Seismic data processing method, device, equipment and storage medium

Abstract

The application discloses a seismic data processing method, device and equipment and a storage medium, and belongs to the technical field of seismic exploration. The method first determines an initial shear wave velocity model based on seismic data of a target work area, then determines an observed travel time of a single-frequency surface wave component based on the seismic data, determines a theoretical travel time of the single-frequency surface wave component based on the initial shear wave velocity model, constructs an objective function by using the observed travel time and the theoretical travel time, iteratively updates the initial shear wave velocity model based on the objective function, and continuously approaches a real shear wave velocity structure, so that a target shear wave velocity model is finally obtained.

Description

Technical Field

[0001] This application relates to the field of seismic exploration technology, and in particular to a seismic data processing method, apparatus, equipment, and storage medium. Background Technology

[0002] Compared to natural earthquakes, seismic exploration is a medium-scale detection technique, typically covering depths of less than 10 kilometers. When seismic waves are generated at the Earth's surface, surface waves are formed that propagate along the near-surface strata. Surface waves exhibit dispersion during propagation, meaning that different frequency surface wave components propagate at different speeds. The dispersion characteristics of surface waves are closely related to the thickness of the near-surface strata and the shear wave velocity structure.

[0003] Near-surface strata are typically thin layers composed of low-velocity, uncompacted material. In most cases, near-surface strata can be assumed to be a geological structure where velocity increases with depth. The shear wave velocity model of near-surface strata significantly impacts the imaging quality of seismic data. Therefore, the influence of near-surface shear wave velocity must be removed before imaging seismic data. Determining how to obtain a near-surface shear wave velocity model has become a pressing issue. Summary of the Invention

[0004] This application provides a seismic data processing method, apparatus, device, and storage medium that can continuously approximate the actual shear wave velocity structure through iterative updates. The technical solution is as follows:

[0005] On the one hand, a seismic data processing method is provided, the method comprising:

[0006] The target work area is divided into a grid to obtain a first grid and a second grid; wherein the second grid is obtained by thinning the first grid.

[0007] First seismic data of the target work area is acquired. Based on the first seismic data, an initial shear wave velocity model of the target work area is determined. The initial shear wave velocity model is used to represent the initial shear wave velocity distribution at each depth at each node in the second grid.

[0008] Based on the first seismic data, the observation travel time of each single-frequency surface wave component in each shot-receiver pair is determined;

[0009] Based on the initial shear wave velocity model, the first grid, and the second grid, the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair is determined;

[0010] Based on the observed travel time, theoretical travel time, and shear wave velocity variation of each single-frequency surface wave component in each shot-receiver pair, an objective function is constructed. The objective function is used to represent the relationship between travel time error and shear wave velocity variation. The travel time error is the difference between the observed travel time and the theoretical travel time.

[0011] Based on the objective function, the initial shear wave velocity model is iteratively updated until the travel time error meets the preset condition, thus obtaining the target shear wave velocity model.

[0012] On the other hand, a seismic data processing apparatus is provided, the apparatus comprising:

[0013] The grid division module is used to divide the target work area into a first grid and a second grid; wherein the second grid is obtained by thinning the first grid.

[0014] The first determining module is used to acquire the first seismic data of the target work area, and based on the first seismic data, determine the initial shear wave velocity model of the target work area. The initial shear wave velocity model is used to represent the initial shear wave velocity distribution at each depth at each node in the second grid.

[0015] The second determining module is used to determine the observation travel time of each single-frequency surface wave component in each shot-receiver pair based on the first seismic data.

[0016] The third determining module is used to determine the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair based on the initial shear wave velocity model, the first grid, and the second grid.

[0017] The construction module is used to construct an objective function based on the observed travel time, theoretical travel time, and shear wave velocity variation of each single-frequency surface wave component in each shot-receiver pair. The objective function is used to represent the relationship between travel time error and shear wave velocity variation, where the travel time error is the difference between the observed travel time and the theoretical travel time.

[0018] The update module is used to iteratively update the initial shear wave velocity model based on the objective function until the travel time error meets the preset condition, thereby obtaining the target shear wave velocity model.

[0019] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one piece of program code, which is loaded and executed by the processor to implement the seismic data processing method described in any of the preceding claims.

[0020] On the other hand, a computer-readable storage medium is provided, wherein at least one piece of program code is stored in the computer-readable storage medium, the at least one piece of program code being loaded and executed by a processor to implement the seismic data processing method described in any of the preceding claims.

[0021] On the other hand, a computer program product is provided, wherein at least one piece of program code is stored in the computer program product, the at least one piece of program code being loaded and executed by a processor to implement the seismic data processing method described in any of the preceding claims.

[0022] This application provides a seismic data processing method. The method first determines an initial shear wave velocity model based on seismic data of the target work area, then determines the observation travel time of a single-frequency surface wave component based on the seismic data, and determines the theoretical travel time of the single-frequency surface wave component based on the initial shear wave velocity model. An objective function is constructed by using the observation travel time and the theoretical travel time, and the initial shear wave velocity model is iteratively updated based on the objective function to continuously approximate the real shear wave velocity structure, and finally obtain the target shear wave velocity model.

[0023] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this disclosure. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the implementation environment of a seismic data processing method provided in an embodiment of this application;

[0025] Figure 2 This is a flowchart of a seismic data processing method provided in an embodiment of this application;

[0026] Figure 3 This is a schematic diagram illustrating the distribution range of gun and receiver points provided in an embodiment of this application;

[0027] Figure 4 (a) is a schematic diagram of a three-dimensional seismic observation system provided in an embodiment of this application;

[0028] Figure 4 Image (b) is a schematic diagram of surface wave data provided in an embodiment of this application;

[0029] Figure 4 Image (c) is a schematic diagram of a phase velocity dispersion curve provided in an embodiment of this application;

[0030] Figure 4 (d) is a schematic diagram of a transverse wave velocity structure at the midpoint of a receiving line according to an embodiment of this application;

[0031] Figure 5(a) is a schematic diagram of top and bottom cutting of a single-shot seismic record provided in an embodiment of this application;

[0032] Figure 5 (b) is a schematic diagram of surface wave data obtained by top and bottom cutting according to an embodiment of this application;

[0033] Figure 5 (c) is a schematic diagram of surface wave data of a seismic trace provided in an embodiment of this application;

[0034] Figure 5 (d) is a time-frequency analysis diagram of a seismic trace provided in an embodiment of this application;

[0035] Figure 6 This is a schematic diagram of multiple ray path segments traced on an undulating surface provided in an embodiment of this application;

[0036] Figure 7 This is a schematic diagram of a target shear wave velocity model provided in an embodiment of this application;

[0037] Figure 8 This is a schematic diagram of a model for determining target shear wave velocity provided in an embodiment of this application;

[0038] Figure 9 This is a schematic diagram of a model for determining target shear wave velocity provided in an embodiment of this application;

[0039] Figure 10 This is a schematic diagram of a functional module provided in an embodiment of this application;

[0040] Figure 11 This is a schematic diagram of the structure of an earthquake data processing device provided in an embodiment of this application;

[0041] Figure 12 This is a structural block diagram of a terminal provided in an embodiment of this application. Detailed Implementation

[0042] To make the technical solution and advantages of this application clearer, the embodiments of this application will be described in further detail below.

