Fault determination method and device, equipment and medium

Abstract

The invention discloses a fault determination method and device, equipment and a medium. The method comprises the following steps: determining a first preset number of sub-azimuth data volumes and a second preset number of frequency division data volumes of a target block according to a pre-stack common reflection point gather and post-stack seismic data of the target block; determining the dominant orientation of the target layer in the target block according to the coherent attribute of each sub-orientation data body; determining the dominant frequency of the target layer according to the coherence attribute of each frequency division data body; and determining whether the target layer is a fault according to the dominant orientation and the dominant frequency. According to the technical scheme, the prestack common reflection point gather and the post-stack seismic data of the target block are fully utilized to determine the dominant orientation and the dominant frequency of the target layer, a reasonable and effective judgment criterion is provided for fault identification, and the accuracy of fault identification is improved.

Description

Technical Field

[0001] The present application relates to the field of geophysical exploration technology, and in particular to a method, device, equipment and medium for determining a fault. Background Art

[0002] Faults are structures where the rock blocks on both sides of the crust undergo significant relative displacement after being fractured by stress, and they contain abundant oil and gas resources. At present, with the breakthrough of marine and continental shale oil and gas in many basins in China, the design and engineering implementation of horizontal wells have become the key to increasing the production of such unconventional oil and gas reservoirs, and the development of small faults has seriously affected the design and engineering implementation of horizontal wells; moreover, the mature exploration blocks of some old oil fields in China have entered the stage of residual oil production, and finding micro-structures controlled by small faults is the key to increasing reserves. Therefore, accurate identification of faults is an important research work in oil and gas exploration.

[0003] Regarding fault detection methods, most scholars use seismic structural attributes such as coherence, curvature and dip to carry out fault detection. Such attributes can effectively predict faults above 20 meters; some scholars use structural guidance filtering, ant body and other attributes to carry out fault detection. Such attributes can effectively predict faults above 10 meters. Although the above attributes and methods have shown obvious effects in large fault detection, there are still the following shortcomings in fault detection: 1) Such fault detection attributes and new methods are heavily dependent on the change of seismic phase axis. Faults below 10 meters do not form obvious seismic reflection characteristics on the seismic profile, so conventional attributes and some new methods in recent years are difficult to use the change of seismic phase axis to predict faults below 10 meters. 2) Conventional post-stack seismic data often have a low main frequency and lose some pre-stack azimuth information, which is not conducive to the detection of faults below 10 meters.

[0004] Therefore, how to provide a technical solution for effectively and accurately identifying faults is a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0005] The present application provides a method, device, equipment and medium for determining a fault, which fully utilizes the pre-stack common reflection point gathers and post-stack seismic data of the target block to determine the dominant orientation and dominant frequency of the target layer, provides a reasonable and effective judgment criterion for fault identification, and improves the accuracy of fault identification.

[0006] According to one aspect of the present application, a method for determining a fault is provided, the method comprising:

[0007] Determine a first preset number of azimuth data volumes and a second preset number of frequency data volumes of the target block according to the pre-stack common reflection point gathers and post-stack seismic data of the target block;

[0008] Determining the dominant orientation of the target layer in the target block according to the coherent attributes of each of the sub-orientation data volumes;

[0009] Determining the dominant frequency of the target layer according to the coherent properties of each of the frequency-divided data volumes;

[0010] Whether the target layer is a fault is determined according to the dominant orientation and the dominant frequency.

[0011] According to another aspect of the present application, a device for determining a fault is provided, the device comprising:

[0012] A seismic data volume division module is used to determine a first preset number of azimuth data volumes and a second preset number of frequency data volumes of the target block according to the pre-stack common reflection point gathers and post-stack seismic data of the target block;

[0013] A dominant orientation determination module, used to determine the dominant orientation of the target layer in the target block according to the coherent attributes of each of the sub-orientation data volumes;

[0014] A dominant frequency determination module, used to determine the dominant frequency of the target layer according to the coherent attributes of each of the frequency-divided data bodies;

[0015] A fault identification module is used to determine whether the target layer is a fault according to the dominant orientation and the dominant frequency.

