A seismic data acquisition design method, electronic equipment and storage medium

Abstract

A seismic data acquisition design method, electronic device and storage medium belong to the technical field of seismic data acquisition. To achieve better seismic data acquisition and reconstruction, the present invention includes arranging initial sampling points in a target area using a jitter sampling method; calculating the dynamic time matching distance between each two adjacent initial sampling points for two-dimensional seismic trace data; performing plane triangulation on the initial sampling points for three-dimensional seismic trace data, calculating the dynamic time matching distance for each triangle based on the seismic trace data of each vertex in the triangle, and then calculating the average value of the dynamic time matching distance for the obtained dynamic time matching distance; performing distance sorting, extracting the current maximum area of ​​seismic signals in the target area as a key area; adding new sampling points in the key area; adding the newly added sampling points to the initial sampling point set, and then iterating cyclically continuing to add sampling points in the updated key area until the number of arranged sampling points reaches the total number of sampling points.

Description

Technical Field

[0001] The present invention belongs to the technical field of seismic data acquisition, and in particular relates to a seismic data acquisition design method, electronic equipment and storage medium. Background Art

[0002] At present, due to the influence of economic cost and environmental factors, seismic data acquisition has gradually been designed under the framework of compressed sensing. Seismic data acquisition and reconstruction under this framework are closely related. Most of the research focuses on reconstruction algorithms, but acquisition design is equally important. High-quality acquisition design can significantly improve the accuracy of data reconstruction.

[0003] Traditional acquisition and reconstruction need to satisfy Shannon's theorem, requiring high-density and equally spaced acquisition to ensure accurate reconstruction. This requirement greatly increases the cost and is not suitable for actual acquisition. The emergence of compressed sensing breaks this limitation, provides a new direction for seismic data acquisition, and provides a more practical and effective method. Under this framework, it is advocated that the layout of sampling points is irregular and sparse, and then the sampled data is interpolated through reconstruction algorithms, which is a more practical and efficient method.

[0004] Commonly used sampling methods based on the compressed sensing framework mainly include random sampling and jitter sampling. Random sampling is to randomly arrange sampling points in space, while jitter sampling introduces constraints on the maximum spacing on the basis of random sampling to avoid excessive sampling intervals, which is more conducive to the reconstruction of seismic data. However, these methods are all based on prior information and do not fully utilize the signals and features in the actual seismic data. Therefore, they have a large degree of randomness in the actual data acquisition and reconstruction process.

[0005] In recent years, sampling methods based on deep learning have gradually emerged. This type of method uses fully sampled seismic data for network training to optimize the layout of sampling points. However, since the underground velocity model cannot be obtained in advance during the actual seismic data acquisition process, it is impossible to obtain fully sampled seismic data, so these methods are subject to certain limitations in practical applications. At present, there is no seismic data acquisition method that guides the use of information from the characteristics of the collected seismic data through preliminary acquisition. Therefore, the development of a new seismic data acquisition design method has important research significance and practical application value. Summary of the invention

[0006] The problem to be solved by the present invention is to achieve better seismic data acquisition and reconstruction, and a seismic data acquisition design method, electronic equipment and storage medium are proposed.

[0007] To achieve the above object, the present invention is implemented through the following technical solutions:

[0008] A seismic data acquisition design method comprises the following steps:

[0009] S1. In the target area, initial sampling points are arranged using a jitter sampling method, wherein the initial sampling point arrangement includes a two-dimensional sampling point arrangement or a three-dimensional sampling point arrangement to obtain an initial sampling point set;

[0010] S2. Collecting seismic trace data based on the initial sampling point set obtained in step S1, where the seismic trace data includes two-dimensional seismic trace data or three-dimensional seismic trace data;

[0011] S3. For the two-dimensional seismic trace data collected in step S2, the dynamic time matching distance between each two adjacent initial sampling points is calculated;

