Small fault identification method, device, medium and electronic equipment

Abstract

The present application discloses a method, device, medium, and electronic device for identifying small faults. The method comprises: determining an effective frequency high cutoff by performing spectrum scanning on raw seismic data; performing energy focusing on the raw seismic data based on a high-frequency energy focusing filter and the effective frequency high cutoff, thereby obtaining high-frequency energy focused seismic data; calculating an intrinsic coherence value based on the high-frequency energy focused seismic data, thereby obtaining high-frequency energy focused coherence data; calculating a coherence enhancement value based on the high-frequency energy focused coherence data, thereby obtaining high-frequency energy focused coherence enhanced data; and realizing small fault identification based on the high-frequency energy focused coherence enhanced data. The technical solution provided by the present application can improve the accuracy of identifying small faults.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of oil and gas exploration, and particularly relates to a small fault identification method and device, a medium and an electronic device. BACKGROUND

[0002] In the exploration and development process of coal measures strata deep coalbed gas and tight sandstone gas, fine depiction of small faults and study of their control on natural gas reservoirs are key problems to be solved in current production research. Small faults are difficult to identify because of their short lateral extension, small vertical throw and strong concealment. In particular, affected by strong reflection shielding of coal seams, seismic events show continuous strong reflection, resulting in low resolution of seismic reflection waves and further increasing the difficulty of identifying small faults.

[0003] Existing small fault identification techniques mainly include manual interpretation and application of various seismic attributes for small fault depiction. Manual interpretation mainly determines whether a small fault exists by observing changes in amplitude, phase and time difference of seismic waves on a seismic section with the naked eye. However, the range of observation by the naked eye is limited, and it is difficult to detect small changes in seismic characteristics. Seismic attribute interpretation mainly identifies faults by attribute changes of original seismic data and through section and plane slices. Common seismic attributes mainly include coherent body technology, ant technology, maximum likelihood attribute and frequency division technology. It is difficult to truly and reliably depict small faults by using conventional or single seismic attribute technology.

[0004] Therefore, in order to more accurately identify small faults, the present application provides a small fault identification method to achieve the above needs. SUMMARY

[0005] Embodiments of the present application provide a small fault identification method, device, medium and electronic device, which can improve the accuracy of identifying small faults.

[0006] Other characteristics and advantages of the present application will become apparent from the following detailed description, or will be learned by practice of the present application.

[0007] According to a first aspect of embodiments of the present application, a small fault identification method is provided, characterized in that the method comprises: determining an effective high-frequency cutoff value by performing frequency spectrum scanning on original seismic data; performing energy focusing data on the original seismic data based on a high-frequency energy focusing filter and the effective high-frequency cutoff value, thereby obtaining high-frequency energy focusing seismic data; calculating an intrinsic coherence value according to the high-frequency energy focusing seismic data, thereby obtaining high-frequency energy focusing coherence data; calculating a coherence enhancement value according to the high-frequency energy focusing coherence data, thereby obtaining high-frequency energy focusing coherence enhancement data; and identifying small faults based on the high-frequency energy focusing coherence enhancement data.

[0008] In some embodiments of the present application, based on the foregoing scheme, the determining the effective high-frequency cutoff by performing a spectral scan on the original seismic data comprises: performing a spectral scan on the original seismic data to obtain a spectral graph by determining a target layer and a scan length; and determining the effective high-frequency cutoff based on the spectral graph and in combination with a target seismic amplitude.

[0009] In some embodiments of the present application, based on the foregoing scheme, before performing the energy focusing on the original seismic data, the method further comprises: determining a low-frequency cutoff, a low-pass frequency, a high-pass frequency, and a high-frequency cutoff according to a spectral graph and a target seismic amplitude; and constructing the high-frequency energy focusing filter by focusing a main frequency to the effective high-frequency cutoff according to the low-frequency cutoff, the low-pass frequency, the high-pass frequency, and the high-frequency cutoff.

