A method and device for imaging the position of a fractured body

Abstract

This application proposes a method, device, electronic device, and storage medium for imaging the location of a fault-karst body. The method comprises: obtaining a coherent attribute volume of seismic data; obtaining the location of the fault-karst body based on the coherent attribute volume; obtaining the velocity percentage at the location of the fault-karst body based on the coherent attribute volume; establishing a velocity model of the fault-karst body based on the velocity percentage; and obtaining an imaging result at the location of the fault-karst body based on the velocity model of the fault-karst body. This method solves the technical problem in the prior art of poor imaging results at the location of the fault-karst body due to inaccurate velocity models of the fault-karst body.

Description

Technical Field

[0001] The present application belongs to the field of geophysical exploration technology, and specifically relates to a method and device for imaging the position of a fault-karst body. Background Art

[0002] Prestack depth migration is currently a common requirement for seismic data processing, and the key is effective prestack depth-domain velocity modeling. In areas with well-developed fault zones, the signal-to-noise ratio of seismic data is low. Due to inaccurate velocity models of fault-karst locations, imaging of these locations is also poor. Obtaining an accurate fault zone velocity model using grid tomography iteration is difficult, while obtaining accurate fault zone locations using fault interpretation and then performing fault-controlled velocity modeling requires significant effort. Improving imaging of fault-karst locations while minimizing the workload is a pressing issue.

[0003] It should be noted that in the prior art, the velocity model of the fractured body position is not accurate enough, resulting in poor imaging effect at the fractured body position. Summary of the Invention

[0004] In order to overcome the problems existing in the related art to at least a certain extent, the present application provides a method, device, electronic device and storage medium for imaging the position of a discontinuity, which can solve the technical problem in the prior art that the imaging effect at the position of a discontinuity is poor due to the inaccurate velocity model of the discontinuity position.

[0005] To achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a method for imaging the position of a dissolution body, comprising:

[0007] Obtaining coherent attribute volumes of seismic data;

[0008] Based on the coherent attribute body, obtaining the position of the fractured body;

[0009] Based on the coherent attribute body, obtaining the velocity percentage at the position of the disintegration body;

[0010] Establishing a velocity model of the fractured body according to the velocity percentage;

[0011] Based on the velocity model of the fractured body, an imaging result at the position of the fractured body is obtained.

[0012] This application adopts the above method. This solution can improve the model accuracy in pre-stack depth domain velocity modeling of pre-stack depth migration and improve the imaging effect at the fault carve position, thereby solving the technical problem in the prior art that the velocity model at the fault carve position is not accurate enough, resulting in poor imaging effect at the fault carve position.

[0013] Furthermore, the step of obtaining a coherent attribute volume of seismic data includes:

[0014] Ant tracing is performed on the seismic data volume to obtain a coherent attribute volume of the seismic data.

[0015] Furthermore, before performing ant tracing on the seismic data volume to obtain the coherent attribute volume of the seismic data, the method includes:

[0016] The seismic data is subjected to denoising and smoothing processing.

[0017] Furthermore, the coherence value of the coherence attribute body has the following properties: the coherence value ranges from 0 to 1, the closer the coherence value is to 1, the stronger the fracture at that position is, and the closer the coherence value is to 0, the weaker the fracture at that position is.

[0018] Furthermore, based on the coherent attribute body, the step of obtaining the velocity percentage at the position of the disintegration body includes:

[0019] Obtaining a velocity change trend at the location of the fractured body;

[0020] The speed percentage is calculated based on the speed change trend.

[0021] Furthermore, the step of obtaining the velocity change trend at the fractured body position includes:

[0022] Subtracting the coherence value of the coherent attribute from 1 to obtain the speed change trend, wherein the closer the speed change trend is to 1, the smaller the speed change is, and the closer the speed change trend is to 0, the larger the speed change is;

[0023] Calculating the speed percentage based on the speed change trend includes:

[0024] Multiplying the velocity change trend by a preset coefficient and adding the velocity change percentage corresponding to the position with the strongest fracture to obtain a calculation result;

[0025] The speed percentage is determined based on the calculation result.

[0026] Furthermore, the preset coefficient is 0.1.

[0027] Furthermore, the speed change percentage is determined according to the actual speed of the dissolution body.

[0028] Further, determining the speed percentage based on the calculation result includes:

[0029] Replace the values ​​greater than 1 in the calculation result with 1 to obtain a new calculation result;

[0030] Based on the new calculation result, the speed percentage is determined.

[0031] In a second aspect, the present application provides a device for imaging the position of a dissolution body, comprising:

[0032] A first acquisition unit, configured to acquire a coherent attribute volume of seismic data;

[0033] A second acquiring unit, configured to acquire a position of a disintegration body based on the coherent attribute body;

[0034] A third acquiring unit is configured to acquire a velocity percentage at a position of the disintegration body based on the coherent attribute body;

[0035] An establishing unit is used to establish a velocity model of the fractured body according to the velocity percentage;

[0036] The fourth acquisition unit is used to acquire an imaging result at the position of the fractured body based on the velocity model of the fractured body.

[0037] This application uses multiple units in the above-mentioned device. This solution can improve the model accuracy in pre-stack depth domain velocity modeling of pre-stack depth migration, improve the imaging effect at the fault carve position, and solve the technical problem in the prior art that the velocity model at the fault carve position is not accurate enough, resulting in poor imaging effect at the fault carve position.

