Random optimization design method of seismic acquisition source with automatic obstacle avoidance

Abstract

This invention provides an automatic obstacle avoidance seismic acquisition source random optimization design method, which includes: Step 1: Determining the physical location points of the acquisition sources according to actual conditions; Step 2: Calculating the number of sources corresponding to obstacles based on actual surface conditions; Step 3: Selecting optimization operators and determining the length and number of random sampling groups; Step 4: Generating multiple random sampling matrices with the constraint of not placing sources at obstacle locations; Step 5: Selecting the data reconstruction transformation space and calculating the correlation coefficient of the random sampling matrices; Step 6: Finding the random sampling matrix with the smallest correlation coefficient, which is the location of the seismic source. This automatic obstacle avoidance seismic acquisition source random optimization design method fully considers surface obstacle conditions, reduces the number of sources, and ensures high-precision seismic data reconstruction, achieving the goal of cost reduction and efficiency improvement in oil and gas exploration.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas exploration seismic data acquisition and processing, and in particular to a random optimization design method for seismic acquisition sources with automatic obstacle avoidance. Background Art

[0002] The main method of oil and gas exploration in the eastern exploration area of ​​China is high-density seismic technology. The seismic data obtained by this technology has high fidelity and vertical and horizontal resolution. However, there are two prominent problems in its large-scale application. The first problem is that there are many surface obstacles such as towns, reservoirs, and farmland in the eastern exploration area. These places cannot be used to place seismic acquisition sources, especially explosive sources, resulting in serious loss of seismic data and low data quality. The second problem is that high-density seismic has high requirements for the density of the gun channel. There are corresponding requirements for the gun points and detection points arranged per unit area. In areas with complex structures, the number of gun points needs to be increased to ensure the data acquisition and processing effect, resulting in a sharp increase in exploration costs. At present, in order to solve these two problems of high-density seismic technology in the eastern exploration area, the conventional solution is to implement the gun point position variable view processing and add the same number of sources near the obstacles. The acquisition cost of this method is the same, but the data acquisition effect is greatly reduced. The other is to use small controllable sources or electric sparks instead of explosive sources for excitation. The acquisition data obtained in this way has a low signal-to-noise ratio in the deep layer, which is difficult to meet the needs of exploration and development.

[0003] The Chinese patent application with application number: CN201410249923.0 relates to a method for constructing a source of OBC seismic acquisition in a shallow-water obstacle area, which belongs to the technical field of shallow-water OBC seismic acquisition and marine geological survey in the presence of obstacles. The method includes the following steps: (1) Detailed survey to determine the specific location of the obstacle in the work area. (2) Plot the coordinates of the obstacle on acquisition design software such as Kelang or Lushan. (3) Perform obstacle avoidance and encryption design based on the obstacles on the acquisition design software. (4) After performing obstacle avoidance and encryption design on the obstacles, use acquisition design and processing software to analyze the missing shot points and data gaps to determine whether the number of coverage, data gaps, etc. meet the relevant technical requirements. (5) Construction according to the obstacle avoidance and encryption design.

[0004] In the Chinese patent application with application number: CN201710107996.X, a method, device and electronic device for determining the trajectory of a navigation source are involved. The method includes: determining the position information of each source point in the current block; determining a source point from the source points as the current starting point of the block; determining the distance between the source points and the current starting point according to the position information; and determining the trajectory of the navigation source of the block according to the distance between the source points and the current starting point.

[0005] In the Chinese patent application with application number: CN200910243766.1, a two-way non-longitudinal rolling observation seismic exploration and acquisition method is involved, which is applied to seismic exploration and acquisition in urban areas or obstacle areas. Small-tonnage controllable seismic sources and / or well gun seismic sources are used to excite seismic waves, and more than 5,000 seismic instruments and moving coil detectors are used to receive seismic signals. A. Construction point layout; B. Non-longitudinal observation system design; C. Two-way non-longitudinal rolling observation implementation; D. The key to the implementation of two-way non-longitudinal rolling observation is to correctly determine the position of non-longitudinal shot points. Non-longitudinal shot points have the same receiving arrangement as normal shot points in the longitudinal direction.

