A strike-slip fault identification method, device and equipment and storage medium

Abstract

The application discloses a strike-slip fault identification method, device and equipment and a storage medium. The method comprises the following steps: obtaining original acquisition data of an underground rock layer of seismic exploration; separating the original acquisition data to obtain separated diffraction wave data; imaging based on the diffraction wave data to obtain a diffraction wave imaging data body; and observing and identifying a profile and a plane based on the diffraction wave imaging data body to determine the spatial distribution information of the strike-slip fault in the underground rock layer. Through the technical scheme of the embodiment of the application, the strike-slip fault in the underground rock layer can be effectively identified, and the spatial distribution position of the strike-slip fault is determined, thereby providing sufficient data support for regional geological analysis and exploration well point deployment.

Description

Technical Field

[0001] This invention relates to the field of geophysical technology in the petroleum industry, and in particular to a method, apparatus, equipment and storage medium for identifying strike-slip fractures. Background Technology

[0002] Seismic exploration is a primary method for oil exploration and development in my country. Different geological targets exhibit varying degrees of response to seismic waves. Strike-slip faults are fractures formed when the two sides of a fault move horizontally relative to each other under the action of a couple, under the influence of torsional or shear stress fields. The most prominent characteristic of most strike-slip faults is their small displacement and good lateral continuity between the hanging wall and footwall, resulting in inconspicuous response characteristics on seismic profiles.

[0003] Currently, strike-slip fault identification primarily relies on seismic data. Optimized seismic trace algorithms consider not only energy variations between traces but also geometric and spatial characteristics. However, in subsurface rock formations, seismic responses are often masked by various noises, making it difficult to distinguish the response characteristics of seismic waves on seismic profiles. This hinders the determination of the spatial distribution of deep strike-slip faults, making it difficult to provide sufficient data for regional geological analysis and exploration well deployment. Therefore, the exploration of ultra-deep strike-slip faults has become a key factor constraining oil exploration and development. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and storage medium for identifying strike-slip fractures, enabling effective identification of strike-slip fractures in underground rock strata, determining the spatial distribution of strike-slip fractures, and providing sufficient data support for regional geological analysis and exploration well deployment.

[0005] In a first aspect, embodiments of the present invention provide a method for identifying strike-slip fractures, comprising:

[0006] To obtain raw data of underground rock strata from seismic exploration;

[0007] The original acquired data is separated to obtain the separated diffraction wave data;

[0008] Based on the diffraction wave data, imaging is performed to obtain a diffraction wave imaging data volume;

[0009] Based on the diffraction wave imaging data, cross-sectional and planar observations are performed to identify the spatial distribution information of strike-slip faults in underground rock strata.

[0010] Secondly, embodiments of the present invention also provide a strike-slip fracture identification device, comprising:

[0011] The raw data acquisition module is used to acquire raw data of underground rock strata in seismic exploration.

[0012] The diffraction wave data acquisition module is used to separate the original acquired data to obtain the separated diffraction wave data;

[0013] A diffraction wave data volume acquisition module is used to perform imaging based on the diffraction wave data to obtain a diffraction wave imaging data volume.

[0014] The spatial distribution determination module is used to perform profile and planar observation and identification based on the diffraction wave imaging data volume to determine the spatial distribution information of strike-slip faults in underground rock strata.

[0015] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising: at least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the slip-slip fracture identification method provided in any embodiment of the present invention.

[0018] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions that enable a processor to execute the strike-slip fracture identification method provided in any embodiment of the present invention.

[0019] The technical solution of this invention acquires raw data of underground rock strata from seismic exploration and separates diffraction wave data, which is more sensitive to spatial discontinuities in the strata, from the raw data. Based on the diffraction wave data, imaging is performed to obtain a diffraction wave imaging data volume. Based on the diffraction wave imaging data volume, profile and planar observations are performed, which can more clearly and accurately determine the spatial distribution information of strike-slip faults in underground rock strata. This achieves effective identification of strike-slip faults in underground rock strata without increasing acquisition costs, and provides sufficient data support for regional geological analysis and exploration well deployment.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of a strike-slip fracture identification method provided in Embodiment 1 of the present invention;

