Method and device for establishing speed model, computer device and storage medium

Abstract

The application discloses a method and device for establishing a velocity model, equipment and a storage medium, and belongs to the technical field of seismic data interpretation. The method comprises the following steps: obtaining a middle-deep layer geological velocity model composed of multiple closed geological blocks based on fault scatter point data and stratum scatter point data of a middle-deep layer of a target work area; determining coordinate values of feature points of the middle-deep layer geological velocity model according to a first preset grid size; obtaining a near-surface geological velocity model of a target local area in the target work area; dividing attribute points of the near-surface geological velocity model into multiple second grid bodies according to a second preset grid size; determining whether the coordinate values of the feature points are located in the coordinate range of any second grid body for any feature point; and determining the velocity values of the feature points. According to the application, the velocity values of the feature points in the near-surface range of the middle-deep layer geological velocity model can be discretized and corrected, and the model precision of the near-surface range of the middle-deep layer geological velocity model is improved.

Description

Technical Field

[0001] This application relates to the field of seismic data interpretation technology, and in particular to a method, apparatus, computer equipment, and storage medium for establishing a velocity model. Background Technology

[0002] Forward illumination technology is an important technique in the field of seismic observation, providing strong technical support for the design and optimization of seismic observation schemes in complex geological areas. Applying forward illumination technology requires the use of a three-dimensional geological model.

[0003] Currently, near-surface modeling software can create high-precision 3D geological velocity models, but it typically only models within the near-surface area (approximately 1000 meters below the surface). Forward illumination modeling using models created with near-surface modeling software cannot assist in seismic observations beyond the near-surface area. Conventional modeling software can create 3D geological velocity models covering a larger area (approximately 10,000 meters below the surface), but the model accuracy is lower. Forward illumination modeling using models created with conventional modeling software cannot guarantee the accuracy of seismic observations within the near-surface area.

[0004] Therefore, there is an urgent need for a modeling method that can simultaneously guarantee the accuracy of both the model extent and the near-surface extent. Summary of the Invention

[0005] This application provides a method, apparatus, computer device, and storage medium for establishing a speed model, which can solve related problems. The technical solution is as follows:

[0006] Firstly, a method for establishing a velocity model is provided, the method comprising:

[0007] Acquire mid-to-deep fault scatter point data and stratigraphic scatter point data of the target work area. The fault scatter point data includes the coordinate values ​​and marker values ​​of multiple fault scatter points, and the stratigraphic scatter point data includes the coordinate values ​​and marker values ​​of multiple stratigraphic scatter points. The marker value of the fault scatter point is the fault number to which the fault scatter point belongs, and the marker value of the stratigraphic scatter point is the stratigraphic number to which the stratigraphic scatter point belongs.

[0008] Based on the scattered fault data and strata data of the target work area in the middle and deep layers, multiple closed geological blocks were obtained;

[0009] Based on geological exploration data, the velocity values ​​of the multiple closed geological blocks are determined to obtain a medium-deep geological velocity model. The geological exploration data includes the coordinates and velocity values ​​of multiple exploration points in the medium-deep layers of the target work area. The velocity values ​​of the multiple closed geological blocks are the propagation velocity values ​​of seismic P-waves or seismic S-waves in the multiple closed geological blocks.

[0010] According to the first preset grid size, the intermediate-deep geological velocity model is divided into multiple first grid bodies, and the vertex of each first grid body is determined as the feature point of the intermediate-deep geological velocity model, and the coordinate values ​​of all feature points of the intermediate-deep geological velocity model are determined.

[0011] Obtain a near-surface geological velocity model of a target local area in the target work area, wherein the near-surface geological velocity model includes the coordinate values ​​and velocity values ​​of multiple attribute points in the target local area; according to a second preset grid size, divide the near-surface geological velocity model into multiple second grids, wherein each second grid includes at least a preset number of attribute points;

[0012] For any feature point, determine whether the coordinate value of the feature point is within the coordinate range of any second grid cell;

[0013] When the coordinate value of the feature point is not within the coordinate range of any second grid cell, the velocity value of the closed geological block where the feature point is located is determined as the velocity value of the feature point;

[0014] When the coordinates of the feature point are within the coordinate range of any second grid cell, if the coordinates of any attribute point are the same as those of the feature point, then the velocity value of the attribute point is determined as the velocity value of the feature point; if the coordinates of each attribute point are different from those of the feature point, then a target second grid cell adjacent to the second grid cell corresponding to the feature point is determined, and in each target second grid cell, the target attribute point closest to the feature point is determined, and the velocity value of the feature point is determined according to the inverse distance weighting method.

[0015] Based on the velocity value of each feature point, a near-surface-to-mid-deep geological fusion velocity model is determined.

[0016] In one possible implementation, before acquiring the mid-to-deep fault scatter plot data and stratigraphic scatter plot data of the target work area, the method further includes:

[0017] Acquire initial fault scatter point data and initial stratum scatter point data of the middle and deep layers of the target work area, wherein the initial fault scatter point data includes the coordinate values ​​and label values ​​of multiple initial fault scatter points, and the initial stratum scatter point data includes the coordinate values ​​and label values ​​of multiple initial stratum scatter points;

[0018] Based on the coordinate values, label values, and distance thresholds of the initial fault scatter data, clustering is performed on the initial fault scatter data with the same label value to obtain multiple initial fault scatter set sets. All initial fault scatter data not in any initial fault scatter set are deleted. In each initial fault scatter set set, the label value of each initial fault scatter point is the same, and in the set to which any initial fault scatter point belongs, there is at least one other initial fault scatter point whose distance to any fault initial scatter point is less than or equal to the distance threshold.

[0019] Based on the coordinate values, label values, and distance thresholds of the initial stratigraphic scatter data, clustering is performed on the initial stratigraphic scatter data with the same label value to obtain multiple initial fault scatter data sets. All initial stratigraphic scatter data that are not in any initial stratigraphic scatter data set are deleted. In each initial stratigraphic scatter data set, the label values ​​of each initial stratigraphic scatter point are the same, and in the set to which any initial stratigraphic scatter point belongs, there is at least one other initial stratigraphic scatter point whose distance to any initial stratigraphic scatter point is less than or equal to the distance threshold.

[0020] The initial fault scatter data that was not deleted was identified as the mid-to-deep fault scatter data of the target work area, and the initial stratigraphic scatter data that was not deleted was identified as the mid-to-deep stratigraphic scatter data of the target work area.

[0021] In one possible implementation, multiple closed geological blocks are obtained based on the mid-to-deep fault scatter data and stratigraphic scatter data of the target work area, including:

[0022] Multiple fault plane triangulation networks are established based on the fault scatter data, and multiple stratigraphic plane triangulation networks are established based on the stratigraphic scatter data. The intersection relationships between the multiple fault plane triangulation networks and the multiple stratigraphic plane triangulation networks are processed to obtain multiple closed geological blocks.

[0023] In one possible implementation, determining the velocity values ​​of the plurality of enclosed geological blocks based on geological exploration data includes:

[0024] For any closed geological block, based on geological exploration data, determine the velocity values ​​of all exploration points within that closed geological block;

[0025] Determine the average velocity value of all the velocity values ​​at the exploration points;

[0026] The average velocity value is determined as the velocity value of any closed geological block.