[0010] In some embodiments of the present application, based on the foregoing scheme, the intrinsic coherence value is calculated by the following formula:

[0011]

[0012] wherein E c is a total energy for representing the intrinsic coherence value; λ1 is a main eigenvalue; N is a number of traces; and j is a number of sampling points corresponding to each trace.

[0013] In some embodiments of the present application, based on the foregoing scheme, the coherence enhancement value is calculated by the following formula:

[0014]

[0015] wherein, is the coherence enhancement value; ρ is an enhancement factor; BB' and AA' are respectively an ant colony direction and a normal direction estimated by a ridge line direction; ΔC represents a coherence gradient in a certain direction; and g represents a Gaussian filter centered at k in a certain direction.

[0016] In some embodiments of the present application, based on the foregoing scheme, the scan length is greater than or equal to 200 ms.

[0017] In some embodiments of the present application, based on the foregoing scheme, the target seismic amplitude is 12 db.

[0018] Compared with the prior art, the present application has at least the following beneficial effects:

[0019] The application firstly obtains an effective high-frequency cutoff value through frequency scanning and destination amplitude determination, and sets a high-frequency energy focusing filter according to the effective high-frequency cutoff value. Then, the high-frequency energy focusing filter is used to perform energy focusing on the original seismic data to obtain high-frequency energy focusing seismic data. The high-frequency energy focusing seismic data can improve the resolution of seismic data.

[0020] After obtaining the high-frequency energy focusing seismic data, intrinsic coherence calculation and coherent enhancement calculation are performed on the high-frequency energy focusing seismic data to obtain high-frequency energy focusing coherent enhancement data. The high-frequency energy focusing coherent enhancement data can retain full-band information of seismic data, maintain the natural state of the same phase axis, and overcome the defect of false frequency data caused by the narrow frequency band of the conventional frequency filter. At the same time, through the high-frequency energy focusing coherent enhancement data, the interpretation of small faults in the plane and profile can improve the accuracy of identifying small faults.

[0021] Based on the above method, the small fault identification method provided by the application can retain full-band information of seismic data and avoid the appearance of false frequency data, thereby improving the accuracy of identifying small faults.

[0022] According to a second aspect of the embodiments of the application, a small fault identification device is provided, characterized in that the device comprises: a first confirmation unit configured to determine an effective high-frequency cutoff value by performing frequency spectrum scanning on original seismic data; a second confirmation unit configured to perform energy focusing on the original seismic data based on a high-frequency energy focusing filter and the effective high-frequency cutoff value, thereby obtaining high-frequency energy focusing seismic data; a first calculation unit configured to calculate an intrinsic coherence value according to the high-frequency energy focusing seismic data, thereby obtaining high-frequency energy focusing coherent data; a second calculation unit configured to calculate a coherent enhancement value according to the high-frequency energy focusing coherent data, thereby obtaining high-frequency energy focusing coherent enhancement data; and an identification unit configured to realize small fault identification based on the high-frequency energy focusing coherent enhancement data.

[0023] According to a third aspect of the embodiments of the application, a computer readable storage medium is provided, characterized in that the computer readable storage medium stores at least one program code, and the at least one program code is loaded and executed by a processor to realize the operations performed by the method.

[0024] According to a fourth aspect of the embodiments of the application, an electronic device is provided, characterized in that the electronic device comprises one or more processors and one or more memories, and the one or more memories store at least one program code, and the at least one program code is loaded and executed by the one or more processors to realize the operations performed by the method.

[0025] The advantages of the embodiments of the second aspect to the fourth aspect can refer to the advantages of the first aspect and the embodiments of the first aspect, which will not be repeated here.