[0012] For the three-dimensional seismic trace data collected in step S2, the initial sampling points are plane triangulated to generate multiple triangles, and for each triangle, a dynamic time matching distance is calculated based on the seismic trace data of each vertex in the triangle, and then the dynamic time matching distance average value is calculated for the obtained dynamic time matching distances;

[0013] S4. Based on the dynamic time matching distance or the average dynamic time matching distance obtained in step S3, the distance is sorted, and the current largest area of ​​the seismic signal in the target area is extracted as the key area;

[0014] S5. Add new sampling points in key areas;

[0015] S6. Add the newly added sampling points to the initial sampling point set, and delete the dynamic time matching distance corresponding to the current maximum area of ​​the seismic signal in the target area in step S4, then iterate steps S4 to S5 to update the key area, and continue to add sampling points in the updated key area until the number of deployed sampling points reaches the total number of sampling points.

[0016] Furthermore, in step S1, the ratio of the number of initial sampling points to the total number of sampling points is α, α∈(0,1), and the total number of sampling points is set to N.

[0017] Furthermore, the jitter sampling method in step S1 is performed by adding random disturbances on a regular grid;

[0018] The jitter sampling formula for two-dimensional sampling point layout is as follows:

[0019]

[0020] Among them, x i The i-th x-direction sampling point arranged for the jitter sampling method, is the position of the i-th sampling point on the regular grid, r i For The random number in the x direction is uniformly distributed in the interval, Δx is the sampling interval in the x direction, and round(·) is the rounding function;

[0021] The jitter sampling formula for the three-dimensional sampling point layout is as follows:

[0022]

[0023] in, is the i-th sampling point on the two-dimensional regular grid, r i 、p i Respectively in The random numbers in the x direction and the random numbers in the y direction are uniformly distributed in the interval. Δx and Δy are the sampling intervals in the x0 direction and the y direction respectively. i The i-th sampling point in the y direction arranged for the jitter sampling method.

[0024] Furthermore, in step S3, for the collected two-dimensional seismic trace data, the jth and j+1th adjacent initial sampling points x are calculated. j 、x j+1 The dynamic time matching distance between j , the expression is:

[0025] dis j =dtw(x j ,x j+1 ),j=1,…,N / 2-1

[0026] Among them, dtw is the dynamic time matching function;

[0027] In step S3, for the collected 3D seismic data, the initial sampling points are plane triangulated to generate multiple triangles, and the sampling points corresponding to the three vertices of the triangle are set as s a =(x a ,y a ),s b =(x b ,y b ),s c =(x c ,y c );Calculate the vertices s in the triangle a ,s b ,s c The dtw distance dtw(s) corresponding to the seismic trace data a ,s b )、dtw(s b ,s c ) and dtw(s c ,s a ), and calculate the average dynamic time matching distance dis2j , the expression is:

[0028]

[0029] Furthermore, in step S4, the distances are sorted in descending order, and then the current largest area of ​​seismic signals in the target area is extracted, i.e., dis j or dis2 j The area with the largest value is the key area.

[0030] Furthermore, in step S5, for two-dimensional data collection, two new sampling points are inserted at equal intervals between the adjacent sampling point pairs with the largest distance values, and the positions of the new sampling points are:

[0031]

[0032] Among them, x new1 is the first new sampling point in two-dimensional data collection, x new2 is the second new sampling point in two-dimensional data collection;

[0033] For 3D data collection, two new sampling points are added within the triangle area with the largest distance. The positions of the new sampling points are:

[0034]

[0035] Among them, s new1 is the first new sampling point in 3D data collection, s new2 It is the second new sampling point in 3D data collection.

[0036] An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of a seismic data acquisition design method when executing the computer program.

[0037] A computer-readable storage medium stores a computer program, which implements the seismic data acquisition design method when executed by a processor.

[0038] Beneficial effects of the present invention:

[0039] The seismic data acquisition design method described in the present invention innovatively combines the seismic data acquisition process into two steps. By arranging sampling points in two stages, it dynamically reflects the changing characteristics of seismic data and increases the density of sampling points in areas with complex terrain and low similarity, thereby significantly improving the accuracy and effect of data reconstruction.