[0023] Figure 2(a) is the original data collection data body according to Embodiment 1 of the present invention;

[0024] Figure 2(b) is a diffraction wave imaging data volume according to Embodiment 1 of the present invention;

[0025] Figure 3 This is a flowchart of a strike-slip fracture identification method provided in Embodiment 2 of the present invention;

[0026] Figure 4(a) is a plan view of the reflected wave imaging data volume according to Embodiment 2 of the present invention;

[0027] Figure 4(b) is a plan view of the fused data volume according to Embodiment 2 of the present invention;

[0028] Figure 5 This is a schematic diagram of a slip fracture identification device according to Embodiment 3 of the present invention;

[0029] Figure 6 This is a schematic diagram of the structure of an electronic device that implements the slippage fracture identification method of this invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "target," "current," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Example 1

[0033] Figure 1 The flowchart illustrates a strike-slip fracture identification method provided in Embodiment 1 of the present invention. This embodiment is applicable to determining the spatial distribution information of strike-slip fractures in underground rock strata. Figure 1 As shown, this method can be executed by a strike-slip fracture identification device, which can be implemented in hardware and / or software and can be configured in an electronic device. For example... Figure 1 As shown, the method specifically includes the following steps:

[0034] S110. Obtain raw data of underground rock strata from seismic exploration.

[0035] In this context, raw acquisition data can refer to the response data of underground rock strata to seismic waves after an earthquake. For example, raw acquisition data can be raw acquisition shot gather records. Raw acquisition shot gather records refer to the original sampling records obtained by geophones at different locations sampling seismic waves after an artificial earthquake is conducted at a selected location as the shot point.

[0036] Specifically, an artificial earthquake is conducted at a selected location as the shot point. Geophones are set up at multiple locations on the ground. The geophones sample and record the seismic waves at their locations during the earthquake at fixed time intervals. The data recorded by each geophone are arranged according to geographical location to obtain the original acquisition shot gather record. The original acquisition shot gather record is used as the original acquisition data of the underground rock strata.

[0037] S120. Separate the original acquired data to obtain the separated diffraction wave data.

[0038] Diffraction wave data refers to data generated when seismic waves encounter drastic changes in the geological strata, such as strike-slip faults, and these points act as new seismic sources, producing vibrations that propagate outwards as spherical waves. Diffraction waves are waves caused by seismic waves encountering drastic changes in the geological strata during propagation. Diffraction waves are a type of anomalous wave, often appearing as a continuation of reflected waves. Their frequency and effective velocity are lower than normal reflected waves, with fewer peaks (or troughs) and faster energy attenuation. It should be noted that when a stratum is broken by a strike-slip fault, the most obvious characteristic is the diffraction of seismic waves at the fault location. Therefore, diffraction waves are more sensitive to spatial discontinuities in the geological strata and can more clearly reflect the location of strike-slip faults.

[0039] Specifically, based on the difference in characteristic values ​​between the diffracted wave and the emitted wave, the original acquired data is analyzed to extract the reflected wave data, while the remaining original data is the diffracted wave data.

[0040] For example, S120 may include: separating the reflected wave and the diffracted wave from the original acquired data based on at least one of the time-distance relationship difference between the reflected wave and the diffracted wave in the data space, the difference in wave field dynamic characteristics, and the difference in time-distance relationship in the imaging space, to obtain the separated diffracted wave data.

[0041] Specifically, based on at least one of the differences in temporal distance between reflected and diffracted waves in the data space, the differences in wave field dynamic characteristics, and the differences in temporal distance between reflected and diffracted waves in the imaging space, principal component analysis-related algorithms are used to separate the original acquired data, extracting the reflected wave data, while the remaining original data is the diffracted wave data. This achieves signal-to-noise separation between reflected and diffracted waves.

[0042] For example, based on the difference in eigenvalues ​​between diffracted waves and emitted waves in wave field dynamics, principal component analysis-related algorithms are used to separate the original acquired data, extracting reflected wave data with larger eigenvalues, while the remaining original data are diffracted wave data with very small eigenvalues.

[0043] S130. Based on the diffraction wave data, perform imaging to obtain diffraction wave imaging data volume.

