Near-surface three-dimensional velocity modeling method and device, storage medium and electronic equipment

Abstract

The invention relates to a near-surface three-dimensional speed modeling method and device, a storage medium and electronic equipment. The near-surface three-dimensional speed modeling method comprises the following steps: generating a three-dimensional speed model based on acquired survey result data of each surface layer; performing interpolation operation based on the surface survey result data of each grid point on the three-dimensional speed model to obtain a three-dimensional speed interpolation model; based on the construction boundary position information of the target work area, shearing the three-dimensional speed interpolation model to obtain a near-surface three-dimensional speed model of the target work area; the near-surface three-dimensional speed model is sliced according to a preset slicing strategy, a near-surface three-dimensional speed slicing model is obtained, and based on the near-surface three-dimensional speed slicing model, surface layer speed information and speed reduction layer thickness change information of the target work area are obtained; and based on the obtained surface layer speed information and the speed reduction layer thickness change information, optimizing the preliminarily arranged surface layer survey control points of the target work area. The layout precision of the control points can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic exploration, and particularly to a method, device, storage medium, and electronic device for near-surface three-dimensional velocity modeling. Background Art

[0002] In field seismic exploration, near-surface investigation work is a process of obtaining near-surface seismic exploration data (geophysical information) using necessary observation equipment and corresponding observation methods to study the near-surface structure in seismic exploration.

[0003] Near-surface investigation work mainly includes four aspects: (1) Layout of control points in the work area: That is, the design of the density and position of near-surface investigation points, with the principle of controlling the variation law of the surface layer structure; (2) Acquisition method design: First, according to the differences in the surface layer structure characteristics and terrain undulations at the layout positions of the control points, determine the investigation methods to be used for each control point. Then, based on the investigation methods selected for each control point, conduct specific acquisition parameter design; (3) Implementation of the acquisition method: Construct at the control points according to the acquisition method and acquisition parameters. During the acquisition process, conduct on-site evaluation of the original records of the control points, and after passing the evaluation, proceed with the acquisition of the next near-surface investigation point (control point); (4) Data processing and interpretation: In near-surface investigation methods of the seismic method category, generally, the surface layer structure including the near-surface layer velocity and the velocity reduction layer velocity is solved through the relationship between the wave propagation time and the shot-receiver offset.

[0004] The main functions of near-surface investigation work are: (1) Obtain the thickness of the near-surface medium and the propagation velocity of seismic waves, providing basic data for surface layer modeling or first arrival travel time inversion of seismic records; (2) Provide a basis for determining reasonable excitation and reception conditions in seismic exploration; (3) Provide basic information for scientifically, efficiently, and environmentally friendly organizing field production; (4) Provide a reference for analyzing the characteristics of the surface layer structure in the work area and selecting a reasonable static correction method.

[0005] Due to the influence of complex near-surface conditions, for geological structures where the near-surface velocity and the thickness of the velocity reduction layer change rapidly, such as the Sichuan Basin, in related technologies, the variation law of the near-surface layer velocity and the thickness of the velocity reduction layer is mainly analyzed through the plane velocity distribution map and the plane velocity reduction layer thickness distribution map made by software. However, this near-surface analysis method separates the near-surface layer velocity and the thickness of the velocity reduction layer, which is not conducive to analyzing areas where both the near-surface layer velocity and the thickness of the velocity reduction layer change rapidly, thereby reducing the layout accuracy of fine control points. Summary of the Invention

[0006] In view of this, the present invention provides a method, device, storage medium, and electronic device for near-surface three-dimensional velocity modeling.

[0007] Specifically, the present invention is implemented through the following technical solutions:

[0008] According to a first aspect of the present invention, there is provided a method for near-surface three-dimensional velocity modeling, and the method for near-surface three-dimensional velocity modeling includes:

[0009] Obtain the surface survey result data of the preliminarily arranged surface survey control points;

[0010] Generate a three-dimensional velocity model based on the surface survey result data of each surface survey control point, and each grid point of the three-dimensional velocity model corresponds to a surface survey control point;

[0011] Perform interpolation operations based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model, determine each interpolation grid point on the three-dimensional velocity model, and obtain a three-dimensional velocity interpolation model;

[0012] Obtain the construction boundary position information of the target work area, and based on the construction boundary position information, shear the three-dimensional velocity interpolation model to obtain the near-surface three-dimensional velocity model of the target work area;

[0013] Slice the near-surface three-dimensional velocity model according to a preset slicing strategy, obtain a near-surface three-dimensional velocity slice model, and based on the near-surface three-dimensional velocity slice model, obtain the surface velocity information and the change information of the thickness of the velocity reduction layer of the target work area;

[0014] Optimize the preliminarily arranged surface survey control points of the target work area based on the obtained surface velocity information and the change information of the thickness of the velocity reduction layer.

[0015] Preferably, the performing interpolation operations based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model and determining each interpolation grid point on the three-dimensional velocity model includes:

[0016] Determine the position information of the grid points to be interpolated on the three-dimensional velocity model;

[0017] Calculate the Euclidean distances between the grid points to be interpolated and each grid point within a predetermined range respectively, obtain the reciprocals of the Euclidean distances, and obtain the inverse distance weighting coefficients of the grid points to be interpolated and the corresponding grid points;

[0018] For each grid point within the predetermined range, calculate the product of the velocity data in the surface survey result data of the grid point and the corresponding inverse distance weighting coefficient, and obtain the sum value of each product;

[0019] Obtain the sum value of the inverse distance weighting coefficients of each grid point, calculate the quotient of the sum value of each product and the sum value of the inverse distance weighting coefficients of each grid point, and obtain the velocity data of the grid point to be interpolated.