[0016] According to another aspect of the present application, a device for determining a fault is provided, the device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the fault determination method described in any embodiment of the present application.

[0020] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the fault determination method described in any embodiment of the present application when executed.

[0021] The technical solution provided by the present application determines the first preset number of sub-azimuth data bodies and the second preset number of sub-frequency data bodies of the target block according to the pre-stack common reflection point gathers and post-stack seismic data of the target block; determines the dominant azimuth of the target layer in the target block according to the coherent properties of each sub-azimuth data body; determines the dominant frequency of the target layer according to the coherent properties of each sub-frequency data body; determines whether the target layer is a fault according to the dominant azimuth and dominant frequency. The technical solution makes full use of the pre-stack common reflection point gathers and post-stack seismic data of the target block to determine the dominant azimuth and dominant frequency of the target layer, provides a reasonable and effective judgment criterion for fault identification, and improves the accuracy of fault identification.

[0022] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 A flow chart of a method for determining a fault provided in Example 1 of the present application;

[0025] Figure 2 A flow chart of a method for determining a fault provided in Embodiment 2 of the present application;

[0026] Figure 3 A schematic diagram of a first fault detection plane provided in Embodiment 2 of the present application;

[0027] Figure 4a A schematic diagram of a second fault detection plane provided in Embodiment 2 of the present application;

[0028] Figure 4b Another schematic diagram of a first fault detection plane provided in Embodiment 2 of the present application;

[0029] Figure 5 A schematic diagram of the structure of a fault determination device provided in Embodiment 3 of the present application;

[0030] Figure 6 It is a structural schematic diagram of a device for implementing a method for determining a fault in an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0032] It should be noted that the terms "first", "second", "third", "candidate", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or precedence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] Embodiment 1

[0034] Figure 1 This is a flow chart of a method for determining a fault provided in the first embodiment of the present application. This embodiment can be applied to the detection of small faults in oil and gas exploration and development. The method can be executed by a fault determination device, which can be implemented in the form of hardware and / or software. The fault determination device can be configured in a device with data processing capabilities. Figure 1 As shown, the method includes:

[0035] S110, determining a first preset number of azimuth data volumes and a second preset number of frequency data volumes of the target block according to pre-stack common reflection point gathers and post-stack seismic data of the target block.

[0036] Among them, the pre-stack common reflection point gather is a gather composed of corresponding recording traces with common depth reflection points when the reflection interface is horizontal in the pre-stack seismic data. The post-stack seismic data can be the data after the seismic data is denoised and amplitude normalized. The azimuth data volume can be the amplitude data volume at different axis azimuths, and the frequency data volume can be the amplitude data volume at different frequencies.

[0037] Specifically, the first preset number and the second preset number can be determined according to actual needs.

[0038] As an optional but non-limiting implementation, according to the pre-stack common reflection point gathers and post-stack seismic data of the target block, a first preset number of azimuth data volumes and a second preset number of frequency data volumes of the target block are determined, including but not limited to the following steps A1 to A2:

[0039] Step A1: dividing a first preset number of sub-azimuth data volumes according to a pre-stack common reflection point gather of a target block at preset angle intervals; wherein the preset angle is determined according to the fault strike of the target block.

[0040] Since the pre-stack common reflection point gather contains rich seismic azimuth information, the pre-stack common reflection point gather can be divided according to the preset angle interval to obtain a first preset number of sub-azimuth data volumes. In an embodiment of the present invention, the first preset number of sub-azimuth data volumes can be divided according to the preset angle interval based on the quality analysis of the pre-stack common reflection point gather and the main strike of the fault in the target block.