[0038] Furthermore, the first acquiring unit includes:

[0039] The obtaining module is used to perform ant tracing on the seismic data volume to obtain the coherent attribute volume of the seismic data.

[0040] Furthermore, the device further comprises:

[0041] A denoising unit is used to perform denoising and smoothing processing on the seismic data.

[0042] Furthermore, the coherence value of the coherence attribute body has the following properties: the coherence value ranges from 0 to 1, the closer the coherence value is to 1, the stronger the fracture at that position is, and the closer the coherence value is to 0, the weaker the fracture at that position is.

[0043] Furthermore, the third obtaining unit includes:

[0044] An acquisition module, configured to acquire a velocity change trend at the location of the fractured body;

[0045] A first calculation module is configured to calculate the speed percentage based on the speed change trend.

[0046] Furthermore, the acquisition module includes:

[0047] an obtaining module, configured to obtain the speed change trend by subtracting the coherence value of the coherence attribute body from 1, wherein the closer the speed change trend is to 1, the smaller the speed change is, and the closer the speed change trend is to 0, the larger the speed change is;

[0048] The first calculation module includes:

[0049] A second calculation module is used to multiply the velocity change trend by a preset coefficient, and add the velocity change percentage corresponding to the position with the strongest fracture to obtain a calculation result;

[0050] A first determining module is configured to determine the speed percentage based on the calculation result.

[0051] Furthermore, the preset coefficient is 0.1.

[0052] Furthermore, the speed change percentage is determined according to the actual speed of the dissolution body.

[0053] Furthermore, the determining module includes:

[0054] A third calculation module, configured to replace values ​​greater than 1 in the calculation result with 1 to obtain a new calculation result;

[0055] The second determining module is configured to determine the speed percentage based on the new calculation result.

[0056] In a third aspect, the present application provides an electronic device comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the method for imaging the position of a dissolution body as described in any one of the first aspects are performed.

[0057] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, executes the steps of the method for imaging the position of a dissolution body as described in any one of the first aspects.

[0058] This solution obtains a coherent attribute volume from seismic data; determines the location of a fault-karst body based on this coherent attribute volume; obtains the velocity percentage at the fault-karst body location based on this coherent attribute volume; establishes a velocity model for the fault-karst body based on the velocity percentage; and obtains imaging results at the fault-karst body location based on the velocity model. This solution improves model accuracy and imaging quality at the fault-karst body location in pre-stack depth migration, resolving the existing technical problem of poor imaging quality at the fault-karst body location due to inaccurate velocity models at the fault-karst body location.

[0059] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0061] Figure 1 is a flow chart showing a method for imaging the position of a fractured body according to an exemplary embodiment;

[0062] Figure 2 1 is a schematic diagram of a device for imaging the position of a disintegrating body according to an exemplary embodiment;

[0063] Figure 3 is a flow chart showing a method for imaging the position of a fractured body according to an exemplary embodiment;

[0064] Figures 4 to 7 It is a schematic diagram illustrating the technical effect of the present application according to an exemplary embodiment. DETAILED DESCRIPTION

[0065] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0066] It should be noted that the terms "first", "second", 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 sequential order. 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 a sequence 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 comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0067] Example 1:

[0068] like Figure 1 As shown, this embodiment provides a method for imaging the position of a dissolution body, the method comprising:

[0069] Step S11: obtaining a coherent attribute volume of seismic data.

[0070] Specifically, in this solution, a computer device with processing capabilities, such as a server, can be used as the execution subject of the method of this embodiment. The server can perform coherent processing on the seismic data to obtain a coherent attribute body of the seismic data.

[0071] It should be noted that the coherent attribute bodies of seismic data include corresponding coherent attribute values, and the magnitude of the coherent attribute value represents the strength of the fault.

[0072] It should also be noted that the term "fault-karst body" in this example broadly refers to reservoirs formed by the dissolution of surrounding rocks by atmospheric water or buried fluids along faults. Faults, as crucial fluid pathways, play a crucial role both during the surface and burial periods. As fluids flow through faults, a series of dissolution-filling processes occur. Localized dissolution can lead to the formation of new reservoir spaces or the expansion of pre-existing fractures and pores. The resulting reservoir's development and distribution are closely related to faults, hence the name "fault-karst body."

[0073] Step S13: Based on the above coherent attribute body, the position of the dissolution body is obtained.

[0074] Specifically, in this solution, the server can determine the location of the fracture body based on the coherence value of the coherence attribute body. The size of the coherence attribute value represents the strength of the fracture, so the server can determine the specific location of the fracture body based on the different coherence values ​​of different coherence attribute bodies.

[0075] Step S15: Based on the coherent attribute body, the velocity percentage at the position of the dissolution body is obtained.

[0076] Specifically, in this solution, after determining the position of the discontinuity body, the server can also determine the speed percentage at the position of the discontinuity body based on the above-mentioned coherent attribute body.

[0077] It should be noted that the velocity percentage at the above-mentioned fractured body position may be the percentage of the fractured body velocity change. In this solution, the percentage of the fractured body velocity change may be determined based on the velocity change trend at the fractured body position.

[0078] Step S17: establishing a velocity model of the fractured body according to the above velocity percentage.

[0079] Specifically, in this solution, after obtaining the velocity percentage at the position of the fractured body, a velocity model of the fractured body can be established according to the velocity percentage.

[0080] It should be noted that, in this solution, a high-precision velocity model including the velocity of the fractured body can be obtained by multiplying the preset velocity model with the velocity percentage at the fractured body position.