[0006] The above existing technologies are all significantly different from the present invention and fail to solve the technical problem we want to solve. For this reason, we have invented a new random optimization design method for seismic acquisition sources with automatic obstacle avoidance. Summary of the invention

[0007] The purpose of the present invention is to provide a random optimization design method for seismic acquisition sources with automatic obstacle avoidance, which can reduce the seismic exploration acquisition cost by reducing the number of acquisition sources.

[0008] The purpose of the present invention can be achieved by the following technical measures: a random optimization design method for a seismic acquisition source with automatic obstacle avoidance, the random optimization design method for a seismic acquisition source with automatic obstacle avoidance comprising:

[0009] Step 1: Determine the physical location of the source of the earthquake according to the actual situation;

[0010] Step 2: Calculate the number of earthquake sources corresponding to obstacles based on the actual surface conditions;

[0011] Step 3: Select the optimization operator and determine the length and number of random sampling groups;

[0012] Step 4: Generate multiple sets of random sampling matrices with the constraint that no seismic source is placed at the obstacle;

[0013] Step 5: Select data to reconstruct the transformation space and calculate the correlation coefficient of the random sampling matrix;

[0014] Step 6: Find the random sampling matrix with the smallest correlation coefficient, which is the location of the earthquake source.

[0015] The purpose of the present invention can also be achieved by the following technical measures:

[0016] In step 1, according to the actual situation of the exploration area, the physical location points of the earthquake source are collected according to the rules of shot point range, shot line distance and shot point distance.

[0017] In step 1, the sampling value of each physical location point is set to 1, and the number of original sources is calculated as N, and the number of source points in each shot line is n.

[0018] In step 2, according to the scope of the surface obstacle zone and the sampling rules of the physical location points of the earthquake sources in the exploration area, the values ​​of the physical sampling points of the earthquake sources corresponding to the surface obstacle zone are set to 0, and the number of earthquake sources at the obstacle points is calculated and recorded as M.

[0019] In step 3, the number of random optimized sources A is determined using the original number of sources and the optimization operator, where A = N*F; the number of original sources is N, the optimization operator is F, and 0 <F<1。

[0020] In step 3, the random sampling group length B is determined according to the number of shot points n in each original shot line, so the number of groups is

[0021] In step 4, with the constraint that no seismic sources are set at the M physical points at the obstacles, within each random sampling group length B, first a group of B random numbers is generated within a given range, and then the first B*F points are selected and the sampling values ​​are set to 1 after sorting. After all random sampling groups are completed, a random sampling matrix is ​​formed; repeat this process to generate N random sampling matrices.

[0022] In step 5, data is selected to reconstruct the transformation space, and the correlation coefficients of N random sampling matrices are calculated as C1, C2, ..., C N .

[0023] In step 6, N correlation coefficients are compared, and a random sampling matrix with the smallest correlation coefficient is selected as the final random layout position of the earthquake source.

[0024] The random optimization design method for seismic acquisition sources with automatic obstacle avoidance in the present invention can automatically avoid surface obstacles and meet the requirements of high-precision seismic data reconstruction, so that it can be implemented in surface obstacle areas and reduce the number of sources. The random optimization design method for seismic acquisition sources with automatic obstacle avoidance fully considers surface obstacle conditions, reduces the number of sources, and ensures high-precision seismic data reconstruction, thereby achieving the purpose of reducing costs and increasing efficiency in oil and gas exploration. Compared with the prior art, the present invention has the following advantages:

[0025] First, the invention fully considers the situation of surface obstacles, and can automatically remove the physical points corresponding to the obstacles in the design of the earthquake source physical points, which is conducive to the implementation of random earthquake source optimization design;