[0027] In one possible implementation, multiple closed geological blocks are obtained based on the mid-to-deep fault scatter data and stratigraphic scatter data of the target work area, including:

[0028] For any closed geological block, determine the coordinates of the geometric center point of the closed geological block, determine the coordinates of all exploration points in the closed geological block, if the coordinates of any exploration point are the same as the coordinates of the geometric center point of the closed geological block, then determine the velocity value of the exploration point as the velocity value of the closed geological block, if the coordinates of all exploration points are different from the coordinates of the geometric center point of the closed geological block, then determine the average velocity value of all exploration points, and determine the average velocity value as the velocity value of the closed geological block.

[0029] In one possible implementation, the preset number is greater than or equal to 10.

[0030] In one possible implementation, determining the velocity value of the feature point according to the inverse distance weighting method includes:

[0031] Based on the distance between each target attribute point and the feature point, a weight coefficient for each target attribute point is determined, wherein the distance is negatively correlated with the weight coefficient.

[0032] Based on the weight coefficient of each target attribute point, the weighted average of the velocity values ​​of each target attribute point is determined as the velocity value of the feature point.

[0033] Secondly, an apparatus for establishing a velocity model is provided, the apparatus comprising:

[0034] The acquisition module is used to acquire mid-to-deep fault scatter point data and stratigraphic scatter point data of the target work area. The fault scatter point data includes the coordinate values ​​and marker values ​​of multiple fault scatter points, and the stratigraphic scatter point data includes the coordinate values ​​and marker values ​​of multiple stratigraphic scatter points. The marker value of the fault scatter point is the fault number to which the fault scatter point belongs, and the marker value of the stratigraphic scatter point is the stratigraphic number to which the stratigraphic scatter point belongs.

[0035] The calculation module is used to obtain multiple closed geological blocks based on the mid-to-deep fault scatter data and stratigraphic scatter data of the target work area;

[0036] The first determining module is used to determine the velocity values ​​of the multiple closed geological blocks based on geological exploration data to obtain a medium-deep geological velocity model. The geological exploration data includes the coordinates and velocity values ​​of multiple exploration points in the medium-deep layers of the target work area. The velocity values ​​of the multiple closed geological blocks are the propagation velocity values ​​of seismic P-waves or seismic S-waves in the multiple closed geological blocks.

[0037] The first partitioning module is used to divide the intermediate-deep geological velocity model into multiple first grid bodies according to the first preset grid size, determine the vertex of each first grid body as the feature point of the intermediate-deep geological velocity model, and determine the coordinate values ​​of all feature points of the intermediate-deep geological velocity model.

[0038] The second partitioning module is used to obtain a near-surface geological velocity model of a target local area in the target work area, wherein the near-surface geological velocity model includes the coordinate values ​​and velocity values ​​of multiple attribute points in the target local area; and to divide the near-surface geological velocity model into multiple second grids according to a second preset grid size, wherein each second grid includes at least a preset number of attribute points;

[0039] The second determining module is used to determine whether the coordinate value of any feature point is within the coordinate range of any second grid body for any feature point.

[0040] When the coordinate value of the feature point is not within the coordinate range of any second grid cell, the velocity value of the closed geological block where the feature point is located is determined as the velocity value of the feature point;

[0041] When the coordinates of the feature point are within the coordinate range of any second grid cell, if the coordinates of any attribute point are the same as those of the feature point, then the velocity value of the attribute point is determined as the velocity value of the feature point; if the coordinates of each attribute point are different from those of the feature point, then a target second grid cell adjacent to the second grid cell corresponding to the feature point is determined, and in each target second grid cell, the target attribute point closest to the feature point is determined, and the velocity value of the feature point is determined according to the inverse distance weighting method.

[0042] The third determination module is used to determine the near-surface-to-deep geological fusion velocity model based on the velocity value of each feature point.

[0043] In one possible implementation, the acquisition module is further configured to:

[0044] Acquire initial fault scatter point data and initial stratum scatter point data of the middle and deep layers of the target work area, wherein the initial fault scatter point data includes the coordinate values ​​and label values ​​of multiple initial fault scatter points, and the initial stratum scatter point data includes the coordinate values ​​and label values ​​of multiple initial stratum scatter points;

[0045] Based on the coordinate values, label values, and distance thresholds of the initial fault scatter data, clustering is performed on the initial fault scatter data with the same label value to obtain multiple initial fault scatter set sets. All initial fault scatter data not in any initial fault scatter set are deleted. In each initial fault scatter set set, the label value of each initial fault scatter point is the same, and in the set to which any initial fault scatter point belongs, there is at least one other initial fault scatter point whose distance to any fault initial scatter point is less than or equal to the distance threshold.

[0046] Based on the coordinate values, label values, and distance thresholds of the initial stratigraphic scatter data, clustering is performed on the initial stratigraphic scatter data with the same label value to obtain multiple initial fault scatter data sets. All initial stratigraphic scatter data that are not in any initial stratigraphic scatter data set are deleted. In each initial stratigraphic scatter data set, the label values ​​of each initial stratigraphic scatter point are the same, and in the set to which any initial stratigraphic scatter point belongs, there is at least one other initial stratigraphic scatter point whose distance to any initial stratigraphic scatter point is less than or equal to the distance threshold.

[0047] The initial fault scatter data that was not deleted was identified as the mid-to-deep fault scatter data of the target work area, and the initial stratigraphic scatter data that was not deleted was identified as the mid-to-deep stratigraphic scatter data of the target work area.

[0048] In one possible implementation, the computing module is used for:

[0049] Multiple fault plane triangulation networks are established based on the fault scatter data, and multiple stratigraphic plane triangulation networks are established based on the stratigraphic scatter data. The intersection relationships between the multiple fault plane triangulation networks and the multiple stratigraphic plane triangulation networks are processed to obtain multiple closed geological blocks.

[0050] In one possible implementation, the first determining module is configured to:

[0051] For any closed geological block, based on geological exploration data, determine the velocity values ​​of all exploration points within that closed geological block;

[0052] Determine the average velocity value of all the velocity values ​​at the exploration points;

[0053] The average velocity value is determined as the velocity value of any closed geological block.

[0054] In one possible implementation, the first determining module is configured to:

[0055] For any closed geological block, determine the coordinates of the geometric center point of the closed geological block, determine the coordinates of all exploration points in the closed geological block, if the coordinates of any exploration point are the same as the coordinates of the geometric center point of the closed geological block, then determine the velocity value of the exploration point as the velocity value of the closed geological block, if the coordinates of all exploration points are different from the coordinates of the geometric center point of the closed geological block, then determine the average velocity value of all exploration points, and determine the average velocity value as the velocity value of the closed geological block.

[0056] In one possible implementation, the preset number is greater than or equal to 10.

[0057] In one possible implementation, the second determining module is configured to:

[0058] Based on the distance between each target attribute point and the feature point, a weight coefficient for each target attribute point is determined, wherein the distance is negatively correlated with the weight coefficient.

