Seismic data processing method and device, equipment and storage medium

Abstract

The invention discloses a seismic data processing method and device, equipment and a storage medium, and belongs to the technical field of seismic exploration. According to the method, an initial shear wave velocity model is determined based on seismic data of a target work area, then observation travel time of a single-frequency surface wave component is determined based on the seismic data, theoretical travel time of the single-frequency surface wave component is determined based on the initial shear wave velocity model, and a target function is constructed through the observation travel time and the theoretical travel time. And iteratively updating the initial shear wave velocity model based on the target function so as to continuously approach a real shear wave velocity structure, and finally obtaining a target shear wave velocity model.

Description

Technical Field

[0001] The present application relates to the field of seismic exploration technology, and in particular to a seismic data processing method, device, equipment and storage medium. Background Art

[0002] Compared with natural earthquakes, seismic exploration is a medium-scale detection technology, and the depth of its detection area is generally within 10 kilometers. When seismic waves are excited on the surface, surface waves are formed that propagate along the near-surface strata. Surface waves will be dispersed during propagation, that is, surface wave components of different frequencies have different propagation 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 usually thin layers composed of low-velocity, uncompacted materials. In most cases, near-surface strata can be assumed to be a geological structure whose velocity increases with depth. Among them, the shear wave velocity model of near-surface strata has a significant impact on the imaging effect of seismic data. Therefore, before imaging the seismic data, the influence of the shear wave velocity of the near-surface strata must be removed. How to obtain the shear wave velocity model of the near-surface strata has become an urgent problem to be solved. Summary of the invention

[0004] The embodiments of the present application provide a seismic data processing method, device, equipment and storage medium, which can continuously approach the real shear wave velocity structure through iterative updating. The technical solution is as follows:

[0005] In one aspect, a method for processing seismic data is provided, the method comprising:

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

[0007] Acquire first seismic data of the target work area, and determine an initial shear wave velocity model of the target work area based on the first seismic data, wherein the initial shear wave velocity model is used to represent an initial shear wave velocity distribution at each depth at each node in the second grid;

[0008] Determining the observed travel time of each single-frequency surface wave component in each shot-check pair based on the first seismic data;

[0009] Determining a theoretical travel time of each single-frequency surface wave component in each shot-detection pair based on the initial shear wave velocity model, the first grid, and the second grid;

[0010] Based on the observed traveltime, theoretical traveltime and shear wave velocity variation of each single-frequency surface wave component in each shot detection pair, constructing an objective function, wherein the objective function is used to represent the relationship between the traveltime error and the shear wave velocity variation, and the traveltime error is the difference between the observed traveltime and the theoretical traveltime;

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

[0012] In another aspect, a seismic data processing device is provided, the device comprising:

[0013] A division module, used for dividing the target work area into grids to obtain a first grid and a second grid; wherein the second grid is obtained by thinning the first grid;

[0014] A first determination module is used to obtain first seismic data of the target work area, and determine an initial shear wave velocity model of the target work area based on the first seismic data, wherein the initial shear wave velocity model is used to represent an initial shear wave velocity distribution at each depth at each node in the second grid;

[0015] A second determination module is used to determine the observed travel time of each single-frequency surface wave component in each shot-check pair based on the first seismic data;

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

[0017] A construction module, configured to construct an objective function based on the observed traveltime, theoretical traveltime and shear wave velocity variation of each single-frequency surface wave component in each shot detection pair, wherein the objective function is used to represent the relationship between the traveltime error and the shear wave velocity variation, and the traveltime error is the difference between the observed traveltime and the theoretical traveltime;

[0018] An updating module is used to iteratively update the initial shear wave velocity model based on the objective function until the travel time error meets a preset condition, thereby obtaining a 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 program code, and the at least one program code is loaded and executed by the processor to implement any of the above-mentioned seismic data processing methods.

[0020] On the other hand, a computer-readable storage medium is provided, in which at least one program code is stored. The at least one program code is loaded and executed by a processor to implement any of the above-mentioned seismic data processing methods.

[0021] On the other hand, a computer program product is provided, wherein at least one program code is stored in the computer program product, and the at least one program code is loaded and executed by a processor to implement any of the above-mentioned seismic data processing methods.

[0022] An embodiment of the present application provides a seismic data processing method, which first determines an initial shear wave velocity model based on the seismic data of a target work area, then determines the observed travel time of a single-frequency surface wave component based on the seismic data, determines the theoretical travel time of the single-frequency surface wave component based on the initial shear wave velocity model, constructs an objective function through the observed travel time and the theoretical travel time, and iteratively updates the initial shear wave velocity model based on the objective function, so as to continuously approximate the actual shear wave velocity structure and finally obtain the target shear wave velocity model.