[0044] In this context, the diffraction wave imaging data volume can refer to the rendering of a three-dimensional diffraction wave data volume. A three-dimensional data volume is a collection of data whose position is a function of three-dimensional spatial coordinates (x, y, z).

[0045] Specifically, a three-dimensional data volume of diffracted waves is obtained based on the diffracted wave data, and the three-dimensional data volume of diffracted waves is rendered and imaged to obtain a diffracted wave imaging data volume.

[0046] S140. Based on the diffraction wave imaging data volume, perform profile and planar observation and identification to determine the spatial distribution information of strike-slip faults in underground rock strata.

[0047] Specifically, such as Figure 2(a) and 2(b) As shown in Figure 2(a), the original acquired data is an image volume, and Figure 2(b) is a diffraction wave image volume. The strip-shaped information within the box and circular areas in the figures represents strike-slip fracture characteristic information. A comparison of Figure 2(a) and Figure 2(b) reveals that the diffraction wave image volume exhibits more pronounced strike-slip fracture characteristic information. The spatial distribution information of strike-slip fractures in underground rock strata can be automatically obtained by extracting the strip-shaped information from the diffraction wave image volume. Alternatively, the cross-section and planar views of the diffraction wave image volume can be displayed for user observation and identification. Based on the spatial distribution information of the strip-shaped information observed in the cross-section and planar views of the diffraction wave image volume, the location distribution information of strike-slip fractures can be determined. Users can trigger a selection operation based on the identified strike-slip fractures, determining the selected spatial location as the spatial distribution information of strike-slip fractures in underground rock strata.

[0048] For example, S140 may include: determining fault attribute data volume based on the diffraction wave imaging data volume; and performing profile and planar observation and identification based on the fault attribute data volume to determine the spatial distribution information of strike-slip faults in the underground rock strata.

[0049] The fault attributes can be attributes reflecting the location of strike-slip faults. For example, fault attributes may include coherence attributes and dip attributes. The fault attribute data volume can refer to a data volume composed of seismic wave data related to strike-slip faults. For example, the fault attribute data volume includes at least one of a coherence attribute data volume and a dip attribute data volume. Specifically, fault attributes are calculated based on diffraction wave imaging data volumes to determine the fault attribute data volume. The computer can automatically identify fault attributes by extracting fault attribute information from the fault attribute data volume, and can also display the cross-sections and planes of the fault attribute data volume, thereby further amplifying the response characteristics of strike-slip faults using fault attributes, and more clearly displaying the location information of strike-slip faults. This allows users to observe and identify cross-sections and planes. Users can trigger selection operations based on the identified fault attributes, and based on the selection operations, obtain the spatial distribution information of strike-slip faults in underground rock strata.

[0050] The technical solution of this invention acquires raw data of underground rock strata from seismic exploration and separates diffraction wave data, which is more sensitive to spatial discontinuities in the lower layers, from the raw data. Based on the diffraction wave data, imaging is performed to obtain a diffraction wave imaging data volume. Based on the diffraction wave imaging data volume, profile and planar observation and identification are performed. This can more clearly and accurately determine the spatial distribution information of strike-slip faults in underground rock strata, thereby achieving effective identification of strike-slip faults in underground rock strata without increasing acquisition costs. It also determines the spatial distribution location of strike-slip faults, providing sufficient data support for regional geological analysis and exploration well deployment.

[0051] Example 2

[0052] Figure 3 This is a flowchart of a strike-slip fracture identification method provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment optimizes the step of "performing cross-sectional and planar observations and identifications based on the diffraction wave imaging data volume to determine the spatial distribution information of strike-slip fractures in underground rock strata". Explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0053] See Figure 3 Another strike-slip fracture identification method provided in this embodiment specifically includes the following steps:

[0054] S210. Obtain raw data of underground rock strata from seismic exploration.

[0055] S220. Separate the original acquired data to obtain the separated diffraction wave data and reflection wave data.

[0056] S230. Based on diffraction wave data, imaging is performed to obtain diffraction wave imaging data volume.

[0057] S240. Imaging is performed based on reflected wave data to obtain reflected wave imaging data volume.