[0081] Step S19: obtaining an imaging result at the position of the fractured body based on the velocity model of the fractured body.

[0082] Specifically, after generating a high-precision velocity model of the fractured body, the present solution can determine the imaging result at the position of the fractured body by using the velocity model of the fractured body.

[0083] It should be noted that the imaging results at the fault-karst body positions determined by the velocity model of the fault-karst body can be used for the analysis of pre-stack depth migration of seismic data.

[0084] It can be seen from this that the solution of this embodiment is a method for establishing a fault-karst body velocity model in velocity modeling, which can accurately realize fault-karst body modeling and obtain a relatively reasonable high-precision velocity model, thereby improving the imaging at the fault-karst body location and laying a good foundation for pre-stack depth migration of seismic data.

[0085] This solution obtains a coherent attribute volume from seismic data; determines the location of a fault-karst body based on this coherent attribute volume; obtains the velocity percentage at the fault-karst body location based on this coherent attribute volume; establishes a velocity model for the fault-karst body based on the velocity percentage; and obtains imaging results at the fault-karst body location based on the velocity model. This solution improves model accuracy and imaging quality at the fault-karst body location in pre-stack depth migration, resolving the existing technical problem of poor imaging quality at the fault-karst body location due to inaccurate velocity models at the fault-karst body location.

[0086] In an optional embodiment, the step of obtaining the coherent attribute volume of the seismic data in step S11 includes:

[0087] Step S111 : performing ant tracing on the seismic data volume to obtain a coherent attribute volume of the seismic data.

[0088] Specifically, in this solution, the ant tracking algorithm is a complex land shockThis attribute algorithm overcomes subjectivity in interpretation, effectively improving the accuracy of fault interpretation and significantly reducing manual interpretation time. This method utilizes 3D seismic volumes to clearly display fault outlines and automatically extracts fault planes using intelligent search capabilities and 3D visualization technology. This allows geologists to interpret faults with a broader perspective, increasing the objectivity, accuracy, and repeatability of structural interpretation. The ant tracking algorithm's workflow consists of four steps: pre-processing seismic data by enhancing boundary features and highlighting specific stratigraphic discontinuities; generating an ant tracking cube to extract faults; confirming and verifying faults; and creating a final fault interpretation model.

[0089] In an optional embodiment, before performing ant tracing on the seismic data volume to obtain the coherent attribute volume of the seismic data in step S111, the method of this embodiment may include:

[0090] Step S110: performing denoising and smoothing processing on the seismic data.

[0091] Specifically, in this scheme, the above-mentioned seismic data can be smoothed and denoised by using methods such as mean filtering, box filtering, Gaussian filtering, median filtering, and bilateral filtering. After smoothing and denoising, this scheme can perform ant tracking on the smoothed and denoised seismic data to obtain the coherent attribute body of the seismic data.

[0092] In an optional embodiment, the coherence value of the above-mentioned coherence attribute body has the following properties: the coherence value ranges from 0 to 1, the closer the coherence value is to 1, the stronger the fracture at that position is, and the closer the coherence value is to 0, the weaker the fracture at that position is.

[0093] Specifically, in this scheme, the size of the coherent attribute value represents the strength of the fracture, so the server performs coherent value analysis, that is, the specific position of the fracture body can be determined according to the different coherent values ​​of different coherent attribute bodies. After determining the specific position of the fracture body, this scheme obtains the velocity percentage at the fracture body position based on the value of the coherent attribute body.

[0094] In an optional embodiment, step S15 of obtaining the velocity percentage at the position of the disintegration body based on the coherent attribute body may include:

[0095] Step S151, obtaining the velocity change trend at the position of the above-mentioned fractured body.

[0096] Step S153: Calculate the speed percentage based on the speed change trend.

[0097] Specifically, in this solution, the server may first obtain the velocity change trend at the location of the above-mentioned broken melt, and then calculate the velocity percentage at the location of the broken melt based on the velocity change trend at the location of the broken melt. It should be noted that the velocity percentage at the location of the broken melt may be the percentage of the velocity change of the broken melt. After obtaining the percentage of the velocity change of the broken melt, this solution establishes a velocity model of the broken melt based on the velocity percentage.

[0098] In an optional embodiment, the step S151 of obtaining the velocity change trend at the position of the fractured body may include:

[0099] Step S1511 , subtracting the coherence value of the coherent attribute from 1 to obtain the speed change trend, wherein the closer the speed change trend is to 1, the smaller the speed change is, and the closer the speed change trend is to 0, the larger the speed change is.

[0100] Step S1513, calculating the speed percentage based on the speed change trend, includes:

[0101] Step S1515: multiply the velocity change trend by a preset coefficient, and add the velocity change percentage corresponding to the position with the strongest fracture to obtain a calculation result;

[0102] Step S1517: Determine the speed percentage based on the calculation result.

[0103] Specifically, in this solution, the velocity trend at the fracture location is represented by subtracting the coherence value from 1. That is, the closer the value is to 1, the more constant the velocity is, and the closer it is to 0, the greater the velocity change. This solution multiplies the velocity trend at the fracture location by a preset coefficient, then adds the velocity change percentage corresponding to the strongest fracture location to the calculated result. Finally, the aforementioned velocity percentage is determined based on this calculated result.

[0104] In an optional embodiment, the preset coefficient is 0.1.

[0105] In an optional embodiment, the above-mentioned velocity change percentage is determined according to the actual velocity of the dissolution body.