[0059] Based on the weight coefficient of each target attribute point, the weighted average of the velocity values ​​of each target attribute point is determined as the velocity value of the feature point.

[0060] Thirdly, a computer device is provided, the computer device including a processor and a memory, the memory storing at least one instruction, the instruction being loaded and executed by the processor to implement the operation performed by the method of establishing a speed model.

[0061] Fourthly, a computer-readable storage medium is provided, wherein at least one instruction is stored in the storage medium, the instruction being loaded and executed by a processor to implement the operation performed by the method for establishing a speed model.

[0062] Fifthly, a computer program product is provided, the computer program product including at least one instruction, the at least one instruction being loaded and executed by a processor to implement the operations performed by the method for establishing a speed model.

[0063] The beneficial effects of the technical solutions provided in this application are:

[0064] In this embodiment, a medium-deep geological velocity model composed of multiple closed geological blocks is obtained based on scattered fault data, stratigraphic data, and geological exploration data of the target work area. The coordinate values ​​of feature points in the medium-deep geological velocity model are determined according to a first preset grid size. A near-surface geological velocity model of a target local area is obtained, and the attribute points of the near-surface geological velocity model are divided into multiple second grids according to a second preset grid size. For any feature point, the velocity value of that feature point is determined based on the relationship between its coordinate values ​​and the coordinate range of the multiple closed geological blocks. Therefore, the velocity values ​​of each feature point in the near-surface range of the medium-deep geological velocity model can be discretized and corrected based on the velocity values ​​of each attribute point in the near-surface geological velocity model with higher model accuracy, thereby improving the model accuracy of the near-surface range in the medium-deep geological velocity model. Attached Figure Description

[0065] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0066] Figure 1 This is a flowchart of a method for establishing a velocity model provided in an embodiment of this application;

[0067] Figure 2 This is a schematic diagram of scatter plot data of faults and scatter plot data of strata in a target work area provided in an embodiment of this application;

[0068] Figure 3 This is a schematic diagram of a mid-deep fault bedding triangulation and stratigraphic bedding triangulation of a target work area provided in an embodiment of this application;

[0069] Figure 4 This is a schematic diagram of a closed geological block in a target work area, provided in an embodiment of this application;

[0070] Figure 5 This is a schematic diagram of a near-surface geological velocity model divided into multiple second grid cells according to an embodiment of this application;

[0071] Figure 6 This is a schematic diagram of an x-slice image of a medium-deep geological velocity model provided in an embodiment of this application;

[0072] Figure 7 This is a schematic diagram illustrating the principle of determining the velocity value of a feature point using an inverse distance weighting method, as provided in an embodiment of this application.

[0073] Figure 8This is a schematic diagram of the structure of a device for establishing a velocity model provided in an embodiment of this application;

[0074] Figure 9 This is a structural block diagram of a server provided in an embodiment of this application. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0076] This application provides a method for establishing a speed model. This method can be implemented by a computer device, which can be a server or a terminal. The server can be a single server or a server cluster consisting of multiple servers.

[0077] A server may include a processor, memory, communication components, etc., with the processor connected to the memory and communication components respectively.

[0078] The processor can be a CPU (Central Processing Unit). The processor can be used to read instructions and process data, for example, acquiring scattered fault and stratigraphic data of the target work area in the middle and deep layers; obtaining multiple closed geological blocks based on the scattered fault and stratigraphic data of the target work area; determining the velocity values ​​of multiple closed geological blocks based on geological exploration data to obtain a middle-deep geological velocity model; dividing the middle-deep geological velocity model into multiple first grids according to a first preset grid size; acquiring a near-surface geological velocity model of a target local area in the target work area; dividing the near-surface geological velocity model into multiple second grids according to a second preset grid size; determining whether the coordinates of any feature point are within the coordinate range of any second grid, and so on.

[0079] Memory can include ROM (Read-Only Memory), RAM (Random Access Memory), CD-ROM (Compact Disc Read-Only Memory), hard disk, optical data storage devices, etc. Memory can be used for data storage, such as storing the acquired mid-to-deep fault scatter plot data and stratigraphic scatter plot data of the target work area; storing the coordinate and marker values ​​of the fault scatter plot data and stratigraphic scatter plot data; storing data of multiple closed geological blocks; storing data of the first and second grid cells; storing data of feature points and attribute points; storing data of the near-surface-mid-deep geological fusion velocity model, and so on.

[0080] Communication components can be wired network connectors, WiFi (Wireless Fidelity) modules, Bluetooth modules, cellular network communication modules, etc. Communication components can be used to receive and transmit signals.

[0081] Figure 1 This is a flowchart illustrating a method for establishing a velocity model according to an embodiment of this application. See also... Figure 1 This embodiment includes:

[0082] 101. Obtain scattered fault data and stratum data of the medium and deep layers of the target work area.

[0083] 102. Based on the scattered fault data and stratigraphic data of the medium and deep layers of the target work area, multiple closed geological blocks are obtained.

[0084] 103. Based on geological exploration data, a medium-deep geological velocity model is obtained to determine the velocity values ​​assigned to multiple closed geological blocks.

[0085] 104. Based on the first preset grid size, the intermediate-deep geological velocity model is divided into multiple first grid bodies, and the vertices of each first grid body are determined as feature points of the intermediate-deep geological velocity model. The coordinate values ​​of all feature points of the intermediate-deep geological velocity model are then determined.

[0086] 105. Obtain the near-surface geological velocity model of the target local area in the target work area, and divide the near-surface geological velocity model into multiple second grid bodies according to the second preset grid size.

[0087] 106. For any feature point, determine whether the coordinates of the feature point are within the coordinate range of any second grid cell;

[0088] When the coordinates of a feature point are not within the coordinate range of any second grid cell, the velocity value of the closed geological block where the feature point is located is determined as the velocity value of the feature point.

[0089] When the coordinates of a feature point are within the coordinate range of any second grid cell, if the coordinates of any attribute point are the same as those of the feature point, then the velocity value of the attribute point is determined as the velocity value of the feature point; if the coordinates of each attribute point are different from those of the feature point, then the target second grid cell adjacent to the second grid cell corresponding to the feature point is determined, and the target attribute point closest to the feature point is determined in each target second grid cell, and the velocity value of the feature point is determined according to the inverse distance weighting method.

[0090] 107. Based on the velocity value of each feature point, determine the near-surface-to-deep geological fusion velocity model.

[0091] Before executing step 101, it is necessary to first obtain the initial fault scatter data and initial stratigraphic scatter data of the intermediate and deep layers of the target work area, and then process the initial fault scatter data and initial stratigraphic scatter data accordingly to obtain the intermediate and deep fault scatter data and stratigraphic scatter data of the target work area.

[0092] The initial fault scatter plot data and initial stratigraphic scatter plot data are processed accordingly as follows:

[0093] The first step is to obtain initial fault scatter data and initial stratigraphic scatter data for the intermediate and deep layers of the target work area.

[0094] The initial fault scatter data includes the coordinates and labels of multiple initial fault scatter points, and the initial stratigraphic scatter data includes the coordinates and labels of multiple initial stratigraphic scatter points.