[0043] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0044] It should be noted that all information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this application have been 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. For example, the earthquake data, shear wave velocity, travel time, etc. involved in this application were obtained with full authorization.

[0045] Figure 1 This is a schematic diagram illustrating the implementation environment of a seismic data processing method provided in an embodiment of this application. See also... Figure 1 The implementation environment includes electronic devices, which can be provided as terminal 101 and server 102, and terminal 101 and server 102 can be connected via a wireless or wired network. In this embodiment, no specific limitations are imposed.

[0046] The target application is installed on terminal 101. Terminal 101 can process seismic data based on the target application to obtain the target shear wave velocity model. Server 102 can provide background services for the target application. Specifically, server 102 can undertake the main computational work, and terminal 101 can undertake secondary computational work; alternatively, server 102 can undertake secondary computational work, and terminal 101 can undertake the main computational work; or, server 102 and terminal 101 can collaborate on computation using a distributed computing architecture.

[0047] The terminal 101 can be at least one of the following: mobile phone, tablet computer, PC (Personal Computer) device, intelligent voice interaction device, and vehicle terminal. The server 102 can be at least one of the following: a single server, a server cluster consisting of multiple servers, a cloud server, a cloud computing platform, and a virtualization center.

[0048] Figure 2 This is a flowchart of a seismic data processing method provided in an embodiment of this application, executed by an electronic device. See also... Figure 2 The method includes:

[0049] Step 201: The electronic device divides the target work area into grids to obtain the first grid and the second grid.

[0050] The target work area is the seismic exploration construction area. Electronic equipment divides the target work area into a two-dimensional plane grid, with the side length of each grid being half the distance between detector points in the seismic observation system, resulting in the first grid. The first grid is then thinned according to the accuracy requirements of the shear wave velocity model to obtain the second grid.

[0051] For example, three-dimensional seismic data of an explosive source was collected in a certain area. The shot point interval was 100 meters, the geophone interval was 20 meters, and there were 600 channels per shot. A region with a length of 3000 meters and a width of 2500 meters was selected from this area, involving 26 shots of seismic data and 546 geophones. See Figure 3 . Take half of the geophone interval, that is, 10 meters, to establish the first grid, and the size of the grid unit in the first grid is 10 meters × 10 meters. Thin out the first grid at an interval of 80 meters to obtain the second grid, and the size of the grid unit in the second grid is 80 meters × 80 meters.

[0052] In the embodiment of the present application, the electronic device can also generate a surface undulation surface based on the first grid. The process is as follows: The electronic device performs adaptive hierarchical B-spline interpolation based on the spatial coordinates of the shot points and geophones to calculate the elevation of each node in the first grid, and performs a "meter" - shaped dissection on each rectangular unit in the first grid, thereby generating a surface undulation surface.

[0053] Step 202: The electronic device acquires the first seismic data of the target work area, and based on the first seismic data, determines the initial shear wave velocity model of the target work area.

[0054] The first seismic data includes first seismic sub - data corresponding to multiple shot points, and the first seismic sub - data is surface wave data collected by geophones on the receiving line closest to the shot point.

[0055] For each shot point, the electronic device performs dispersion spectrum analysis on the first seismic sub - data corresponding to the shot point to obtain a phase velocity dispersion curve; performs inversion on the phase velocity dispersion curve to obtain the shear wave velocity structure at the target position; where the target position is the mid - point position of the receiving line, and the shear wave velocity structure is used to represent the shear wave velocity corresponding to different depths; projects the shear wave velocity structure at the target position into the second grid based on the spatial coordinates of the target position to obtain the first shear wave velocity model; for each depth at each node in the second grid, performs spatial interpolation on the basis of the first shear wave velocity model to obtain the initial shear wave velocity model.

[0056] In this implementation manner, the electronic device can perform inversion on the phase velocity dispersion curve according to the multi - channel transient surface wave inversion method to obtain the shear wave velocity structure at the target position. Based on the three - dimensional spatial coordinates of the target position, project the depth - shear wave velocity pairs at the target position into the second grid to obtain the shear wave velocity distribution in three - dimensional space, that is, the first shear wave velocity model, and then divide the first shear wave velocity model by depth. For example, the electronic device divides the first shear wave velocity model into H depths according to depth. For each depth at each node, perform spatial interpolation to obtain the initial shear wave velocity model.

[0057] See Figure 4 , Figure 4 (a) shows a three-dimensional seismic observation system. Figure 4 (b) is Figure 4 The surface wave data acquired by the shot point shown in (a) and the nearest receiver line to the left of that shot point. Figure 4 (c) is Figure 4 The phase velocity dispersion curve corresponding to the surface wave data in (b) Figure 4 (d) shows the transverse wave velocity structure at the midpoint of the receiver line to the left of the shot point. Figure 4 As can be seen from (d), different depths correspond to different transverse wave velocities.

[0058] Step 203: The electronic device determines the observation travel time of each single-frequency surface wave component in each shot-receiver pair based on the first seismic data.

[0059] For each shot point, the electronic equipment performs top and bottom cuts on the first seismic sub-data corresponding to that shot point to obtain the second seismic sub-data; wherein, the first seismic sub-data includes the second seismic sub-data of multiple shot-receiver pairs; time-frequency analysis is performed on the second seismic sub-data corresponding to each shot-receiver pair to obtain the observation travel time of each single-frequency surface wave component in each shot-receiver pair.

[0060] In this implementation, the electronic equipment performs top and bottom cuts on the single-shot seismic record based on the apparent velocity distribution range of the surface wave to extract the surface wave data. Then, time-frequency analysis is performed on the surface wave data corresponding to each shot-receiver pair to obtain the observation travel time of the single-frequency surface wave component.

[0061] See Figure 5 , Figure 5 (a) is a schematic diagram of top and bottom cuts for single-shot seismic records. Figure 5 (b) is Figure 5 The surface wave data obtained in (a) Figure 5 (c) is Figure 5 (b) Surface wave data from a seismic trace. Figure 5 (d) is Figure 5 The time-frequency analysis plot of the surface wave data shown in (c) is used to represent the relationship between time and frequency. Therefore, according to Figure 5 The time corresponding to each single-frequency surface wave component can be determined by (d), which is the observation travel time.

[0062] It should be noted that after the electronic equipment acquires the first seismic data, it can first determine the initial shear wave velocity model based on the first seismic data, and then determine the observation travel time of each single-frequency surface wave component in each shot-receiver pair, or it can first determine the observation travel time of each single-frequency surface wave component in each shot-receiver pair, and then determine the initial shear wave velocity model. There is no specific restriction on the order of these steps.