[0040] The seismic data acquisition design method described in the present invention adopts jitter sampling as the initial sampling method, which effectively reduces the problem of missing seismic data with large spacing during the acquisition process, avoids the defects of regular sampling, and ensures the rationality of the distribution of sampling points.

[0041] The seismic data acquisition design method described in the present invention can be applied to two-dimensional and three-dimensional seismic data acquisition, has good versatility, can be efficiently applied to actual seismic data acquisition scenarios, and improves the quality of collected data. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A flow chart of a seismic data acquisition design method according to the present invention;

[0043] Figure 2 A schematic diagram of simulated two-dimensional seismic data of size 800*560 used in the test in Example 1;

[0044] Figure 3 is a sampling point distribution diagram in Example 1, wherein (a) is random sampling, (b) is jitter sampling, and (c) is a sampling point distribution diagram after 50% sampling of two-dimensional seismic data by the method of Example 1;

[0045] Figure 4 The results and error diagram of the seismic data reconstruction after random sampling in Example 1, wherein (a) is the seismic data reconstruction result after random sampling, and (b) is the seismic data reconstruction error after random sampling;

[0046] Figure 5 The results and error diagram of the seismic data reconstruction after the jitter sampling in Example 1, wherein (a) is the seismic data reconstruction result after the jitter sampling, and (b) is the seismic data reconstruction error after the jitter sampling;

[0047] Figure 6 The results and error diagram of the seismic data reconstruction after sampling by the invention in Example 1, wherein (a) is the seismic data reconstruction result after sampling by the invention method, and (b) is the seismic data reconstruction error after sampling by the invention method;

[0048] Figure 7 It is a box-line comparison diagram of the signal-to-noise ratio after sampling and reconstruction of two-dimensional seismic data by three methods in multiple experiments in Example 1;

[0049] Figure 8 A schematic diagram of triangulating sampling points in Example 2;

[0050] Fig. 9 A schematic diagram of simulated 3D seismic data of size 256*200*200 used for the test in Example 2;

[0051] Fig.10 The sampling point distribution diagram of the three-dimensional seismic data in Example 2, wherein (a) is random sampling, (b) is jitter sampling, and (c) is the sampling point distribution diagram after 50% sampling of the two-dimensional seismic data by the method of Example 2;

[0052] Fig.11 This is a box-line comparison diagram of the signal-to-noise ratio after sampling and reconstructing three-dimensional seismic data using three methods in multiple experiments in Example 2. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the specific embodiments described are only part of the embodiments of the present invention, rather than all of the specific embodiments. The components of the specific embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations, and the present invention can also have other embodiments.

[0054] Therefore, the following detailed description of the specific embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents the selected specific embodiments of the present invention. Based on the specific embodiments of the present invention, all other specific embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0055] In order to further understand the content, features and effects of the present invention, the following specific implementation modes are given as examples and described in detail with reference to the accompanying drawings:

[0056] Embodiment 1:

[0057] A seismic data acquisition design method comprises the following steps:

[0058] S1. In the target area, the initial sampling points are arranged using a jitter sampling method, and the initial sampling points are arranged as two-dimensional sampling points to obtain an initial sampling point set;

[0059] Furthermore, in step S1, the ratio of the number of initial sampling points to the total number of sampling points is α, α∈(0,1), and the total number of sampling points is set to N. In this embodiment, α is N is 280;

[0060] Furthermore, the jitter sampling method in step S1 is performed by adding random disturbances on a regular grid;

[0061] The jitter sampling formula for two-dimensional sampling point layout is as follows:

[0062]

[0063] Among them, x i The i-th x-direction sampling point arranged for the jitter sampling method, is the position of the i-th sampling point on the regular grid, r i For The random number in the x direction is uniformly distributed in the interval, Δx is the sampling interval in the x direction, and round(·) is the rounding function;