[0020] Preferably, generating a three-dimensional velocity model based on the surface survey result data of each surface survey control point includes:

[0021] Obtain the position information in each of the surface survey result data, where the position information includes: surface lateral position information, surface longitudinal position information, and depth position information;

[0022] Extract the minimum surface lateral position information, maximum surface lateral position information, minimum surface longitudinal position information, maximum surface longitudinal position information, minimum depth position information, and maximum depth position information from the respective position information;

[0023] Based on the minimum surface lateral position information and the maximum surface lateral position information, determine the lateral coordinate length of the three-dimensional velocity model, and based on the minimum value of the projections of adjacent surface survey result data on the lateral coordinate, determine the unit length of the lateral coordinate of the three-dimensional velocity model;

[0024] Based on the minimum surface longitudinal position information and the maximum surface lateral position information, determine the longitudinal coordinate length of the three-dimensional velocity model, and based on the minimum value of the projections of adjacent surface survey result data on the longitudinal coordinate, determine the unit length of the longitudinal coordinate of the three-dimensional velocity model;

[0025] Based on the minimum depth position information and the maximum depth position information, determine the depth coordinate length of the three-dimensional velocity model, and based on the minimum value of the projections of adjacent surface survey result data on the depth coordinate, determine the unit length of the depth coordinate of the three-dimensional velocity model;

[0026] Based on the position information in the surface survey result data, determine the grid points to which the surface survey result data is mapped in the three-dimensional velocity model, and set the surface survey result data as the attribute data of the determined grid points.

[0027] Preferably, the interpolation operation includes: Kriging interpolation method, moving average method, least squares method, minimum curvature method, natural neighbor interpolation method, nearest neighbor interpolation method, inverse distance weighted interpolation method, discrete smoothing interpolation algorithm, local polynomial method, multiple regression method, linear interpolation triangulation method, improved Shepard method, and radial basis function method.

[0028] Preferably, optimizing the initially arranged surface survey control points in the target work area based on the obtained surface velocity information and the change information of the downgoing layer thickness includes:

[0029] Slice along the depth direction based on the grid points corresponding to the surface survey control points, and sequentially obtain the velocity data corresponding to each depth in the slice;

[0030] Calculate the velocity difference of the velocity data corresponding to the surface survey control points at adjacent depths;

[0031] If the velocity difference exceeds a pre-set velocity threshold, add surface survey control points between the surface survey control points at the adjacent depths.

[0032] Preferably, the method further includes:

[0033] Based on the surface survey result data of the surface survey control points optimized and deployed in the target work area, correct the near-surface three-dimensional velocity model, so as to perform slice analysis based on the corrected near-surface three-dimensional velocity model.

[0034] Preferably, the correcting the near-surface three-dimensional velocity model based on the surface survey result data of the surface survey control points optimized and deployed in the target work area includes:

[0035] Query and obtain the grid points corresponding to the optimized and deployed surface survey control points in the near-surface three-dimensional velocity model, and update the velocity data of the grid points to the velocity data corresponding to the surface survey control points;

[0036] If there are no grid points corresponding to the optimized and deployed surface survey control points in the near-surface three-dimensional velocity model, add grid points corresponding to the surface survey control points in the near-surface three-dimensional velocity model;

[0037] Based on the velocity data of the updated grid points in the near-surface three-dimensional velocity model, use the interpolation operation to update the velocity data of the interpolation grid points in the near-surface three-dimensional velocity model.

[0038] The method for near-surface three-dimensional velocity modeling in this technical solution includes obtaining the surface survey result data of the preliminarily arranged surface survey control points; generating a three-dimensional velocity model based on the surface survey result data of each surface survey control point, where each grid point of the three-dimensional velocity model corresponds to a surface survey control point; performing interpolation operations based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model to determine each interpolation grid point on the three-dimensional velocity model and obtaining a three-dimensional velocity interpolation model; obtaining the construction boundary position information of the target work area, and based on the construction boundary position information, shearing the three-dimensional velocity interpolation model to obtain the near-surface three-dimensional velocity model of the target work area; slicing the near-surface three-dimensional velocity model according to a pre-set slicing strategy to obtain a near-surface three-dimensional velocity slice model, and based on the near-surface three-dimensional velocity slice model, obtaining the surface velocity information and the variation information of the velocity reduction layer thickness of the target work area; optimizing the preliminarily arranged surface survey control points of the target work area based on the obtained surface velocity information and the variation information of the velocity reduction layer thickness. In this way, by generating a three-dimensional velocity model from the surface survey result data and performing interpolation operations, and analyzing the near-surface three-dimensional velocity slice model in the target work area obtained from the interpolation operations, velocity slices in all directions can be obtained, so that the surface velocity and thickness variation laws of the target work area can be analyzed more precisely. Furthermore, based on the surface velocity and thickness variation laws, the rationality of the deployment of the surface survey control points can be analyzed in detail, thereby improving the layout accuracy of the control points and better obtaining the surface information of the target work area.