[0095] In implementation, the target work area can be determined on the surface first. The scope of the target work area can be set according to actual needs; for example, it can be set as a rectangle of 30,000m × 30,000m. Then, geological exploration blasting is carried out at near-surface locations of multiple exploration wells within the target work area to artificially generate seismic waves. Seismic wave data is then received using detectors on the surface to collect and process the geological exploration blasting data, obtaining initial fault scatter data and initial stratigraphic scatter data for the mid-to-deep layers of the target work area.

[0096] Within the medium-deep range of the target work area, there may be multiple faults and multiple strata. The computer equipment can assign numbers to each fault and each stratum. For example, each fault can be numbered F1, F2, F3, ..., and each stratum can be numbered L1, L2, ... Correspondingly, in the initial fault scatter data and the initial stratum scatter data, the label value of each fault scatter point is the number of the fault to which the fault scatter point belongs, and the label value of each stratum scatter point is the number of the stratum to which the stratum scatter point belongs.

[0097] The second step involves clustering initial fault scatter data based on the coordinates, labels, and distance thresholds of the initial fault scatter data, resulting in multiple initial fault scatter data sets. All initial fault scatter data not found in any of these sets are then deleted.

[0098] The coordinates of the initial fault scatter data are the three-dimensional coordinates of multiple initial fault scatter points underground. The distance threshold is an empirical value that technicians can set according to actual needs.

[0099] In implementation, the distance between any two initial fault scatter points with the same label value can be calculated based on their coordinates and label values. This distance is then compared to a distance threshold. If the distance between any two initial fault scatter points with the same label value is less than or equal to the distance threshold, these two initial fault scatter points are defined as an initial fault scatter point set. This results in multiple initial fault scatter point sets. In each set, the label values ​​of each initial fault scatter point are the same, and within any set of any initial fault scatter point, there is at least one other initial fault scatter point whose distance to any other fault scatter point is less than or equal to the distance threshold. The computer can then delete all initial fault scatter point data that is not in any initial fault scatter point set.

[0100] The third step involves clustering initial stratigraphic scatter data based on the coordinates, labels, and distance thresholds of the initial stratigraphic scatter data, resulting in multiple initial stratigraphic scatter data sets. All initial stratigraphic scatter data not found in any of these sets are then deleted.

[0101] The coordinates of the initial stratum scatter data are the three-dimensional coordinates of multiple initial stratum scatter points underground. The distance threshold is an empirical value that technicians can set according to actual needs.

[0102] In implementation, the distance between any two initial stratigraphic scatter points with the same label value can be calculated based on their coordinates and label values. This distance is then compared to a distance threshold. If the distance between any two initial stratigraphic scatter points with the same label value is less than or equal to the distance threshold, these two initial stratigraphic scatter points are defined as a single initial stratigraphic scatter point set. This results in multiple initial stratigraphic scatter point sets. In each set, the label values ​​of all initial stratigraphic scatter points are the same, and within any set of any initial stratigraphic scatter point, there exists at least one other initial stratigraphic scatter point whose distance to any given initial stratigraphic scatter point is less than or equal to the distance threshold. The computer can then delete all initial stratigraphic scatter point data that is not in any of the initial stratigraphic scatter point sets.

[0103] The second and third steps can be performed simultaneously or sequentially. Furthermore, when the second and third steps are performed sequentially, the execution order of the second and third steps is not limited in this embodiment.

[0104] The fourth step is to identify the undeleted initial fault scatter data as the mid-to-deep fault scatter data of the target work area, and to identify the undeleted initial stratigraphic scatter data as the mid-to-deep stratigraphic scatter data of the target work area.

[0105] After obtaining the fault scatter plot data and stratigraphic scatter plot data for the target work area, the velocity model can be established, and the corresponding processing is as follows:

[0106] Regarding step 101 above: Obtain scattered fault data and stratum data of the target work area in the middle and deep layers.

[0107] Among them, the scatter plot data of faults and scatter plot data of the middle and deep layers of the target work area are as follows: Figure 2 As shown. Fault scatter data includes the coordinates and labels of fault points, and stratigraphic scatter data includes the coordinates and labels of stratigraphic points. The labels indicate that the fault points or stratigraphic points belong to the same fault or the same stratigraphic layer. Both fault scatter data and stratigraphic scatter data can be multidimensional vector data, which includes the three-dimensional coordinates and labels of the corresponding fault points or stratigraphic points.

[0108] Regarding step 102 above: Based on the mid-to-deep fault scatter data and stratigraphic scatter data of the target work area, multiple closed geological blocks are obtained.

[0109] In this context, for each closed geological block, it can be assumed that the materials composing that block are identical. Alternatively, it can be assumed that the propagation speed of seismic P-waves or seismic S-waves is the same within any closed geological block.

[0110] Optionally, multiple fault plane triangular networks can be established based on fault scatter data, and multiple stratigraphic plane triangular networks can be established based on stratigraphic scatter data. The intersection relationships between multiple fault plane triangular networks and multiple stratigraphic plane triangular networks can be processed to obtain multiple closed geological blocks.

[0111] Among them, such as Figure 3 As shown, the fault plane triangulation network is composed of multiple fault plane triangles, and each fault plane triangle is composed of three fault points. The stratigraphic plane triangulation network is composed of multiple stratigraphic plane triangles, and each stratigraphic plane triangle is composed of three stratigraphic points.

[0112] In implementation, for each set of fault points, the computer equipment can ensure that three adjacent fault points form a fault plane triangle. When forming the fault plane triangle, the computer equipment can select three fault points that form an acute triangle as much as possible, so that these three fault points form a fault plane triangle. This ensures that each fault plane triangle in the fault plane triangulation network is not too narrow or elongated.

[0113] Correspondingly, computer equipment can establish stratigraphic triangulation networks. The detailed process of establishing stratigraphic triangulation networks is the same as that of establishing fault triangulation networks, and will not be repeated here.

[0114] After establishing the fault bedding triangulation network and the stratigraphic bedding triangulation network, the intersection relationships between multiple fault bedding triangulation networks and multiple stratigraphic bedding triangulation networks can be processed to obtain multiple closed geological blocks. The process can be as follows:

[0115] First, determine whether the triangular network of the fault plane and the triangular network of the stratigraphic plane intersect.

[0116] If the fault plane triangulation network and the stratigraphic plane triangulation network intersect, the fault plane triangulation network is identified as the main body, and the complete fault plane triangulation network is retained. Then, for each stratigraphic plane triangulation network that intersects with the fault plane triangulation network, the smaller area can be determined as the first part of the stratigraphic plane triangulation network based on the intersection line of the fault plane triangulation network and the stratigraphic plane triangulation network. This first part can then be deleted.

[0117] If the fault plane triangulation network and the stratigraphic plane triangulation network do not intersect, but only intersect at different fault plane triangulation networks, then the fault plane triangulation network with the larger area is identified as the main body, and the complete larger fault plane triangulation network is retained. Then, for each pair of intersecting fault plane triangulation networks, based on the intersection line of each pair of fault plane triangulation networks, the smaller area within the smaller fault plane triangulation network is identified as the second part of the fault plane triangulation network. This second part can then be deleted.