[0106] In an optional embodiment, the step of determining the speed percentage based on the calculation result in step S1517 includes:

[0107] Step S15171: Replace the values ​​greater than 1 in the above calculation results with 1 to obtain a new calculation result.

[0108] Step S15172: Determine the speed percentage based on the new calculation result.

[0109] Specifically, this solution can be edited for the speed change percentage. For the speed ratio to be obtained, the value greater than 1 is changed to 1. This also eliminates the speed change at the small fracture position and obtains the speed percentage at the final fracture dissolution position.

[0110] In summary, this embodiment is a method for establishing a fault-karst body velocity model in velocity modeling, which can accurately implement fault-karst body modeling and obtain a relatively reasonable high-precision velocity model, thereby improving the imaging at the fault-karst body location and laying a good foundation for pre-stack depth migration of seismic data.

[0111] Example 2:

[0112] like Figure 2 As shown, this embodiment provides a device for imaging the position of a dissolution body. The device can be set in a server and can also be used to perform the method of the above embodiment 1. The device can include: a first acquisition unit 20, a second acquisition unit 22, a third acquisition unit 24, an establishment unit 26, and a fourth acquisition unit 28. The functions of the above multiple units are described as follows:

[0113] The first acquisition unit 20 is used to acquire a coherent attribute volume of seismic data.

[0114] Specifically, in this solution, the seismic data may be coherently processed to obtain a seismic data coherent attribute body.

[0115] It should be noted that the coherent attribute bodies of seismic data include corresponding coherent attribute values, and the magnitude of the coherent attribute value represents the strength of the fault.

[0116] It should also be noted that the term "fault-karst body" in this example broadly refers to reservoirs formed by the dissolution of surrounding rocks by atmospheric water or buried fluids along faults. Faults, as crucial fluid pathways, play a crucial role both during the surface and burial periods. As fluids flow through faults, a series of dissolution-filling processes occur. Localized dissolution can lead to the formation of new reservoir spaces or the expansion of pre-existing fractures and pores. The resulting reservoir's development and distribution are closely related to faults, hence the name "fault-karst body."

[0117] The second acquiring unit 22 is configured to acquire the position of the dissolution body based on the coherent attribute body.

[0118] Specifically, in this solution, the position of the fracture body can be determined based on the coherence value of the coherence attribute body. The size of the coherence attribute value represents the strength of the fracture. Therefore, the server can determine the specific position of the fracture body based on the different coherence values ​​of different coherence attribute bodies.

[0119] The third acquiring unit 24 is configured to acquire a velocity percentage at the position of the disintegration body based on the coherent attribute body.

[0120] Specifically, in this solution, after determining the position of the discontinuity body, the server can also determine the speed percentage at the position of the discontinuity body based on the above-mentioned coherent attribute body.

[0121] It should be noted that the velocity percentage at the above-mentioned fractured body position may be the percentage of the fractured body velocity change. In this solution, the percentage of the fractured body velocity change may be determined based on the velocity change trend at the fractured body position.

[0122] The establishing unit 26 is used to establish a velocity model of the fractured body according to the above velocity percentage.

[0123] Specifically, in this solution, after obtaining the velocity percentage at the position of the fractured body, a velocity model of the fractured body can be established according to the velocity percentage.

[0124] It should be noted that, in this solution, a high-precision velocity model including the velocity of the fractured body can be obtained by multiplying the preset velocity model with the velocity percentage at the fractured body position.

[0125] The fourth acquiring unit 28 is configured to acquire an imaging result at the position of the fractured body based on the velocity model of the fractured body.

[0126] Specifically, after generating a high-precision velocity model of the fractured body, the present solution can determine the imaging result at the position of the fractured body by using the velocity model of the fractured body.

[0127] It should be noted that the imaging results at the fault-karst body positions determined by the velocity model of the fault-karst body can be used for the analysis of pre-stack depth migration of seismic data.

[0128] It can be seen from this that the solution of this embodiment is a method for establishing a fault-karst body velocity model in velocity modeling, which can accurately realize fault-karst body modeling and obtain a relatively reasonable high-precision velocity model, thereby improving the imaging at the fault-karst body location and laying a good foundation for pre-stack depth migration of seismic data.

[0129] This solution utilizes multiple units in the aforementioned device to obtain coherent attributes from seismic data; obtain the location of a fault-knee body based on the coherent attributes; obtain the velocity percentage at the location of the fault-knee body based on the coherent attributes; establish a velocity model for the fault-knee body based on the velocity percentage; and obtain imaging results at the location of the fault-knee body based on the velocity model. This solution improves model accuracy and imaging quality at the location of the fault-knee body in pre-stack depth migration velocity modeling, thereby resolving the prior art technical problem of poor imaging quality at the location of the fault-knee body due to inaccurate velocity models at the location of the fault-knee body.

[0130] In an optional embodiment, the first obtaining unit includes:

[0131] The obtaining module is used to perform ant tracing on the seismic data volume to obtain the coherent attribute volume of the seismic data.

[0132] Specifically, in this solution, the ant tracking algorithm is a complex seismic attribute algorithm within the existing Petrel software. This attribute algorithm overcomes subjectivity in interpretation, effectively improving the accuracy of fault interpretation and significantly reducing manual interpretation time. This method utilizes 3D seismic volumes to clearly display fault outlines and automatically extracts fault planes using intelligent search capabilities and 3D visualization technology. This allows geologists to interpret faults with a broader perspective, increasing the objectivity, accuracy, and repeatability of structural interpretation. The ant tracking algorithm's workflow consists of four steps: pre-processing seismic data by enhancing boundary features and highlighting specific stratigraphic discontinuities; generating an ant tracking cube to extract faults; confirming and verifying faults; and creating a final fault interpretation model.