[0039] According to the second aspect of the present invention, there is provided an apparatus for near-surface three-dimensional velocity modeling. The apparatus for near-surface three-dimensional velocity modeling includes:

[0040] A data acquisition module for obtaining the surface survey result data of the preliminarily arranged surface survey control points;

[0041] A grid point mapping module for generating a three-dimensional velocity model based on the surface survey result data of each surface survey control point, where each grid point of the three-dimensional velocity model corresponds to a surface survey control point;

[0042] An interpolation operation module for performing interpolation operations based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model to determine each interpolation grid point on the three-dimensional velocity model and obtaining a three-dimensional velocity interpolation model;

[0043] A model construction module for obtaining the construction boundary position information of the target work area, and based on the construction boundary position information, shearing the three-dimensional velocity interpolation model to obtain the near-surface three-dimensional velocity model of the target work area;

[0044] The slice analysis module is used to slice the near-surface three-dimensional velocity model according to a preset slicing strategy to obtain a near-surface three-dimensional velocity slice model, and based on the near-surface three-dimensional velocity slice model, obtain the surface velocity information and the variation information of the thickness of the velocity reduction layer in the target work area;

[0045] The point layout optimization module is used to optimize the initially laid surface survey control points in the target work area based on the obtained surface velocity information and the variation information of the thickness of the velocity reduction layer.

[0046] According to the third aspect of the present invention, there is provided a storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the method for near-surface three-dimensional velocity modeling in any possible implementation manner of the first aspect are implemented.

[0047] According to the fourth aspect of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the steps of the method for near-surface three-dimensional velocity modeling in any possible implementation manner of the first aspect are implemented. Description of the Drawings

[0048] The drawings here are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present invention, and are used together with the specification to explain the principles of the present invention.

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0050] Figure 1 It is a schematic flow chart of a method for near-surface three-dimensional velocity modeling provided by an embodiment of the present invention;

[0051] Figure 2 It is a schematic diagram of a processing device for near-surface three-dimensional velocity modeling provided by an embodiment of the present invention;

[0052] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed Embodiments

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0054] In the related art, a method of analyzing the variation law of the near-surface layer velocity and the thickness of the velocity reduction layer by using the planar velocity distribution map and the planar velocity reduction layer thickness distribution map made by software separates the near-surface layer velocity and the thickness of the velocity reduction layer, which is not conducive to analyzing the area where both the near-surface layer velocity and the thickness of the velocity reduction layer change rapidly, thereby reducing the layout accuracy of fine control points, and thus making the accuracy of the near-surface layer velocity and the velocity reduction layer velocity based on the seismic exploration data collected based on the control points not high.

[0055] The low velocity reduction layer has the characteristics of low velocity, loose geological structure, and fast longitudinal and transverse changes, and is an important factor affecting seismic exploration. Therefore, how to deploy surface survey control points in the velocity reduction layer to obtain field-collected seismic exploration data is a technical problem that urgently needs to be solved to improve the accuracy of seismic exploration.

[0056] In this embodiment, for the fine surface survey construction, using the seismic exploration data collected from the near-surface layer, based on the near-surface layer velocity and the velocity reduction layer thickness data in the seismic exploration data, a near-surface three-dimensional velocity model of the entire work area is established. Through the slicing operation of the near-surface three-dimensional velocity model, the near-surface layer velocity and the velocity reduction layer thickness data in the corresponding slice area can be obtained, and the analysis of the changes in the near-surface layer velocity and the velocity reduction layer thickness can be carried out, which provides help for the optimization of the later control point layout, static correction, and fine processing of the profile, and provides a reference for promoting oil and gas discovery and expanding the exploration market.

[0057] See Figure 1 , the embodiments of the present invention provide a method for near-surface three-dimensional velocity modeling, and the method may include the following steps:

[0058] S101. Obtain the surface survey result data of the preliminarily arranged surface survey control points;

[0059] In this embodiment, by using software to explain in detail the seismic exploration data of each micro-log in the work area, the surface survey result data including the velocity reduction layer velocity and the surface layer thickness can be obtained. As an alternative embodiment, the surface survey result data includes, but is not limited to: the abscissa, ordinate, elevation, construction depth, and corresponding velocity of the surface survey control points, where the area where the construction depth is located includes the near-surface layer and the velocity reduction layer.

[0060] S102. Generate a three-dimensional velocity model based on the surface survey result data of each surface survey control point. Each grid point of the three-dimensional velocity model corresponds to a surface survey control point.

[0061] In this embodiment, the surface survey result data is processed and converted to form format data required for the three-dimensional velocity model. The format data is imported into pre-set modeling software to form a three-dimensional velocity model based on each surface survey result data. In the three-dimensional velocity model, each surface survey control point corresponds to a grid point, and the surface survey result data of the surface survey control point is set as the attribute data of the grid point corresponding to the surface survey control point.

[0062] In this embodiment, as an alternative embodiment, generating a three-dimensional velocity model based on the surface survey result data of each surface survey control point includes:

[0063] Obtain the position information in each of the surface survey result data. The position information includes: surface horizontal position information, surface longitudinal position information, and depth position information.

[0064] Extract the minimum surface horizontal position information, maximum surface horizontal position information, minimum surface longitudinal position information, maximum surface longitudinal position information, minimum depth position information, and maximum depth position information from the respective position information.

[0065] Based on the minimum surface horizontal position information and the maximum surface horizontal position information, determine the horizontal coordinate length of the three-dimensional velocity model. Based on the minimum value of the projections of adjacent surface survey result data on the horizontal coordinate, determine the unit length of the horizontal coordinate of the three-dimensional velocity model.

