Seismic data reconstruction method, device and computer equipment

Abstract

This application discloses a seismic data reconstruction method, apparatus, and computer equipment, belonging to the field of seismic data processing. The method includes: acquiring three-dimensional seismic data corresponding to a geological structure; acquiring a first distribution location and shot point data corresponding to seismic firing points during geological exploration; acquiring a second distribution location and geophone data corresponding to geophone points during geological exploration; generating a seismic data matrix based on the shot point data and geophone data, using the first distribution location as the horizontal dimension and the second distribution location as the vertical dimension; and reconstructing the three-dimensional seismic data based on the three-dimensional seismic data and the seismic data matrix to obtain supplementary seismic data, which is used to supplement the missing seismic data at each seismic firing point and geophone point during geological exploration. This improves the completeness of the acquired seismic data.

Description

Technical Field

[0001] This application relates to the field of earthquake data processing, and in particular to an earthquake data reconstruction method, apparatus, and computer equipment. Background Technology

[0002] As the resolution requirements of seismic exploration and processing technologies increase, the demands on modern seismic data acquisition technologies are also rising.

[0003] In related technologies, during geological exploration, seismic firing points and geophones are set up at the exploration site. The seismic firing points send seismic waves to the geological structure, and the seismic waves return to the ground to generate signals. The geophones receive the signals related to the seismic waves returned by the seismic firing points to obtain seismic data.

[0004] However, if the shot data corresponding to the seismic trigger shot point and the receiver data corresponding to the receiver point are lost or not detected, the subsequent geological interpretation process cannot be carried out. Summary of the Invention

[0005] This application provides a seismic data reconstruction method, apparatus, and computer equipment. It constructs an observation system for receiver and shot point data, and then combines this with actual acquired 3D seismic data to supplement missing seismic data. While ensuring that the original 3D seismic resolution and other characteristics remain unchanged, it improves the completeness of the acquired seismic data and enhances the efficiency of subsequent seismic data interpretation. The technical solution is as follows:

[0006] According to one aspect of this application, a seismic data reconstruction method is provided, the method comprising:

[0007] Acquire three-dimensional seismic data corresponding to geological structures, wherein the three-dimensional seismic data is used to indicate the data collected during geological exploration.

[0008] Obtain the first distribution location and shot point data of the geological structure corresponding to the seismic firing points during the geological exploration process;

[0009] Obtain the second distribution location of the geophone points corresponding to the geological structure during the geological exploration process, as well as the geophone point data;

[0010] Using the first distribution location as the horizontal dimension and the second distribution location as the vertical dimension, a seismic data matrix is ​​generated based on the shot point data and the receiver point data.

[0011] Based on the three-dimensional seismic data and the seismic data matrix, the three-dimensional seismic data is reconstructed to obtain supplementary seismic data, which is used to supplement the seismic data missing at each seismic firing point and each geophone point during the geological exploration process.

[0012] According to one aspect of this application, a seismic data reconstruction apparatus is provided, the apparatus comprising:

[0013] The acquisition module is used to acquire three-dimensional seismic data corresponding to geological structures, wherein the three-dimensional seismic data is used to indicate the data collected during geological exploration.

[0014] The acquisition module is used to acquire the first distribution location and shot point data corresponding to the seismic firing points of the geological structure during the geological exploration process.

[0015] The acquisition module is used to acquire the second distribution location of the geophone points corresponding to the geological structure and the geophone point data during the geological exploration process.

[0016] The generation module is used to generate a seismic data matrix based on the shot point data and the receiver point data, with the first distribution location as the horizontal dimension and the second distribution location as the vertical dimension.

[0017] The reconstruction module is used to reconstruct the three-dimensional seismic data based on the three-dimensional seismic data and the seismic data matrix to obtain supplementary seismic data. The supplementary seismic data is used to supplement the seismic data missing from each seismic firing point and each receiver point during the geological exploration process.

[0018] According to one aspect of this application, a computer device is provided, the computer device including a processor and a memory, the memory storing a computer program, the processor loading and executing the computer program to implement the seismic data reconstruction method as described above.

[0019] According to another aspect of this application, a computer-readable storage medium is provided, which stores a computer program that is loaded and executed by a processor to implement the seismic data reconstruction method described above.

[0020] According to another aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the aforementioned seismic data reconstruction method.

[0021] The beneficial effects of the technical solutions provided in this application include at least the following:

[0022] By using the location information (first and second distribution locations) of shot points and receiver points during geological exploration and the specific acquired data (shot point data and receiver point data), a seismic data matrix is ​​generated. Then, based on the seismic data matrix and the 3D seismic data, the 3D seismic data is reconstructed, and the missing data in the seismic data matrix is ​​supplemented, further improving the data integrity of the 3D seismic data, making it more comprehensively reflect the actual situation of the geological structure, and facilitating the efficiency of subsequent geological interpretation. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram illustrating an exemplary embodiment of the seismic data reconstruction method provided in this application;

[0025] Figure 2 This is a flowchart of a seismic data reconstruction method provided in an exemplary embodiment of this application;

[0026] Figure 3 This is a flowchart of a seismic data reconstruction method provided in another exemplary embodiment of this application;

[0027] Figure 4 This is a flowchart of a seismic data reconstruction method provided in another exemplary embodiment of this application;

[0028] Figure 5 This is a schematic diagram corresponding to the minimum subset of earthquakes provided in an exemplary embodiment of this application;

[0029] Figure 6 This is a schematic diagram illustrating the comparison of reconstructed data provided in an exemplary embodiment of this application;

[0030] Figure 7 This is a flowchart of a seismic data reconstruction apparatus provided in an exemplary embodiment of this application;

[0031] Figure 8 This is a flowchart of a seismic data reconstruction apparatus provided in another exemplary embodiment of this application;

[0032] Figure 9 This is a structural block diagram of a computer device provided in an exemplary embodiment of this application. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0034] First, the terminology and related technologies involved in this application will be introduced.