[0026] It should be understood that the general description above and the detailed description below are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0027] The drawings incorporated in the specification and constituting a part of the specification illustrate embodiments consistent with the present application and, together with the specification, serve to explain the principles of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings. In the drawings:

[0028] Figure 1 A flow chart of a small fault identification method in an embodiment of the present application is shown;

[0029] Figure 2 A frequency spectrum in an embodiment of the present application is shown;

[0030] Figure 3 A conventional high-frequency filter in an embodiment of the present application is shown;

[0031] Figure 4 A high-frequency seismic data graph in an embodiment of the present application is shown;

[0032] Figure 5 A high-frequency energy focusing filter in an embodiment of the present application is shown;

[0033] Figure 6 A high-frequency energy focusing seismic data graph in an embodiment of the present application is shown;

[0034] Figure 7 A neighboring trace coherence slice graph in an embodiment of the present application is shown;

[0035] Figure 8 A high-frequency energy focusing coherence data slice graph in an embodiment of the present application is shown;

[0036] Figure 9 A high-frequency energy focusing coherence enhanced data slice graph in an embodiment of the present application is shown;

[0037] Figure 10 A fault profile feature interpretation graph in an embodiment of the present application is shown;

[0038] Figure 11 A small fault interpretation comparison graph in an embodiment of the present application is shown;

[0039] Figure 12A structure diagram of a small fault identification device in the embodiment of the present application is shown.

[0040] Figure 13 A structure diagram of an electronic device in the embodiment of the present application is shown. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0042] In addition, the described features, structures or characteristics can be combined in any suitable way in one or more embodiments. In the following description, many specific details are provided to give a full understanding of the embodiments of the present application. However, a person of ordinary skill in the art will realize that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be used. In other cases, well-known methods, devices, implementations or operations are not shown or described in detail to avoid obscuring the aspects of the present application.

[0043] The block diagrams shown in the drawings are only functional entities, and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0044] The flowcharts shown in the drawings are only exemplary descriptions, and do not necessarily include all contents and operations / steps, nor do they necessarily be executed in the described order. For example, some operations / steps can be further decomposed, and some operations / steps can be combined or partially combined, so the actual execution order can be changed according to the actual situation.

[0045] Next, the present application will be described in detail:

[0046] Figure 1 A flowchart of a small fault identification method in the embodiment of the present application is shown. The small fault identification method can be executed by a device with computing processing function, such as a small fault identification device. Referring to Figure 1 The small fault identification method at least includes steps 110 to 150, which are described in detail as follows:

[0047] Step 110, determining an effective frequency high cut value by performing spectrum scanning on original seismic data.

[0048] Step 120 : Based on the high-frequency energy focusing filter and the effective frequency high cutoff value, energy focusing is performed on the original seismic data to obtain high-frequency energy focused seismic data.

[0049] Step 130 : Calculate the intrinsic coherence value based on the high-frequency energy focusing seismic data, thereby obtaining high-frequency energy focusing coherence data.

[0050] Step 140 : Calculate a coherence enhancement value based on the high-frequency energy focusing coherence data, thereby obtaining high-frequency energy focusing coherence enhancement data.

[0051] Step 150: Identify small faults based on the high-frequency energy focusing coherence enhancement data.

[0052] In this application, the effective frequency high cutoff is first determined by performing a spectrum scan on the original seismic data. During the spectrum scan, the target layer segment to be scanned and the scan length are determined, wherein the scan length is greater than or equal to 200ms. It should be noted that if the scan length is less than 200ms, the stability of the spectrum graph obtained by scanning will be destroyed. At the same time, during the scanning of the target layer segment, if the thickness of the target layer segment is found to be too small, the stability of the spectrum graph obtained by scanning can be maintained by extending it up and down toward the top and bottom layers.

[0053] Reference Figure 2 , shows the spectrum diagram in the embodiment of the present application. Figure 2 As shown, the horizontal axis is the frequency in Hz, and the vertical axis is the earthquake amplitude in decibels (db). Figure 2 For example, taking the target earthquake amplitude as 12dB, the effective frequency band can be determined to be 10Hz~70Hz, that is, the effective frequency low cutoff Fre _low =10Hz, effective frequency high cutoff Fre _high =70Hz.