[0064] S2. Collecting seismic trace data based on the initial sampling point set obtained in step S1, where the seismic trace data is two-dimensional seismic trace data;

[0065] S3. For the two-dimensional seismic trace data collected in step S2, the dynamic time matching distance between each two adjacent initial sampling points is calculated;

[0066] Furthermore, in step S3, for the collected two-dimensional seismic trace data, the jth and j+1th adjacent initial sampling points x are calculated. j 、x j+1 The dynamic time matching distance between j , the expression is:

[0067] dis j =dtw(x j ,x j+1 ),j=1,…,N / 2-1

[0068] Among them, dtw is the dynamic time matching function;

[0069] Furthermore, the calculation formula of dtw distance is as follows: For two earthquake sequences f = {f1, f2, …, f n} and g={g1,g2,…,g n}, the definition of its dtw distance dtw(f,g) is as follows, create an n×n matrix D, where:

[0070] D(i,j)=|f i -g j |,i=1,…,n; j=1,…,n;

[0071] Create a matrix C of the same size to store the accumulated distances, where:

[0072] C(1,1)=D(1,1)

[0073] C(i,1)=D(i,1)+C(i-1,1),i=2,…,n

[0074] C(1,j)=D(1,j)+C(1,j-1),j=2,…,n

[0075] For i = 2,…,n, j = 2,…,n:

[0076] C(i,j)=D(i,j)+min{C(i-1,j),C(i,j-1),C(i-1,j-1)}

[0077] After the calculations are completed, the dtw distance can be obtained as follows:

[0078] dtw(f,g)=C(n,n);

[0079] S4. Based on the dynamic time matching distance or the average dynamic time matching distance obtained in step S3, the distance is sorted, and the current largest area of ​​the seismic signal in the target area is extracted as the key area;

[0080] Furthermore, in step S4, the distances are sorted in descending order, and then the current largest area of ​​seismic signals in the target area is extracted, i.e., dis j The area with the largest value is the key area.

[0081] S5. Add new sampling points in key areas;

[0082] Furthermore, in step S5, for two-dimensional data collection, two new sampling points are inserted at equal intervals between the adjacent sampling point pairs with the largest distance values, and the positions of the new sampling points are:

[0083]

[0084] Among them, x new1 is the first new sampling point in two-dimensional data collection, x new2 is the second new sampling point in two-dimensional data collection;

[0085] S6. Add the newly added sampling points to the initial sampling point set, and delete the dynamic time matching distance corresponding to the current maximum area of ​​the seismic signal in the target area in step S4, then iterate steps S4 to S5 to update the key area, and continue to add sampling points in the updated key area until the number of deployed sampling points reaches the total number of sampling points.

[0086] The following uses random sampling and jitter sampling methods and the method of the present invention to sample and reconstruct 50% of the sampled two-dimensional simulated seismic data. After sampling, the three methods are reconstructed using the same convex set projection reconstruction algorithm. The quality of the reconstructed seismic data is compared based on the signal-to-noise ratio, and the signal-to-noise ratio calculation formula is:

[0087]

[0088] Among them, Y is the complete earthquake data, Y rec To reconstruct earthquake data.

[0089] Figure 2 It is a simulated two-dimensional seismic data with a size of 800*560 (800 time sampling points and 560 seismic channels); Figure 3 (a)- Figure 3 (c) using random sampling, jitter sampling and the method of the invention respectively Figure 2 The distribution diagram of sampling points after 50% sampling of the data. It can be seen that there are many local large spacings without sampling points in random sampling, and the overall distribution of jitter sampling is more uniform. The inventive method has denser sampling in the middle and on both sides, indicating that the data similarity in these areas is lower and more complex.