[0118] If the fault plane triangulation network and the stratigraphic plane triangulation network do not intersect, but only intersect different stratigraphic plane triangulation networks, the corresponding processing of the intersection relationship between multiple stratigraphic plane triangulation networks is the same as the processing of the intersection relationship between multiple fault plane triangulation networks described above, and will not be repeated here.

[0119] Thus, as Figure 4 As shown, after processing the intersection relationships between multiple fault plane triangular networks and multiple stratigraphic plane triangular networks, multiple closed geological blocks can be obtained between the fault plane triangular network, the stratigraphic plane triangular network, and the mid-deep boundary of the target work area.

[0120] Regarding step 103 above: Based on geological exploration data, in order to determine the velocity values ​​assigned to multiple closed geological blocks, a medium-deep geological velocity model is obtained.

[0121] Among them, geological exploration data can be historical data obtained from blasting during geological exploration to artificially generate seismic waves. Geological exploration data includes the coordinates and velocity values ​​of multiple exploration points in the middle and deep layers of the target work area, and the velocity values ​​of multiple closed geological blocks are the propagation velocity values ​​of seismic P-waves or seismic S-waves in the aforementioned closed geological blocks.

[0122] Optionally, in implementation, for any closed geological block, the velocity values ​​of all exploration points within the closed geological block can be determined based on geological exploration data. Then, the average velocity value of all exploration points within the closed geological block can be determined. Finally, the aforementioned average velocity value is determined as the velocity value of the closed geological block.

[0123] Optionally, in implementation, for any closed geological block, the coordinates of its geometric center point can be determined first. Then, the coordinates of all exploration points within the closed geological block can be determined. If any exploration point in the closed geological block has the same coordinates as its geometric center point, this exploration point can be designated as the center exploration point of the closed geological block. The velocity value of this center exploration point is then determined as the velocity value of the closed geological block. If the coordinates of all exploration points in the closed geological block are not the same as those of its geometric center point, the velocity values ​​of all exploration points in the closed geological block can be determined based on geological exploration data. The average velocity value of all exploration points in the closed geological block can then be determined. Finally, this average velocity value is determined as the velocity value of the closed geological block.

[0124] Thus, for each closed geological block, a velocity value can be determined within the scope of the closed geological block, that is, it is assumed that the propagation velocity of seismic P-waves or seismic S-waves is the same in any specific closed geological block.

[0125] Regarding step 104 above: Based on the first preset grid size, the intermediate-deep geological velocity model is divided into multiple first grid bodies, and the vertices of each first grid body are determined as feature points of the intermediate-deep geological velocity model, and the coordinate values ​​of all feature points of the intermediate-deep geological velocity model are determined.

[0126] The first preset grid size is an empirical size that technicians can set according to actual needs, such as setting it to 10m or 20m. The coordinate value of the feature point is a three-dimensional coordinate value.

[0127] In implementation, assuming the target work area is a 30,000m × 30,000m square region and the intermediate-deep layer extends to 10,000m, the intermediate-deep geological velocity model is a 30,000m × 30,000m × 10,000m cube model. If the first preset grid size is set to 10m, 3,000 × 3,000 × 1,000 first grid cells can be obtained in three-dimensional coordinates. Determining the same vertex of each first grid cell as a feature point results in 3,000 × 3,000 × 1,000 feature points in three-dimensional coordinates. The coordinates of each feature point in the intermediate-deep geological velocity model are three-dimensional coordinates (X0, Y0, Z0).

[0128] Regarding step 105 above: Obtain the near-surface geological velocity model of the target local area in the target work area, and divide the near-surface geological velocity model into multiple second grid bodies according to the second preset grid size.

[0129] The near-surface geological velocity model includes the coordinates and velocity values ​​of multiple attribute points in the target local area. Each second grid cell includes at least a preset number of attribute points. The preset second grid size is an empirical size, which can be set by technicians according to actual needs, such as setting the preset second grid size to 20m. The preset second grid size is a two-dimensional size.

[0130] In implementation, the near-surface geological velocity model contains multiple attribute points, which are divided into multiple second grid cells. When the preset size of the second grid is 20m and the preset number is 10, the computer equipment divides the near-surface geological velocity model into multiple second grid cells. Each second grid cell has a length and width of 20m and a depth equal to the depth of the corresponding area in the near-surface geological velocity model. Then, the number of attribute points in each second grid cell is calculated. If the number of attribute points in a certain second grid cell is less than 10, while the number of attribute points in the surrounding second grid cells is greater than 10, the computer equipment can expand the size of this second grid cell, increasing the number of attribute points in it, so that each second grid cell contains at least the preset number of attribute points. If, in many adjacent second grid cells, the number of attribute points in each second grid cell is less than 10, the computer equipment can adjust the preset size of the second grid cell, expanding it to ensure that each second grid cell contains at least 10 attribute points. Figure 5 As shown, the No. 1 second grid cell contains 10 attribute points, and the other second grid cells also contain at least 10 attribute points.

[0131] Regarding the preset number setting, a smaller preset number results in fewer attribute points in each second grid cell, leading to higher accuracy in the subsequent near-surface-mid-deep geological fusion velocity model. However, this also increases the computational burden on the computer equipment. Therefore, the preset number can be set according to actual needs to balance model accuracy and the computational burden on the computer equipment.

[0132] Optionally, the preset number can be greater than or equal to 10. Setting the preset number to greater than or equal to 10 ensures that the subsequent near-surface-to-deep geological fusion velocity model has high accuracy, while also reducing the computational burden on the computer, thus achieving a good balance between model accuracy and the computational burden on the computer.

[0133] Regarding step 106 above: For any feature point, determine whether the coordinate value of the feature point is within the coordinate range of any second grid cell; when the coordinate value of the feature point is not within the coordinate range of any second grid cell, determine the velocity value of the closed geological block where the feature point is located as the velocity value of the feature point; when the coordinate value of the feature point is within the coordinate range of any second grid cell, if there is any attribute point with the same coordinate value as the feature point, then determine the velocity value of the attribute point as the velocity value of the feature point; if the coordinate values ​​of each attribute point are different from the coordinate values ​​of the feature point, then determine the target second grid cell adjacent to the second grid cell corresponding to the feature point, determine the target attribute point closest to the feature point in each target second grid cell, and determine the velocity value of the feature point according to the inverse distance weighting method.

[0134] The coordinate range of the second grid cell is a three-dimensional coordinate range. The target second grid cell is the second grid cell adjacent to the second grid cell corresponding to the feature point; each feature point corresponds to at least 3 and at most 8 target second grid cells. The formula for the inverse distance weighted method can be:

[0135]

[0136] Among them, V i D is the velocity value of the attribute point closest to the current feature point in the second mesh volume for each target. i The distance between the attribute point closest to the current feature point in the second grid volume for each target and the current feature point.