[0058] S250. The reflected wave imaging data volume and the diffraction wave imaging data volume are fused to obtain a fused data volume.

[0059] Specifically, the reflected wave imaging data volume and the diffracted wave imaging data volume are added and fused according to their position information in three-dimensional space to obtain a fused data volume.

[0060] For example, S250 may include: normalizing the energy of the reflected wave imaging data volume and the diffraction wave imaging data volume; and adding and fusing the energy-normalized reflected wave imaging data volume and the diffraction wave imaging data volume to obtain a fused data volume.

[0061] Specifically, based on the energy value of the reflected wave imaging data volume, the diffracted wave imaging data volume is amplified so that the amplified diffracted wave imaging data volume has the same order of magnitude as the reflected wave imaging data volume. The amplified diffracted wave imaging data volume and the reflected wave imaging data volume are then added and fused to obtain a fused data volume. This allows the fused data volume to have more pronounced diffracted wave characteristics.

[0062] S260. Based on the fused data volume, perform profile and planar observation and identification to determine the spatial distribution information of strike-slip faults in underground rock strata.

[0063] Specifically, such as Figure 4(a) and 4(b) As shown in Figure 4(a), a planar view of the reflected wave imaging data volume, and Figure 4(b), a planar view of the fused data volume, the strip-shaped information within the circular area represents strike-slip fracture characteristic information. A comparison of Figure 4(a) and Figure 4(b) reveals that the fused data volume exhibits more pronounced strike-slip fracture characteristic information. The spatial distribution information of strike-slip fractures in underground rock strata can be automatically obtained by extracting the strip-shaped information from the fused data volume. Alternatively, the cross-section and planar view of the fused data volume can be displayed for user observation and identification. Based on the spatial distribution information of the strip-shaped information observed in the cross-section and planar view of the fused data volume, the location distribution information of strike-slip fractures can be determined. Users can trigger a selection operation based on the identified strike-slip fractures, defining the selected spatial location as the spatial distribution information of strike-slip fractures in underground rock strata.

[0064] For example, S260 may include: determining a fault attribute data volume based on the fused data volume; and performing profile and planar observation and identification based on the fault attribute data volume to determine the spatial distribution information of strike-slip faults in the underground rock strata.

[0065] Specifically, calculating fault attributes based on fused data volumes can result in more pronounced strike-slip fracture identification, thus defining the fault attribute data volume. Computers can automatically identify faults by extracting strip-like information from the fused data volume, and can also display the cross-sections and planes of the fused data volume. Utilizing fault attributes can further amplify the response characteristics of strike-slip fractures, thereby more clearly displaying their location information. This allows users to observe and identify cross-sections and planes. Based on the spatial distribution information of the strip-like information observed by the user in the cross-sections and planes of the fused data volume, the location distribution information of strike-slip fractures can be determined. Users can trigger selection operations based on the identified strike-slip fractures, and based on these selection operations, obtain the spatial distribution information of strike-slip fractures in the underground rock strata.

[0066] The technical solution of this invention involves imaging based on separated reflected wave data to obtain a reflected wave imaging data volume. The reflected wave imaging data volume and the diffracted wave imaging data volume are then fused to obtain a fused data volume. Based on this fused data volume, profile and planar observations are performed to determine the spatial distribution information of strike-slip faults in underground rock strata. This amplifies the response characteristics of strike-slip faults to seismic waves, reduces interference from other irrelevant features on strike-slip fault identification, and makes strike-slip faults easier to identify.

[0067] Example 3

[0068] Figure 5 This is a schematic diagram of a slip-slip fracture identification device provided in Embodiment 3 of the present invention. Figure 5 As shown, the device includes: a raw data acquisition module 310, a diffraction wave data acquisition module 320, a diffraction wave data volume acquisition module 330, and a spatial distribution determination module 340.

[0069] Among them, the raw data acquisition module 310 is used to acquire raw data of underground rock strata in seismic exploration;

[0070] The diffraction wave data acquisition module 320 is used to separate the original acquired data to obtain the separated diffraction wave data;

[0071] The diffraction wave data volume acquisition module 330 is used to perform imaging based on the diffraction wave data to obtain a diffraction wave imaging data volume.