[0063] Step 204: The electronic equipment determines the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair based on the initial shear wave velocity model, the first grid, and the second grid.

[0064] This step can be achieved through the following steps (1) to (5), including:

[0065] (1) The electronic device determines the group velocity of each single-frequency surface wave component of each node in the second grid based on the initial shear wave velocity model.

[0066] Step (1) can be achieved through the following steps (1-1) to (1-5), including:

[0067] (1-1) The electronic device determines the shear wave velocity at each depth at each node in the second grid based on the initial shear wave velocity model.

[0068] The electronic device can determine the shear wave velocity at each depth at each node in the second grid from the initial shear wave velocity model. For example, the shear wave velocity at depth h at the nth node is represented as b. nh Where n is a positive integer, and h = 1, 2, ..., H. The nodes in the second grid are the vertices of the grid cells in the second grid.

[0069] (1-2) The electronic device substitutes the transverse wave velocity at each depth at each node in the second grid into the third relational data to obtain the longitudinal wave velocity at each depth at each node in the second grid.

[0070] The third relationship data is used to represent the relationship between the transverse wave velocity and the longitudinal wave velocity.

[0071] In this embodiment of the application, the third relation data can be represented as: a nh =1.732b nh , where a nh This represents the longitudinal wave velocity at depth h at the nth node.

[0072] For each depth at each node in the second grid, the electronic device substitutes the corresponding transverse wave velocity into the third relational data to obtain the corresponding longitudinal wave velocity.

[0073] (1-3) The electronic device substitutes the longitudinal wave velocity at each depth at each node in the second grid into the fourth relational data to obtain the density at each depth at each node in the second grid.

[0074] The fourth relational data is used to represent the relationship between P-wave velocity and density.

[0075] In this embodiment of the application, the fourth relational data can be represented as: ρ nh =0.31a nh0.25 ; where ρ nh This represents the density at the nth node when the depth is h.

[0076] For each depth at each node in the second grid, the electronic device substitutes the corresponding longitudinal wave velocity into the fourth relational data to obtain the corresponding density.

[0077] (1-4) The electronic device determines the surface wave group velocity dispersion curve of each node in the second grid based on the transverse wave velocity, longitudinal wave velocity and density at each depth at each node in the second grid.

[0078] The electronic device calculates the surface wave group velocity dispersion curve for each node in the second grid based on the transverse wave velocity, longitudinal wave velocity, and density at each depth at each node in the second grid.

[0079] (1-5) The electronic device determines the group velocity of each single-frequency surface wave component of each node in the second grid based on the dispersion curve of the surface wave group velocity of each node in the second grid.

[0080] The surface wave group velocity dispersion curve is a curve showing how the surface wave group velocity changes with frequency. Based on the surface wave group velocity dispersion curve of each node in the second grid, the electronic device determines the group velocity of each single-frequency surface wave component of each node in the second grid.

[0081] (2) The electronic device determines the group velocity of each single-frequency surface wave component of each node in the first grid based on the group velocity of the single-frequency surface wave component of each node in the first relational data and the group velocity of the single-frequency surface wave component of each node in the second grid.

[0082] The first relational data represents the relationship between the f-frequency single-frequency surface wave component group velocity of the j-th node in the first grid and the f-frequency single-frequency surface wave component group velocity of each node in the second grid, where j is a positive integer and f > 0. The nodes in the first grid are the vertices of the grid cells in the first grid.

[0083] In this embodiment of the application, the first relational data can be represented as:

[0084]

[0085] Among them, V j (f) represents the group velocity of the f-frequency single-frequency surface wave component at the j-th node in the first grid, υ n (f) represents the group velocity of the f-frequency single-frequency surface wave component at the nth node in the second grid, γ jnThis represents the interpolation coefficients used to generate the group velocity of the single-frequency surface wave component at the f-frequency of the j-th node in the second grid, based on the group velocity of the single-frequency surface wave component at the f-frequency of the j-th node in the first grid, using the bicubic B-spline interpolation method. N is the total number of nodes in the second grid.

[0086] For each node in the first grid, the electronic device substitutes the f-frequency single-frequency surface wave component group velocity and the corresponding interpolation coefficients of each node in the second grid into the first relational data to obtain the f-frequency single-frequency surface wave component group velocity of that node.

[0087] (3) The electronic equipment projects the coordinates of the shot point and the receiver point of each shot-receiver pair onto the undulating surface of the ground.

[0088] The shot point coordinates and receiver coordinates in step (3) are planar coordinates. The electronic device projects the shot point and receiver of each shot-receiver pair onto the undulating surface of the ground according to the planar coordinates. This undulating surface is generated in step 201.

[0089] (4) For each shot-receiver pair, the electronic equipment determines the multiple ray path segments corresponding to each single-frequency surface wave component in the shot-receiver pair on the undulating surface of the ground based on the group velocity of each single-frequency surface wave component of each node in the first grid.

[0090] The ray path segment is used to represent the distance from the shot point to the receiver point in the shot-receiver pair.

[0091] For each shot-receiver pair, the electronic equipment tracks K ray path segments from the shot point to the receiver point based on the group velocity of each single-frequency surface wave component at each node in the first grid, using a fast travel method. The lengths of these K ray path segments can be represented as d1, d2, ..., d... k ...d K K is a positive integer. See also Figure 6 , Figure 6 This is a schematic diagram of multiple ray paths traced from the shot point to the receiver point on an undulating surface.

[0092] (5) Based on the multiple ray path segments corresponding to each shot-receiver pair, the group velocity of each single-frequency surface wave component of each node in the second grid, and the second relationship data, determine the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair.

[0093] The second relational data is used to represent the relationship between the theoretical travel time of the f-frequency single-frequency surface wave component in the i-th shot-receiver pair, the multiple ray path segments corresponding to the i-th shot-receiver pair, and the group velocity of the f-frequency single-frequency surface wave component of each node in the second grid, where i is a positive integer.

[0094] In this embodiment of the application, the second relational data can be represented as:

[0095]

[0096] Among them, t i (f) represents the theoretical travel time of the f-frequency single-frequency surface wave component in the i-th shot-receiver pair, γ kn This represents the interpolation coefficients used to generate the surface wave group velocity at the midpoint of the path segment of the k-th ray, based on the group velocity of the single-frequency surface wave component at the f-th node in the second grid, using the bicubic B-spline interpolation method.

[0097] For each shot-receiver pair, the electronic device substitutes the group velocity of each single-frequency surface wave component corresponding to the multiple ray path segments in the shot-receiver pair and each node in the second grid into the second relational data to obtain the theoretical travel time of each single-frequency surface wave component in the shot-receiver pair.

[0098] Step 205: The electronic equipment constructs an objective function based on the observed travel time, theoretical travel time, and shear wave velocity change of each single-frequency surface wave component in each shot-receiver pair.