[0066] Based on the minimum surface longitudinal position information and the maximum surface horizontal position information, determine the longitudinal coordinate length of the three-dimensional velocity model. Based on the minimum value of the projections of adjacent surface survey result data on the longitudinal coordinate, determine the unit length of the longitudinal coordinate of the three-dimensional velocity model.

[0067] Based on the minimum depth position information and the maximum depth position information, determine the depth coordinate length of the three-dimensional velocity model. Based on the minimum value of the projections of adjacent surface survey result data on the depth coordinate, determine the unit length of the depth coordinate of the three-dimensional velocity model.

[0068] Based on the position information in the surface survey result data, determine the grid point to which the surface survey result data is mapped in the three-dimensional velocity model, and set the surface survey result data as the attribute data of the determined grid point.

[0069] In this embodiment, each surface survey control point serves as a grid point of the three-dimensional velocity model, and the surface survey result data corresponding to the surface survey control point is mapped to the grid point of the three-dimensional velocity model. By determining the unit length of the three-dimensional velocity model, the grid point layout can be made reasonable.

[0070] S103. Perform interpolation operations based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model to determine each interpolation grid point on the three-dimensional velocity model, and obtain a three-dimensional velocity interpolation model.

[0071] In this embodiment, by performing interpolation operations on the grid points (surface survey control points), based on the surface survey control points and the interpolated survey points obtained by interpolation, surface survey control points including surface survey control points and interpolated survey points are obtained to expand the three-dimensional velocity model.

[0072] In this embodiment, as an alternative embodiment, after gridifying the surface survey result data corresponding to the surface survey control points, the interpolation search radius of the surface survey control points is adjusted, and interpolation operations are performed on each surface survey control point. The interpolation operations include, but are not limited to: Kriging interpolation method, moving average method, least squares method, minimum curvature method, natural neighbor interpolation method, nearest neighbor interpolation method, inverse distance weighted (IDW) interpolation method, discrete smooth interpolation (DSI) algorithm, local polynomial method, multiple regression method, linear interpolation triangulation method, improved Shepard method, radial basis function method, etc.

[0073] In this embodiment, as an alternative embodiment, using the inverse distance weighted interpolation method, based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model, perform interpolation operations to determine each interpolation grid point on the three-dimensional velocity model, including:

[0074] Determine the position information of the grid point to be interpolated on the three-dimensional velocity model.

[0075] Calculate the Euclidean distances between the grid point to be interpolated and each grid point within a predetermined range respectively, obtain the reciprocals of the Euclidean distances, and obtain the inverse distance weighted coefficients between the grid point to be interpolated and this grid point.

[0076] For each grid point within the predetermined range, calculate the product of the velocity data in the surface survey result data of this grid point and the corresponding inverse distance weighted coefficient, and obtain the sum value of each product.

[0077] Obtain the sum value of the inverse distance weighted coefficients of each grid point, calculate the quotient value of the sum value of each product and the sum value of the inverse distance weighted coefficients of each grid point, and obtain the velocity data of the grid point to be interpolated.

[0078] In this embodiment, for the surface survey result data, the velocity data of grid points with a relatively short distance are more similar to the velocity data of grid points with a relatively long distance. Therefore, using the inverse distance weighted interpolation method, through weighted average interpolation, accurate or smooth grid point interpolation can be performed. Among them, the inverse distance weighted coefficient decreases as the Euclidean distance between the point to be interpolated and the target grid node increases.

[0079] S104. Obtain the construction boundary position information of the target work area, and based on the construction boundary position information, shear the three-dimensional velocity interpolation model to obtain the near-surface three-dimensional velocity model of the target work area;

[0080] In this embodiment, when collecting seismic exploration data for the target work area, in order to comprehensively collect the full-range coverage data of the target work area, the surface survey result data obtained may include the seismic exploration data of multiple adjacent work areas adjacent to the target work area. In order to reduce the influence of adjacent work areas on the target work area in subsequent analysis and improve the analysis accuracy, according to the construction boundary data of the target work area, for example, the construction boundary position information, the construction boundary data of the target work area and the three-dimensional velocity interpolation model are combined, and the data outside the construction boundary of the target work area are deleted to form a near-surface three-dimensional velocity model within the boundary range of the target work area.

[0081] S105. Slice the near-surface three-dimensional velocity model according to a preset slicing strategy to obtain a near-surface three-dimensional velocity slice model, and based on the near-surface three-dimensional velocity slice model, obtain the surface velocity information and the variation information of the velocity reduction layer thickness of the target work area;

[0082] In this embodiment, the near-surface three-dimensional velocity model can be sliced from different angles and different orientations to form a cross-sectional view of the near-surface three-dimensional velocity model. Through the near-surface three-dimensional velocity slice model obtained by slicing, the rationality of the surface point deployment can be finely analyzed, so that for areas with large changes in surface velocity and thickness, the construction of surface survey control points can be encrypted to better obtain the surface information of the target work area.

[0083] In this embodiment, by finely analyzing the near-surface three-dimensional velocity slice model to guide the precise encryption of surface survey control points in the field, more comprehensive near-surface data (seismic exploration data) can be obtained, and it can also better guide the subsequent indoor static correction work, and better seismic profiles can be obtained for areas with large surface undulations.

[0084] Table 1 is a schematic table of the surface survey result data of each grid point in the near-surface three-dimensional velocity slice model obtained by slicing in the depth direction based on a surface survey control point.

[0085] Table 1

[0086]

[0087]

[0088] S106. Optimize the initially arranged surface survey control points in the target work area based on the obtained surface velocity information and the information on the change in the thickness of the velocity reduction layer.