[0133] In an optional embodiment, the above device further includes:

[0134] The denoising unit is used to perform denoising and smoothing processing on the above seismic data.

[0135] Specifically, in this scheme, the above-mentioned seismic data can be smoothed and denoised by using methods such as mean filtering, box filtering, Gaussian filtering, median filtering, and bilateral filtering. After smoothing and denoising, this scheme can perform ant tracking on the smoothed and denoised seismic data to obtain the coherent attribute body of the seismic data.

[0136] In an optional embodiment, the coherence value of the above-mentioned coherence attribute body has the following properties: the coherence value ranges from 0 to 1, the closer the coherence value is to 1, the stronger the fracture at that position is, and the closer the coherence value is to 0, the weaker the fracture at that position is.

[0137] Specifically, in this scheme, the size of the coherent attribute value represents the strength of the fracture, so the server performs coherent value analysis, that is, the specific position of the fracture body can be determined according to the different coherent values ​​of different coherent attribute bodies. After determining the specific position of the fracture body, this scheme obtains the velocity percentage at the fracture body position based on the value of the coherent attribute body.

[0138] In an optional embodiment, the third obtaining unit includes:

[0139] An acquisition module is used to obtain the velocity change trend at the position of the fractured body;

[0140] The first calculation module is used to calculate the speed percentage based on the speed change trend.

[0141] Specifically, in this solution, the server may first obtain the velocity change trend at the location of the above-mentioned broken melt, and then calculate the velocity percentage at the location of the broken melt based on the velocity change trend at the location of the broken melt. It should be noted that the velocity percentage at the location of the broken melt may be the percentage of the velocity change of the broken melt. After obtaining the percentage of the velocity change of the broken melt, this solution establishes a velocity model of the broken melt based on the velocity percentage.

[0142] In an optional embodiment, the acquisition module includes:

[0143] an obtaining module, configured to obtain the speed change trend by subtracting the coherence value of the coherence attribute body from 1, wherein the closer the speed change trend is to 1, the smaller the speed change is, and the closer the speed change trend is to 0, the larger the speed change is;

[0144] The first computing module includes:

[0145] The second calculation module is used to multiply the above velocity change trend by a preset coefficient, and add the velocity change percentage corresponding to the position with the strongest fracture to obtain a calculation result;

[0146] The first determining module is configured to determine the speed percentage based on the calculation result.

[0147] Specifically, in this solution, the velocity trend at the fracture location is represented by subtracting the coherence value from 1. That is, the closer the value is to 1, the more constant the velocity is, and the closer it is to 0, the greater the velocity change. This solution multiplies the velocity trend at the fracture location by a preset coefficient, then adds the velocity change percentage corresponding to the strongest fracture location to the calculated result. Finally, the aforementioned velocity percentage is determined based on this calculated result.

[0148] In an optional embodiment, the preset coefficient is 0.1.

[0149] In an optional embodiment, the above-mentioned velocity change percentage is determined according to the actual velocity of the dissolution body.

[0150] In an optional embodiment, the determination module includes:

[0151] A third calculation module is used to replace the values ​​greater than 1 in the above calculation results with 1 to obtain a new calculation result;

[0152] The second determining module is configured to determine the speed percentage based on the new calculation result.

[0153] Specifically, this solution can be edited for the speed change percentage. For the speed ratio to be obtained, the value greater than 1 is changed to 1. This also eliminates the speed change at the small fracture position and obtains the speed percentage at the final fracture dissolution position.

[0154] In summary, the device provided in this embodiment is a device for establishing a fault-karst body velocity model in velocity modeling. It can accurately implement fault-karst body modeling and obtain a relatively reasonable high-precision velocity model, thereby improving the imaging at the fault-karst body location and laying a good foundation for pre-stack depth migration of seismic data.

[0155] Example 3

[0156] The present application also provides an electronic device, comprising: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate via the bus. When the machine-readable instructions are executed by the processor, the following steps are performed:

[0157] Obtaining coherent attribute volumes of seismic data;

[0158] Based on the above coherent attribute body, the position of the fractured body is obtained;

[0159] Based on the above coherent attribute body, obtaining the velocity percentage at the position of the above disintegration body;

[0160] A velocity model of the fault melt is established based on the above velocity percentages;

[0161] Based on the velocity model of the fractured body, an imaging result at the position of the fractured body is obtained.

[0162] When the processor executes the machine-readable instructions, the processor further executes the following steps:

[0163] Ant tracing is performed on the seismic data volume to obtain the coherent attribute volume of the seismic data.

[0164] When the processor executes the machine-readable instructions, the processor further executes the following steps:

[0165] The above seismic data are subjected to denoising and smoothing processing.

[0166] When the above machine-readable instructions are executed by the above processor, the following functions are further performed:

[0167] The coherence value of the above coherence attribute body has the following properties: the coherence value ranges from 0 to 1. The closer the coherence value is to 1, the stronger the fracture at that location is, and the closer the coherence value is to 0, the weaker the fracture at that location is.