[0137] In implementation, the coordinate range of each second grid cell can be determined first. Then, as follows: Figure 6 As shown, the mid-deep geological velocity model can be sliced ​​along the x-axis at intervals of a first preset grid size, resulting in multiple model x-slice images composed of feature points with the same X0 coordinate value. Then, it can be sequentially determined whether each feature point in the slice image lies within the coordinate range of any second grid cell; for different results, the processing can be as follows:

[0138] (1) When the coordinates of a feature point are not within the coordinate range of any second grid cell, the velocity value of the closed geological block where the feature point is located is determined as the velocity value of the feature point. For example, if the range (in meters) of the near-surface model is (0-20000, 0-18000, 0-1000), and the feature point has coordinates of (15000, 2000, 7500), this feature point is not within the range of the near-surface model, and therefore not within the coordinate range of any second grid cell. In this case, the velocity value of the closed geological block where the feature point is located is determined as the velocity value of the feature point. For example, in step 103, if the velocity value of the closed geological block is determined to be 5100 m / s, then the velocity value of the feature point is 5100 m / s.

[0139] (2) When the coordinate value of the feature point is within the coordinate range of any second grid body, if there is any attribute point whose coordinate value is the same as the coordinate value of the feature point, then the velocity value of the attribute point is determined as the velocity value of the feature point.

[0140] (3) When the coordinates of a feature point are within the coordinate range of any second grid cell, if the coordinates of each attribute point are not the same as the coordinates of the feature point, then determine the target second grid cell adjacent to the second grid cell corresponding to the feature point. In each target second grid cell, determine the target attribute point closest to the feature point, and determine the velocity value of the feature point according to the inverse distance weighting method. For example, ... Figure 7 As shown, point A is a feature point located in the first grid cell of the mid-deep geological velocity model of the target area, adjacent to the boundary of the target area. Feature point A corresponds to five target second grid cells, each containing a target attribute point closest to feature point A. Points B, C, D, E, and F are target attribute points with velocity values ​​of 3400 m / s, 3300 m / s, 2700 m / s, 3000 m / s, and 2200 m / s, respectively. The distances between target attribute points B, C, D, and F and feature point A are 10 m, 20 m, 25 m, 30 m, and 40 m, respectively. Substituting these data into the formula, the velocity value of feature point A is calculated to be 3238 m / s. The velocity values ​​of the remaining feature points in this x-slice image are then determined using the same steps. Finally, the above operations are repeated for the remaining x-slices.

[0141] Optionally, after determining the coordinate range of each second grid cell, the intermediate-deep geological velocity model can be sliced ​​along the y-axis using the first preset grid size as the nucleus, resulting in multiple model y-slice images composed of feature points with the same Y0 coordinate value. The process of determining the velocity values ​​of feature points based on the y-slice images is the same as the process of determining the velocity values ​​of feature points based on the x-slice images described above, and will not be repeated here.

[0142] Optionally, when the coordinate values ​​of a feature point are within the coordinate range of any second grid body, if the coordinate values ​​of each attribute point are not the same as the coordinate values ​​of the feature point, it can be determined whether there is an attribute point whose distance to the current feature point is less than or equal to a second distance threshold. If there is an attribute point whose distance to the current feature point is less than or equal to the second distance threshold, the velocity value of that attribute point can be determined as the velocity value of the current feature point.

[0143] The second distance threshold is a small distance value, such as 0.1m.

[0144] Optionally, the process of determining the velocity values ​​of feature points using the inverse distance weighting method can be as follows:

[0145] Based on the distance between each target attribute point and the feature point, a weight coefficient is determined for each target attribute point. Then, based on the weight coefficients of each target attribute point, a weighted average of the velocity values ​​of each target attribute point is determined, which is used as the velocity value of the feature point.

[0146] The distance between each target attribute point and a feature point is negatively correlated with the weight coefficient of each target attribute point. The formula for determining the weight coefficient of each target attribute point can be:

[0147]

[0148] Among them, D i The distance between the attribute point closest to the current feature point in the second grid volume for each target and the current feature point is a positive number.

[0149] Regarding step 107 above: Based on the velocity value of each feature point, determine the near-surface-to-deep geological fusion velocity model.

[0150] After completing step 107, the obtained near-surface-intermediate-deep geological fusion velocity model can be applied to forward modeling illumination technology, providing strong technical support for the design and optimization of seismic observation schemes in complex work areas.

[0151] In practice, when applying forward modeling illumination technology, if forward modeling illumination is required for seismic P-waves, the above-mentioned velocity values ​​are the velocity values ​​of the seismic P-waves; if forward modeling illumination is required for seismic S-waves, the above-mentioned velocity values ​​are the velocity values ​​of the seismic S-waves.

[0152] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0153] In this embodiment, a medium-deep geological velocity model composed of multiple closed geological blocks is obtained based on scattered fault data, stratigraphic data, and geological exploration data of the target work area. The coordinate values ​​of feature points in the medium-deep geological velocity model are determined according to a first preset grid size. A near-surface geological velocity model of a target local area is obtained, and the attribute points of the near-surface geological velocity model are divided into multiple second grids according to a second preset grid size. For any feature point, its velocity value is determined based on the relationship between its coordinate values ​​and the coordinate range of the multiple closed geological blocks. Therefore, the velocity values ​​of each feature point in the near-surface range of the medium-deep geological velocity model can be discretized and corrected based on the velocity values ​​of each attribute point in the near-surface geological velocity model with higher model accuracy, thereby improving the model accuracy of the near-surface range in the medium-deep geological velocity model.

[0154] This application provides an apparatus for establishing a velocity model. This apparatus can be the computer device described in the above embodiments, such as... Figure 8 As shown, the device includes:

[0155] The acquisition module 810 is used to acquire mid-to-deep fault scatter point data and stratigraphic scatter point data of the target work area. The fault scatter point data includes the coordinate values ​​and marker values ​​of multiple fault scatter points, and the stratigraphic scatter point data includes the coordinate values ​​and marker values ​​of multiple stratigraphic scatter points. The marker value of the fault scatter point is the fault number to which the fault scatter point belongs, and the marker value of the stratigraphic scatter point is the stratigraphic number to which the stratigraphic scatter point belongs.

[0156] Calculation module 820 is used to obtain multiple closed geological blocks based on the mid-to-deep fault scatter data and stratigraphic scatter data of the target work area;

[0157] The first determining module 830 is used to determine the velocity values ​​of the multiple closed geological blocks based on geological exploration data to obtain a medium-deep geological velocity model. The geological exploration data includes the coordinate values ​​and velocity values ​​of multiple exploration points in the medium-deep layers of the target work area. The velocity values ​​of the multiple closed geological blocks are the propagation velocity values ​​of seismic P-waves or seismic S-waves in the multiple closed geological blocks.

[0158] The first partitioning module 840 is used to divide the intermediate-deep geological velocity model into multiple first grid bodies according to the first preset grid size, determine the vertex of each first grid body as the feature point of the intermediate-deep geological velocity model, and determine the coordinate values ​​of all feature points of the intermediate-deep geological velocity model.