[0072] The spatial distribution determination module 340 is used to perform profile and planar observation and identification based on the diffraction wave imaging data volume to determine the spatial distribution information of strike-slip faults in underground rock strata.

[0073] The technical solution of this embodiment acquires the original data of underground rock strata from seismic exploration and separates diffraction wave data, which is more sensitive to spatial discontinuities in the strata, from the original data. Based on the diffraction wave data, imaging is performed to obtain diffraction wave imaging data volume. Based on the diffraction wave imaging data volume, profile and planar observation and identification can be performed, which can more clearly and accurately determine the spatial distribution information of strike-slip faults in underground rock strata. This achieves effective identification of strike-slip faults in underground rock strata and determines the spatial distribution location of strike-slip faults without increasing the acquisition cost, providing sufficient data support for regional geological analysis and exploration well deployment.

[0074] Optionally, the diffraction wave data acquisition module 320 is specifically used to: separate the reflected wave and diffraction wave from the original acquired data based on at least one of the differences in the time distance relationship between the reflected wave and the diffraction wave in the data space, the differences in the wave field dynamic characteristics, and the differences in the time distance relationship in the imaging space, to obtain the separated diffraction wave data.

[0075] Optionally, the spatial distribution determination module includes:

[0076] The attribute data volume determination unit is used to determine the fault attribute data volume based on the diffraction wave imaging data volume;

[0077] The spatial distribution determination unit performs profile and planar observation and identification based on the fault attribute data volume to determine the spatial distribution information of strike-slip faults in underground rock strata.

[0078] Optionally, the fault attribute data volume includes at least one of a coherence attribute data volume and a dip attribute data volume.

[0079] Optionally, the spatial distribution determination module 340 includes:

[0080] The reflected wave data volume acquisition unit is used to perform imaging based on the separated reflected wave data to obtain the reflected wave imaging data volume.

[0081] The fused data volume acquisition unit is used to fuse the reflected wave imaging data volume and the diffraction wave imaging data volume to obtain a fused data volume;

[0082] The strike-slip fault spatial distribution determination unit is used to identify and determine the spatial distribution information of strike-slip faults in underground rock strata based on the fused data volume through profile and planar observations.

[0083] Optionally, the data volume acquisition unit is specifically used to: normalize the energy of the reflected wave imaging data volume and the diffraction wave imaging data volume; and add and fuse the energy-normalized reflected wave imaging data volume and the diffraction wave imaging data volume to obtain a fused data volume.

[0084] Optionally, the strike-slip fault spatial distribution determination unit is specifically used for: determining fault attribute data based on the fused data volume; and performing profile and planar observation and identification based on the fault attribute data volume to determine the spatial distribution information of strike-slip faults in underground rock strata.

[0085] The vehicle network data synchronization device provided in this embodiment of the invention can execute the vehicle network data synchronization method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0086] Figure 6A schematic diagram of an electronic device 12 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as desktop computers, workbenches, servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0087] like Figure 6 As shown, the electronic device 12 is represented in the form of a general-purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0088] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0089] Electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0090] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (… Figure 6 Not shown; usually referred to as a "hard drive"). Although Figure 6Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0091] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of the present invention.

[0092] Electronic device 12 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable a user to interact with electronic device 12, and / or with any device that enables electronic device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed via input / output (I / O) interface 22. Furthermore, electronic device 12 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. As shown, network adapter 20 communicates with other modules of electronic device 12 via bus 18. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0093] Processing unit 16 executes various functional applications and data processing by running programs stored in system memory 28, such as implementing the steps of a strike-slip fracture identification method provided in this embodiment, the method including:

[0094] To obtain raw data of underground rock strata from seismic exploration;

[0095] The original acquired data is separated to obtain the separated diffraction wave data;

[0096] Based on the diffraction wave data, imaging is performed to obtain a diffraction wave imaging data volume;

[0097] Based on the diffraction wave imaging data, cross-sectional and planar observations are performed to identify the spatial distribution information of strike-slip faults in underground rock strata.

[0098] Of course, those skilled in the art will understand that the processor can also implement the technical solution of the strike-slip fracture identification method provided in any embodiment of the present invention.