[0099] This step can be achieved through the following steps (1) to (4), including:

[0100] (1) Electronic devices determine the travel time error between observed travel time and theoretical travel time.

[0101] For each shot-receiver pair, the electronic equipment determines the difference between the observed travel time and the theoretical travel time of each single-frequency surface wave component in the shot-receiver pair, thus obtaining the travel time error.

[0102] It should be noted that the observed travel time is obtained from the collected seismic data, while the theoretical travel time is calculated from the initial shear wave velocity model. There is an inevitable error between the two, namely the travel time error.

[0103] (2) The electronic device determines the first sensitivity, second sensitivity and third sensitivity at each depth at each node in the second grid based on the group velocity of each single-frequency surface wave component at each node in the second grid, the transverse wave velocity, longitudinal wave velocity and density at each depth at each node in the second grid.

[0104] The first sensitivity is used to represent the rate of change of the single-frequency surface wave group velocity relative to the transverse wave velocity in the depth direction, the second sensitivity is used to represent the rate of change of the single-frequency surface wave group velocity relative to the longitudinal wave velocity in the depth direction, and the third sensitivity is used to represent the rate of change of the single-frequency surface wave group velocity relative to the density in the depth direction.

[0105] For each node in the second grid, the electronic device determines the rate of change of the group velocity of each single-frequency surface wave component of that node relative to the transverse wave velocity in the depth direction, thus obtaining a first sensitivity; determines the rate of change of the group velocity of each single-frequency surface wave component of that node relative to the longitudinal wave velocity in the depth direction, thus obtaining a second sensitivity; and determines the rate of change of the group velocity of each single-frequency surface wave component of that node relative to the density in the depth direction, thus obtaining a third sensitivity.

[0106] (3) The electronic device constructs a first sensitivity matrix based on the fifth relation data, the sixth relation data, the first sensitivity, the second sensitivity and the third sensitivity at each depth at each node in the second grid.

[0107] The fifth relational data is used to represent the relationship between the change in the group velocity of the f-frequency single-frequency surface wave component, the change in the transverse wave velocity, the first sensitivity, the second sensitivity, and the third sensitivity of the nth node in the second grid. The sixth relational data is used to represent the relationship between the travel time error and the change in the group velocity of the f-frequency single-frequency surface wave component of the nth node in the second grid.

[0108] In this embodiment of the application, the fifth relation data can be represented as:

[0109]

[0110] Where, Δυ n (f) represents the change in the group velocity of the f-frequency surface wave component at the nth node in the second grid, Δb nh This represents the change in transverse wave velocity at depth h at the nth node in the second grid. Indicates the first sensitivity. Indicates the second sensitivity. E represents the third sensitivity. h F is the empirical coefficient of the group velocity of the f-frequency single-frequency surface wave component at the nth node in the second grid with respect to the second sensitivity. h , where f is the empirical coefficient of the group velocity of the single-frequency surface wave component at the nth node in the second grid with respect to the third sensitivity.

[0111] The sixth relation data can be represented as:

[0112]

[0113] Where, Δt i (f) represents the travel time error. Let f represent the theoretical travel time of the single-frequency surface wave component at frequency f in the i-th shot-receiver pair. Let f represent the observation travel time of the single-frequency surface wave component at frequency f in the i-th shot-receiver pair.

[0114] Electronic devices will use Δυ in the fifth relation datan (f) Substitute the data into the sixth relation and determine the part other than the travel time error and the change in shear wave velocity as the first sensitivity matrix.

[0115] (4) The electronic device constructs an objective function based on the first sensitivity matrix, travel time error and shear wave velocity change.

[0116] In this embodiment of the application, the objective function constructed by the electronic device based on the first sensitivity matrix, travel time error and shear wave velocity change is: d = Gm;

[0117] Where d represents the travel time error vector of Q single-frequency surface wave components on P shot-receiver pairs, which is composed of multiple travel time errors, Q is the total number of frequencies, P is the total number of shot-receiver pairs, and d = [Δt1(f1), ..., Δt] p (f1), Δt1(f2), ..., Δt p (f2), ..., Δt1(f Q ), ..., Δt p (f Q )] T m represents the perturbation vector of shear wave velocities at H depths at N nodes in the second grid, composed of multiple shear wave velocity changes, m = [Δb 11 , …, Δb 1H , Δb 21 , ..., Δb 2H , ..., Δb N1 , ..., Δb NH ] T G represents the second sensitivity matrix, which is composed of multiple first sensitivity matrices. Each row in the second sensitivity matrix represents a source of travel time error for a single-frequency surface wave vector on a shot-receiver pair.

[0118] Step 206: The electronic device iteratively updates the initial shear wave velocity model based on the objective function until the travel time error meets the preset conditions, thus obtaining the target shear wave velocity model.

[0119] This step can be achieved through the following steps (1) to (3), including:

[0120] (1) The electronic device determines the change in transverse wave velocity at each depth at each node in the second grid based on the objective function.

[0121] The objective function is a large sparse ill-conditioned linear system of equations. The electronic device can use the LSQR (Least Squares QR Decomposition) algorithm to solve the objective function and obtain the change in transverse wave velocity at each depth at each node in the second grid.

[0122] (2) The electronic device updates the initial shear wave velocity model based on the change in shear wave velocity at each depth at each node in the second grid, and obtains the updated shear wave velocity model.

[0123] The electronic device can determine the shear wave velocity at each depth at each node in the second grid based on the initial shear wave velocity model. For each depth at each node in the second grid, the change in shear wave velocity at the depth of that node is added to the shear wave velocity at that depth to obtain the updated shear wave velocity at that depth, thus obtaining the updated shear wave velocity model.

[0124] (3) The electronic device uses the updated shear wave velocity model as the initial shear wave velocity model and repeatedly executes the steps of determining the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair based on the initial shear wave velocity model, the first grid and the second grid, until the travel time error meets the preset conditions and the target shear wave velocity model is obtained.

[0125] The electronic device uses the updated shear wave velocity model as the initial shear wave velocity model, and then executes step 204. After determining the theoretical travel time, it checks whether the travel time error meets a preset condition. If the preset condition is met, the updated shear wave velocity model is used as the target shear wave velocity model. If the preset condition is not met, the objective function is reconstructed. Based on the reconstructed objective function, the shear wave velocity change at each depth at each node in the second grid is re-determined. Based on the re-determined shear wave velocity change, the shear wave velocity model is updated again. This process is repeated until the travel time error meets the preset condition. The shear wave velocity model corresponding to the travel time error meeting the preset condition is then used as the target shear wave velocity model. See also... Figure 7 , Figure 7 This is a schematic diagram of the final target shear wave velocity model. Figure 7 The image shows the transverse wave velocities at different depths.

[0126] The preset conditions can be set and changed as needed. For example, the preset conditions are that the travel time error is less than a preset threshold or that the travel time error is within a preset range.