[0159] The second partitioning module 850 is used to obtain a near-surface geological velocity model of a target local area in the target work area, wherein the near-surface geological velocity model includes the coordinate values ​​and velocity values ​​of multiple attribute points in the target local area; and to divide the near-surface geological velocity model into multiple second grids according to a second preset grid size, wherein each second grid includes at least a preset number of attribute points;

[0160] The second determining module 860 is used to determine whether the coordinate value of any feature point is within the coordinate range of any second grid body for any feature point;

[0161] When the coordinate value of the feature point is not within the coordinate range of any second grid cell, the velocity value of the closed geological block where the feature point is located is determined as the velocity value of the feature point;

[0162] When the coordinates of the feature point are within the coordinate range of any second grid cell, if the coordinates of any attribute point are the same as those of the feature point, then the velocity value of the attribute point is determined as the velocity value of the feature point; if the coordinates of each attribute point are different from those of the feature point, then a target second grid cell adjacent to the second grid cell corresponding to the feature point is determined, and in each target second grid cell, the target attribute point closest to the feature point is determined, and the velocity value of the feature point is determined according to the inverse distance weighting method.

[0163] The third determination module 870 is used to determine the near-surface-to-deep geological fusion velocity model based on the velocity value of each feature point.

[0164] In one possible implementation, the acquisition module 810 is further configured to:

[0165] Acquire initial fault scatter point data and initial stratum scatter point data of the middle and deep layers of the target work area, wherein the initial fault scatter point data includes the coordinate values ​​and label values ​​of multiple initial fault scatter points, and the initial stratum scatter point data includes the coordinate values ​​and label values ​​of multiple initial stratum scatter points;

[0166] Based on the coordinate values, label values, and distance thresholds of the initial fault scatter data, clustering is performed on the initial fault scatter data with the same label value to obtain multiple initial fault scatter set sets. All initial fault scatter data not in any initial fault scatter set are deleted. In each initial fault scatter set set, the label value of each initial fault scatter point is the same, and in the set to which any initial fault scatter point belongs, there is at least one other initial fault scatter point whose distance to any fault initial scatter point is less than or equal to the distance threshold.

[0167] Based on the coordinate values, label values, and distance thresholds of the initial stratigraphic scatter data, clustering is performed on the initial stratigraphic scatter data with the same label value to obtain multiple initial fault scatter data sets. All initial stratigraphic scatter data that are not in any initial stratigraphic scatter data set are deleted. In each initial stratigraphic scatter data set, the label values ​​of each initial stratigraphic scatter point are the same, and in the set to which any initial stratigraphic scatter point belongs, there is at least one other initial stratigraphic scatter point whose distance to any initial stratigraphic scatter point is less than or equal to the distance threshold.

[0168] The initial fault scatter data that was not deleted was identified as the mid-to-deep fault scatter data of the target work area, and the initial stratigraphic scatter data that was not deleted was identified as the mid-to-deep stratigraphic scatter data of the target work area.

[0169] In one possible implementation, the computing module 820 is used for:

[0170] Multiple fault plane triangulation networks are established based on the fault scatter data, and multiple stratigraphic plane triangulation networks are established based on the stratigraphic scatter data. The intersection relationships between the multiple fault plane triangulation networks and the multiple stratigraphic plane triangulation networks are processed to obtain multiple closed geological blocks.

[0171] In one possible implementation, the first determining module 830 is configured to:

[0172] For any closed geological block, based on geological exploration data, determine the velocity values ​​of all exploration points within that closed geological block;

[0173] Determine the average velocity value of all the velocity values ​​at the exploration points;

[0174] The average velocity value is determined as the velocity value of any closed geological block.

[0175] In one possible implementation, the first determining module 830 is configured to:

[0176] For any closed geological block, determine the coordinates of the geometric center point of the closed geological block, determine the coordinates of all exploration points in the closed geological block, if the coordinates of any exploration point are the same as the coordinates of the geometric center point of the closed geological block, then determine the velocity value of the exploration point as the velocity value of the closed geological block, if the coordinates of all exploration points are different from the coordinates of the geometric center point of the closed geological block, then determine the average velocity value of all exploration points, and determine the average velocity value as the velocity value of the closed geological block.

[0177] In one possible implementation, the preset number is greater than or equal to 10.

[0178] In one possible implementation, the second determining module 860 is configured to:

[0179] Based on the distance between each target attribute point and the feature point, a weight coefficient for each target attribute point is determined, wherein the distance is negatively correlated with the weight coefficient.

[0180] Based on the weight coefficient of each target attribute point, the weighted average of the velocity values ​​of each target attribute point is determined as the velocity value of the feature point.

[0181] It should be noted that the apparatus for establishing a speed model provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the apparatus can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus for establishing a speed model and the method embodiment for establishing a speed model provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiment, which will not be repeated here.

[0182] Figure 9 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. The computer device can be a server or a terminal. The computer device 900 can vary significantly due to differences in configuration or performance, and may include one or more processors 901 and one or more memories 902. The memories 902 store at least one instruction, which is loaded and executed by the processors 901 to implement the methods provided in the above-described method embodiments. Of course, the server may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The server may also include other components for implementing device functions, which will not be elaborated upon here.

[0183] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including instructions that can be executed by a processor in a terminal to complete the method for establishing a speed model in the above embodiments. This computer-readable storage medium may be non-transitory. For example, the computer-readable storage medium may be ROM (read-only memory), RAM (random access memory), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0184] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0185] It should be noted that the information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals (including but not limited to signals transmitted between user terminals and other devices) involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0186] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for establishing a velocity model, characterized in that, The method includes: Acquire mid-to-deep fault scatter point data and stratigraphic scatter point data of the target work area. The fault scatter point data includes the coordinate values ​​and marker values ​​of multiple fault scatter points, and the stratigraphic scatter point data includes the coordinate values ​​and marker values ​​of multiple stratigraphic scatter points. The marker value of the fault scatter point is the fault number to which the fault scatter point belongs, and the marker value of the stratigraphic scatter point is the stratigraphic number to which the stratigraphic scatter point belongs. Based on the scattered fault data and strata data of the target work area in the middle and deep layers, multiple closed geological blocks were obtained; Based on geological exploration data, the velocity values ​​of the multiple closed geological blocks are determined to obtain a medium-deep geological velocity model. The geological exploration data includes the coordinates and velocity values ​​of multiple exploration points in the medium-deep layers of the target work area. The velocity values ​​of the multiple closed geological blocks are the propagation velocity values ​​of seismic P-waves or seismic S-waves in the multiple closed geological blocks. According to the first preset grid size, the intermediate-deep geological velocity model is divided into multiple first grid bodies, and the vertex of each first grid body is determined as the feature point of the intermediate-deep geological velocity model, and the coordinate values ​​of all feature points of the intermediate-deep geological velocity model are determined. Obtain a near-surface geological velocity model of a target local area in the target work area, wherein the near-surface geological velocity model includes the coordinate values ​​and velocity values ​​of multiple attribute points in the target local area; according to a second preset grid size, divide the near-surface geological velocity model into multiple second grids, wherein each second grid includes at least a preset number of attribute points; For any feature point, determine whether the coordinate value of the feature point is within the coordinate range of any second grid cell; When the coordinate value of the feature point is not within the coordinate range of any second grid cell, the velocity value of the closed geological block where the feature point is located is determined as the velocity value of the feature point; When the coordinates of the feature point are within the coordinate range of any second grid cell, if the coordinates of any attribute point are the same as those of the feature point, then the velocity value of the attribute point is determined as the velocity value of the feature point; if the coordinates of each attribute point are different from those of the feature point, then a target second grid cell adjacent to the second grid cell corresponding to the feature point is determined, and in each target second grid cell, the target attribute point closest to the feature point is determined, and the velocity value of the feature point is determined according to the inverse distance weighting method. Based on the velocity value of each feature point, a near-surface-to-mid-deep geological fusion velocity model is determined.