[0026] Second, the invention adopts grouped and segmented random sampling to implement the earthquake source design, which can not only ensure the randomness of the physical points of the earthquake source, but also select the optimal observation matrix by controlling the correlation coefficient, which is conducive to the high-precision reconstruction of seismic data. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1A flowchart of a specific embodiment of the random optimization design method for seismic acquisition sources with automatic obstacle avoidance of the present invention;

[0028] Figure 2 A schematic diagram of the physical location points of the regular acquisition source in a specific embodiment 1 of the present invention;

[0029] Figure 3 It is a schematic diagram of automatically calculating the number of earthquake source physical points at obstacles in a specific embodiment 1 of the present invention;

[0030] Figure 4 A schematic diagram of the random sampling group length and the number of groups in a specific embodiment 1 of the present invention;

[0031] Figure 5 It is a schematic diagram of the final random arrangement of physical point positions of the seismic source in a specific embodiment 1 of the present invention;

[0032] Figure 6 A schematic diagram of the physical location points of the regular acquisition source in a specific embodiment 2 of the present invention;

[0033] Figure 7 It is a schematic diagram of automatically calculating the number of earthquake source physical points at obstacles in a specific embodiment 2 of the present invention;

[0034] Figure 8 A schematic diagram of the random sampling group length and the number of groups in a specific embodiment 2 of the present invention;

[0035] Fig. 9 It is a schematic diagram of the final random arrangement of physical point positions of the earthquake sources in a specific embodiment 3 of the present invention;

[0036] Fig.10 A schematic diagram of the physical location points of the regular acquisition source in a specific embodiment 3 of the present invention;

[0037] Fig.11 It is a schematic diagram of automatically calculating the number of earthquake source physical points at obstacles in a specific embodiment 3 of the present invention;

[0038] Fig.12 A schematic diagram of random sampling group length and group number in a specific embodiment 3 of the present invention;

[0039] Fig.13 It is a schematic diagram of the final random arrangement of physical point positions of seismic sources in a specific embodiment 3 of the present invention. DETAILED DESCRIPTION

[0040] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0041] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0042] The automatic obstacle avoidance seismic acquisition source random optimization design method of the present invention includes the following steps:

[0043] (1) According to the actual situation of the exploration area, determine each physical position point of the regular acquisition source according to the shot point range, shot line distance, and shot point distance. The sampling value of each physical position point is set to 1, and calculate the original source number denoted as N, and the number of source points per shot line is n.

[0044] (2) According to the range of the surface obstacle area, set the numerical value of the physical sampling points of the source corresponding to the surface obstacle area to 0 according to the sampling rule of the source physical position points in the exploration area, and calculate the number of sources at the obstacle points denoted as M.

[0045] (3) Determine the random optimization source number A using the original source number and the optimization operator, where A = N * F; the original source number is N, the optimization operator is F, and 0 < F < 1 is satisfied. Determine the random sampling group length B according to the number of shots n in each original shot line, then the number of groups is

[0046] (4) Taking the non - deployment of sources at M physical points at the obstacle as a constraint, within each random sampling group length B, first generate a set of random numbers with a quantity of B within the given range, then after sorting, select the first B * F points and set their sampling values to 1. After all random sampling groups are completed, form a random sampling matrix. Then repeat this process to generate N random sampling matrices.

[0047] (5) Select the data reconstruction transformation space, and calculate the correlation coefficients of the N random sampling matrices as C1, C2,..., C N .

[0048] (6) Compare the N correlation coefficients, and select the random sampling matrix with the smallest correlation coefficient as the final random layout position of the source.