[0127] To more clearly illustrate the scheme of this application, the following will be used... Figure 8 and Figure 9 Further explanation is needed. See also Figure 8Based on the first seismic data, the electronic equipment calculates the observation travel time of each single-frequency surface wave component in each shot-receiver pair according to the shot-receiver pair cycle. It determines whether the current shot-receiver pair is the last one; if so, it obtains the observation travel time of all single-frequency surface wave components. Furthermore, based on the first seismic data, the electronic equipment performs multi-channel transient surface wave analysis on the nearest receiver line to the shot point according to the shot point cycle, obtaining the depth-semantic velocity structure at the target location. It determines whether the current shot point is the last shot point; if so, it performs three-dimensional spatial interpolation to obtain the initial shear wave velocity model. Additionally, the electronic equipment performs triangulation surface interpolation based on the measurement results of the shot point and receiver point to generate a three-dimensional surface undulation.

[0128] The electronic equipment, based on the initial shear wave velocity model, forward models the surface wave group velocity dispersion curve to obtain the group velocity of all surface wave components. Then, following the surface wave component cycle, it performs three-dimensional surface ray tracing on all shot-receiver pairs to calculate the ray path segment and theoretical travel time of each single-frequency surface wave component, constructing the first sensitivity matrix. It determines whether the current single-frequency surface wave component is the last frequency component. If it is, it calculates the travel time error vector based on the observed and theoretical travel times, establishes and solves the objective function, and determines whether the travel time error meets the preset conditions. If not, it updates the shear wave velocity model until the conditions are met, obtaining the target shear wave velocity model.

[0129] See Figure 9 The electronic equipment extracts single-shot seismic data from the first seismic data set. Then, based on the single-shot seismic data, it determines the observation travel time of the single-frequency surface wave component and constructs an initial shear wave velocity model. An objective function is constructed based on the observation travel time and the initial shear wave velocity model. The target shear wave velocity model is obtained by solving the objective function and iteratively updating it.

[0130] As described above, the process of determining the target shear wave velocity model using electronic equipment involves several steps: constructing a three-dimensional undulating surface, building an initial shear wave velocity model, determining the observational travel time of all single-frequency surface wave components, determining the theoretical travel time of all single-frequency surface wave components, constructing the objective function, and updating the shear wave velocity model. In practical applications, electronic equipment can implement these processes through different functional modules, as detailed below. Figure 10 .

[0131] In summary, this application, based on the principle that near-surface shear wave velocity structure is closely related to surface wave dispersion, utilizes surface wave data acquired during oil and gas seismic exploration for travel time inversion. A three-dimensional surface undulation is established using measurements from shot and receiver points. Theoretical travel times are obtained through surface ray tracing. The actual near-surface shear wave velocity structure is approximated by solving the travel time error inversion equation, i.e., the objective function, to obtain the target shear wave velocity model. The resolution of this model in the depth direction depends on the thickness of the depth-direction layers, and the resolution in the horizontal direction depends on the spacing of the receiver points, exhibiting the same horizontal resolution as seismic data. This model can be used to calculate static corrections for shear waves in multi-wave and converted-wave exploration, and can also be used for near-surface shear wave velocity modeling in pre-stack depth migration.

[0132] This application provides a seismic data processing method. The method first determines an initial shear wave velocity model based on seismic data of the target work area, then determines the observation travel time of a single-frequency surface wave component based on the seismic data, and determines the theoretical travel time of the single-frequency surface wave component based on the initial shear wave velocity model. An objective function is constructed by using the observation travel time and the theoretical travel time, and the initial shear wave velocity model is iteratively updated based on the objective function to continuously approximate the real shear wave velocity structure, and finally obtain the target shear wave velocity model.

[0133] Figure 11 This is a schematic diagram of the structure of a seismic data processing device provided in an embodiment of this application. See also... Figure 11 The device includes:

[0134] The meshing module 1101 is used to mesh the target work area to obtain a first mesh and a second mesh; wherein the second mesh is obtained by thinning the first mesh.

[0135] The first determining module 1102 is used to acquire the first seismic data of the target work area and, based on the first seismic data, determine the initial shear wave velocity model of the target work area. The initial shear wave velocity model is used to represent the initial shear wave velocity distribution at each depth at each node in the second grid.

[0136] The second determining module 1103 is used to determine the observation travel time of each single-frequency surface wave component in each shot-receiver pair based on the first seismic data.

[0137] The third determination module 1104 is used to determine the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair based on the initial shear wave velocity model, the first grid, and the second grid.

[0138] Module 1105 is used to construct an objective function based on the observed travel time, theoretical travel time, and shear wave velocity variation of each single-frequency surface wave component in each shot-receiver pair. The objective function is used to represent the relationship between travel time error and shear wave velocity variation. The travel time error is the difference between the observed travel time and the theoretical travel time.

[0139] The update module 1106 is used to iteratively update the initial shear wave velocity model based on the objective function until the travel time error meets the preset conditions, thereby obtaining the target shear wave velocity model.

[0140] In one possible implementation, the first seismic data includes first seismic sub-data corresponding to multiple shot points, and the first seismic sub-data is surface wave data collected by the receiver point on the receiving line closest to the shot point;

[0141] The first determining module 1102 is used to perform dispersion spectrum analysis on the first seismic sub-data corresponding to each shot point to obtain the phase velocity dispersion curve; to invert the phase velocity dispersion curve to obtain the shear wave velocity structure at the target location; wherein, the target location is the midpoint of the receiver line, and the shear wave velocity structure is used to represent the shear wave velocity corresponding to different depths; based on the spatial coordinates of the target location, the shear wave velocity structure at the target location is projected onto the second grid to obtain the first shear wave velocity model; for each depth at each node in the second grid, spatial interpolation is performed on the first shear wave velocity model to obtain the initial shear wave velocity model.

[0142] In another possible implementation, the first seismic data includes first seismic sub-data corresponding to multiple shot points, and the first seismic sub-data is surface wave data collected by the receiver point on the receiving line closest to the shot point;

[0143] The second determining module 1103 is used to perform top-cutting and bottom-cutting on the first seismic sub-data corresponding to each shot point to obtain the second seismic sub-data; wherein the first seismic sub-data includes the second seismic sub-data of multiple shot-receiver pairs; and to perform time-frequency analysis on the second seismic sub-data corresponding to each shot-receiver pair to obtain the observation travel time of each single-frequency surface wave component in each shot-receiver pair.