2. The method according to claim 1, characterized in that, Before acquiring the mid-to-deep fault scatter plot data and stratigraphic scatter plot data of the target work area, the following steps are also included: Acquire initial fault scatter point data and initial stratum scatter point data of the middle and deep layers of the target work area, wherein the initial fault scatter point data includes the coordinate values ​​and label values ​​of multiple initial fault scatter points, and the initial stratum scatter point data includes the coordinate values ​​and label values ​​of multiple initial stratum scatter points; Based on the coordinate values, label values, and distance thresholds of the initial fault scatter data, clustering is performed on the initial fault scatter data with the same label value to obtain multiple initial fault scatter set sets. All initial fault scatter data not in any initial fault scatter set are deleted. In each initial fault scatter set set, the label value of each initial fault scatter point is the same, and in the set to which any initial fault scatter point belongs, there is at least one other initial fault scatter point whose distance to any fault initial scatter point is less than or equal to the distance threshold. Based on the coordinate values, label values, and distance thresholds of the initial stratigraphic scatter data, clustering is performed on the initial stratigraphic scatter data with the same label value to obtain multiple initial stratigraphic scatter data sets. All initial stratigraphic scatter data not in any initial stratigraphic scatter data set are deleted. In each initial stratigraphic scatter data set, the label value of each initial stratigraphic scatter point is the same, and in the set to which any initial stratigraphic scatter point belongs, there is at least one other initial stratigraphic scatter point whose distance to any initial stratigraphic scatter point is less than or equal to the distance threshold. The initial fault scatter data that was not deleted was identified as the mid-to-deep fault scatter data of the target work area, and the initial stratigraphic scatter data that was not deleted was identified as the mid-to-deep stratigraphic scatter data of the target work area.

3. The method according to claim 1, characterized in that, Based on the mid-to-deep fault scatter plot data and stratigraphic scatter plot data of the target work area, multiple closed geological blocks are obtained, including: Multiple fault plane triangulation networks are established based on the fault scatter data, and multiple stratigraphic plane triangulation networks are established based on the stratigraphic scatter data. The intersection relationships between the multiple fault plane triangulation networks and the multiple stratigraphic plane triangulation networks are processed to obtain multiple closed geological blocks.

4. The method according to claim 1, characterized in that, The determination of velocity values ​​for the multiple closed geological blocks based on geological exploration data includes: For any closed geological block, based on geological exploration data, determine the velocity values ​​of all exploration points within that closed geological block; Determine the average velocity value of all the velocity values ​​at the exploration points; The average velocity value is determined as the velocity value of any closed geological block.

5. The method according to claim 1, characterized in that, The determination of velocity values ​​for the multiple closed geological blocks based on geological exploration data includes: For any closed geological block, determine the coordinates of the geometric center point of the closed geological block, determine the coordinates of all exploration points in the closed geological block, if the coordinates of any exploration point are the same as the coordinates of the geometric center point of the closed geological block, then determine the velocity value of the exploration point as the velocity value of the closed geological block, if the coordinates of all exploration points are different from the coordinates of the geometric center point of the closed geological block, then determine the average velocity value of all exploration points, and determine the average velocity value as the velocity value of the closed geological block.

6. The method according to claim 1, characterized in that, The preset number is greater than or equal to 10.

7. The method according to claim 1, characterized in that, The step of determining the velocity value of the feature point according to the inverse distance weighting method includes: Based on the distance between each target attribute point and the feature point, a weight coefficient for each target attribute point is determined, wherein the distance is negatively correlated with the weight coefficient. Based on the weight coefficient of each target attribute point, the weighted average of the velocity values ​​of each target attribute point is determined as the velocity value of the feature point.

8. An apparatus for establishing a velocity model, characterized in that, The device includes: The acquisition module is used to acquire mid-to-deep fault scatter point data and stratigraphic scatter point data of the target work area. The fault scatter point data includes the coordinate values ​​and marker values ​​of multiple fault scatter points, and the stratigraphic scatter point data includes the coordinate values ​​and marker values ​​of multiple stratigraphic scatter points. The marker value of the fault scatter point is the fault number to which the fault scatter point belongs, and the marker value of the stratigraphic scatter point is the stratigraphic number to which the stratigraphic scatter point belongs. The calculation module is used to obtain multiple closed geological blocks based on the mid-to-deep fault scatter data and stratigraphic scatter data of the target work area; The first determining module is used to determine the velocity values ​​of the multiple closed geological blocks based on geological exploration data to obtain a medium-deep geological velocity model. The geological exploration data includes the coordinates and velocity values ​​of multiple exploration points in the medium-deep layers of the target work area. The velocity values ​​of the multiple closed geological blocks are the propagation velocity values ​​of seismic P-waves or seismic S-waves in the multiple closed geological blocks. The first partitioning module is used to divide the intermediate-deep geological velocity model into multiple first grid bodies according to the first preset grid size, determine the vertex of each first grid body as the feature point of the intermediate-deep geological velocity model, and determine the coordinate values ​​of all feature points of the intermediate-deep geological velocity model. The second partitioning module is used to obtain a near-surface geological velocity model of a target local area in the target work area, wherein the near-surface geological velocity model includes the coordinate values ​​and velocity values ​​of multiple attribute points in the target local area; and to divide the near-surface geological velocity model into multiple second grids according to a second preset grid size, wherein each second grid includes at least a preset number of attribute points; The second determining module is used to determine whether the coordinate value of any feature point is within the coordinate range of any second grid body for any feature point. When the coordinate value of the feature point is not within the coordinate range of any second grid cell, the velocity value of the closed geological block where the feature point is located is determined as the velocity value of the feature point; When the coordinates of the feature point are within the coordinate range of any second grid cell, if the coordinates of any attribute point are the same as those of the feature point, then the velocity value of the attribute point is determined as the velocity value of the feature point; if the coordinates of each attribute point are different from those of the feature point, then a target second grid cell adjacent to the second grid cell corresponding to the feature point is determined, and in each target second grid cell, the target attribute point closest to the feature point is determined, and the velocity value of the feature point is determined according to the inverse distance weighting method. The third determination module is used to determine the near-surface-to-deep geological fusion velocity model based on the velocity value of each feature point.

9. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one instruction, which is loaded and executed by the processor to perform the operations performed by the method for establishing a speed model as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, which is loaded and executed by a processor to perform the operations performed by the method for establishing a speed model as described in any one of claims 1 to 7.

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