seismic dataset in the standard format; using a standard format seismic dataset of the sensor readings, generating synchronized seismic data from the standard format seismic dataset by synchronizing seismic recording times with fracturing treatment times; generating quality-controlled synchronous seismic data by removing dead channels and anomalous data samples from the synchronous seismic data; performing time-frequency analysis on the quality-controlled synchronous seismic data, including performing a short-time Fourier transform to analyze changes in the Fourier spectrum over time; extracting a resonant frequency from each spectrum at different time samples and based on the time-frequency analysis, including using a sliding frequency window to increase the amplitude of weak frequency components of the quality-controlled synchronous seismic data, including applying automatic gain control to the spectrum, stacking the spectrum with different intervals, and selecting a frequency interval with the highest stack energy as the estimated resonant frequency; as well as The interpretation result based on the extraction is presented to the user.

2. The computer-implemented method of claim 1 , wherein: The three-component sensor is located outside the wellhead.

3. The computer-implemented method of claim 1 , wherein: The earthquake datasets generated in this standard format include: receiving raw data corresponding to sensor readings obtained by the three-component sensor; and The seismic dataset in the standard format is generated by converting the raw data corresponding to the sensor readings into a standard format.

4. The computer-implemented method of claim 3, wherein: The standard format is the Society of Exploration Geophysicists SEGY format.

5. The computer-implemented method of claim 4, wherein: Adding the coordinates and the recording times includes updating the SEGY trace header of the seismic data set in the standard format with the coordinates and the recording times.

6. The computer-implemented method of claim 1 , wherein: Presenting interpretation results based on this extraction includes generating a fracture conductivity histogram.

7. The computer-implemented method of claim 1 , wherein: Sensor readings obtained from the three-component sensor include signals less than 10 Hz.

8. A non-transitory computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising: generating a seismic data set in a standard format of sensor readings obtained from a three-component sensor, the seismic data set including x-component, y-component, and z-component of a wave motion of a guided wave propagating along the wellbore; adding the coordinates and recording times corresponding to these sensor readings to the seismic dataset in this standard format; using a standard format seismic dataset of the sensor readings, generating synchronized seismic data from the standard format seismic dataset by synchronizing seismic recording times with fracturing treatment times; generating quality-controlled synchronous seismic data by removing dead channels and anomalous data samples from the synchronous seismic data; performing time-frequency analysis on the quality-controlled synchronous seismic data, including performing a short-time Fourier transform to analyze changes in the Fourier spectrum over time; extracting a resonant frequency from each spectrum at different time samples and based on the time-frequency analysis, including using a sliding frequency window to increase the amplitude of weak frequency components of the quality-controlled synchronous seismic data, including applying automatic gain control to the spectrum, stacking the spectrum with different intervals, and selecting a frequency interval with the highest stack energy as the estimated resonant frequency; as well as The interpretation result based on the extraction is presented to the user.

9. The non-transitory computer readable medium of claim 8, wherein: The three-component sensor is located outside the wellhead.

10. The non-transitory computer readable medium of claim 8, wherein: The earthquake datasets generated in this standard format include: receiving raw data corresponding to sensor readings obtained by the three-component sensor; and The seismic dataset in the standard format is generated by converting the raw data corresponding to the sensor readings into a standard format.

11. The non-transitory computer readable medium of claim 10, wherein: The standard format is the Society of Exploration Geophysicists SEGY format.

12. The non-transitory computer readable medium of claim 11, wherein: Adding the coordinates and the recording times includes updating the SEGY trace header of the seismic data set in the standard format with the coordinates and the recording times.

13. The non-transitory computer readable medium of claim 8, wherein: Presenting interpretation results based on this extraction includes generating a fracture conductivity histogram.

14. The non-transitory computer readable medium of claim 8, wherein: Sensor readings obtained from the three-component sensor include signals less than 10 Hz.

15. A computer-implemented system comprising: one or more processors; as well as a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors, the programming instructions directing the one or more processors to perform operations including: generating a seismic data set in a standard format of sensor readings obtained from a three-component sensor, the seismic data set including x-component, y-component, and z-component of a wave motion of a guided wave propagating along the wellbore; adding the coordinates and recording times corresponding to these sensor readings to the seismic dataset in this standard format; using a standard format seismic dataset of the sensor readings, generating synchronized seismic data from the standard format seismic dataset by synchronizing seismic recording times with fracturing treatment times; generating quality-controlled synchronous seismic data by removing dead channels and anomalous data samples from the synchronous seismic data; performing time-frequency analysis on the quality-controlled synchronous seismic data, including performing a short-time Fourier transform to analyze changes in the Fourier spectrum over time; extracting a resonant frequency from each spectrum at different time samples and based on the time-frequency analysis, including using a sliding frequency window to increase the amplitude of weak frequency components of the quality-controlled synchronous seismic data, including applying automatic gain control to the spectrum, stacking the spectrum with different intervals, and selecting a frequency interval with the highest stack energy as the estimated resonant frequency; as well as The interpretation result based on the extraction is presented to the user.

16. The computer-implemented system of claim 15, wherein: The three-component sensor is located outside the wellhead.

17. The computer-implemented system of claim 15, wherein: The earthquake datasets generated in this standard format include: receiving raw data corresponding to sensor readings obtained by the three-component sensor; and The seismic dataset in the standard format is generated by converting the raw data corresponding to the sensor readings into a standard format.

18. The computer-implemented system of claim 17, wherein: The standard format is the Society of Exploration Geophysicists SEGY format.

19. The computer-implemented system of claim 18, wherein: Adding the coordinates and the recording times includes updating the SEGY trace header of the seismic data set in the standard format with the coordinates and the recording times.

20. The computer-implemented system of claim 15, wherein: Presenting interpretation results based on this extraction includes generating a fracture conductivity histogram.

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