[0168] When the above machine-readable instructions are executed by the above processor, the following functions are further performed:

[0169] Obtain the velocity change trend at the location of the above-mentioned fault melt;

[0170] The speed percentage is calculated based on the speed change trend.

[0171] When the above machine-readable instructions are executed by the above processor, the following functions are further performed:

[0172] The speed change trend is obtained by subtracting the coherence value of the coherent attribute from 1, wherein the closer the speed change trend is to 1, the smaller the speed change is, and the closer the speed change trend is to 0, the larger the speed change is.

[0173] The above speed percentage is calculated based on the above speed change trend, including:

[0174] The above velocity change trend is multiplied by the preset coefficient, and then the velocity change percentage corresponding to the location with the strongest fracture is added to obtain the calculation result;

[0175] The above speed percentage is determined based on the above calculation results.

[0176] When the above machine-readable instructions are executed by the above processor, the following functions are further performed:

[0177] Set the above preset coefficient to 0.1

[0178] When the above machine-readable instructions are executed by the above processor, the following functions are further performed:

[0179] The above velocity change percentage is determined according to the actual velocity of the fractured body.

[0180] When the above machine-readable instructions are executed by the above processor, the following functions are further performed:

[0181] Replace the values ​​greater than 1 in the above calculation results with 1 to obtain a new calculation result;

[0182] Based on the above new calculation results, the above speed percentages are determined.

[0183] Based on the multiple steps performed when the processor executes the machine-readable instructions, the present solution first obtains a coherent attribute volume of seismic data; obtains the location of a fault-knee body based on the coherent attribute volume; obtains the velocity percentage at the location of the fault-knee body based on the coherent attribute volume; establishes a velocity model for the fault-knee body based on the velocity percentage; and obtains an imaging result at the location of the fault-knee body based on the velocity model for the fault-knee body. This solution improves model accuracy and imaging quality at the location of the fault-knee body in pre-stack depth migration velocity modeling, thereby resolving the technical problem in the prior art of poor imaging quality at the location of the fault-knee body due to inaccurate velocity models at the location of the fault-knee body.

[0184] Example 4

[0185] This embodiment further provides a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and the storage medium may be a volatile or non-volatile computer-readable storage medium.

[0186] The computer program is executed by a processor to perform the following steps:

[0187] Obtaining coherent attribute volumes of seismic data;

[0188] Based on the above coherent attribute body, the position of the fractured body is obtained;

[0189] Based on the above coherent attribute body, obtaining the velocity percentage at the position of the above disintegration body;

[0190] A velocity model of the fault melt is established based on the above velocity percentages;

[0191] Based on the velocity model of the fractured body, an imaging result at the position of the fractured body is obtained.

[0192] The computer program is executed by a processor to perform the following steps:

[0193] Ant tracing is performed on the seismic data volume to obtain the coherent attribute volume of the seismic data.

[0194] When the processor executes the machine-readable instructions, the processor further executes the following steps:

[0195] The above seismic data are subjected to denoising and smoothing processing.

[0196] The computer program is executed by a processor to perform the following functions:

[0197] The coherence value of the above coherence attribute body has the following properties: the coherence value ranges from 0 to 1. The closer the coherence value is to 1, the stronger the fracture at that location is, and the closer the coherence value is to 0, the weaker the fracture at that location is.

[0198] The computer program is executed by a processor to perform the following functions:

[0199] Obtain the velocity change trend at the location of the above-mentioned fault melt;

[0200] The speed percentage is calculated based on the speed change trend.

[0201] The speed change trend is obtained by subtracting the coherence value of the coherent attribute from 1, wherein the closer the speed change trend is to 1, the smaller the speed change is, and the closer the speed change trend is to 0, the larger the speed change is.

[0202] The above speed percentage is calculated based on the above speed change trend, including:

[0203] The above velocity change trend is multiplied by the preset coefficient, and then the velocity change percentage corresponding to the location with the strongest fracture is added to obtain the calculation result;

[0204] The above speed percentage is determined based on the above calculation results.

[0205] The computer program is executed by a processor to perform the following functions:

[0206] Set the above preset coefficient to 0.1

[0207] The computer program is executed by a processor to perform the following functions:

[0208] The above velocity change percentage is determined according to the actual velocity of the fractured body.

[0209] The computer program is executed by a processor to perform the following functions:

[0210] Replace the values ​​greater than 1 in the above calculation results with 1 to obtain a new calculation result;

[0211] Based on the above new calculation results, the above speed percentages are determined.

[0212] Based on the multiple steps performed when the computer program is executed by the processor, this solution first obtains a coherent attribute volume from seismic data; obtains the location of a fault-knee body based on the coherent attribute volume; obtains the velocity percentage at the location of the fault-knee body based on the coherent attribute volume; establishes a velocity model for the fault-knee body based on the velocity percentage; and obtains an imaging result at the location of the fault-knee body based on the velocity model of the fault-knee body. This solution improves model accuracy and imaging quality at the location of the fault-knee body in pre-stack depth migration, thereby resolving the technical problem in the prior art of poor imaging quality at the location of the fault-knee body due to inaccurate velocity models at the location of the fault-knee body.

[0213] The present disclosure also provides a computer program product that carries a program code. The program code includes instructions that can be used to execute the steps of the method for imaging the position of a dissolution body in the method embodiment. For details, please refer to the method embodiment, which will not be repeated here.