[0144] In another possible implementation, the third determining module 1104 is used to determine the group velocity of each single-frequency surface wave component of each node in the second grid based on the initial shear wave velocity model; and to determine the group velocity of each single-frequency surface wave component of each node in the first grid based on the first relational data and the group velocity of each single-frequency surface wave component of each node in the second grid; wherein, the first relational data is used to represent the relationship between the group velocity of the single-frequency surface wave component of the j-th node in the first grid and the group velocity of the single-frequency surface wave component of the j-th node in the second grid, where j is a positive integer and f > 0; and to project the coordinates of the shot point and the receiver point of each shot-receiver pair onto the undulating surface of the ground; wherein, the undulating surface of the ground is generated based on the first grid; for each For a shot-receiver pair, based on the group velocity of each single-frequency surface wave component at each node in the first grid, multiple ray path segments corresponding to each single-frequency surface wave component in the shot-receiver pair are determined on the undulating surface. These ray path segments represent the distance from the shot point to the receiver point in the shot-receiver pair. Based on the multiple ray path segments corresponding to each shot-receiver pair, the group velocity of each single-frequency surface wave component at each node in the second grid, and second relational data, the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair is determined. The second relational data represents the relationship between the theoretical travel time of the f-frequency single-frequency surface wave component in the i-th shot-receiver pair, the multiple ray path segments corresponding to the i-th shot-receiver pair, and the group velocity of the f-frequency single-frequency surface wave component at each node in the second grid, where i is a positive integer.

[0145] In another possible implementation, the third determining module 1104 is used to determine the shear wave velocity at each depth at each node in the second grid based on the initial shear wave velocity model; substitute the shear wave velocity at each depth at each node in the second grid into the third relational data to obtain the P-wave velocity at each depth at each node in the second grid; wherein the third relational data is used to represent the relationship between the shear wave velocity and the P-wave velocity; substitute the P-wave velocity at each depth at each node in the second grid into the fourth relational data to obtain the density at each depth at each node in the second grid; wherein the fourth relational data is used to represent the relationship between the P-wave velocity and the density; determine the surface wave group velocity dispersion curve of each node in the second grid based on the shear wave velocity, P-wave velocity and density at each depth at each node in the second grid; and determine the group velocity of each single-frequency surface wave component of each node in the second grid based on the surface wave group velocity dispersion curve of each node in the second grid.

[0146] In another possible implementation, the third determining module 1104 is used to determine the travel time error between the observed travel time and the theoretical travel time; based on the single-frequency surface wave component group velocity at each node in the second grid, the shear wave velocity, longitudinal wave velocity, and density at each depth at each node in the second grid, it determines the first sensitivity, the second sensitivity, and the third sensitivity at each depth at each node in the second grid, respectively; wherein, the first sensitivity is used to represent the rate of change of the single-frequency surface wave component group velocity relative to the shear wave velocity in the depth direction, the second sensitivity is used to represent the rate of change of the single-frequency surface wave component group velocity relative to the longitudinal wave velocity in the depth direction, and the third sensitivity is used to represent the rate of change of the single-frequency surface wave component group velocity relative to the shear wave velocity in the depth direction. The rate of change of density along the depth direction; based on the fifth relation data, the sixth relation data, and the first sensitivity, second sensitivity, and third sensitivity at each depth at each node in the second grid, a first sensitivity matrix is ​​constructed; wherein, the fifth relation data is used to represent the relationship between the change in the f-frequency single-frequency surface wave component group velocity, the change in the shear wave velocity, the first sensitivity, the second sensitivity, and the third sensitivity at the nth node in the second grid, and the sixth relation data is used to represent the relationship between the travel time error and the change in the f-frequency single-frequency surface wave component group velocity at the nth node in the second grid, where n is a positive integer; based on the first sensitivity matrix, the travel time error, and the change in the shear wave velocity, an objective function is constructed.

[0147] In another possible implementation, update module 1106 is used to determine the change in shear wave velocity at each depth at each node in the second grid based on the objective function; update the initial shear wave velocity model based on the change in shear wave velocity at each depth at each node in the second grid to obtain the updated shear wave velocity model; use the updated shear wave velocity model as the initial shear wave velocity model, and repeatedly execute the step of determining the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair based on the initial shear wave velocity model, the first grid, and the second grid, until the travel time error meets the preset condition to obtain the target shear wave velocity model.

[0148] This application provides a seismic data processing device. The device first determines an initial shear wave velocity model based on seismic data of the target work area, then determines the observation travel time of the single-frequency surface wave component based on the seismic data, and determines the theoretical travel time of the single-frequency surface wave component based on the initial shear wave velocity model. An objective function is constructed by the observation travel time and the theoretical travel time. The initial shear wave velocity model is iteratively updated based on the objective function to continuously approximate the real shear wave velocity structure, and finally obtain the target shear wave velocity model.

[0149] refer to Figure 12 , Figure 12A structural block diagram of a terminal 1200 provided in an exemplary embodiment of this application is shown. The terminal 1200 may be a portable mobile terminal, such as a smartphone, tablet computer, MP3 player (Moving Picture Experts Group Audio Layer III), MP4 player (Moving Picture Experts Group Audio Layer IV), laptop computer, or desktop computer. The terminal 1200 may also be referred to as a user device, portable terminal, laptop terminal, desktop terminal, or other names.

[0150] Typically, terminal 1200 includes a processor 1201 and a memory 1202.

[0151] Processor 1201 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 1201 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 1201 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 1201 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 1201 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0152] The memory 1202 may include one or more computer-readable storage media, which may be non-transitory. The memory 1202 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 1202 are used to store at least one line of program code, which is executed by the processor 1201 to implement the seismic data processing method provided in the method embodiments of this application.

[0153] In some embodiments, the terminal 1200 may also optionally include a peripheral device interface 1203 and at least one peripheral device. The processor 1201, memory 1202, and peripheral device interface 1203 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 1203 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of the following: radio frequency circuitry 1204, display screen 1205, camera assembly 1206, audio circuitry 1207, and power supply 1208.

[0154] Peripheral device interface 1203 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 1201 and memory 1202. In some embodiments, processor 1201, memory 1202 and peripheral device interface 1203 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 1201, memory 1202 and peripheral device interface 1203 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0155] The radio frequency (RF) circuit 1204 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 1204 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 1204 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 1204 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 1204 can communicate with other terminals through at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 1204 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0156] Display screen 1205 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 1205 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 1201 for processing. In this case, display screen 1205 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 1205, disposed on the front panel of terminal 1200; in other embodiments, there may be at least two display screens, disposed on different surfaces of terminal 1200 or in a folded design; in still other embodiments, display screen 1205 may be a flexible display screen, disposed on a curved or folded surface of terminal 1200. Furthermore, display screen 1205 may also be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. The display screen 1205 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0157] The camera assembly 1206 is used to acquire images or videos. Optionally, the camera assembly 1206 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the terminal, and the rear-facing camera is located on the back of the terminal. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In some embodiments, the camera assembly 1206 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm-light flash and a cool-light flash, which can be used for light compensation at different color temperatures.

[0158] The audio circuit 1207 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting the sound waves into electrical signals that are input to the processor 1201 for processing, or input to the radio frequency circuit 1204 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each positioned at a different location on the terminal 1200. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert electrical signals from the processor 1201 or the radio frequency circuit 1204 into sound waves. The speaker may be a conventional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 1207 may also include a headphone jack.