[0049] In a specific embodiment 1 of applying the present invention, Figure 1 The flowchart of the random optimization design method of the seismic acquisition source with automatic obstacle avoidance of the present invention comprises the following steps:

[0050] In step 101, the physical location points of the seismic sources are determined according to the actual situation. The vertical distance is 5000m, the shot point distance is 50m, the horizontal distance is 5000m, and the shot line distance is 125m. It is calculated that there are 40 shot lines, so the original number of seismic sources is N = 40*100 = 4000, and the number of source points in each shot line is n = 100 ( Figure 2 );

[0051] Step 102, the number of physical points of the earthquake source corresponding to the obstacle is calculated according to the actual surface conditions, which is M=182, that is, Figure 3 The number of sources obscured by obstacles;

[0052] Step 103, based on the comprehensive consideration of cost and acquisition effect, select the optimization factor F = 0.5, then the number of sources without considering obstacles is A = 4000*0.5 = 2000; according to the original number of gun points in each gun row n = 100 in step 1, determine the random sampling group length B = 10, then the number of groups is like Figure 4 As shown;

[0053] Step 104: With the constraint that no earthquake source is set at M = 182 physical points at the obstacle, within each random sampling group length B = 10, first generate a group of 10 random numbers within a given range, then sort and select the first B*F = 5 points and set the sampling value to 1. After all random sampling groups are completed, a random sampling matrix is ​​formed. Then repeat this process to generate 4000 random sampling matrices.

[0054] Step 105, select Shearlet transform as the data reconstruction transform space, and calculate the correlation coefficients of 4000 random sampling matrices, which are C1, C2, ..., C 4000 ;

[0055] Step 106, compare 4000 correlation coefficients, select a random sampling matrix with the smallest correlation coefficient to determine the final random source layout position, such as Figure 5 shown.

[0056] In a specific embodiment 2 of the present invention, the random optimization design method for seismic acquisition sources with automatic obstacle avoidance includes the following steps:

[0057] In step 101, the physical location points of the seismic sources are determined according to the actual situation. The horizontal distance is 3800m, the shot point distance is 50m, the vertical distance is 4200m, and the shot line distance is 175m. It is calculated that there are 24 shot lines, so the original number of seismic sources is N = 24*76 = 1824, and the number of source points in each shot line is n = 76 ( Figure 6 );

[0058] Step 102, the number of physical points of the earthquake source corresponding to the obstacle is calculated according to the actual surface conditions, which is M = 95, that is, Figure 7 The number of sources obscured by obstacles;

[0059] Step 103, based on the comprehensive consideration of cost and acquisition effect, select the optimization factor F = 0.75, then the number of sources without considering obstacles is A = 1824 * 0.75 = 1368; according to the original number of gun points in each gun row n = 76 in step 1, determine the random sampling group length B = 4, then the number of groups is like Figure 8 As shown;

[0060] Step 104, with M = 95 physical points at the obstacle as the constraint that no earthquake source is set, within each random sampling group length B = 4, first generate a group of 4 random numbers within a given range, then sort and select the first B*F = 3 points and set the sampling value to 1. After all random sampling groups are completed, a random sampling matrix is ​​formed. Then repeat this process to generate 1824 random sampling matrices;

[0061] Step 105, selecting Shearlet transform as the data reconstruction transform space, and calculating the correlation coefficients of 1824 random sampling matrices;

[0062] Step 106, compare the 1824 correlation coefficients, select a random sampling matrix with the smallest correlation coefficient to determine the final random source layout position, such as Fig. 9 shown.

[0063] In a specific embodiment 3 of the present invention, the random optimization design method of the seismic acquisition source with automatic obstacle avoidance includes the following steps:

[0064] In step 101, the physical location points of the seismic sources are determined according to the actual situation. The longitudinal distance is 2000m, the shot point distance is 25m, the horizontal distance is 4800m, and the shot line distance is 150m. It is calculated that there are 32 shot lines, so the original number of seismic sources is N = 32*80 = 2560, and the number of source points in each shot line is n = 80 ( Fig.10 );

[0065] Step 102, the number of physical points of the earthquake source corresponding to the obstacle is calculated according to the actual surface conditions, which is M = 158, that is, Fig.11The number of sources obscured by obstacles;