[0214] Example 5

[0215] The following introduces a preferred embodiment of the present application, which provides a method for fault-karst velocity modeling. This embodiment relates to the field of geophysical exploration technology, and specifically to the velocity modeling process in seismic data processing. The invention can be applied to pre-stack depth migration velocity modeling in oil and gas seismic exploration and fault-karst seismic exploration.

[0216] The purpose of the embodiments of this application is described below:

[0217] The purpose of this embodiment is to perform high-precision velocity modeling at the locations of fault-karst bodies, obtaining a more accurate depth-domain velocity model, thereby improving imaging at these locations. This invention can improve model accuracy and imaging at fault-karst bodies in pre-stack depth-domain velocity modeling for pre-stack depth migration, thus showing promising application prospects in the field of depth-domain imaging of seismic exploration data.

[0218] It should be noted that the technical principle of this embodiment is to obtain a relatively accurate position of the fault-karst body based on the coherence of seismic data, and to perform fault-karst body velocity modeling on this basis.

[0219] The following combination Figure 3 , introduces the implementation process of this embodiment:

[0220] Step S31, data preparation: ant tracing is performed on the appropriate denoised and smoothed depth domain seismic data volume to obtain the coherent attribute volume of the data.

[0221] Specifically, in this solution, a computer device with processing capabilities, such as a server, can be used as the execution subject of the method of this embodiment. The server can perform coherent processing on the seismic data to obtain a coherent attribute body of the seismic data.

[0222] It should be noted that the ant tracking algorithm is a complex seismic attribute algorithm within the existing Petrel software. This attribute algorithm overcomes subjectivity in interpretation, effectively improves fault interpretation accuracy, and significantly reduces manual interpretation time. This method utilizes a 3D seismic volume to clearly display fault outlines and automatically extracts fault planes using intelligent search capabilities and 3D visualization technology. This allows geologists to interpret faults with a broader perspective, increasing the objectivity, accuracy, and repeatability of structural interpretation. The ant tracking algorithm workflow consists of four steps: preprocessing the seismic data by enhancing boundary features and highlighting specific stratigraphic discontinuities; generating an ant tracking cube to extract faults; confirming and verifying faults; and creating a final fault interpretation model. In this approach, the seismic data can be smoothed and denoised using methods such as mean filtering, box filtering, Gaussian filtering, median filtering, and bilateral filtering. After smoothing and denoising, this approach can perform ant tracking on the smoothed and denoised seismic data to obtain a coherent attribute volume for the acquired seismic data.

[0223] Step S32, analyzing the coherence value: for a coherent body, the coherence value ranges from 0 to 1. The closer the coherence value is to 1, the stronger the fracture is, and the closer the coherence value is to 0, the weaker the fracture is.

[0224] Specifically, in this solution, the server can determine the location of the fracture body based on the coherence value of the coherence attribute body. The size of the coherence attribute value represents the strength of the fracture, so the server can determine the specific location of the fracture body based on the different coherence values ​​of different coherence attribute bodies.

[0225] Step S33, obtaining the velocity change trend: subtracting the coherence value from 1 represents the velocity change trend at the fracture position, that is, the closer to 1, the more constant the velocity is, and the closer to 0, the greater the velocity change is.

[0226] Step S34, calculate the velocity change percentage: multiply the velocity change trend calculated in the previous step by a coefficient of 0.1, and add the velocity change percentage corresponding to the strongest fracture location. This percentage is determined based on the actual velocity of the fractured body.

[0227] Step S35, edit the speed change percentage: for the speed ratio obtained in the previous step, change the value greater than 1 to 1, which also eliminates the speed change at the small fracture position and obtains the speed percentage at the final fracture melt position.

[0228] Step S36, establishing a velocity model of the fractured body: by multiplying the velocity model with the velocity percentage at the fractured body position, a high-precision velocity model including the fractured body velocity is obtained.

[0229] Specifically, in this embodiment, "fault-karst bodies" broadly refer to reservoirs formed by the dissolution of surrounding rocks by atmospheric water or buried fluids along faults. Faults, as crucial fluid pathways, play a crucial role both during the surface and burial periods. As fluids flow through faults, they undergo a series of dissolution-filling processes. Localized dissolution can lead to the formation of new reservoir spaces or the expansion of pre-existing fractures and pores. The resulting reservoirs exhibit a close relationship between their development and distribution with faults, hence the term "fault-karst bodies."

[0230] This solution obtains a coherent attribute volume from seismic data; determines the location of a fault-karst body based on this coherent attribute volume; obtains the velocity percentage at the fault-karst body location based on this coherent attribute volume; establishes a velocity model for the fault-karst body based on the velocity percentage; and obtains imaging results at the fault-karst body location based on the velocity model. This solution improves model accuracy and imaging quality at the fault-karst body location in pre-stack depth migration, resolving the existing technical problem of poor imaging quality at the fault-karst body location due to inaccurate velocity models at the fault-karst body location.

[0231] Combine Figures 4 to 7 , Figure 4 is the velocity model before fault melt modeling, Figure 5 It is the velocity model after the fault melt modeling is carried out through the process of this scheme. Figure 6 is the migration profile corresponding to the velocity model before fault-karst body modeling, Figure 7 It is the offset profile corresponding to the velocity model after fault-karst modeling. Figures 4 to 7 It can be seen that the technical effect of this solution is that through this embodiment, a more accurate fracture-dissolved body velocity model is established, and fracture-dissolved body imaging is improved.