[0035] Seismic data refers to information about underground geological structures and tectonic features acquired through seismic exploration activities. Seismic data is generated by physical phenomena such as reflection, refraction, and scattering of seismic waves, and is used to infer the type, distribution, structure, and potential oil and gas reservoirs of underground rocks. Seismic data includes at least one of the following: reflection data, refraction data, seismic amplitude, seismic travel time, seismic frequency and waveform, seismic time slices, seismic velocity data, and seismic data quality. In this embodiment, the seismic data mainly includes data related to the seismic shot point and receiver point. Schematally, the seismic data is implemented as three-dimensional seismic data, which includes time data, shot point data, and receiver point data.

[0036] Secondly Figure 1 A structural block diagram of a computer system provided by an exemplary embodiment is shown. Based on this structural block diagram, the execution process of the seismic data reconstruction method provided in this application embodiment will be described. The computer system is implemented as a terminal 100. The following process is described using the terminal 100 as the execution subject as an example.

[0037] In this embodiment of the application, the terminal 100 acquires three-dimensional seismic data of the geological structure collected during the geological exploration process, relevant information corresponding to the seismic firing point, and relevant information corresponding to the geophone point.

[0038] Among them, the relevant information corresponding to the seismic trigger shot points includes the first distribution location and shot point data, and the relevant information corresponding to the receiver points includes the second distribution location and receiver point data.

[0039] Terminal 100 generates a seismic data matrix based on the relevant information corresponding to the seismic trigger shot points and the relevant information corresponding to the receiver points. The horizontal dimension of the seismic data matrix represents the seismic trigger shot points, and the vertical dimension represents the receiver points. Each matrix contains a binary array of values, including shot point data and receiver point data. In an optional embodiment, each matrix contains a single value, which includes a first value and a second value. The first value indicates that both the seismic trigger shot points and receiver points have corresponding data, and the second value indicates that shot point data and / or receiver point data are missing. Figure 1 As shown, the seismic data matrix includes m*n data points, where m is the number of seismic trigger shot points and n is the number of receiver points. Here, a1 represents the data collected at the first seismic trigger shot point and the first receiver point (this data is implemented as a tuple, including shot point data and receiver point data).

[0040] It should be noted that missing data in the seismic data matrix is ​​replaced with preset values, such as: None. This is illustrative, as shown below. Figure 1 As shown, a1 is (P1, None), which indicates that only the shot data P1 corresponding to the seismic trigger shot point exists at this location, and the receiver data corresponding to the receiver point is missing.

[0041] Terminal 100 reconstructs supplementary seismic data based on 3D seismic data and a seismic data matrix. This supplementary seismic data is used to fill in the missing seismic data at various shot points and receiver points during geological exploration. Illustratively, during actual acquisition, data corresponding to shot point 1, shot point 2, receiver point 1, and receiver point 2 are collected, resulting in 3D seismic data (shot point data 1, None) and (None, None). Shot point 1 corresponds to receiver point 1, and shot point 2 corresponds to receiver point 2. If no data is detected at a shot point, it is confirmed that the shot point is in an abnormal state, and the receiver point should also not receive receiver data. Using the above process, the missing data in the 3D seismic data is reconstructed and supplemented to obtain supplementary seismic data (shot point data 1, receiver data) and (shot point data 2, receiver data).

[0042] The above process only describes the execution process on one side of terminal 100. In actual applications, the terminal can perform the above model training process with the server, and this application does not limit this. The terminal can be any intelligent device with data interaction capabilities.

[0043] It is worth noting that when terminal 100 is implemented as a smart terminal, the smart terminal can be: a smartphone, tablet computer, MP3 player (Moving Picture Experts Group Audio Layer III), MP4 player (Moving Picture Experts Group Audio Layer IV), laptop computer, or desktop computer. The terminal can also be referred to as user equipment, portable terminal, laptop terminal, desktop terminal, or other names, and this application does not limit this to any particular name.

[0044] A server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, a server can also be implemented as a node in a blockchain system.

[0045] It should be noted that the information (including but not limited to earthquake data), data (including but not limited to data used for analysis, data stored, data displayed), and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of the relevant data must comply with the relevant laws, regulations, and standards of the relevant countries and regions.

[0046] like Figure 2 As shown, Figure 2 A flowchart illustrating the execution process of a seismic data reconstruction method provided in an exemplary embodiment of this application is shown. The description focuses on the execution entity of the method as the terminal.

[0047] Step 200: Obtain the three-dimensional seismic data corresponding to the geological structure.

[0048] Optionally, 3D seismic data can be used to indicate data acquired during geological exploration.

[0049] During geological exploration, seismic firing points and geophones are set up at geological structures. The seismic firing points emit seismic waves into the ground, which propagate downwards and are reflected back to the ground. The geophones receive the relevant data reflected back from the seismic waves.

[0050] During exploration, shot point data is generated at the seismic triggering shot point, and receiver data is generated at the receiver point. Shot point data indicates the data generated at the moment of triggering, such as profile data, shot site data, and shot point information. Profile data refers to the specific cross-section during seismic exploration, including the propagation path and reflection of seismic waves underground. Shot site data refers to the geographical location and environmental conditions of the seismic triggering shot point during seismic exploration. Shot point information indicates the specific coordinates of the seismic triggering shot point, the triggering velocity, and the triggering pressure.