[0090] Figure 4-Figure 6 The results and error diagrams are divided into random sampling, jitter sampling and reconstruction after sampling by the invented method. It can be seen that at the red boxes and arrows, only the seismic data reconstructed by the invented method have stronger continuity of the phase axis. The error diagram also shows that the reconstruction error of the invented method is the smallest and is closer to the original data. Figure 7 The box plot of the signal-to-noise ratio of the sampling reconstruction results of 30 experiments of the three methods shows that the average sampling reconstruction signal-to-noise ratio of the invention method is 17.96dB, and the average signal-to-noise ratios of random sampling and jitter sampling reconstruction are 14.35dB and 15.38dB respectively. The average reconstruction signal-to-noise ratio of the invention method is the highest, and Figure 7 It can be seen that the reconstruction result of the invented method is the most stable, and the lowest reconstruction signal-to-noise ratio is also higher than the highest reconstruction signal-to-noise ratio of the other two comparison methods, which further illustrates the effectiveness of the invented method.

[0091] Embodiment 2:

[0092] A seismic data acquisition design method comprises the following steps:

[0093] S1. In the target area, the initial sampling points are arranged using a jitter sampling method, and the initial sampling points are arranged as three-dimensional sampling points to obtain an initial sampling point set;

[0094] Furthermore, in step S1, the ratio of the number of initial sampling points to the total number of sampling points is α, α∈(0,1), and the total number of sampling points is set to N. In this embodiment, α is N is 20000;

[0095] Furthermore, the jitter sampling method in step S1 is performed by adding random disturbances on a regular grid;

[0096] The jitter sampling formula for the three-dimensional sampling point layout is as follows:

[0097]

[0098] in, is the i-th sampling point on the two-dimensional regular grid, r i 、p i Respectively in The random numbers in the x direction and the random numbers in the y direction are uniformly distributed in the interval. Δx and Δy are the sampling intervals in the x0 direction and the y direction respectively. i The i-th sampling point in the y direction arranged for the jitter sampling method.

[0099] S2. Collecting seismic trace data as three-dimensional seismic trace data based on the initial sampling point set obtained in step S1;

[0100] S3. For the three-dimensional seismic data collected in step S2, plane triangulation is performed on the initial sampling points to generate multiple triangles, and for each triangle, a dynamic time matching distance is calculated based on the seismic data of each vertex in the triangle, and then the average value of the dynamic time matching distance is calculated for the obtained dynamic time matching distance;

[0101] Furthermore, in step S3, for the collected three-dimensional seismic data, the initial sampling points are plane triangulated to generate multiple triangles, and the sampling points corresponding to the three vertices of the triangle are set as s a =(x a ,y a ),s b =(x b ,y b ),s c =(x c ,y c );Calculate the vertices s in the triangle a ,s b ,s c The dtw distance dtw(s) corresponding to the seismic trace data a ,s b )、dtw(s b ,s c ) and dtw(s c ,s a ), and calculate the average dynamic time matching distance dis2 j , the expression is:

[0102]

[0103] Furthermore, the calculation formula of dtw distance is as follows: For two earthquake sequences f = {f1, f2, …, f n} and g={g1,f2,…,g n}, the definition of its dtw distance dtw(f,g) is as follows, create an n×n matrix D, where:

[0104] D(i,j)=|f i -g j |,i=1,…,n; j=1,…,n;

[0105] Create a matrix C of the same size to store the accumulated distances, where:

[0106] C(1,1)=D(1,1)

[0107] C(i,1)=D(i,1)+C(i-1,1),i=2,…,n

[0108] C(1,j)=D(1,j)+C(1,j-1),j=2,…,n

[0109] For i = 2,…,n, j = 2,…,n:

[0110] C(i,j)=D(i,j)+min{C(i-1,j),C(i,j-1),C(i-1,j-1)}

[0111] After the calculations are completed, the dtw distance can be obtained as follows:

[0112] dtw(f,g)=C(n,n);

[0113] S4. Based on the dynamic time matching distance or the average dynamic time matching distance obtained in step S3, the distance is sorted, and the current largest area of ​​the seismic signal in the target area is extracted as the key area;

[0114] Furthermore, in step S4, the distances are sorted in descending order, and then the current largest area of ​​seismic signals in the target area is extracted, i.e., dis2 j The area with the largest value is the key area.