[0023] It is to be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0025] Figure 2 is a flow chart of a seismic data processing method provided in an embodiment of the present application;

[0026] Figure 3 is a schematic diagram of a distribution range of artillery inspection points provided in an embodiment of the present application;

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

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

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

[0030] Figure 4 (d) is a schematic diagram of a shear wave velocity structure at the midpoint of a receiving line provided in an embodiment of the present application;

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

[0032] Figure 5 (b) is a schematic diagram of surface wave data obtained by top cutting and bottom cutting provided in an embodiment of the present application;

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

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

[0035] Figure 6 is a schematic diagram of multiple ray path segments traced on an undulating surface provided by an embodiment of the present application;

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

[0037] Figure 8 is a schematic diagram of a target shear wave velocity model provided in an embodiment of the present application;

[0038] Fig. 9 is a schematic diagram of a target shear wave velocity model provided in an embodiment of the present application;

[0039] Fig.10 is a schematic diagram of a functional module provided in an embodiment of the present application;

[0040] Fig.11 is a structural schematic diagram of a seismic data processing device provided in an embodiment of the present application;

[0041] Fig.12 It is a structural block diagram of a terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] In order to make the technical solutions and advantages of the present application clearer, the implementation methods of the present application are described in further detail below.

[0043] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0044] It should be noted that the 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 are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions. For example, the seismic data, shear wave velocity, travel time, etc. involved in this application are all obtained with full authorization.

[0045] Figure 1 is a schematic diagram of an implementation environment of a seismic data processing method provided in an embodiment of the present application, see Figure 1 The implementation environment includes: electronic devices, which can be provided as a terminal 101 and a server 102, and the terminal 101 and the server 102 can be connected via a wireless or wired network. In the embodiments of the present application, this is not specifically limited.

[0046] The terminal 101 is installed with a target application, and the terminal 101 can process the seismic data based on the target application to obtain a target shear wave velocity model. The server 102 can provide background services for the target application. The server 102 can undertake the main computing work, and the terminal 101 can undertake the secondary computing work; or, the server 102 undertakes the secondary computing work, and the terminal 101 undertakes the main computing work; or, the server 102 and the terminal 101 use a distributed computing architecture for collaborative computing.

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

[0048] Figure 2 is a flowchart of a seismic data processing method provided in an embodiment of the present application, which is executed by an electronic device, see Figure 2 , the method comprising:

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

[0050] The target work area is the seismic exploration construction area. The electronic equipment divides the target work area into two-dimensional grids. The side length of each grid is half of the distance between the detection points in the seismic observation system to obtain the first grid. The first grid is thinned according to the accuracy requirements of the shear wave velocity model to obtain the second grid.

[0051] For example, a 3D seismic data of explosive source was collected in a certain area, with a shot point spacing of 100 meters, a receiver point spacing of 20 meters, and 600 channels per shot. From this area, an area of ​​3000 meters long and 2500 meters wide was selected, involving 26 shot seismic data and 546 receiver points. Figure 3 The first grid is established by taking half of the detection point distance, that is, 10 meters, and the size of the grid unit in the first grid is 10 meters × 10 meters. The first grid is thinned out at intervals 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 an embodiment of the present application, the electronic device can also generate a undulating surface based on the first grid. The process is: the electronic device performs adaptive hierarchical B-spline interpolation based on the spatial coordinates of the shot point and the detection point to calculate the elevation of each node in the first grid, and divides each rectangular unit in the first grid into a "M" shape, thereby generating a undulating surface.

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

[0054] The first seismic data includes first seismic sub-data corresponding to a plurality of shot points, and the first seismic sub-data are surface wave data collected by a detection point on a 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; the phase velocity dispersion curve is inverted to obtain the shear wave velocity structure at the target position; wherein the target position is the midpoint of the receiving line, and the shear wave velocity structure is used to represent the shear wave velocities corresponding to different depths; based on the spatial coordinates of the target position, the shear wave velocity structure at the target position is projected into the second grid to obtain a first shear wave velocity model; for each depth at each node in the second grid, spatial interpolation is performed on the basis of the first shear wave velocity model to obtain an initial shear wave velocity model.

[0056] In this implementation, the electronic device can invert 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, the depth-shear wave velocity pair at the target position is projected into the second grid to obtain the shear wave velocity distribution in the three-dimensional space, that is, the first shear wave velocity model, and then the first shear wave velocity model is divided according to the depth. For example, the electronic device divides the first shear wave velocity model into H depths according to the depth. For each depth at each node, spatial interpolation is performed to obtain an initial shear wave velocity model.