[0051] In this embodiment, the seismic data is implemented as three-dimensional seismic data, which includes time data, shot point data, and receiver point data. The time data is used to indicate the acquisition time of the shot point data and receiver point data.

[0052] In this embodiment, the three-dimensional seismic data is the actual seismic data acquired.

[0053] Step 201: Obtain the first distribution location of the geological structure corresponding to the seismic firing point during the geological exploration process, as well as the firing point data.

[0054] Optionally, the location information and shot data corresponding to all seismic firing points during the geological exploration process are obtained. Based on the location information, the first distribution location corresponding to the seismic firing points is generated. The location information refers to the coordinate information of the seismic firing points at the geological exploration site, including latitude and longitude information.

[0055] The first distribution location is used to characterize the positional and arrangement relationships among all seismic firing points. Schematic, location 1 corresponding to firing point 1 and location 2 corresponding to firing point 2, set at the geological exploration site, are obtained. Based on location 1 and location 2, the first distribution locations (location 1, location 2, 20) corresponding to the two firing points are generated, where 20 in the first distribution location indicates the distance between firing point 1 and firing point 2.

[0056] It should be noted that the first distribution position can also be implemented in other forms; the above (position 1, position 2, 20) are just examples.

[0057] Optionally, based on the location information corresponding to all seismic trigger shot points, a shot point distribution map is drawn, and a first distribution location is generated based on the shot point distribution map.

[0058] Step 202: Obtain the second distribution location of the geophone points corresponding to the geological structure during the geological exploration process, as well as the geophone point data.

[0059] Optionally, the location information and data of all geophones during the geological exploration process can be obtained. Based on this location information, a second distribution location corresponding to the geophones can be generated. This location information refers to the coordinate information of the geophones at the geological exploration site, including latitude and longitude information.

[0060] The second distribution position is used to characterize the positional relationship between all detector points.

[0061] Optionally, based on the location information corresponding to all detector points, a detector point distribution map is drawn, and a second distribution location is generated based on the detector point distribution map.

[0062] Step 203: Using the first distribution location as the horizontal dimension and the second distribution location as the vertical dimension, generate a seismic data matrix based on shot point data and receiver data.

[0063] Optionally, determine the first number of all seismic firing points within the geological exploration site, and determine the second number of all geophone points within the geological exploration site.

[0064] An initial data matrix is ​​generated using the first distribution position and the first quantity as the horizontal dimension, and the second distribution position and the second quantity as the vertical dimension. The initial data matrix contains m * n initial data points of the first quantity and n initial quantities. The initial data points are replaced with 0.

[0065] Input the shot point data and receiver data into the initial data matrix to obtain the seismic data matrix.

[0066] In this embodiment, a binary array is generated based on shot point data and receiver data. This binary array is then input into an initial data matrix to obtain a seismic data matrix. Schematic, the binary array corresponding to the first seismic trigger shot point and the first receiver point is (P1, J1). This binary array (P1, J1) replaces the value 0 in the initial data matrix.

[0067] In this embodiment of the application, the seismic data matrix includes missing shot point data, missing receiver data, and data with both missing points; wherein, missing shot point data is used to indicate that the current seismic firing shot point has not acquired shot point acquisition data, missing receiver data is used to indicate that the current receiver has not acquired receiver data, and data with both missing points is used to indicate that the current seismic shot point has not acquired the shot point acquisition data and the current receiver has not acquired the receiver data.

[0068] Step 204: Based on the three-dimensional seismic data and the seismic data matrix, reconstruct the three-dimensional seismic data to obtain supplementary seismic data.

[0069] In this embodiment of the application, three-dimensional seismic data is mapped to the spatiotemporal domain and the curve wave domain for data analysis.

[0070] The spatiotemporal domain refers to the distribution and characteristics of 3D seismic data in both spatial and temporal dimensions. In geological exploration, 3D seismic data in the spatiotemporal domain refers to the temporal and spatial information of seismic waves propagating in the subsurface medium. Temporal and spatial information are described using parameters such as the arrival time and amplitude of seismic waves. By analyzing 3D seismic data in the spatiotemporal domain, the propagation path, velocity, and reflection characteristics of seismic waves in the subsurface medium can be obtained.

[0071] Curves transform refers to the analysis and processing of 3D seismic data in the spatiotemporal domain based on curves transform methods. In other words, it maps 3D seismic data from the spatiotemporal domain to the curves transform domain, and by analyzing the performance of the 3D seismic data in the curves transform domain, further characterizes the sparsity properties of the 3D seismic data.

[0072] In the embodiments of this application, curve wave domain technology is used to process irregular three-dimensional seismic data, thereby improving the resolution of three-dimensional seismic data, achieving denoising and data reconstruction, etc.

[0073] In this embodiment, a first linear equation is constructed corresponding to the supplementary seismic data, the 3D seismic data, and the seismic data matrix. At this time, the supplementary seismic data is unknown. The first linear equation can be found in Formula 1 below.

[0074] Formula 1: A × x = b;

[0075] In Formula 1, x represents supplementary seismic data, A represents the seismic data matrix, and b represents 3D seismic data.

[0076] Based on 3D seismic data and a seismic data matrix, spatiotemporal domain data is obtained through the first linear equation. This spatiotemporal domain data refers to the data corresponding to the 3D seismic data in the spatiotemporal domain. As can be seen from the above, the spatiotemporal domain refers to the domain jointly modulated in the time and space dimensions, which is used to provide basic spatiotemporal information of 3D seismic data.

