A method of constructing ridge identification

Abstract

This invention belongs to the field of geophysical exploration technology and discloses a method for identifying structural ridges. The method includes selecting a target layer structural map, setting gridding parameters to grid the target layer structural map, and smoothing it once according to the gridding parameters to obtain structural map A; setting gridding parameters to grid structural map A, and smoothing it three times according to the gridding parameters to obtain structural map B; setting gridding parameters to grid structural map B, and smoothing it once according to the gridding parameters to obtain structural map C; subtracting structural map C from structural map A to obtain the remaining structures after removing structural trends; assigning a value of 0 to areas where the remaining structures have negative values ​​to obtain a structural ridge distribution map. This invention is simple and obtains the distribution of structural ridges, reflecting the distribution of dominant hydrocarbon migration channels and the distribution of micro-amplitude structures, providing important reference for the prediction of remaining hydrocarbons. This invention is applicable to the identification of structural ridges.

Description

Technical Field

[0001] This invention belongs to the field of geophysical exploration technology, specifically a method for identifying structural ridges. Background Technology

[0002] As exploration and development continue to deepen, easily identifiable large-scale structural oil and gas reservoirs are becoming increasingly scarce. Therefore, micro-scale structures and structural ridges are receiving more and more attention as advantageous channels for oil and gas migration.

[0003] To improve the accuracy of micro-amplitude tectonic identification, researchers have adopted many improvements in seismic data processing, velocity mapping, and synthetic record calibration. However, these improvements ultimately combine coherent time slices with fine-grained tectonic mapping. Because time slice identification of micro-amplitude tectonic structures is not precise enough, and because of the four key parameters in tectonic mapping (grid increment, search radius, grid filtering, and contour interval), only the contour interval is determinable; the other three are significantly influenced by human factors, resulting in poor reliability of micro-amplitude tectonic research findings.

[0004] In the field of geophysical exploration, the commonly used method for identifying structural ridges is to use the most positive curvature to identify structural ridge lines. This method is simple and fast, but it is greatly affected by the quality of seismic data and has many interfering factors. The identified structural ridges have large errors and poor regularity, so the applicability of this method is poor. Summary of the Invention

[0005] The purpose of this invention is to provide a method for constructing ridge recognition.

[0006] To achieve the above objectives, the present invention employs the following technical methods:

[0007] A method for constructing ridge recognition includes the following steps:

[0008] S1. Select the target layer structure map, set the meshing parameters to mesh the target layer structure map, and smooth it once according to the meshing parameters to obtain structure map A;

[0009] S2. Set the meshing parameters to mesh the construction graph A, and perform three smoothing operations according to the meshing parameters to obtain the construction graph B;

[0010] S3. Set the meshing parameters to mesh the construction graph B, and then smooth it once according to the meshing parameters to obtain the construction graph C;

[0011] S4. Subtract construction diagram C from construction diagram A to obtain the remaining construction diagram after removing the construction trend;

[0012] S5. Assign 0 to the regions with negative values ​​in the remaining construction map to obtain the construction ridge distribution map.

[0013] As a limitation: the gridding method used in step S1 is the least squares algorithm or the distance-weighted algorithm; the smoothing level of the first smoothing is the three-point smoothing level, and the smoothing algorithm is the point average smoothing method; the smoothing level of the third smoothing in step S2 is the five-point smoothing level, and the smoothing algorithm is the point average smoothing method; the smoothing level of the first smoothing in step S3 is the three-point smoothing level, and the smoothing algorithm is the point average smoothing method.

[0014] As a further limitation: the difference between adjacent contour lines on the target layer structure map is greater than or equal to 10 meters.

[0015] As a further limitation: the meshing parameters in step S1 are set as follows: the mesh spacing is X meters and the search radius is Y meters; the meshing parameters in step S2 are set as follows: the mesh spacing is 4X meters and the search radius is 2Y meters; the meshing parameters in step S3 are set as follows: the mesh spacing is 10X meters and the search radius is 5Y meters.

[0016] The beneficial effects achieved by this invention, due to the adoption of the above-described solution, compared with the prior art, are as follows:

[0017] This invention provides a structural ridge identification method that identifies and characterizes structural ridges based on structural maps. This method is unaffected by the quality of seismic data, has wider adaptability, and clearly defines the grid increment, search radius, and number of grid filters, making it more operable. A three-step structural map smoothing method is used to obtain structural maps reflecting low-amplitude structures and structural backgrounds. By subtracting these two maps, the distribution of remaining structures is obtained, leading to the distribution of structural ridges. This reflects the distribution of dominant hydrocarbon migration channels and the distribution of micro-amplitude structures, providing important reference for the prediction of remaining hydrocarbons.