[0089] In this embodiment, as an optional embodiment, optimizing the initially arranged surface survey control points in the target work area based on the obtained surface velocity information and the information on the change in the thickness of the velocity reduction layer includes:

[0090] Perform slicing along the depth direction based on the grid points corresponding to the surface survey control points, and sequentially obtain the velocity data corresponding to each depth in the slice;

[0091] Calculate the velocity difference between the velocity data corresponding to the surface survey control points at adjacent depths;

[0092] If the velocity difference exceeds a pre-set velocity threshold, add surface survey control points between the surface survey control points at the adjacent depths.

[0093] In this embodiment, if the velocity difference does not exceed the pre-set velocity threshold, remove one of the surface survey control points at the adjacent depths.

[0094] In this embodiment, by analyzing the near-surface three-dimensional velocity slice model in the target work area, velocity slices in each azimuth can be obtained, so that the surface velocity and thickness change laws in the target work area can be analyzed more precisely. Furthermore, based on the surface velocity and thickness change laws, the rationality of the deployment of surface points (surface survey control points) can be analyzed in detail. For areas with large changes in surface velocity and thickness, fine surface densification is carried out, so that better surface information of the work area can be obtained, and the situation of additional point layout can be significantly reduced, and the investment in human and material resources can be reduced. For example, for the velocity analysis of Table 1, the velocity changes greatly between the points at depth -4 and depth -5, and between the points at depth -7 and depth -8. Therefore, surface survey control points can be densely deployed between the points at depth -4 and depth -5, and between the points at depth -7 and depth -8 to obtain higher-quality seismic exploration data.

[0095] Furthermore, through fine near-surface three-dimensional velocity modeling, the subsequent indoor static correction work can be better guided, so that for areas with large surface undulations, better seismic profiles can be obtained, which has good effects on implementing the spatial distribution of the main target layer in the target work area, depicting the structural details, and various micro-scale structures.

[0096] In this embodiment, by using the surface survey result data, through processing and conversion, format data used by the software is formed. The data is imported into the software to form surface survey control points for modeling. The data of the surface survey control points is gridded, the search radius of the control point difference is adjusted, and the inverse distance weighted method is used for difference operation to generate a velocity interpolation model with a three-dimensional structure. Then, by editing the boundary position information of the target work area to form format data used by the software, importing it into the software, merging the target work area boundary and the three-dimensional velocity interpolation model, and then performing operations to delete the redundant data outside the target work area boundary, a near-surface three-dimensional velocity model within the target work area boundary is finally formed. By slicing the near-surface three-dimensional velocity model from different angles and azimuths, the velocity change law and the change law of the thickness of the low-velocity zone at each position in the target work area can be finely analyzed, guiding the method of fine surface survey and surface interpretation in the field; at the same time, based on the analysis results, the rationality of the surface point deployment can also be finely analyzed, and fine surface densification can be carried out for places with large changes in surface velocity and thickness, so as to better obtain the surface information of the target work area. At the same time, through fine three-dimensional velocity modeling, it can also better guide the later indoor static correction work, so as to obtain a better seismic profile for areas with large surface undulations, and has good effects on implementing the spatial distribution of the main target layers, tectonic details, and the delineation of various microstructures in the target work area.

[0097] In this embodiment, as an alternative embodiment, the method further includes:

[0098] Based on the surface survey result data of the surface survey control points optimized and deployed for the target work area, the near-surface three-dimensional velocity model is corrected to perform slice analysis based on the corrected near-surface three-dimensional velocity model.

[0099] In this embodiment, as an alternative embodiment, based on the surface survey result data of the surface survey control points optimized and deployed for the target work area, correcting the near-surface three-dimensional velocity model includes:

[0100] Query and obtain the grid points corresponding to the optimized and deployed surface survey control points in the near-surface three-dimensional velocity model, and update the velocity data of the grid points to the velocity data of the corresponding surface survey control points;

[0101] If there are no grid points corresponding to the optimized and deployed surface survey control points in the near-surface three-dimensional velocity model, grid points corresponding to the surface survey control points are newly added in the near-surface three-dimensional velocity model;

[0102] Based on the velocity data of the updated grid points in the near-surface three-dimensional velocity model, the velocity data of the interpolation grid points in the near-surface three-dimensional velocity model is updated by using the interpolation operation.

[0103] In this embodiment, after optimizing the deployment of surface survey control points, by obtaining the surface survey result data of the optimized deployed surface survey control points, the constructed near-surface three-dimensional velocity model is corrected, thereby further improving the accuracy of the corrected near-surface three-dimensional velocity model and facilitating subsequent analysis.

[0104] Based on the same inventive concept, as Figure 2 shown, an embodiment of the present invention further provides a device for near-surface three-dimensional velocity modeling, the device includes:

[0105] A data acquisition module 201, configured to acquire surface survey result data of initially arranged surface survey control points;

[0106] A grid point mapping module 202, configured to generate a three-dimensional velocity model based on the surface survey result data of each surface survey control point, and each grid point of the three-dimensional velocity model corresponds to a surface survey control point;

[0107] In this embodiment, as an optional embodiment, the grid point mapping module 202 includes:

[0108] A position information extraction unit, configured to acquire position information in each of the surface survey result data, where the position information includes: surface horizontal position information, surface longitudinal position information, and depth position information;

[0109] A minimum and maximum value acquisition unit, configured to extract the minimum surface horizontal position information, the maximum surface horizontal position information, the minimum surface longitudinal position information, the maximum surface longitudinal position information, the minimum depth position information, and the maximum depth position information from each position information;