[0077] In another alternative embodiment, a candidate data matrix is ​​randomly selected from the seismic data matrix, the candidate data matrix being a subset of the seismic data matrix. Based on the candidate data matrix and the 3D seismic data, spatiotemporal domain data is determined using a first linear equation.

[0078] In response to the spatiotemporal domain data satisfying a preset sparsity condition, the spatial domain data is identified as supplementary seismic data. The preset sparsity condition indicates that the sum of all values ​​in the spatiotemporal domain of the supplementary seismic data is less than a preset value. The sparsity condition is specifically expressed in Formula 2.

[0079] Formula 2: min‖x‖1s.tA×x=b;

[0080] In Formula 2, ||·||1 is the l1 norm in compressed sensing theory, x is the supplementary seismic data, A is the seismic data matrix, b is the 3D seismic data, and min||x||1 is the minimum sum of the absolute values ​​of all values ​​in the reconstructed supplementary seismic data.

[0081] Based on the above, supplementary seismic data is used to reconstruct and supplement missing shot point data, missing receiver data, and missing data in the seismic data matrix.

[0082] In this application, a seismic data matrix is ​​generated by using the location information (first distribution location and second distribution location) of shot points and receiver points during geological exploration and the specific acquired data (shot point data and receiver point data). Then, based on the seismic data matrix and the three-dimensional seismic data, the three-dimensional seismic data is reconstructed, and the missing data in the seismic data matrix is ​​supplemented, thereby further improving the data integrity of the three-dimensional seismic data and making it more comprehensively reflect the actual situation of the geological structure, which is conducive to the efficiency of subsequent geological interpretation.

[0083] like Figure 3 As shown, Figure 3 A flowchart illustrating the execution of a seismic data reconstruction method provided in another exemplary embodiment of this application is shown. The description focuses on the execution entity of the method as the terminal. The following detailed explanation primarily addresses the process of receiving editing operations on a seismic data sharing platform.

[0084] Step 300: In response to the spatiotemporal domain data not meeting the preset sparsity conditions, the three-dimensional seismic data is converted and the converted three-dimensional seismic data meets the preset sparsity conditions.

[0085] In response to the fact that the spatiotemporal domain data does not meet the preset sparsity condition, the three-dimensional seismic data is converted into curve wave domain three-dimensional seismic data using a preset data processing method, and the seismic data matrix is ​​converted into a curve wave domain seismic data matrix using the preset data processing method.

[0086] In this embodiment of the application, the preset data processing method is implemented as Fourier transform.

[0087] A second linear equation is constructed corresponding to the curvewave domain 3D seismic data, the curvewave domain seismic data matrix, and the supplementary seismic data. The relationship among the three elements in the second linear equation is the same as that in the first linear equation mentioned above.

[0088] Based on the curve wave domain 3D seismic data and the curve wave domain seismic data matrix, supplementary curve wave domain seismic data are determined through a second linear equation.

[0089] In another optional embodiment, in response to the spatiotemporal domain data not satisfying a preset sparsity condition, a conversion operator for mutual conversion between the spatiotemporal domain and the curvelet domain is determined. As described above, the spatiotemporal domain refers to the domain jointly modulated in the time and spatial dimensions, while the curvelet domain refers to the domain obtained by modulating the spatiotemporal domain after applying a curvelet transformation. Optionally, the conversion operator is determined based on the curvelet transform function. In practical applications, staff determine the curvelet transform function and the corresponding conversion operator for converting from the spatiotemporal domain to the curvelet domain based on the on-site conditions.

[0090] The transformation coefficients corresponding to the conversion of supplementary seismic data from the spatial domain to the curvelet domain are determined. Based on 3D seismic data and the seismic data matrix, candidate supplementary seismic data are determined using the first linear equation.

[0091] Based on the transformation operator and the transformation coefficients, the candidate theoretical seismic data are adjusted to obtain the target supplementary seismic data. In response to the target supplementary seismic data satisfying a preset sparsity condition, the target supplementary seismic data is determined as supplementary seismic data. The sparsity condition is specifically expressed in the form of Formula 3.

[0092] Formula 3: min‖y‖1s.tA×S T ×y=b;

[0093] In Formula 2, ||·||1 represents the l1 norm in compressed sensing theory, y represents candidate supplementary seismic data, A represents the seismic data matrix, and S represents the transformation operator. T For the inverse transformation of the transformation operator S, b is the three-dimensional seismic data, and min‖y‖1 is the minimum sum of the absolute values ​​of all values ​​in the candidate supplementary seismic data obtained from reconstruction.

[0094] In an optional embodiment, supplementary seismic data is determined by Formula 2, using x(supplementary seismic data) = S T ×y represents the data representation of candidate supplementary seismic data in the curve wave domain.

[0095] In this application, a seismic data matrix is ​​generated by using the location information (first distribution location and second distribution location) of shot points and receiver points during geological exploration and the specific acquired data (shot point data and receiver point data). Then, based on the seismic data matrix and the three-dimensional seismic data, the three-dimensional seismic data is reconstructed, and the missing data in the seismic data matrix is ​​supplemented, thereby further improving the data integrity of the three-dimensional seismic data and making it more comprehensively reflect the actual situation of the geological structure, which is conducive to the efficiency of subsequent geological interpretation.

[0096] like Figure 4 As shown, Figure 4 A flowchart illustrating the execution process of a seismic data reconstruction method provided in another exemplary embodiment of this application is shown. The description focuses on the execution entity of the method as the terminal.

[0097] Step 400: Design an observation system based on compressed sensing theory.

[0098] Optionally, a linear relationship is determined between the supplementary seismic data, the actual acquired 3D seismic data, and the seismic data matrices corresponding to the receiver point data and shot point data, and this linear relationship is determined as the observation system mentioned in this embodiment.