[0041] Exemplarily, the pre-stack common reflection point gathers can be divided into 30° intervals within the range of 0° to 180° to obtain a 0° azimuth data volume, a 30° azimuth data volume, a 60° azimuth data volume, a 90° azimuth data volume, a 120° azimuth data volume, and a 150° azimuth data volume, respectively.

[0042] Step A2: dividing the post-stack seismic data of the target block into a second preset number of frequency-divided data volumes according to preset frequency intervals.

[0043] Since the frequency characteristics in the post-stack seismic data can better highlight the anisotropy, the post-stack seismic data can be divided according to the preset frequency interval to obtain a second preset number of divided frequency data volumes. In an embodiment of the present invention, the post-stack seismic data of the target block can be divided into a second preset number of divided frequency data volumes according to the preset frequency interval through the main frequency analysis.

[0044] For example, the post-stack seismic data can be divided at intervals of 10 Hz from 10 Hz to 60 Hz to obtain a 10 Hz frequency division data volume, a 20 Hz frequency division data volume, a 30 Hz frequency division data volume, a 40 Hz frequency division data volume, a 50 Hz frequency division data volume and a 60 Hz frequency division data volume.

[0045] The beneficial effect of the above technical solution is that by fully considering the advantages of pre-stack common reflection point gathers in azimuth and the advantages of post-stack seismic data in frequency, the division of azimuth data volumes and frequency data volumes is made more scientific and reasonable, which not only effectively utilizes pre-stack common reflection point gathers and post-stack seismic data, but also is more conducive to the identification of faults.

[0046] S120: Determine the dominant orientation of the target layer in the target block according to the coherent attributes of each of the sub-orientation data volumes.

[0047] Among them, the coherence attribute can be used to represent the discontinuity characteristics of the data body and can be calculated by a preset coherence algorithm, such as an algorithm based on correlation (C1 algorithm), an algorithm based on seismic trace similarity (C2 algorithm), an algorithm based on matrix eigenvalues ​​(C3 algorithm), or an algorithm based on sub-volume characteristics (C4 algorithm).

[0048] In geology, the process of stratum deposition is gradual, that is, the stratum is generally horizontally continuous or gradually uniform. Therefore, the signals measured by adjacent seismic channels should have a high degree of similarity. When there is a fault, the stratum is no longer continuous or gradually uniform, but abruptly changes, and the coherence between adjacent channels is very low. Therefore, the coherence attributes of each sub-azimuth data volume can be calculated to highlight the irrelevant data in each sub-azimuth data volume, and then determine the dominant orientation of the target layer in the target block.

[0049] The target layer may be a layer for fault identification, which may be determined according to actual needs. The dominant orientation may be the orientation corresponding to the sub-orientation data volume with the largest coherent attribute value.

[0050] In an embodiment of the present invention, the coherent attributes of the target layer in each sub-azimuth data volume can be determined based on the coherent attributes of each sub-azimuth data volume and the seismic layer interpreted by the 1*1 grid density of the target layer segment, and then the coherent attributes of the target layer in each sub-azimuth data volume can be compared to determine the dominant orientation of the target layer in the target block.

[0051] As an optional but non-limiting implementation, determining the dominant orientation of the target layer in the target block according to the coherent attributes of each of the sub-orientation data volumes includes but is not limited to the following steps B1 to B2:

[0052] Step B1: extracting first coherent attribute plane graphs corresponding to target layers in the target blocks from each of the sub-azimuth data volumes according to the coherent attributes of each of the sub-azimuth data volumes.

[0053] Specifically, the coherent attribute plane map may be extracted after interpolation of each sub-azimuth data volume according to the 1*1 grid density of the target layer segment, so as to obtain the first coherent attribute plane map corresponding to the target layer in the target block in each sub-azimuth data volume.

[0054] Step B2: Compare the first coherent attribute plane diagrams to determine the dominant orientation of the target layer.

[0055] In the embodiment of the present invention, the coherent attribute values ​​in each first coherent attribute plane map can be compared, and the orientation of the first coherent attribute plane map corresponding to the maximum coherent attribute value can be used as the dominant orientation of the target layer. Specifically, the orientation corresponding to the first coherent attribute plane map with relatively good indication effect can also be used as the dominant orientation.