[0054] Specifically, refer to Figure 3 , shows a conventional high frequency filter in the embodiment of the present application. In conventional high frequency filters, a single frequency filter with a dominant frequency of about 10 Hz is usually selected for filtering. Figure 3 As shown, the high frequency filter of conventional frequency division technology _Single )'s low-cutoff frequency, low-pass frequency, high-pass frequency, and high-cutoff frequency are [Fre _high -10Hz、Fre _high 、Fre _high 、Fre _high +10Hz], where Figure 3 Fre _high is 70Hz. In addition,Figure 3 As can be seen from FIG. 6, the frequency bandwidth of the conventional filter is only 20 Hz, which is relatively narrow. Meanwhile, the high-frequency seismic data (Seis_Single) can be obtained by filtering the original seismic data (Seis) by using the conventional frequency division technique high-frequency filter. Referring to Figure 4 , a high-frequency seismic data diagram in the embodiment of the present application is shown. According to Figure 4 , it can be known that the high-frequency seismic data (Seis_Single) obtained by the conventional frequency division technique high-frequency filter has false frequency data due to the narrow frequency band, and causes the too continuous phase axis. Therefore, in order to overcome the defect of the narrow frequency band of the conventional frequency division filter and prevent the false frequency data, a high-frequency energy focusing filter (Filter _high ) is needed.

[0055] Based on this, in the embodiment of the present application, the high-frequency energy focusing filter can be constructed by the following steps: determining the effective frequency low cut-off value and the effective frequency high cut-off value according to the frequency spectrum diagram and the target seismic amplitude; focusing the main frequency to the effective frequency high cut-off value, and combining the effective frequency low cut-off value, thereby constructing the high-frequency energy focusing filter.

[0056] Referring to Figure 5 , a high-frequency energy focusing filter in the embodiment of the present application is shown. Based on Figure 2 , the high-frequency energy focusing filter can be obtained in combination with the effective frequency high cut-off value, as shown in Figure 5 . In Figure 5 , the low cut-off frequency, the low-pass frequency, the high-pass frequency, and the high cut-off frequency of the high-frequency energy focusing filter are [Fre _low -10 Hz, Fre _low , Fre _high , Fre _high +10 Hz], wherein Fre _low is 10 Hz, and Fre _high is 70 Hz. Referring to Figure 6 , a high-frequency energy focusing seismic data diagram in the embodiment of the present application is shown. From Figure 6 , it can be known that the high-frequency energy focusing filter improves the resolution of the seismic data by focusing the high-frequency energy focusing seismic data (Seis_high) to the high-frequency end. Meanwhile, due to the wide frequency band of the high-frequency energy focusing filter, the natural development trend of the phase axis is ensured, and the appearance of the false frequency data is prevented.

[0057] After obtaining the high-frequency energy focusing seismic data, the intrinsic coherence value is calculated by using the high-frequency energy focusing seismic data (Seis _high ), thereby obtaining the high-frequency energy focusing coherence data (Coh _high ). Referring toFigure 7 , shows the adjacent channel coherence slice diagram in the embodiment of the present application. Figure 8 , showing a slice of high-frequency energy focusing coherent data in an embodiment of the present application. By comparing the slice of high-frequency energy focusing coherent data with the adjacent channel coherent slice, it can be found that the signal-to-noise ratio and resolution in the slice of high-frequency energy focusing coherent data are significantly improved. Therefore, based on high-frequency energy focusing coherent data, the shortcomings of single-channel coherence and adjacent channel coherence in identifying small faults can be overcome, and the accuracy of fault identification can be improved.

[0058] Reference Figure 9 , shows a slice diagram of high-frequency energy focusing coherence enhancement data in an embodiment of the present application. Since the signals of the fault on the coherence volume slice are all linear features, and the linear features are ridge features in texture image processing. Therefore, ant colony tracking coherence enhancement can be performed according to the ridge direction estimation based on seed region growth in texture image processing, and the coherence enhancement value can be calculated to obtain high-frequency energy focusing coherence enhancement data, and the recognition accuracy of small faults can be further improved based on the high-frequency energy focusing coherence enhancement data. Furthermore. The intrinsic coherence value is calculated by the following formula:

[0059]

[0060] Among them, E c is the total energy, which is used to characterize the intrinsic coherence value; λ1 is the main eigenvalue; N is the number of channels; j is the number of sampling points corresponding to each channel.