[0110] A horizontal length determination unit, configured to determine the horizontal coordinate length of the three-dimensional velocity model based on the minimum surface horizontal position information and the maximum surface horizontal position information, and determine the unit length of the horizontal coordinate of the three-dimensional velocity model based on the minimum value of the projection of adjacent surface survey result data on the horizontal coordinate;

[0111] A longitudinal length determination unit, configured to determine the longitudinal coordinate length of the three-dimensional velocity model based on the minimum surface longitudinal position information and the maximum surface horizontal position information, and determine the unit length of the longitudinal coordinate of the three-dimensional velocity model based on the minimum value of the projection of adjacent surface survey result data on the longitudinal coordinate;

[0112] A depth determination unit, configured to determine the depth coordinate length of the three-dimensional velocity model based on the minimum depth position information and the maximum depth position information, and determine the unit length of the depth coordinate of the three-dimensional velocity model based on the minimum value of the projection of adjacent surface survey result data on the depth coordinate;

[0113] A mapping unit, configured to determine, based on the position information in the surface survey result data, the grid points on the three-dimensional velocity model to which the surface survey result data is mapped, and set the surface survey result data as the attribute data of the determined grid points.

[0114] An interpolation operation module 203, configured to perform an interpolation operation based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model, determine each interpolation grid point on the three-dimensional velocity model, and obtain a three-dimensional velocity interpolation model.

[0115] In this embodiment, as an alternative embodiment, the interpolation operation includes: Kriging interpolation method, moving average method, least squares method, minimum curvature method, natural neighbor interpolation method, nearest neighbor interpolation method, inverse distance weighted interpolation method, discrete smoothing interpolation algorithm, local polynomial method, multiple regression method, linear interpolation triangulation method, improved Shepard method, and radial basis function method.

[0116] In this embodiment, as an alternative embodiment, the interpolation operation module 203 includes:

[0117] A position determination unit, configured to determine the position information of the grid points to be interpolated on the three-dimensional velocity model.

[0118] A coefficient acquisition unit, configured to calculate the Euclidean distance between each grid point within a predetermined range and the grid points to be interpolated respectively, obtain the reciprocal of the Euclidean distance, and obtain the inverse distance weighted coefficient between the grid points to be interpolated and the grid point.

[0119] A weighted sum calculation unit, configured to calculate the product of the velocity data in the surface survey result data of each grid point and the corresponding inverse distance weighted coefficient for each grid point within the predetermined range, and obtain the sum value of each product.

[0120] An interpolation operation unit, configured to obtain the sum value of the inverse distance weighted coefficients of each grid point, calculate the quotient of the sum value of each product and the sum value of the inverse distance weighted coefficients of each grid point, and obtain the velocity data of the grid points to be interpolated.

[0121] A model construction module 204, configured to obtain the construction boundary position information of the target work area, and perform shearing on the three-dimensional velocity interpolation model based on the construction boundary position information to obtain the near-surface three-dimensional velocity model of the target work area.

[0122] A slice analysis module 205, configured to slice the near-surface three-dimensional velocity model according to a preset slice strategy, obtain a near-surface three-dimensional velocity slice model, and obtain the surface velocity information and the variation information of the thickness of the velocity reduction layer of the target work area based on the near-surface three-dimensional velocity slice model.

[0123] The layout optimization module 206 is configured to optimize the initially arranged surface survey control points in the target work area based on the obtained surface velocity information and the change information of the thickness of the velocity reduction layer.

[0124] In this embodiment, as an alternative embodiment, the layout optimization module 206 includes:

[0125] The slice data acquisition unit is configured to perform slicing along the depth direction based on the grid points corresponding to the surface survey control points, and sequentially acquire the velocity data corresponding to each depth in the slice;

[0126] The velocity difference acquisition unit is configured to calculate the velocity difference of the velocity data corresponding to the surface survey control points at adjacent depths;

[0127] The layout optimization unit is configured to add surface survey control points between the surface survey control points at the adjacent depths if the velocity difference exceeds a preset velocity threshold.

[0128] In this embodiment, as another alternative embodiment, the layout optimization module 206 further includes:

[0129] The layout merging unit is configured to remove one of the surface survey control points at the adjacent depths if the velocity difference does not exceed the preset velocity threshold.

[0130] In this embodiment, as an alternative embodiment, the device further includes:

[0131] The model correction module (not shown in the figure) is configured to correct the near-surface three-dimensional velocity model based on the surface survey result data of the surface survey control points optimized and deployed in the target work area, so as to perform slice analysis based on the corrected near-surface three-dimensional velocity model.

[0132] In this embodiment, as an alternative embodiment, the model correction module includes:

[0133] The query unit is configured to query and obtain the grid points corresponding to the optimized and deployed surface survey control points in the near-surface three-dimensional velocity model, and update the velocity data of the grid points to the velocity data corresponding to the surface survey control points;

[0134] The layout processing unit is configured to add grid points corresponding to the surface survey control points in the near-surface three-dimensional velocity model if there are no grid points corresponding to the optimized and deployed surface survey control points in the near-surface three-dimensional velocity model;

[0135] The model update unit is configured to update the velocity data of the interpolation grid points in the near-surface three-dimensional velocity model by using the interpolation operation based on the velocity data of the updated grid points in the near-surface three-dimensional velocity model.

[0136] Based on the same inventive concept, an embodiment of the present invention further provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method for near-surface three-dimensional velocity modeling in any of the above possible implementation manners are implemented.