[0099] Optionally, the observation system in this step is the same as Formula 1 and Formula 2 mentioned in step 204 above, and will not be repeated here.

[0100] Step 401: Obtain missing seismic acquisition data.

[0101] Optionally, the shot point data and first distribution location corresponding to the seismic excitation shot point are obtained, and the receiver point data and second distribution location corresponding to the receiver point are obtained.

[0102] Based on the above, a seismic data matrix is ​​generated. Analysis of the data within this seismic data matrix yields missing shot point data, missing receiver data, and data with both missing shot and receiver points.

[0103] Missing data at shot points, receiver points, and both were identified as missing data from seismic acquisition.

[0104] In one optional embodiment, the number n corresponding to seismic shot points is obtained, and this number n is considered as the existence of n shot points in the geological exploration process. The number m corresponding to geophone points is obtained, and this number m is considered as the existence of m geophone points in the geological exploration process. The n shot points and m geophone points are rearranged into n*m seismic data subsets. One shot point and one geophone point constitute one seismic subset.

[0105] When subsequently extracting the minimum seismic subset, if the geophone position remains unchanged for each shot point, the three-dimensional data coordinates of the minimum seismic subset are (time, shot point, geophone point). If the geophone position moves with the shot point position, the three-dimensional data coordinates of the minimum seismic subset are (time, shot point, geophone offset). Figure 5 As shown, Figure 5 A three-dimensional model of the minimum seismic subset 500 is shown. The minimum seismic subset 500 is constructed with time as the vertical axis, shot point as the horizontal axis, and receiver point as the vertical axis. The three-dimensional model is sliced ​​with time as the slice, and a schematic diagram corresponding to a single time slice 501 is obtained. This schematic diagram includes receiver point data. A schematic diagram corresponding to the common shot point gather 502 is obtained. This schematic diagram shows the number of shot points observed and the shot point data.

[0106] Step 402: Obtain 3D seismic data.

[0107] Optionally, acquire the actual 3D seismic data obtained, including receiver point data, shot point data, and other seismic data used to characterize geological structures. See step 200 above for details.

[0108] Step 403: Obtain the conversion operator between the spatiotemporal domain and the curvilinear domain.

[0109] Based on the above, it can be seen that the spatiotemporal domain refers to the domain that is jointly modulated in the time and space dimensions, while the curve domain refers to the domain obtained by modulating the spatiotemporal domain after performing curve transformation.

[0110] The curvelet transform function is obtained, and based on this function, seismic subdata in the spatiotemporal domain is mapped to the curvelet domain, resulting in curvelet domain subdata. The seismic subdata and the curvelet domain subdata are compared to determine the transformation operator between the spatiotemporal domain and the curvelet domain. In practical applications, staff determine the curvelet transform function and the corresponding transformation operator for the spatiotemporal domain to curvelet domain conversion based on the field conditions.

[0111] Step 404: Execute the optimization inversion algorithm based on sparse constraints.

[0112] Optionally, the missing data in the three-dimensional seismic data can be solved using Formula 2 above. The missing data satisfies the preset sparsity condition, that is, the sum of all data in the missing data is the minimum value.

[0113] Step 405: Reconstruct the representation of the 3D data in the curve domain.

[0114] If the missing data does not meet the preset sparsity condition, the 3D seismic data is mapped to the curve domain, and the missing data in the curve domain is obtained by using the above formula 3 until the missing data in the curve domain meets the preset sparsity condition. Then, the missing data in the curve domain is mapped to the spatiotemporal domain again to obtain the representation data.

[0115] like Figure 6 As shown, Figure 6 A comparison diagram before and after seismic data supplementation provided in an exemplary embodiment of this application is shown. A schematic diagram 600 corresponding to the actually acquired 3D seismic data is drawn. Missing data in the actually acquired 3D seismic data is supplemented according to steps 400 to 403 described above. The supplemented 3D seismic data is shown in Figure 601.

[0116] In this embodiment, based on the sparsity characteristics of the seismic data, two different solution methods are provided to satisfy the sparsity constraint of minimizing the sum in both the spatiotemporal domain and the curve wave domain, thereby obtaining supplementary data (missing data and representative data). Under the same sampling cost, the accuracy and precision of the obtained missing data are higher, reducing data processing costs and acquisition costs.

[0117] Figure 7 A structural block diagram of a seismic data reconstruction apparatus provided in an exemplary embodiment of this application is shown. The apparatus includes:

[0118] The acquisition module 700 is used to acquire three-dimensional seismic data corresponding to geological structures, wherein the three-dimensional seismic data is used to indicate the data collected during geological exploration.

[0119] The acquisition module 700 is used to acquire the first distribution location and shot point data corresponding to the seismic firing points during the geological exploration process of the geological structure.

[0120] The acquisition module 700 is used to acquire the second distribution location of the geophone points corresponding to the geological structure and the geophone point data during the geological exploration process.

[0121] The generation module 701 is used to generate a seismic data matrix based on the shot point data and the receiver point data, with the first distribution location as the horizontal dimension and the second distribution location as the vertical dimension.

[0122] The reconstruction module 702 is used to reconstruct the three-dimensional seismic data based on the three-dimensional seismic data and the seismic data matrix to obtain supplementary seismic data. The supplementary seismic data is used to supplement the seismic data missing from each seismic firing point and each geophone point during the geological exploration process.