[0061] Furthermore, the coherence enhancement value is calculated by the following formula:

[0062]

[0063] in, is the coherence enhancement value; ρ is the enhancement factor; BB′ and AA′ are the ant colony direction and normal direction of the ridge direction estimation, respectively; ΔC represents the coherence gradient in a certain direction; g represents the Gaussian filter centered at k in a certain direction.

[0064] Based on the obtained high-frequency energy focusing coherence enhancement data, small faults are identified by combining plane and section. Figure 10 , shows the fault profile feature interpretation diagram in the embodiment of the present application. Figure 10 A total of 122 faults were interpreted, with relatively short extensions, ranging from approximately 200 meters to the longest of about 2 kilometers, with an average length of approximately 500 meters. Analysis of the fault stages reveals that the north-south faults are early faults of the Hercynian period, with numerous fault horizons and large throws. The northwest-south faults are late faults of the Caledonian period, with fewer fault horizons and smaller throws.

[0065] Reference Figure 11A comparison diagram of the interpretation of small faults in an embodiment of the present application is shown. Figure 11 (a) is the interpretation diagram of the adjacent channel coherent slice small fault. Figure 11 (b) is the interpretation diagram of the intrinsic coherence slice small fault. Figure 11 (c) is the interpretation diagram of small fault slices based on high-frequency energy focusing coherent enhancement data. Among them, for a small fault with a minimum length of about 200m, Figure 11 The interpretation of the small fault of the adjacent channel coherent slice shown in (a) is basically uninterpretable. Figure 11 Although the intrinsic coherence slice small fault interpretation map shown in (b) can be identified to a certain extent, the recognition accuracy is far from enough. Figure 11 The small fault interpretation map (c) based on high-frequency energy focusing coherence-enhanced data slices clearly identifies and characterizes small faults with a minimum length of approximately 200 meters. Furthermore, high-frequency energy focusing coherence-enhanced data slices clearly define the planar characteristics of the faults in the study area. Specifically, three northwest-trending fault zones are observed, extending in an en echelon pattern. This is something that adjacent channel coherence and intrinsic coherence cannot achieve.

[0066] Based on the same inventive concept, the present application also provides a small fault identification device, referring to Figure 12 , shows a schematic structural diagram of a small fault identification device in an embodiment of the present application. The small fault identification device 1200 includes: a first confirmation unit 1201, configured to determine an effective frequency high cutoff by performing spectrum scanning on the original seismic data; a second confirmation unit 1202, configured to perform energy focusing on the original seismic data based on a high-frequency energy focusing filter and the effective frequency high cutoff, thereby obtaining high-frequency energy focused seismic data; a first calculation unit 1203, configured to calculate an intrinsic coherence value based on the high-frequency energy focused seismic data, thereby obtaining high-frequency energy focused coherence data; a second calculation unit 1204, configured to calculate a coherence enhancement value based on the high-frequency energy focused coherence data, thereby obtaining high-frequency energy focused coherence enhanced data; and an identification unit 1205, configured to implement small fault identification based on the high-frequency energy focused coherence enhanced data.

[0067] For details not disclosed in the embodiments of the device of this application, please refer to the embodiments of the above method of this application.

[0068] Based on the same inventive concept, the present application may also provide a computer-readable storage medium, characterized in that at least one program code is stored in the computer-readable storage medium, and the at least one program code is loaded and executed by a processor to implement the operations performed by the described method.

[0069] Based on the same inventive concept, the present application also provides an electronic device, referring to Figure 13 , Figure 13A schematic structural diagram of an electronic device in an embodiment of the present application is shown.

[0070] The electronic device includes one or more memories 1304, one or more processors 1302 and at least one computer program (program code) stored in the memory 1304 and executable on the processor 1302. When the processor 1302 executes the computer program, the method described above is implemented.