[0137] Optionally, the storage medium may be a non-transitory computer-readable storage medium. For example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0138] Based on the same inventive concept, refer to Figure 3 , an embodiment of the present invention further provides an electronic device, including a memory 101 (such as a non-volatile memory), a processor 102, and a computer program stored on the memory 101 and executable on the processor 102. When the processor 102 executes the program, the steps of the method for near-surface three-dimensional velocity modeling in any of the above possible implementation manners are implemented, which is equivalent to the device for near-surface three-dimensional velocity modeling as described above. Of course, the processor can also be used to process other data or perform operations. The electronic device may be a device such as a PC, a server, a terminal, etc.

[0139] As Figure 3 shown, the electronic device generally may further include: a memory 103, a network interface 104, and an internal bus 105. In addition to these components, other hardware may also be included, which will not be elaborated herein.

[0140] It should be noted that the above device for near-surface three-dimensional velocity modeling may be implemented by software. As a logically meaningful device, it is formed by the processor 102 of the electronic device where it is located reading the computer program instructions stored in the non-volatile memory into the memory 103 and running.

[0141] The embodiments of the subject matter and functional operations described in this specification can be implemented in the following: digital electronic circuits, tangible embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or a combination of one or more of them. The embodiments of the subject matter described in this specification can be implemented as one or more computer programs, that is, one or more modules in computer program instructions encoded on a tangible non-transitory program carrier to be executed by a data processing device or to control the operation of the data processing device. Alternatively or additionally, the program instructions can be encoded on an artificially generated propagated signal, such as a machine-generated electrical, optical, or electromagnetic signal, which is generated to encode information and transmit it to a suitable receiver device for execution by the data processing device. The computer storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of them.

[0142] The processes and logical flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform the corresponding functions by operating on input data and generating output. The processes and logical flows can also be performed by, for example, special purpose logic circuitry such as an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit), and the apparatus can also be implemented as special purpose logic circuitry.

[0143] Computers suitable for executing computer programs include, by way of example, general and / or special purpose microprocessors, or any other type of central processing unit. Generally, a central processing unit will receive instructions and data from a read only memory and / or a random access memory. Basic components of a computer include a central processing unit for executing or implementing instructions and one or more memory devices for storing the instructions and data. Generally, a computer will also include one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, etc., or the computer will be operatively coupled to such mass storage devices to receive data therefrom or transfer data thereto, or both. However, a computer need not have such devices. In addition, a computer may be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a portable storage device such as a Universal Serial Bus (USB) flash drive, to name just a few.

[0144] Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, including by way of example semiconductor memory devices (such as EPROM, EEPROM, and flash memory devices), magnetic disks (such as internal hard disks or removable disks), magneto-optical disks, and CD-ROM and DVD-ROM disks. The processor and the memory may be supplemented by, or incorporated in, special purpose logic circuitry.

[0145] Although this specification contains many specific implementation details, these should not be construed as limiting the scope of any invention or of what is claimed, but rather as primarily describing features of particular embodiments of a particular invention. Certain features that are described in this specification in the context of multiple embodiments can also be implemented in a single embodiment in combination. On the other hand, various features that are described in a single embodiment can also be implemented in multiple embodiments separately or in any suitable sub-combination. Moreover, although features may operate in certain combinations and even be claimed as such initially, one or more features from a claimed combination can in some cases be removed from the combination, and the claimed combination can be directed to a sub-combination or a variation of a sub-combination.

[0146] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that these operations be performed in the particular order shown or performed sequentially, or requiring that all illustrated operations be performed to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product, or packaged into multiple software products.

[0147] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some implementations, multitasking and parallel processing may be advantageous.

[0148] It should be noted that, in this article, relational terms such as "first" and "second" are only used 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.

[0149] The above is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features applied herein.

Claims

1. A method for near-surface three-dimensional velocity modeling, characterized in that, Including: Obtaining the surface survey result data of the preliminarily arranged surface survey control points; Generating a three-dimensional velocity model based on the surface survey result data of each surface survey control point, where each grid point of the three-dimensional velocity model corresponds to a surface survey control point; Performing interpolation operations based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model to determine each interpolation grid point on the three-dimensional velocity model, and obtaining a three-dimensional velocity interpolation model; Obtaining the construction boundary position information of the target work area, and based on the construction boundary position information, shearing the three-dimensional velocity interpolation model to obtain the near-surface three-dimensional velocity model of the target work area; Slicing the near-surface three-dimensional velocity model according to a pre-set slicing strategy to obtain a near-surface three-dimensional velocity slice model, and based on the near-surface three-dimensional velocity slice model, obtaining the surface velocity information and the deceleration layer thickness change information of the target work area; Optimizing the preliminarily arranged surface survey control points of the target work area based on the obtained surface velocity information and deceleration layer thickness change information.

2. The method for near-surface three-dimensional velocity modeling according to claim 1, wherein The performing interpolation operations based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model to determine each interpolation grid point on the three-dimensional velocity model includes: Determining the position information of the grid point to be interpolated on the three-dimensional velocity model; Respectively calculating the Euclidean distance between the grid point to be interpolated and each grid point within a predetermined range, obtaining the reciprocal of the Euclidean distance, and getting the inverse distance weighted coefficient between the grid point to be interpolated and this grid point; For each grid point within the predetermined range, calculating the product of the velocity data in the surface survey result data of this grid point and the corresponding inverse distance weighted coefficient, and obtaining the sum value of each product; Obtaining the sum value of the inverse distance weighted coefficients of each grid point, calculating the quotient of the sum value of each product and the sum value of the inverse distance weighted coefficients of each grid point, and getting the velocity data of the grid point to be interpolated.