[0056] S130: Determine the dominant frequency of the target layer according to the coherent properties of each of the frequency-divided data volumes.

[0057] The dominant frequency may be the frequency corresponding to the frequency-dividing data volume with the largest coherent attribute value.

[0058] In an embodiment of the present invention, the coherent properties of the target layer in each frequency-divided data volume can be determined based on the coherent properties of each frequency-divided data volume and the seismic layer interpreted by the 1*1 grid density of the target layer segment, and then the coherent properties of the target layer in each frequency-divided data volume can be compared to determine the dominant frequency of the target layer in the target block.

[0059] As an optional but non-limiting implementation, determining the dominant frequency of the target layer according to the coherent attributes of each of the frequency-divided data volumes includes but is not limited to the following steps C1 to C2:

[0060] Step C1: extracting the second coherent attribute plane graph corresponding to the target layer in each of the frequency-divided data volumes according to the coherent attributes of each of the frequency-divided data volumes.

[0061] Specifically, each frequency-divided data volume may be interpolated according to the 1*1 grid density of the target layer segment and then the coherent attribute plane map may be extracted to obtain the second coherent attribute plane map corresponding to the target layer in the target block in each frequency-divided data volume.

[0062] Step C2: Compare the second coherent attribute plane graphs to determine the dominant frequency of the target layer.

[0063] Specifically, the coherent attribute values ​​in each second coherent attribute plane map may be compared, and the frequency of the second coherent attribute plane map corresponding to the maximum coherent attribute value may be used as the dominant frequency of the target layer.

[0064] S140. Determine whether the target layer is a fault according to the dominant orientation and the dominant frequency.

[0065] Specifically, the dominant frequency of the target layer can be used to calculate the dominant azimuth dominant frequency seismic data volume on the sub-azimuth data volume corresponding to the dominant azimuth, and then identify whether the target layer is a fault based on the dominant azimuth dominant frequency seismic data volume.

[0066] Among them, fault identification can be determined by performing coherent algorithm calculation on the seismic data body with dominant azimuth and dominant frequency, and can also be determined by the seismic curvature of the seismic data body with dominant azimuth and dominant frequency.

[0067] The embodiment of the present invention provides a method for determining a fault, which determines a first preset number of sub-azimuth data bodies and a second preset number of sub-frequency data bodies of the target block according to the pre-stack common reflection point gathers and post-stack seismic data of the target block; determines the dominant azimuth of the target layer in the target block according to the coherence properties of each sub-azimuth data body; determines the dominant frequency of the target layer according to the coherence properties of each sub-frequency data body; and determines whether the target layer is a fault according to the dominant azimuth and dominant frequency. This technical solution makes full use of the pre-stack common reflection point gathers and post-stack seismic data of the target block to determine the dominant azimuth and dominant frequency of the target layer, provides a reasonable and effective judgment criterion for fault identification, and improves the accuracy of fault identification.

[0068] Embodiment 2

[0069] Figure 2 This is a flow chart of a method for determining a fault provided in the second embodiment of the present application. This embodiment is optimized based on the above embodiment. Figure 2 As shown, the method of this embodiment specifically includes the following steps:

[0070] S210, determining a first preset number of azimuth data volumes and a second preset number of frequency data volumes of the target block according to the pre-stack common reflection point gathers and post-stack seismic data of the target block.

[0071] S220: Determine the dominant orientation of the target layer in the target block according to the coherent attributes of each of the sub-orientation data volumes.

[0072] S230: Determine the dominant frequency of the target layer according to the coherent properties of each of the frequency-divided data volumes.

[0073] S240: Generate a target seismic data volume according to the dominant azimuth and the dominant frequency.