[0123] In an optional embodiment, such as Figure 8 As shown, the device also includes a construction module 703 and a determination module 704;

[0124] Construction module 703 is used to construct the supplementary seismic data, the three-dimensional seismic data, and the first linear equation corresponding to the seismic data matrix;

[0125] The determination module 704 is used to obtain spatiotemporal domain data based on the three-dimensional seismic data and the seismic data matrix through the first linear equation. The spatiotemporal domain data refers to the data corresponding to the three-dimensional seismic data in the spatiotemporal domain. The spatiotemporal domain refers to the domain jointly modulated in the time and space dimensions.

[0126] The determining module 704 is used to determine the spatial domain data as the supplementary seismic data in response to the spatiotemporal domain data satisfying a preset sparsity condition; wherein the preset sparsity condition is used to indicate that the sum of all values ​​of the supplementary seismic data in the spatiotemporal domain is less than a preset value.

[0127] In an optional embodiment, such as Figure 8 As shown, the device also includes a selection module 705;

[0128] Selection module 705 is used to randomly select candidate data matrices from the seismic data matrix, wherein the candidate data matrices belong to a subset of the seismic data matrix;

[0129] The determining module 704 is used to determine the spatiotemporal domain data based on the candidate data matrix and the three-dimensional seismic data through the first linear equation.

[0130] In an optional embodiment, such as Figure 8 As shown, the conversion module 706 is used to convert the three-dimensional seismic data into curve wave domain three-dimensional seismic data using a preset data processing method in response to the spatiotemporal domain data not meeting the preset sparsity condition, and to convert the seismic data matrix into a curve wave domain seismic data matrix using the preset data processing method, wherein the preset data processing method is implemented as a Fourier transform.

[0131] The construction module 703 is used to construct the curve wave domain three-dimensional seismic data, the curve wave domain seismic data matrix, and the second linear equation corresponding to the supplementary seismic data.

[0132] The determining module 704 is used to determine supplementary seismic data in the curve wave domain based on the curve wave domain three-dimensional seismic data and the curve wave domain seismic data matrix, using the second linear equation.

[0133] In an optional embodiment, such as Figure 8 As shown, the determining module 704 is used to determine the conversion operator between the spatiotemporal domain and the curvelet domain in response to the spatiotemporal domain data not satisfying the preset sparsity condition. The spatiotemporal domain refers to the domain jointly modulated in the time and space dimensions, and the curvelet domain refers to the domain obtained by modulating the spatiotemporal domain after performing curvelet transformation.

[0134] The determining module 704 is used to determine the conversion coefficients corresponding to the conversion of the supplementary seismic data from the spatial domain to the curve wave domain;

[0135] The determining module 704 is used to determine candidate supplementary seismic data based on the three-dimensional seismic data and the seismic data matrix by using a first linear equation.

[0136] The adjustment module 707 is used to adjust the candidate theoretical seismic data based on the conversion operator and the conversion coefficient to obtain the target supplementary seismic data;

[0137] The determining module 704 is used to determine the target supplementary seismic data as the supplementary seismic data in response to the target supplementary seismic data satisfying the preset sparsity condition.

[0138] In an optional embodiment, such as Figure 8 As shown, the determining module 704 is used to determine the first number of the seismic trigger shot points and the second number of the geophone points.

[0139] An initial data matrix is ​​generated using the first distribution position and the first quantity as the horizontal dimension, and the second distribution position and the second quantity as the vertical dimension;

[0140] The determining module 704 is used to input the shot point data and the receiver point data into the initial data matrix to obtain the seismic data matrix.

[0141] In an optional embodiment, the seismic data matrix includes a shot point missing matrix, receiver point missing data, and co-missing data; wherein, the shot point missing data is used to indicate that the current seismic firing shot point did not acquire the shot point acquisition data, the receiver point missing data is used to indicate that the current receiver point did not acquire the receiver point acquisition data, and the co-missing data is used to indicate that the current seismic shot point did not acquire the shot point acquisition data and the current receiver point did not acquire the receiver point acquisition data.

[0142] In this embodiment, a seismic data matrix is ​​generated using the location information (first distribution location and second distribution location) and specific acquisition data (shot point data and receiver point data) corresponding to shot points and receiver points during geological exploration. Then, based on the seismic data matrix and the three-dimensional seismic data, the three-dimensional seismic data is reconstructed, and the missing data in the seismic data matrix is ​​supplemented, thereby further improving the data integrity of the three-dimensional seismic data and making it more comprehensively reflect the actual situation of the geological structure, which is conducive to the efficiency of subsequent geological interpretation.

[0143] Figure 9 This illustration shows a structural block diagram of a computer device 800 provided in an exemplary embodiment of this application. The computer device 800 can be a portable mobile terminal, such as a smartphone, tablet computer, MP3 player (Moving Picture Experts Group Audio Layer III), MP4 player (Moving Picture Experts Group Audio Layer IV), laptop computer, or desktop computer. The computer device 800 may also be referred to as a user device, portable terminal, laptop terminal, desktop terminal, or other names. Optionally, the computer device 800 can also be implemented as a mobile device, such as a vehicle-mounted terminal or other portable smart terminal.

[0144] Typically, computer device 800 includes a processor 801 and a memory 802.

[0145] Processor 801 may include one or more processing cores, such as a quad-core processor or an octa-core processor. Processor 801 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 801 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 801 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 801 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0146] The memory 802 may include one or more computer-readable storage media, which may be non-transitory. The memory 802 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 802 are used to store at least one instruction, which is executed by the processor 801 to implement the model training method or behavior encoding method provided in the method embodiments of this application.