3. The method for near-surface three-dimensional velocity modeling according to claim 1, characterized in that, The generating a three-dimensional velocity model based on the surface survey result data of each surface survey control point includes: Obtaining the position information in each surface survey result data, where the position information includes: surface horizontal position information, surface longitudinal position information, and depth position information; Extracting the surface minimum horizontal position information, surface maximum horizontal position information, surface minimum longitudinal position information, surface maximum longitudinal position information, minimum depth position information, and maximum depth position information from each position information; Based on the surface minimum horizontal position information and surface maximum horizontal position information, determining the horizontal coordinate length of the three-dimensional velocity model, and based on the minimum value of the projections of adjacent surface survey result data on the horizontal coordinate, determining the unit length of the horizontal coordinate of the three-dimensional velocity model; Based on the surface minimum longitudinal position information and surface maximum horizontal position information, determining the longitudinal coordinate length of the three-dimensional velocity model, and based on the minimum value of the projections of adjacent surface survey result data on the longitudinal coordinate, determining the unit length of the longitudinal coordinate of the three-dimensional velocity model; Based on the minimum depth position information and the maximum depth position information, determine the depth coordinate length of the three-dimensional velocity model, and based on the minimum value of the projection of adjacent surface survey result data on the depth coordinate, determine the unit length of the depth coordinate of the three-dimensional velocity model; Based on the position information in the surface survey result data, determine the grid points to which the surface survey result data is mapped to the three-dimensional velocity model, and set the surface survey result data as the attribute data of the determined grid points.

4. The method for near-surface three-dimensional velocity modeling according to claim 1, wherein The interpolation operations include: Kriging interpolation method, moving average method, least squares method, minimum curvature method, natural neighbor interpolation method, nearest neighbor interpolation method, inverse distance weighted interpolation method, discrete smoothing interpolation algorithm, local polynomial method, multiple regression method, linear interpolation triangulation method, improved Shepard method, and radial basis function method.

5. The method for near-surface three-dimensional velocity modeling according to claim 1, characterized in that, The optimization of the preliminarily arranged surface survey control points in the target work area based on the obtained surface velocity information and the change information of the velocity reduction layer thickness includes: Based on the grid points corresponding to the surface survey control points, perform slicing along the depth direction, and sequentially obtain the velocity data corresponding to each depth in the slice; Calculate the velocity difference between the velocity data corresponding to adjacent depth surface survey control points; If the velocity difference exceeds a pre-set velocity threshold, add surface survey control points between the adjacent depth surface survey control points.

6. The method for near-surface three-dimensional velocity modeling according to any one of claims 1 to 5, characterized in that, The method further includes: Based on the surface survey result data of the surface survey control points optimized and deployed in the target work area, correct the near-surface three-dimensional velocity model, so as to perform slice analysis based on the corrected near-surface three-dimensional velocity model.

7. The method for near-surface three-dimensional velocity modeling according to claim 6, characterized in that The correction of the near-surface three-dimensional velocity model based on the surface survey result data of the surface survey control points optimized and deployed in the target work area includes: Query and obtain the grid points corresponding to the optimized and deployed surface survey control points in the near-surface three-dimensional velocity model, and update the velocity data of the grid points to the velocity data of the corresponding surface survey control points; If there are no grid points corresponding to the optimized and deployed surface survey control points in the near-surface three-dimensional velocity model, add grid points corresponding to the surface survey control points in the near-surface three-dimensional velocity model; Based on the velocity data of the updated grid points in the near-surface three-dimensional velocity model, use the interpolation operation to update the velocity data of the interpolation grid points in the near-surface three-dimensional velocity model.

8. An apparatus for near-surface three-dimensional velocity modeling, characterized in that, The device for near-surface three-dimensional velocity modeling includes: A data acquisition module, configured to acquire the surface survey result data of the preliminarily arranged surface survey control points; A grid point mapping module, configured to generate a three-dimensional velocity model based on the surface survey result data of each surface survey control point, and each grid point of the three-dimensional velocity model corresponds to a surface survey control point; An interpolation operation module, configured to perform interpolation operations based on the surface survey result data corresponding to each grid point on the three-dimensional velocity model, determine each interpolation grid point on the three-dimensional velocity model, and obtain a three-dimensional velocity interpolation model; A model construction module, configured to obtain the construction boundary position information of the target work area, and based on the construction boundary position information, shear the three-dimensional velocity interpolation model to obtain the near-surface three-dimensional velocity model of the target work area; A slice analysis module, configured to slice the near-surface three-dimensional velocity model according to a preset slice strategy to obtain a near-surface three-dimensional velocity slice model, and based on the near-surface three-dimensional velocity slice model, obtain the surface velocity information and the deceleration layer thickness change information of the target work area; A point layout optimization module, configured to optimize the initially laid surface survey control points of the target work area based on the obtained surface velocity information and the deceleration layer thickness change information.

9. A storage medium, characterized in that, A program or instruction is stored on a storage medium, and when the program or instruction is run by a processor, the steps of the method for near-surface three-dimensional velocity modeling according to any one of claims 1 to 7 are implemented.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, the steps of the method for near-surface three-dimensional velocity modeling according to any one of claims 1 to 7 are implemented.

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