[0159] Power supply 1208 is used to power the various components in terminal 1200. Power supply 1208 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 1208 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, and a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0160] In some embodiments, the terminal 1200 further includes one or more sensors 1209. The one or more sensors 1209 include, but are not limited to: an acceleration sensor 1210, a gyroscope sensor 1211, a pressure sensor 1212, an optical sensor 1213, and a proximity sensor 1214.

[0161] Accelerometer 1210 can detect the magnitude of acceleration along the three coordinate axes of a coordinate system established with terminal 1200. For example, accelerometer 1210 can be used to detect the components of gravitational acceleration along the three coordinate axes. Processor 1201 can control display screen 1205 to display the user interface in either a landscape or portrait view based on the gravitational acceleration signal acquired by accelerometer 1210. Accelerometer 1210 can also be used for games or for acquiring user motion data.

[0162] The gyroscope sensor 1211 can detect the orientation and rotation angle of the terminal 1200. The gyroscope sensor 1211 can work in conjunction with the accelerometer sensor 1210 to collect 3D motion data from the user on the terminal 1200. Based on the data collected by the gyroscope sensor 1211, the processor 1201 can perform the following functions: motion sensing (e.g., changing the UI based on the user's tilt), image stabilization during shooting, game control, and inertial navigation.

[0163] The pressure sensor 1212 can be disposed on the side bezel of the terminal 1200 and / or on the lower layer of the display screen 1205. When the pressure sensor 1212 is disposed on the side bezel of the terminal 1200, it can detect the user's grip signal on the terminal 1200, and the processor 1201 can perform left / right hand recognition or quick operation based on the grip signal collected by the pressure sensor 1212. When the pressure sensor 1212 is disposed on the lower layer of the display screen 1205, the processor 1201 can control the operable controls on the UI interface based on the user's pressure operation on the display screen 1205. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0164] Optical sensor 1213 is used to collect ambient light intensity. In one embodiment, processor 1201 can control the display brightness of display screen 1205 based on the ambient light intensity collected by optical sensor 1213. Specifically, when the ambient light intensity is high, the display brightness of display screen 1205 is increased; when the ambient light intensity is low, the display brightness of display screen 1205 is decreased. In another embodiment, processor 1201 can also dynamically adjust the shooting parameters of camera assembly 1206 based on the ambient light intensity collected by optical sensor 1213.

[0165] The proximity sensor 1214, also known as a distance sensor, is typically located on the front panel of the terminal 1200. The proximity sensor 1214 is used to detect the distance between the user and the front of the terminal 1200. In one embodiment, when the proximity sensor 1214 detects that the distance between the user and the front of the terminal 1200 is gradually decreasing, the processor 1201 controls the display screen 1205 to switch from a screen-on state to a screen-off state; when the proximity sensor 1214 detects that the distance between the user and the front of the terminal 1200 is gradually increasing, the processor 1201 controls the display screen 1205 to switch from a screen-off state to a screen-on state.

[0166] Those skilled in the art will understand that Figure 12 The structure shown does not constitute a limitation on terminal 1200 and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0167] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one piece of program code that is loaded and executed by a processor to implement the seismic data processing method in the above embodiments.

[0168] In an exemplary embodiment, a computer program product is also provided, which stores at least one piece of program code that is loaded and executed by a processor to implement the seismic data processing method in the above embodiments.

[0169] 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.

[0170] The above description is only for the purpose of enabling those skilled in the art to understand the technical solution 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 seismic data processing method, characterized in that, The method includes: The target work area is divided into a grid to obtain a first grid and a second grid; wherein the second grid is obtained by thinning the first grid. First seismic data of the target work area is acquired. Based on the first seismic data, an initial shear wave velocity model of the target work area is determined. The initial shear wave velocity model is used to represent the initial shear wave velocity distribution at each depth at each node in the second grid. Based on the first seismic data, the observation travel time of each single-frequency surface wave component in each shot-receiver pair is determined; Based on the initial shear wave velocity model, the group velocity of each single-frequency surface wave component of each node in the second grid is determined; Based on the first relational data and the group velocity of each single-frequency surface wave component of each node in the second grid, the group velocity of each single-frequency surface wave component of each node in the first grid is determined; wherein, the first relational data is used to represent the relationship between the group velocity of the single-frequency surface wave component of the j-th node in the first grid and the group velocity of the single-frequency surface wave component of the j-th node in the second grid, where j is a positive integer and f > 0; The shot point coordinates and receiver point coordinates of each shot-receiver pair are projected onto a surface undulation; wherein the surface undulation is generated based on the first grid. For each shot-receiver pair, based on the group velocity of each single-frequency surface wave component of each node in the first grid, multiple ray path segments corresponding to each single-frequency surface wave component in the shot-receiver pair are determined on the undulating surface of the ground; wherein, the ray path segments are used to represent the distance from the shot point to the receiver point in the shot-receiver pair. Based on the multiple ray path segments corresponding to each shot-receiver pair, the group velocity of each single-frequency surface wave component of each node in the second grid, and the second relational data, the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair is determined; wherein, the second relational data is used to represent the relationship between the theoretical travel time of the f-frequency single-frequency surface wave component in the i-th shot-receiver pair, the multiple ray path segments corresponding to the i-th shot-receiver pair, and the group velocity of the f-frequency single-frequency surface wave component of each node in the second grid, where i is a positive integer; Based on the observed travel time, theoretical travel time, and shear wave velocity variation of each single-frequency surface wave component in each shot-receiver pair, an objective function is constructed. The objective function is used to represent the relationship between travel time error and shear wave velocity variation. The travel time error is the difference between the observed travel time and the theoretical travel time. Based on the objective function, the initial shear wave velocity model is iteratively updated until the travel time error meets the preset condition, thus obtaining the target shear wave velocity model.

2. The method according to claim 1, characterized in that, The first seismic data includes first seismic sub-data corresponding to multiple shot points, and the first seismic sub-data is surface wave data collected by the detector point on the receiving line closest to the shot point; The step of determining the initial shear wave velocity model of the target work area based on the first seismic data includes: For each shot point, dispersion spectrum analysis is performed on the first seismic data corresponding to the shot point to obtain the phase velocity dispersion curve; The phase velocity dispersion curve is inverted to obtain the shear wave velocity structure at the target location; wherein, the target location is the midpoint of the receiving line, and the shear wave velocity structure is used to represent the shear wave velocity corresponding to different depths; Based on the spatial coordinates of the target location, the shear wave velocity structure at the target location is projected onto the second grid to obtain the first shear wave velocity model; For each depth at each node in the second grid, spatial interpolation is performed based on the first shear wave velocity model to obtain the initial shear wave velocity model.