[0115] S5. Add new sampling points in key areas;

[0116] Furthermore, for three-dimensional data collection, two new sampling points are added in the triangle area with the largest distance. The positions of the new sampling points are:

[0117]

[0118] Among them, s new1 is the first new sampling point in 3D data collection, s new2 It is the second new sampling point in three-dimensional data collection;

[0119] S6. Add the newly added sampling points to the initial sampling point set, and delete the dynamic time matching distance corresponding to the current maximum area of ​​the seismic signal in the target area in step S4, then iterate steps S4 to S5 to update the key area, and continue to add sampling points in the updated key area until the number of deployed sampling points reaches the total number of sampling points.

[0120] Figure 8 A schematic diagram showing the triangulation of the sampling points is shown, with the small red dots indicating where the sampling points can be placed. Fig. 9 The simulated 3D seismic data used for testing is shown. The size of the data is 256*200*200, the trace spacing is 20m, and the time sampling spacing is 0.004s. Fig.10 (a)- Fig.10 (c) using random sampling, jitter sampling and the method of the invention respectively Fig. 9 The distribution of sampling points after 50% sampling of the data. It can be observed that random sampling has local large-spaced blank areas, resulting in uneven distribution of sampling points, while jitter sampling has a more uniform overall distribution. The method of the present invention presents a denser distribution of sampling points in areas with lower data similarity and higher data complexity, such as the middle part.

[0121] Fig.11 The box plots of the reconstruction signal-to-noise ratios of the three sampling methods after 15 experiments are shown. The average reconstruction signal-to-noise ratio of the 15 experiments of the method in this embodiment is 20.95dB, and the average reconstruction signal-to-noise ratios of random sampling and jitter sampling are 17.53dB and 18.47dB respectively. It can be seen that the average reconstruction signal-to-noise ratio of the method in this embodiment is the highest, and Fig.11 It can be seen that its lowest reconstruction signal-to-noise ratio is also higher than the highest reconstruction signal-to-noise ratio of the other two comparison methods. In addition, compared with two-dimensional seismic data, the advantages of the method in this embodiment in three-dimensional seismic data are more obvious.

[0122] Embodiment 3:

[0123] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of a seismic data acquisition design method described in Example 1 or 2 when executing the computer program.

[0124] The computer device of the present invention may be a device including a processor and a memory, such as a single chip microcomputer including a central processing unit. Furthermore, the processor is used to implement the steps of the above-mentioned recommendation method based on CREO software that can modify the recommendation data driven by the relationship when executing the computer program stored in the memory.

[0125] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0126] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0127] Embodiment 4:

[0128] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, a seismic data acquisition design method as described in any one of Embodiments 1 or 2 is implemented.

[0129] The computer-readable storage medium of the present invention can be any form of storage medium that can be read by a processor of a computer device, including but not limited to non-volatile memory, volatile memory, ferroelectric memory, etc. A computer program is stored on the computer-readable storage medium. When the processor of the computer device reads and executes the computer program stored in the memory, the steps of the above-mentioned modeling method of modifiable relationship-driven modeling data based on CREO software can be implemented.