[0147] In some embodiments, the computer device 800 may also optionally include a peripheral device interface 803 and at least one peripheral device. The processor 801, memory 802, and peripheral device interface 803 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 803 via a bus, signal line, or circuit board. For example, the peripheral device may include at least one of the following: a radio frequency circuit 804, a display screen 805, a camera assembly 806, an audio circuit 807, a positioning assembly 815, and a power supply 808.

[0148] Peripheral device interface 803 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 801 and memory 802. In some embodiments, processor 801, memory 802 and peripheral device interface 803 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 801, memory 802 and peripheral device interface 803 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0149] The radio frequency (RF) circuit 804 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 804 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 804 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 804 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 804 can communicate with other terminals through at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 804 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0150] Display screen 805 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 805 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 801 for processing. In this case, display screen 805 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 805, disposed on the front panel of computer device 800; in other embodiments, there may be at least two display screens, disposed on different surfaces of computer device 800 or in a folded design; in still other embodiments, display screen 805 may be a flexible display screen, disposed on a curved or folded surface of computer device 800. Furthermore, display screen 805 may be configured as a non-rectangular irregular shape, i.e., a non-rectangular screen. Display screen 805 may be made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0151] The camera assembly 806 is used to acquire images or videos. Optionally, the camera assembly 806 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the terminal, and the rear-facing camera is located on the back of the terminal. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In some embodiments, the camera assembly 806 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm-light flash and a cool-light flash, which can be used for light compensation at different color temperatures.

[0152] The audio circuit 807 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting the sound waves into electrical signals that are input to the processor 801 for processing, or input to the radio frequency circuit 804 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each located in a different part of the computer device 800. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert electrical signals from the processor 801 or the radio frequency circuit 804 into sound waves. The speaker may be a conventional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 807 may also include a headphone jack.

[0153] The positioning component 815 is used to calculate the current geographic location of the device 800 in order to enable navigation or LBS (Location Based Service). The positioning component 815 can be a positioning component based on the US GPS (Global Positioning System) or the Chinese BeiDou system.

[0154] Power supply 808 is used to supply power to various components in computer device 800. Power supply 808 can be alternating current, direct current, a disposable battery, or a rechargeable battery. When power supply 808 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, while a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0155] In some embodiments, the computer device 800 further includes one or more sensors 809. The one or more sensors 809 include, but are not limited to, an accelerometer 810, a gyroscope 811, a pressure sensor 812, an optical sensor 813, and a proximity sensor 814.

[0156] Accelerometer 810 can detect the magnitude of acceleration along the three coordinate axes of a coordinate system established by computer device 800. For example, accelerometer 810 can be used to detect the components of gravitational acceleration along the three coordinate axes. Processor 801 can control display screen 805 to display the user interface in either a landscape or portrait view based on the gravitational acceleration signal acquired by accelerometer 810. Accelerometer 810 can also be used for games or for acquiring user motion data.

[0157] The gyroscope sensor 811 can detect the orientation and rotation angle of the computer device 800. The gyroscope sensor 811, in conjunction with the accelerometer sensor 810, can collect 3D motion data from the user on the computer device 800. Based on the data collected by the gyroscope sensor 811, the processor 801 can perform the following functions: motion sensing (e.g., changing the UI based on the user's tilt), image stabilization during shooting, game control, and inertial navigation.

[0158] The pressure sensor 812 can be disposed on the side bezel of the computer device 800 and / or on the lower layer of the display screen 805. When the pressure sensor 812 is disposed on the side bezel of the computer device 800, it can detect the user's grip signal on the computer device 800, and the processor 801 can perform left / right hand recognition or quick operation based on the grip signal collected by the pressure sensor 812. When the pressure sensor 812 is disposed on the lower layer of the display screen 805, the processor 801 can control the operable controls on the UI interface based on the user's pressure operation on the display screen 805. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0159] An optical sensor 813 is used to collect ambient light intensity. In one embodiment, the processor 801 can control the display brightness of the display screen 805 based on the ambient light intensity collected by the optical sensor 813. For example, when the ambient light intensity is high, the display brightness of the display screen 805 is increased; when the ambient light intensity is low, the display brightness of the display screen 805 is decreased. In another embodiment, the processor 801 can also dynamically adjust the shooting parameters of the camera assembly 806 based on the ambient light intensity collected by the optical sensor 813.

[0160] A proximity sensor 814, also known as a distance sensor, is typically located on the front panel of a computer device 800. The proximity sensor 814 is used to detect the distance between the user and the front of the computer device 800. In one embodiment, when the proximity sensor 814 detects that the distance between the user and the front of the computer device 800 is gradually decreasing, the processor 801 controls the display screen 805 to switch from a screen-on state to a screen-off state; when the proximity sensor 814 detects that the distance between the user and the front of the computer device 800 is gradually increasing, the processor 801 controls the display screen 805 to switch from a screen-off state to a screen-on state.

[0161] Those skilled in the art will understand that Figure 8 The structure shown does not constitute a limitation on the computer device 800, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0162] This application also provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the method for identifying the operating status of a pipeline network provided in the above-described method embodiments.

[0163] This application provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for identifying the operating status of a pipeline network provided in the above-described method embodiments.

[0164] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware, or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk. The above descriptions are merely optional embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A seismic data reconstruction method, characterized in that, The method includes: Acquire three-dimensional seismic data corresponding to geological structures, wherein the three-dimensional seismic data is used to indicate the data collected during geological exploration. Obtain the first distribution location and shot point data of the geological structure corresponding to the seismic firing points during the geological exploration process; Obtain the second distribution location of the geophone points corresponding to the geological structure during the geological exploration process, as well as the geophone point data; Using the first distribution location as the horizontal dimension and the second distribution location as the vertical dimension, a seismic data matrix is ​​generated based on the shot point data and the receiver point data. Based on the three-dimensional seismic data and the seismic data matrix, the three-dimensional seismic data is reconstructed to obtain supplementary seismic data, which is used to supplement the seismic data missing at each seismic firing point and each geophone point during the geological exploration process.