[0074] The target seismic data volume can be calculated based on the sub-azimuth data volume corresponding to the dominant frequency at the dominant azimuth; or it can be calculated based on the sub-frequency data volume corresponding to the dominant azimuth at the dominant frequency.

[0075] S250, extracting a first fault detection plane map of the target layer from the target seismic data volume, and determining a fault judgment result of the target layer according to the first fault detection plane map.

[0076] Specifically, the target seismic data volume can be interpolated according to the 1*1 grid density of the target layer segment and then the fault detection plane map can be extracted to obtain the first fault detection plane map. Further, it can be determined whether the target layer is a fault according to the fault characteristics in the first fault detection plane map.

[0077] As an optional but non-limiting implementation method, extracting the first fault detection plan view of the target layer from the target seismic data body includes but is not limited to the following steps: based on the amplitude direction decomposition technology, performing fault detection on the target seismic data body, and extracting the first fault detection plan view of the target layer.

[0078] The amplitude direction decomposition technology can be used to detect faults in the target seismic data volume using the amplitude difference caused by anisotropy. Figure 3 This is a schematic diagram of a first fault detection plane provided in the second embodiment of the present application. Figure 3 As shown, the first fault detection plane map of the target layer extracted according to the target seismic data body has more obvious fault characteristics, is more conducive to intuitive analysis, and improves the accuracy of the fault detection plane map.

[0079] The beneficial effect of the above technical solution is that the fault detection of the target seismic data body is performed through the amplitude difference caused by anisotropy, so that the fault detection is more sensitive, the calculation speed is faster, and the prediction accuracy is also high.

[0080] Based on the above embodiments, optionally, after determining whether the target layer is a fault according to the dominant orientation and the dominant frequency, the method further includes: comparing the second fault detection plan view in the logging data with the first fault detection plan view to determine whether the fault judgment result is correct.

[0081] The second fault detection plane map can be obtained based on the well logging data of the target block, which is a conventional coherent fault detection plane map. For example, taking a deep shale gas reservoir in a basin as an example, Figure 4a A schematic diagram of a second fault detection plane provided in the second embodiment of the present application is shown as follows: Figure 4a Shown is a conventional coherent fault detection plan view from four well engineering data with fault encounter information. Figure 4b Another schematic diagram of the first fault detection plane provided in the second embodiment of the present application is as follows: Figure 4b As shown, Figure 4a The first fault detection plane diagram of the corresponding target layer is analyzed Figure 4b The second fault detection plan shown in FIG. 1 can preliminarily determine that the target layer is a fault. Figure 4a The second tomographic detection plan shown is Figure 4aThe first fault detection plan view shown in the figure is compared with the first fault detection plan view. According to the comparison result, it can be obtained that the fault distance and fault direction are basically consistent, so the judgment result that the target layer is a fault is correct and reliable.

[0082] The beneficial effect of the above technical solution is that it can ensure the reliability and effectiveness of fault determination and improve the accuracy of fault determination.

[0083] The embodiment of the present invention provides a method for determining a fault, which determines a first preset number of sub-azimuth data volumes and a second preset number of sub-frequency data volumes of the target block according to the pre-stack common reflection point gather and post-stack seismic data of the target block; determines the dominant azimuth of the target layer in the target block according to the coherence properties of each sub-azimuth data volume; determines the dominant frequency of the target layer according to the coherence properties of each sub-frequency data volume; generates a target seismic data volume according to the dominant azimuth and the dominant frequency; extracts the first fault detection plane map of the target layer from the target seismic data volume, and determines the fault judgment result of the target layer according to the first fault detection plane map. This technical solution improves the accuracy and precision of fault identification of the target layer by processing the dominant azimuth and the dominant frequency of the target layer to extract the fault detection plane map of the target layer.