[0232] In summary, the solution provided by this embodiment of the present invention is a method for establishing a fault-karst body velocity model in velocity modeling, which can accurately realize fault-karst body modeling and obtain a relatively reasonable high-precision velocity model, thereby improving the imaging at the fault-karst body position, and laying a good foundation for pre-stack depth migration of seismic data. This embodiment belongs to the field of processing seismic data of geophysical exploration, and specifically relates to the velocity modeling process in seismic data processing. The solution of this embodiment is aimed at the velocity at the fault-karst body position in the velocity modeling process, and cleverly uses the data coherence body attributes obtained by ant tracking to obtain the accurate fault-karst body position, and at the same time uses the coherence value to calculate the fault-karst body velocity model percentage, and on this basis obtains a high-precision fault-karst body velocity model. The solution provided by this embodiment can improve the accuracy and efficiency of velocity modeling, and thus has a good application prospect in pre-stack depth migration of seismic data.

[0233] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0234] It should be noted that, in the description of this application, the terms "first," "second," etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, the meaning of "plurality" or "multiple" is at least two.

[0235] It should be understood that when an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or there may be an intervening element at the same time; when an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intervening element at the same time. In addition, the "connection" used here may include wireless connection; the wording "and / or" used includes any unit and all combinations of one or more associated listed items.

[0236] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0237] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0238] Those skilled in the art will understand that all or part of the steps carried out in the method of the above-mentioned embodiment can be completed by instructing the relevant hardware through a program, and the above-mentioned program can be stored in a computer-readable storage medium. When the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0239] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the above-mentioned integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

[0240] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0241] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0242] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for imaging the position of a fractured body, characterized in that: include: Acquire a coherent attribute body of seismic data; wherein the coherent attribute body of seismic data includes a coherent value corresponding thereto, and the magnitude of the coherent value represents the strength of the fault; Obtaining the position of the disintegration body based on the coherence value of the coherent attribute body; Based on the coherent attribute body, obtaining the velocity percentage at the position of the disintegration body includes: obtaining the velocity change trend at the position of the disintegration body; calculating the velocity percentage based on the velocity change trend; wherein, The step of obtaining the velocity change trend at the position of the dissolution body comprises: subtracting the coherence value of the coherent attribute body from 1 to obtain the velocity change trend, wherein the closer the velocity change trend is to 1, the smaller the velocity change is, and the closer the velocity change trend is to 0, the larger the velocity change is; Calculating the speed percentage based on the speed change trend includes: multiplying the speed change trend by a preset coefficient, and adding the speed change percentage corresponding to the position with the strongest fracture to obtain a calculation result; and determining the speed percentage based on the calculation result; A velocity model of the fractured body is established according to the velocity percentage, including: multiplying a preset velocity model by the velocity percentage at the fractured body position to obtain a velocity model including the fractured body velocity; and obtaining an imaging result at the fractured body position based on the velocity model of the fractured body.

2. The method according to claim 1, characterized in that The step of obtaining a coherent attribute volume of seismic data comprises: Ant tracing is performed on the seismic data volume to obtain a coherent attribute volume of the seismic data.

3. The method according to claim 2, characterized in that Before performing ant tracing on the seismic data volume to obtain the coherent attribute volume of the seismic data, the method includes: The seismic data is subjected to denoising and smoothing processing.

4. The method according to claim 1, wherein The coherence value of the coherence attribute body has the following properties: the coherence value ranges from 0 to 1, the closer the coherence value is to 1, the stronger the fracture at that position is, and the closer the coherence value is to 0, the weaker the fracture at that position is.

5. The method according to claim 1, wherein The preset coefficient is 0.

1.

6. The method according to claim 1, characterized in that The speed change percentage is determined according to the actual speed of the dissolution body.

7. The method according to claim 1, characterized in that Determining the speed percentage based on the calculation result includes: Replace the values ​​greater than 1 in the calculation result with 1 to obtain a new calculation result; Based on the new calculation result, the speed percentage is determined.

8. A device for imaging the position of a dissolution body, characterized in that: include: A first acquisition unit is configured to acquire a coherent attribute body of seismic data, wherein the coherent attribute body of seismic data includes a corresponding coherence value, and the magnitude of the coherence value represents the strength of the fault; A second acquiring unit, configured to acquire a position of a disintegration body based on a coherence value of the coherence attribute body; The third acquisition unit is used to acquire the velocity percentage at the position of the fracture body based on the coherent attribute body; wherein the third acquisition unit includes: an acquisition module for acquiring the velocity change trend at the position of the fracture body; a first calculation module for calculating the velocity percentage based on the velocity change trend; wherein, The acquisition module includes: an obtaining module for subtracting the coherence value of the coherence attribute body from 1 to obtain the speed change trend, wherein the closer the speed change trend is to 1, the smaller the speed change is, and the closer the speed change trend is to 0, the larger the speed change is; The first calculation module includes: a second calculation module for multiplying the speed change trend by a preset coefficient and adding the speed change percentage corresponding to the position with the strongest fracture to obtain a calculation result; a first determination module for determining the speed percentage based on the calculation result; An establishing unit is used to establish a velocity model of the fractured body according to the velocity percentage, comprising: multiplying a preset velocity model by the velocity percentage at the fractured body position to obtain a velocity model including the fractured body velocity; The fourth acquisition unit is used to acquire an imaging result at the position of the fractured body based on the velocity model of the fractured body.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the method for imaging the position of a dissolution body as described in any one of claims 1 to 7 are performed.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the method for imaging the position of a dissolution body as claimed in any one of claims 1 to 7.

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