3. The method according to claim 1, characterized in that, The first seismic data includes first seismic sub-data corresponding to multiple shot points, and the first seismic sub-data is surface wave data collected by the detector point on the receiving line closest to the shot point; The step of determining the observation travel time of each single-frequency surface wave component in each shot-receiver pair based on the first seismic data includes: For each shot point, the first seismic sub-data corresponding to the shot point is top-cut and bottom-cut to obtain the second seismic sub-data; wherein, the first seismic sub-data includes the second seismic sub-data of multiple shot-receiver pairs; Time-frequency analysis is performed on the second seismic sub-data corresponding to each shot-receiver pair to obtain the observation travel time of each single-frequency surface wave component in each shot-receiver pair.

4. The method according to claim 1, characterized in that, The determination of the group velocity of each single-frequency surface wave component at each node in the second grid based on the initial shear wave velocity model includes: Based on the initial shear wave velocity model, the shear wave velocity at each depth at each node in the second grid is determined; Substituting the shear wave velocity at each depth at each node in the second grid into the third relational data yields the longitudinal wave velocity at each depth at each node in the second grid; wherein, the third relational data is used to represent the relationship between the shear wave velocity and the longitudinal wave velocity. Substituting the P-wave velocity at each depth at each node in the second grid into the fourth relational data yields the density at each depth at each node in the second grid; wherein, the fourth relational data is used to represent the relationship between P-wave velocity and density; Based on the shear wave velocity, longitudinal wave velocity, and density at each depth at each node in the second grid, the surface wave group velocity dispersion curve of each node in the second grid is determined. Based on the surface wave group velocity dispersion curve of each node in the second grid, the group velocity of each single-frequency surface wave component of each node in the second grid is determined.

5. The method according to claim 4, characterized in that, The objective function is constructed based on the observed travel time, theoretical travel time, and shear wave velocity variation of each single-frequency surface wave component in each shot-receiver pair, including: Determine the travel time error between the observed travel time and the theoretical travel time; Based on the single-frequency surface wave group velocity of each node in the second grid, the shear wave velocity, longitudinal wave velocity, and density at each depth at each node in the second grid, a first sensitivity, a second sensitivity, and a third sensitivity at each depth at each node in the second grid are determined respectively; wherein, the first sensitivity is used to represent the rate of change of the single-frequency surface wave group velocity relative to the shear wave velocity in the depth direction, the second sensitivity is used to represent the rate of change of the single-frequency surface wave group velocity relative to the longitudinal wave velocity in the depth direction, and the third sensitivity is used to represent the rate of change of the single-frequency surface wave group velocity relative to the density in the depth direction; Based on the fifth relation data, the sixth relation data, and the first sensitivity, second sensitivity, and third sensitivity at each depth at each node in the second grid, a first sensitivity matrix is ​​constructed; wherein, the fifth relation data is used to represent the relationship between the change in the f-frequency single-frequency surface wave component group velocity, the change in the shear wave velocity, the first sensitivity, the second sensitivity, and the third sensitivity at the nth node in the second grid, and the sixth relation data is used to represent the relationship between the travel time error and the change in the f-frequency single-frequency surface wave component group velocity at the nth node in the second grid, where n is a positive integer; The objective function is constructed based on the first sensitivity matrix, the travel time error, and the change in shear wave velocity.

6. The method according to claim 1, characterized in that, The step of iteratively updating the initial shear wave velocity model based on the objective function until the travel time error meets a preset condition to obtain the target shear wave velocity model includes: Based on the objective function, determine the change in shear wave velocity at each depth at each node in the second grid; Based on the change in shear wave velocity at each depth at each node in the second grid, the initial shear wave velocity model is updated to obtain the updated shear wave velocity model. Using the updated shear wave velocity model as the initial shear wave velocity model, the step of determining the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair based on the initial shear wave velocity model, the first grid, and the second grid is repeated until the travel time error meets the preset condition, thus obtaining the target shear wave velocity model.

7. A seismic data processing device, characterized in that, The device includes: The grid division module is used to divide the target work area into a first grid and a second grid; wherein the second grid is obtained by thinning the first grid. The first determining module is used to acquire the first seismic data of the target work area, and based on the first seismic data, determine the initial shear wave velocity model of the target work area. The initial shear wave velocity model is used to represent the initial shear wave velocity distribution at each depth at each node in the second grid. The second determining module is used to determine the observation travel time of each single-frequency surface wave component in each shot-receiver pair based on the first seismic data. The third determining module is used to determine the group velocity of each single-frequency surface wave component of each node in the second grid based on the initial shear wave velocity model; and to determine the group velocity of each single-frequency surface wave component of each node in the first grid based on the first relational data and the group velocity of each single-frequency surface wave component of each node in the second grid; wherein, the first relational data is used to represent the relationship between the group velocity of the single-frequency surface wave component of the j-th node in the first grid and the group velocity of the single-frequency surface wave component of the j-th node in the second grid, where j is a positive integer and f > 0; and to project the shot point coordinates and receiver point coordinates of each shot-receiver pair onto the undulating surface of the ground; wherein, the undulating surface of the ground is generated based on the first grid; for each shot-receiver pair, based on the initial shear wave velocity model, the first relational data is used to determine the group velocity of each single-frequency surface wave component of each node in the first grid; and to determine the group velocity of each single-frequency surface wave component of each node in the first grid based on the first relational data and the group velocity of each single-frequency surface wave component of each node in the second grid; wherein, the first relational data is used to represent the relationship between the group velocity of the single-frequency surface wave component of the j-th node in the first grid and the group velocity of each single-frequency surface wave component of each node in the second grid; and to determine the group velocity of each single-frequency surface wave component of each node in the first grid based on the first relational data and the group velocity of each single-frequency surface wave component of each node in the second grid. For each single-frequency surface wave component group velocity of each node in the first grid, multiple ray path segments corresponding to each single-frequency surface wave component in the shot-receiver pair are determined on the undulating surface of the ground. The ray path segments represent the distance from the shot point to the receiver point in the shot-receiver pair. Based on the multiple ray path segments corresponding to each shot-receiver pair, the single-frequency surface wave component group velocity of each node in the second grid, and second relational data, the theoretical travel time of each single-frequency surface wave component in each shot-receiver pair is determined. The second relational data represents the relationship between the theoretical travel time of the f-frequency single-frequency surface wave component in the i-th shot-receiver pair, the multiple ray path segments corresponding to the i-th shot-receiver pair, and the f-frequency single-frequency surface wave component group velocity of each node in the second grid, where i is a positive integer. The construction module is used to construct an objective function based on the observed travel time, theoretical travel time, and shear wave velocity variation of each single-frequency surface wave component in each shot-receiver pair. The objective function is used to represent the relationship between travel time error and shear wave velocity variation, where the travel time error is the difference between the observed travel time and the theoretical travel time. The update module is used to iteratively update the initial shear wave velocity model based on the objective function until the travel time error meets the preset condition, thereby obtaining the target shear wave velocity model.

8. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing at least one line of program code, which is loaded and executed by the processor to implement the seismic data processing method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to implement the seismic data processing method as described in any one of claims 1 to 6.

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