[0099] This embodiment provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the program implements the steps of the strike-slip fracture identification method provided in any embodiment of the present invention. The method includes:

[0100] To obtain raw data of underground rock strata from seismic exploration;

[0101] The original acquired data is separated to obtain the separated diffraction wave data;

[0102] Based on the diffraction wave data, imaging is performed to obtain a diffraction wave imaging data volume;

[0103] Based on the diffraction wave imaging data, cross-sectional and planar observations are performed to identify the spatial distribution information of strike-slip faults in underground rock strata.

[0104] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0105] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0106] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0107] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0108] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computing device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0109] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for identifying strike-slip fractures, characterized in that, include: To obtain raw data of underground rock strata from seismic exploration; The original acquired data is separated to obtain the separated diffraction wave data; Based on the diffraction wave data, imaging is performed to obtain a diffraction wave imaging data volume; Based on the diffraction wave imaging data, cross-sectional and planar observations are performed to identify the spatial distribution information of strike-slip faults in underground rock strata. The process of performing profile and planar observations and identification based on the diffraction wave imaging data volume to determine the spatial distribution information of strike-slip faults in underground rock strata includes: Based on the diffraction wave imaging data volume, determine the fault attribute data volume; Based on the fault attribute data volume, cross-sectional and planar observations and identifications are performed to determine the spatial distribution information of strike-slip faults in underground rock strata; or, Imaging is performed based on the separated reflected wave data to obtain the reflected wave imaging data volume; The reflected wave imaging data volume and the diffraction wave imaging data volume are fused to obtain a fused data volume; Based on the fused data volume, cross-sectional and planar observations and identifications are performed to determine the spatial distribution information of strike-slip faults in underground rock strata.

2. The method according to claim 1, characterized in that, The original acquired data is separated to obtain the separated diffraction wave data, including: Based on at least one of the differences in time-distance relationship between reflected waves and diffracted waves in the data space, the differences in wave field dynamic characteristics, and the differences in time-distance relationship in the imaging space, the original acquired data is separated into reflected waves and diffracted waves to obtain the separated diffracted wave data.

3. The method according to claim 1, characterized in that, The fault attribute data volume includes at least one of the coherence attribute data volume and the dip attribute data volume.

4. The method according to claim 1, characterized in that, The step of fusing the reflected wave imaging data volume and the diffracted wave imaging data volume to obtain a fused data volume includes: The reflected wave imaging data volume and the diffraction wave imaging data volume are energy normalized. The reflected wave imaging data volume and the diffracted wave imaging data volume after energy normalization are added and fused to obtain the fused data volume.

5. The method according to claim 1, characterized in that, The process of identifying profiles and planes based on the fused data volume to determine the spatial distribution information of strike-slip faults in underground rock strata includes: Based on the fused data volume, the fault attribute data volume is determined; Based on the fault attribute data, cross-sectional and planar observations are performed to identify the spatial distribution information of strike-slip faults in underground rock strata.

6. A slip-slip fracture identification device, characterized in that, include: The raw data acquisition module is used to acquire raw data of underground rock strata in seismic exploration. The diffraction wave data acquisition module is used to separate the original acquired data to obtain the separated diffraction wave data; A diffraction wave data volume acquisition module is used to perform imaging based on the diffraction wave data to obtain a diffraction wave imaging data volume. The spatial distribution determination module is used to perform profile and planar observation and identification based on the diffraction wave imaging data volume to determine the spatial distribution information of strike-slip faults in underground rock strata. The spatial distribution determination module is specifically used for: determining fault attribute data volume based on the diffraction wave imaging data volume; performing profile and planar observation and identification based on the fault attribute data volume to determine the spatial distribution information of strike-slip faults in underground rock strata; or, performing imaging based on the separated reflected wave data to obtain reflected wave imaging data volume; and fusing the reflected wave imaging data volume and the diffraction wave imaging data volume to obtain a fused data volume. Based on the fused data volume, cross-sectional and planar observations and identifications are performed to determine the spatial distribution information of strike-slip faults in underground rock strata.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the slip-slip fracture identification method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the slip-slip fracture identification method according to any one of claims 1-5.

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