[0084] Embodiment 3

[0085] Figure 5 This is a schematic diagram of the structure of a fault determination device provided in Example 3 of the present application. Figure 5 As shown, the device comprises:

[0086] The seismic data volume division module 310 is used to determine a first preset number of azimuth data volumes and a second preset number of frequency data volumes of the target block according to the pre-stack common reflection point gathers and post-stack seismic data of the target block;

[0087] A dominant orientation determination module 320, configured to determine the dominant orientation of the target layer in the target block according to the coherent attributes of each of the sub-orientation data volumes;

[0088] A dominant frequency determination module 330, configured to determine the dominant frequency of the target layer according to the coherent properties of each of the frequency-divided data volumes;

[0089] The fault identification module 340 is used to determine whether the target layer is a fault according to the dominant orientation and the dominant frequency.

[0090] The embodiment of the present invention provides a fault determination device, which determines a first preset number of sub-azimuth data bodies and a second preset number of sub-frequency data bodies of the target block according to the pre-stack common reflection point gathers and post-stack seismic data of the target block; determines the dominant azimuth of the target layer in the target block according to the coherence properties of each sub-azimuth data body; determines the dominant frequency of the target layer according to the coherence properties of each sub-frequency data body; and determines whether the target layer is a fault according to the dominant azimuth and dominant frequency. This technical solution makes full use of the pre-stack common reflection point gathers and post-stack seismic data of the target block to determine the dominant azimuth and dominant frequency of the target layer, provides a reasonable and effective judgment criterion for fault identification, and improves the accuracy of fault identification.

[0091] Furthermore, the fault identification module 340 includes:

[0092] A seismic data volume generating unit, configured to generate a target seismic data volume according to the dominant azimuth and the dominant frequency;

[0093] A fault determination unit is used to extract a first fault detection plane map of the target layer from the target seismic data volume, and determine a fault determination result of the target layer according to the first fault detection plane map.

[0094] Furthermore, the fault identification unit includes:

[0095] The fault detection plane map extraction subunit is used to perform fault detection on the target seismic data volume based on the amplitude direction decomposition technology, and extract the first fault detection plane map of the target layer.

[0096] Furthermore, the device also includes:

[0097] The fault result verification module is used to compare the second fault detection plane map in the logging data with the first fault detection plane map after determining whether the target layer is a fault according to the dominant orientation and the dominant frequency to determine whether the fault judgment result is correct.

[0098] Furthermore, the seismic data volume division module 310 includes:

[0099] A sub-azimuth data volume division unit is used to divide a first preset number of sub-azimuth data volumes according to a preset angle interval based on the pre-stack common reflection point gather of the target block; wherein the preset angle is determined according to the fault strike of the target block;

[0100] The frequency division data volume division unit is used to divide the post-stack seismic data of the target block into a second preset number of frequency division data volumes according to the preset frequency intervals.

[0101] Furthermore, the dominant position determination module 320 includes:

[0102] A first coherent attribute plane graph extraction unit is used to extract, according to the coherent attributes of each of the sub-azimuth data volumes, a first coherent attribute plane graph corresponding to a target layer in the target block in each of the sub-azimuth data volumes;

[0103] The dominant orientation determining unit is used to compare the first coherent attribute plane graphs to determine the dominant orientation of the target layer.

[0104] Furthermore, the dominant frequency determination module 330 includes:

[0105] A second coherent attribute plane graph extraction unit, configured to extract, according to the coherent attributes of each of the frequency-divided data volumes, a second coherent attribute plane graph corresponding to the target layer in each of the frequency-divided data volumes;

[0106] The dominant frequency determination unit is used to compare each of the second coherent attribute plane graphs to determine the dominant frequency of the target layer.

[0107] A fault determination device provided in an embodiment of the present application can execute a fault determination method provided in any embodiment of the present application, and has functional modules and beneficial effects corresponding to the execution method.

[0108] Embodiment 4

[0109] Figure 6 A schematic diagram of a device 10 that can be used to implement an embodiment of the present application is shown. The device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0110] like Figure 6As shown, the device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the device 10 can also be stored. The processor 11, ROM 12 and RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0111] A number of components in the device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0112] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a method for determining a fault.