[0018] This invention is applicable to the identification of structural ridges. Attached Figure Description

[0019] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0020] Figure 1 This is a structural diagram A of an embodiment of the present invention;

[0021] Figure 2 This is structural diagram B of an embodiment of the present invention;

[0022] Figure 3 This is a structural diagram C of an embodiment of the present invention;

[0023] Figure 4 The remaining structural diagram is shown in the embodiment of the present invention;

[0024] Figure 5 This is a diagram showing the structural ridge distribution of an embodiment of the present invention;

[0025] Figure 6 This is an overlay diagram of the structural ridge and oil test of an embodiment of the present invention. Detailed Implementation

[0026] The present invention will be further described below with reference to the embodiments. However, those skilled in the art should understand that the present invention is not limited to the following embodiments. Any improvements and equivalent changes made based on the specific embodiments of the present invention are within the scope of protection of the claims of the present invention.

[0027] Example: A method for constructing ridge recognition

[0028] A method for constructing ridge recognition includes the following steps:

[0029] S1. Select the target layer structure map. The difference between adjacent contour lines in the target layer structure map is 10 meters. Grid the target layer structure map using the least squares algorithm or the distance weighted algorithm. The grid spacing is 50 meters and the search radius is 1000 meters. Smooth the map once using the point average smoothing method with three-point smoothing level according to the grid spacing and search radius to obtain structure map A.

[0030] S2. Grid the construction map A with a grid spacing of 200 meters and a search radius of 2000 meters. Then, use the point average smoothing method with five smoothing levels to perform three smoothing operations according to the grid spacing and search radius to obtain the construction map B.

[0031] S3. Grid the construction map B with a grid spacing of 500 meters and a search radius of 5000 meters. Then, use the point average smoothing method with three-point smoothing level to smooth the map once according to the grid spacing and search radius to obtain the construction map C.

[0032] S4. Subtract construction diagram C from construction diagram A to obtain the remaining construction diagram after removing the construction trend, as follows: Figure 4 As shown;

[0033] S5. Assign 0 values ​​to the regions with negative values ​​in the remaining structural map to obtain the structural ridge distribution map, such as... Figure 5 As shown.

[0034] The superimposed diagram of the structural ridge and oil testing in this embodiment is shown below. Figure 6 As shown in the figure, the oil and gas enrichment areas are all distributed on the structural ridges and extend along the structural ridges. The structural ridges have a strong control effect on oil and gas enrichment.

Claims

1. A method for constructing ridge recognition, characterized in that, Includes the following steps: S1. Select the target layer structure map, set the meshing parameters to mesh the target layer structure map, and smooth it once according to the meshing parameters to obtain structure map A; S2. Set the meshing parameters to mesh the construction graph A, and perform three smoothing operations according to the meshing parameters to obtain the construction graph B; S3. Set the meshing parameters to mesh the construction graph B, and then smooth it once according to the meshing parameters to obtain the construction graph C; S4. Subtract construction diagram C from construction diagram A to obtain the remaining construction diagram after removing the construction trend; S5. Assign 0 to the regions with negative values ​​in the remaining structural map to obtain the structural ridge distribution map; In step S1, the gridding method used is either the least squares algorithm or the distance-weighted algorithm; the smoothing level of the first smoothing is a three-point smoothing level, and the smoothing algorithm is the point average smoothing method; in step S2, the smoothing level of the third smoothing is a five-point smoothing level, and the smoothing algorithm is the point average smoothing method; in step S3, the smoothing level of the first smoothing is a three-point smoothing level, and the smoothing algorithm is the point average smoothing method. The meshing parameters in step S1 are set as follows: mesh spacing is X meters and search radius is Y meters; the meshing parameters in step S2 are set as follows: mesh spacing is 4X meters and search radius is 2Y meters; the meshing parameters in step S3 are set as follows: mesh spacing is 10X meters and search radius is 5Y meters.

2. The ridge identification method according to claim 1, characterized in that, The difference between adjacent contour lines on the target layer structure map is greater than or equal to 10 meters.

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