[0071] Among them, Figure 13 In the embodiment of the present invention, a bus architecture (represented by bus 1300) is shown. Bus 1300 may include any number of interconnected buses and bridges, and bus 1300 links various circuits including one or more processors represented by processor 1302 and memory represented by memory 1304. Bus 1300 may also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 1305 provides an interface between bus 1300 and receiver 1301 and transmitter 1303. Receiver 1301 and transmitter 1303 may be the same component, namely a transceiver, which provides a unit for communicating with various other devices over a transmission medium. Processor 1302 is responsible for managing bus 1300 and general processing, while memory 1304 may be used to store data used by processor 1302 when performing operations.

[0072] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and implementations are within the scope and spirit of this application and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwiring, or a combination of any of these. Furthermore, the functional units may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0073] In several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other manners. For example, the described unit embodiments can be divided into other ways, for example, the units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interfaces, access layers, program modules or the like, and can be in electrical, mechanical or other forms.

[0074] The units described as separate components can or can not be physically separate, and the components of the control device can or can not be physical units, i.e., can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0075] The integrated units, if implemented in the form of software functional units and sold or used as independent products, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various program codes that can be stored in the medium.

[0076] The above only describes the embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the scope of the claims of the present application.​

Claims

1. A method for identifying small faults, characterized in that: The method comprises: By performing spectrum scanning on the original seismic data, the effective frequency high cutoff value is determined; performing energy focusing on the original seismic data based on a high-frequency energy focusing filter, thereby obtaining high-frequency energy focused seismic data; Calculating an intrinsic coherence value based on the high-frequency energy focused seismic data to obtain high-frequency energy focused coherence data; Calculating a coherence enhancement value according to the high-frequency energy focusing coherence data, thereby obtaining high-frequency energy focusing coherence enhancement data; Based on the high-frequency energy focusing coherence enhancement data, small fault identification is achieved; The method of determining the effective frequency high cutoff value by performing spectrum scanning on the original seismic data includes: By determining the target layer segment and the scanning length, the original seismic data is subjected to spectrum scanning, thereby obtaining a spectrum diagram; Based on the frequency spectrum and in combination with the target earthquake amplitude, determining the effective frequency high cutoff value; Before performing energy focusing on the raw seismic data, the method further includes: Determine the effective frequency low cutoff value based on the spectrum diagram and target earthquake amplitude; The high-frequency energy focusing filter is constructed by focusing the main frequency to the effective frequency high cutoff value and combining it with the effective frequency low cutoff value.

2. The method according to claim 1, characterized in that The scanning length is greater than or equal to 200 ms.

3. The method according to claim 1, characterized in that The target earthquake amplitude is 12db.

4. A small fault identification device, characterized in that: The device comprises: The first confirmation unit is used to determine the effective frequency high cutoff value by performing spectrum scanning on the original seismic data; a second confirmation unit, configured to perform energy focusing on the original seismic data based on a high-frequency energy focusing filter, thereby obtaining high-frequency energy focused seismic data; a first calculation unit, configured to calculate an intrinsic coherence value based on the high-frequency energy focusing seismic data, thereby obtaining high-frequency energy focusing coherence data; a second calculation unit, configured to calculate a coherence enhancement value based on the high-frequency energy focusing coherence data, thereby obtaining high-frequency energy focusing coherence enhancement data; an identification unit, configured to identify small faults based on the high-frequency energy focusing coherence enhancement data; The first confirmation unit is specifically configured to: By determining the target layer segment and the scanning length, the original seismic data is subjected to spectrum scanning, thereby obtaining a spectrum diagram; Determine the effective frequency low cutoff value and the effective frequency high cutoff value according to the spectrum diagram and the target earthquake amplitude; The high-frequency energy focusing filter is constructed by focusing the main frequency to the effective frequency high cutoff value and combining it with the effective frequency low cutoff value.

5. A computer-readable storage medium, characterized in that At least one program code is stored in the computer-readable storage medium, and the at least one program code is loaded and executed by the processor to implement the operations performed by the method according to any one of claims 1 to 3.

6. An electronic device, characterized in that: The electronic device includes one or more processors and one or more memories, wherein the one or more memories store at least one program code, and the at least one program code is loaded and executed by the one or more processors to implement the operations performed by the method according to any one of claims 1 to 3.

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