[0113] In some embodiments, the fault determination method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the fault determination method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the fault determination method in any other appropriate manner (e.g., by means of firmware).

[0114] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] The computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer programs are executed by the processor, the functions / operations specified in the flow charts and / or block diagrams are implemented. The computer programs may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0116] In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device or equipment. A computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A more specific example of a machine readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] To provide interaction with a user, the systems and techniques described herein can be implemented on a device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0118] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0119] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0120] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution of this application can be achieved, and this document is not limited here.

[0121] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for determining a fault, characterized in that: The method comprises: Determine a first preset number of azimuth data volumes and a second preset number of frequency data volumes of the target block according to the pre-stack common reflection point gathers and post-stack seismic data of the target block; Determining the dominant orientation of the target layer in the target block according to the coherent attributes of each of the sub-orientation data volumes; Determining the dominant frequency of the target layer according to the coherent properties of each of the frequency-divided data volumes; Whether the target layer is a fault is determined according to the dominant orientation and the dominant frequency.

2. The method according to claim 1, characterized in that: Determining a fault judgment result of the target layer according to the dominant orientation and the dominant frequency includes: generating a target seismic data volume according to the dominant azimuth and the dominant frequency; A first fault detection plane map of the target layer is extracted from the target seismic data volume, and a fault judgment result of the target layer is determined according to the first fault detection plane map.

3. The method according to claim 2, characterized in that Extracting a first fault detection plane map of the target layer from the target seismic data volume includes: Based on the amplitude direction decomposition technology, fault detection is performed on the target seismic data volume to extract the first fault detection plane map of the target layer.

4. The method according to claim 2, characterized in that: After determining whether the target layer is a fault according to the dominant orientation and the dominant frequency, the method further includes: The second fault detection plane map in the logging data is compared with the first fault detection plane map to determine whether the fault judgment result is correct.

5. The method according to claim 1, characterized in that According to the pre-stack common reflection point gathers and post-stack seismic data of the target block, a first preset number of azimuth data volumes and a second preset number of frequency data volumes of the target block are determined, including: Dividing a first preset number of sub-azimuth data volumes according to a preset angle interval based on the pre-stack common reflection point gather of the target block; wherein the preset angle is determined according to the fault strike of the target block; According to the post-stack seismic data of the target block, a second preset number of frequency-divided data volumes are divided according to the preset frequency intervals.

6. The method according to claim 1, characterized in that Determining the dominant orientation of the target layer in the target block according to the coherent attributes of each of the sub-orientation data volumes includes: According to the coherent attributes of each of the sub-azimuth data volumes, respectively extracting a first coherent attribute plane graph corresponding to the target layer in the target block in each of the sub-azimuth data volumes; The first coherent attribute plane diagrams are compared to determine the dominant orientation of the target layer.

7. The method according to claim 1, characterized in that Determining the dominant frequency of the target layer according to the coherent attributes of each of the frequency-divided data bodies includes: According to the coherent attributes of each of the frequency-divided data volumes, respectively extracting a second coherent attribute plane graph corresponding to the target layer in each of the frequency-divided data volumes; The second coherent attribute plane graphs are compared to determine the dominant frequency of the target layer.

8. A device for determining a fault, characterized in that: The device comprises: A seismic data volume division module is used to determine a first preset number of azimuth data volumes and a second preset number of frequency data volumes of the target block according to the pre-stack common reflection point gathers and post-stack seismic data of the target block; A dominant orientation determination module, used to determine the dominant orientation of the target layer in the target block according to the coherent attributes of each of the sub-orientation data volumes; A dominant frequency determination module, used to determine the dominant frequency of the target layer according to the coherent attributes of each of the frequency-divided data bodies; A fault identification module is used to determine whether the target layer is a fault according to the dominant orientation and the dominant frequency.

9. An electronic device, characterized in that: The device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the fault determination method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the fault determination method according to any one of claims 1 to 7 when executed.

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