[0066] Step 103, based on the comprehensive consideration of cost and acquisition effect, select the optimization factor F = 0.4, then the number of sources without considering obstacles is A = 2560 * 0.3 = 768; according to the original number of gun points in each gun row n = 80 in step 1, determine the random sampling group length B = 5, then the number of groups is like Fig.12 As shown;

[0067] Step 104, with M = 158 physical points at the obstacle as the constraint that no earthquake source is set, within each random sampling group length B = 5, first generate a group of 5 random numbers within a given range, then sort and select the first B*F = 2 points and set the sampling value to 1. After all random sampling groups are completed, a random sampling matrix is ​​formed. Then repeat this process to generate 2560 random sampling matrices;

[0068] Step 105, selecting Shearlet transform as the data reconstruction transform space, and calculating the correlation coefficients of 2560 random sampling matrices;

[0069] Step 106, compare the 2560 correlation coefficients, select a random sampling matrix with the smallest correlation coefficient to determine the final random source layout position, such as Fig.13 shown.

[0070] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein with equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0071] Except for the technical features described in the specification, all other technical features are known technologies to those skilled in the art.

Claims

1. A random optimization design method for seismic acquisition sources with automatic obstacle avoidance, characterized in that: The random optimization design method of the seismic acquisition source with automatic obstacle avoidance includes: Step 1: According to the actual situation, determine the rules to collect the physical location points of the seismic source, set the sampling value of each physical location point to 1, and calculate the number of original seismic sources as N, and the number of source points in each shot line is n; Step 2: Calculate the number of earthquake sources corresponding to obstacles based on the actual surface conditions; Step 3: Using the original number of earthquake sources and the optimization operator, determine the length and number of random sampling groups; Step 4: Generate multiple sets of random sampling matrices with the constraint that no seismic source is placed at the obstacle; Step 5: Select data to reconstruct the transformation space and calculate the correlation coefficient of the random sampling matrix; Step 6: Find the random sampling matrix with the smallest correlation coefficient, which is the location of the earthquake source; In step 3, the number of random optimized sources A is determined using the original number of sources and the optimization operator, where A = N*F; the number of original sources is N, the optimization operator is F, and 0 <F<1; In step 3, the random sampling group length B is determined according to the number of shot points n in each original shot line, so the number of groups is In step 4, with the constraint that no seismic sources are set at the M physical points at the obstacles, within each random sampling group length B, first a group of B random numbers is generated within a given range, and then the first B*F points are selected and the sampling values ​​are set to 1 after sorting. After all random sampling groups are completed, a random sampling matrix is ​​formed; repeat this process to generate N random sampling matrices.

2. The random optimization design method for seismic acquisition sources with automatic obstacle avoidance according to claim 1 is characterized in that: In step 1, according to the actual situation of the exploration area, the physical location points of the earthquake source are collected according to the rules of shot point range, shot line distance and shot point distance.

3. The random optimization design method for seismic acquisition sources with automatic obstacle avoidance according to claim 1 is characterized in that: In step 2, according to the scope of the surface obstacle zone and the sampling rules of the physical location points of the earthquake sources in the exploration area, the values ​​of the physical sampling points of the earthquake sources corresponding to the surface obstacle zone are set to 0, and the number of earthquake sources at the obstacle points is calculated and recorded as M.

4. The random optimization design method for seismic acquisition sources with automatic obstacle avoidance according to claim 1 is characterized in that: In step 5, data is selected to reconstruct the transformation space, and the correlation coefficients of N random sampling matrices are calculated as C1, C2, ..., C N .

5. The random optimization design method for seismic acquisition sources with automatic obstacle avoidance according to claim 1 is characterized in that: In step 6, N correlation coefficients are compared, and a random sampling matrix with the smallest correlation coefficient is selected as the final random layout position of the earthquake source.

Images