2. The method according to claim 1, characterized in that, The process of reconstructing the three-dimensional seismic data to obtain supplementary seismic data based on the three-dimensional seismic data and the seismic data matrix includes: Construct the first linear equation corresponding to the supplementary seismic data, the three-dimensional seismic data, and the seismic data matrix; Based on the three-dimensional seismic data and the seismic data matrix, spatiotemporal domain data is obtained through the first linear equation. The spatiotemporal domain data refers to the data corresponding to the three-dimensional seismic data in the spatiotemporal domain. The spatiotemporal domain refers to the domain jointly modulated in the time and space dimensions. In response to the spatiotemporal domain data satisfying a preset sparsity condition, the spatial domain data is determined as the supplementary seismic data; The preset sparsity condition is used to indicate that the sum of all values ​​of the supplementary seismic data in the spatiotemporal domain is less than a preset value.

3. The method according to claim 2, characterized in that, The process of obtaining spatiotemporal domain data based on the three-dimensional seismic data and the seismic data matrix through the first linear equation includes: A candidate data matrix is ​​randomly selected from the seismic data matrix, wherein the candidate data matrix belongs to a subset of the seismic data matrix; Based on the candidate data matrix and the three-dimensional seismic data, the spatiotemporal domain data is determined by the first linear equation.

4. The method according to any one of claims 1 to 3, characterized in that, The process of reconstructing the three-dimensional seismic data to obtain supplementary seismic data based on the three-dimensional seismic data and the seismic data matrix includes: In response to the fact that the spatiotemporal domain data does not meet the preset sparsity condition, the three-dimensional seismic data is converted into curve wave domain three-dimensional seismic data using a preset data processing method, and the seismic data matrix is ​​converted into a curve wave domain seismic data matrix using the preset data processing method, wherein the preset data processing method is implemented as a Fourier transform. Construct the curve wave domain 3D seismic data, the curve wave domain seismic data matrix, and the second linear equation corresponding to the supplementary seismic data; Based on the curve wave domain 3D seismic data and the curve wave domain seismic data matrix, supplementary curve wave domain seismic data are determined through the second linear equation.

5. The method according to any one of claims 1 to 3, characterized in that, The method further includes: In response to the fact that the spatiotemporal domain data does not meet the preset sparsity condition, a conversion operator is determined for the mutual conversion between the spatiotemporal domain and the curvelet domain. The spatiotemporal domain refers to the domain jointly modulated in the time and space dimensions, and the curvelet domain refers to the domain obtained by modulating the spatiotemporal domain after performing curvelet transformation. Determine the conversion coefficients corresponding to the conversion of the supplementary seismic data from the spatial domain to the curve wave domain; Based on the three-dimensional seismic data and the seismic data matrix, candidate supplementary seismic data are determined by a first linear equation. Based on the transformation operator and the transformation coefficient, the candidate theoretical seismic data are adjusted to obtain the target supplementary seismic data; In response to the target supplementary seismic data satisfying the preset sparsity condition, the target supplementary seismic data is determined as the supplementary seismic data.

6. The method according to any one of claims 1 to 3, characterized in that, The step of generating a seismic data matrix based on the shot point data and the receiver data, using the first distribution location as the horizontal dimension and the second distribution location as the vertical dimension, includes: Determine the first number corresponding to the seismic trigger shot points, and determine the second number corresponding to the geophone points; An initial data matrix is ​​generated using the first distribution position and the first quantity as the horizontal dimension, and the second distribution position and the second quantity as the vertical dimension; The shot point data and the receiver data are input into the initial data matrix to obtain the seismic data matrix.

7. The method according to any one of claims 1 to 3, characterized in that, The seismic data matrix includes a missing shot point matrix, missing receiver point data, and data with both missing points. Wherein, the missing shot point data is used to indicate that the current seismic firing shot point did not acquire the shot point acquisition data, the missing geophone point data is used to indicate that the current geophone point did not acquire the geophone point acquisition data, and the simultaneous missing data is used to indicate that the current seismic shot point did not acquire the shot point acquisition data and the current geophone point did not acquire the geophone point acquisition data.

8. A seismic data reconstruction device, characterized in that, The device includes: The acquisition module is used to acquire three-dimensional seismic data corresponding to geological structures, wherein the three-dimensional seismic data is used to indicate the data collected during geological exploration. The acquisition module is used to acquire the first distribution location and shot point data corresponding to the seismic firing points of the geological structure during the geological exploration process. The acquisition module is used to acquire the second distribution location of the geophone points corresponding to the geological structure and the geophone point data during the geological exploration process. The generation module is used to generate a seismic data matrix based on the shot point data and the receiver point data, with the first distribution location as the horizontal dimension and the second distribution location as the vertical dimension. The reconstruction module is used to reconstruct the three-dimensional seismic data based on the three-dimensional seismic data and the seismic data matrix to obtain supplementary seismic data. The supplementary seismic data is used to supplement the seismic data missing from each seismic firing point and each receiver point during the geological exploration process.

9. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one program, which is loaded and executed by the processor to implement the seismic data reconstruction method as described in any one of claims 1 to 7.

10. A computer program product or computer program, characterized in that, The computer program product or computer program includes computer instructions stored in a computer-readable storage medium, a processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to implement the seismic data reconstruction method as described in any one of claims 1 to 7.

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