[0130] The computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0131] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0132] Although the present application has been described above with reference to specific embodiments, various modifications may be made thereto and parts thereof may be replaced with equivalents without departing from the scope of the present application. In particular, as long as there is no structural conflict, the various features in the specific embodiments disclosed in the present application may be used in combination with each other in any manner, and the fact that these combinations are not exhaustively described in this specification is only for the sake of omitting space and saving resources. Therefore, the present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A seismic data acquisition design method, characterized in that: The steps include: S1. In the target area, initial sampling points are arranged using a jitter sampling method, wherein the initial sampling point arrangement includes a two-dimensional sampling point arrangement or a three-dimensional sampling point arrangement to obtain an initial sampling point set; S2. Collecting seismic trace data based on the initial sampling point set obtained in step S1, where the seismic trace data includes two-dimensional seismic trace data or three-dimensional seismic trace data; S3. For the two-dimensional seismic trace data collected in step S2, the dynamic time matching distance between each two adjacent initial sampling points is calculated; For the three-dimensional seismic trace data collected in step S2, the initial sampling points are plane triangulated to generate multiple triangles, and for each triangle, a dynamic time matching distance is calculated based on the seismic trace data of each vertex in the triangle, and then the dynamic time matching distance average value is calculated for the obtained dynamic time matching distances; S4. Based on the dynamic time matching distance or the average dynamic time matching distance obtained in step S3, the distance is sorted, and the current largest area of ​​the seismic signal in the target area is extracted as the key area; S5. Add new sampling points in key areas; S6. Add the newly added sampling points to the initial sampling point set, and delete the dynamic time matching distance corresponding to the current maximum area of ​​the seismic signal in the target area in step S4, then iterate steps S4 to S5 to update the key area, and continue to add sampling points in the updated key area until the number of deployed sampling points reaches the total number of sampling points.

2. A seismic data acquisition design method according to claim 1, characterized in that: In step S1, the ratio of the number of initial sampling points to the total number of sampling points is α, α∈(0,1), and the total number of sampling points is set to N.

3. A seismic data acquisition design method according to claim 1 or 2, characterized in that: The jitter sampling method in step S1 is performed by adding random disturbances on a regular grid; The jitter sampling formula for two-dimensional sampling point layout is as follows: Among them, x i The i-th x-direction sampling point arranged for the jitter sampling method, is the position of the i-th sampling point on the regular grid, r i For The random number in the x direction is uniformly distributed in the interval, Δx is the sampling interval in the x direction, and round(·) is the rounding function; The jitter sampling formula for the three-dimensional sampling point layout is as follows: in, is the i-th sampling point on the two-dimensional regular grid, r i 、p i Respectively in The random numbers in the x direction and the random numbers in the y direction are uniformly distributed in the interval. Δx and Δy are the sampling intervals in the x direction and the y direction respectively. i The i-th sampling point in the y direction arranged for the jitter sampling method.

4. A seismic data acquisition design method according to claim 3, characterized in that: In step S3, for the collected two-dimensional seismic trace data, the jth and j+1th adjacent initial sampling points x are calculated. j 、x j+1 The dynamic time matching distance between j , the expression is: dis j =dtw(x j ,x j+1 ),j=1,…,N / 2-1 Where, dtw is the dynamic time matching function, and N is the total number of sampling points; In step S3, for the collected 3D seismic data, the initial sampling points are plane triangulated to generate multiple triangles, and the sampling points corresponding to the three vertices of the triangle are set as s a =(x a ,y a ),s b =(x b ,y b ),s c =(x c ,y c );Calculate the vertices s in the triangle a ,s b ,s c The dtw distance dtw(s) corresponding to the seismic trace data a ,s b )、dtw(s b ,s c ) and dtw(s c ,s a ), and calculate the average dynamic time matching distance dis2 j , the expression is:

5. A seismic data acquisition design method according to claim 4, characterized in that: In step S4, the distances are sorted in descending order, and then the current largest area of ​​seismic signals in the target area is extracted, i.e., the distance j or dis2 j The area with the largest value is the key area.

6. A seismic data acquisition design method according to claim 5, characterized in that: Step S5: For two-dimensional data collection, two new sampling points are inserted at equal intervals between the adjacent sampling point pairs with the largest distance value. The positions of the new sampling points are: Among them, x new1 is the first new sampling point in two-dimensional data collection, x new2 is the second new sampling point in two-dimensional data collection; For 3D data collection, two new sampling points are added within the triangle area with the largest distance. The positions of the new sampling points are: Among them, s new1 is the first new sampling point in 3D data collection, s new2 It is the second new sampling point in 3D data collection.

7. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of a seismic data acquisition design method as claimed in any one of claims 1 to 6 when executing the computer program.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, a seismic data acquisition design method as described in any one of claims 1 to 6 is implemented.

Images