[0057] See also Figure 4 , Figure 4 (a) is a three-dimensional seismic observation system. Figure 4 (b) is Figure 4 The surface wave data collected by the shot point shown in (a) and the nearest receiving line to the left of the shot point, Figure 4 (c) is Figure 4 The phase velocity dispersion curve corresponding to the surface wave data in (b) is: Figure 4 (d) is the shear wave velocity structure at the midpoint of the receiving line on the left side of the shot point. Figure 4 It can be seen in (d) that different depths correspond to different shear wave velocities.

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

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

[0060] In this implementation, the electronic device top-cuts and bottom-cuts the single-shot seismic record according to the apparent velocity distribution range of the surface wave, extracts the surface wave data, and then performs time-frequency analysis on the surface wave data corresponding to each shot inspection pair, thereby obtaining the observed travel time of the single-frequency surface wave component.

[0061] See also Figure 5 , Figure 5 (a) is a schematic diagram of top cutting and bottom cutting of single shot seismic records. Figure 5 (b) is Figure 5 The surface wave data obtained in (a) is Figure 5 (c) is Figure 5 (b) Surface wave data of a seismic trace. Figure 5 (d) is Figure 5 The time-frequency analysis diagram of the surface wave data shown in (c) is used to represent the relationship between time and frequency. Figure 5 In (d), the time corresponding to each single-frequency surface wave component can be determined, that is, the observed travel time.

[0062] One point that needs to be explained is that after the electronic device obtains the first seismic data, it can first determine the initial shear wave velocity model based on the first seismic data, and then determine the observed travel time of each single-frequency surface wave component in each shot-check pair. It can also first determine the observed travel time of each single-frequency surface wave component in each shot-check pair, and then determine the initial shear wave velocity model. There is no specific limitation on this order.

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

[0064] This step can be implemented by following the 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 by 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 the depth h at the nth node is represented by b nh . Wherein, n is a positive integer, and h=1, 2, ..., H. Wherein, the nodes in the second grid are the vertices of the grid units in the second grid.

[0069] (1-2) The electronic device substitutes the shear wave velocity at each depth at each node in the second grid into the third relationship 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 shear wave velocity and the longitudinal wave velocity.

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

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

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

[0075] In the embodiment of the present application, the fourth relationship data can be expressed as: nh =0.31a nh0.25 ; where ρ nh 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 relationship data to obtain the corresponding density.

[0077] (1-4) The electronic device determines a surface wave group velocity dispersion curve for each node in the second grid based on the shear 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 of each node in the second grid using a Thomson-Haskell matrix method based on the shear 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 at each node in the second grid based on the surface wave group velocity dispersion curve of each node in the second grid.

[0080] The surface wave group velocity dispersion curve is a curve showing the surface wave group velocity changing with frequency. The electronic device determines 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.

[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 first relationship data and the group velocity of the single-frequency surface wave component of each node in the second grid.

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

[0083] In the embodiment of the present application, the first relationship data can be expressed as:

[0084]

[0085] Among them, V j (f) represents the group velocity of the single-frequency surface wave component of frequency f at the jth node in the first grid, υ n (f) represents the group velocity of the single-frequency surface wave component of frequency f at the nth node in the second grid, γ jnIt represents the interpolation coefficient of the single-frequency surface wave component group velocity of frequency f at the nth node in the second grid generated by the bicubic B-spline interpolation method according to the single-frequency surface wave component group velocity of frequency f at the jth node in the first grid, and 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 coefficient of each node in the second grid into the first relationship data to obtain the f-frequency single-frequency surface wave component group velocity of the node.

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

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

[0089] (4) For each shot detection pair, the electronic device determines, on the undulating surface of the ground, a plurality of ray path segments corresponding to each single-frequency surface wave component in the shot detection pair 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 detection point in the shot-detection pair.

[0091] For each shot-detection pair, the electronic device uses the fast marching method to track the K ray path segments of the single-frequency surface wave component with a frequency of f from the shot point to the detection point based on the group velocity of each single-frequency surface wave component of each node in the first grid. The lengths of the K ray path segments can be expressed as d 1 d 2 ……d k ……d K , K is a positive integer. Figure 6 , Figure 6 It is a schematic diagram of multiple ray path segments from the shot point to the detection point traced on the undulating surface.

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

[0093] The second relationship 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 detection pair, the multiple ray path segments corresponding to the i-th shot detection pair, and the group velocity of the f-frequency single-frequency surface wave component of each node in the second grid, and i is a positive integer.

[0094] In the embodiment of the present application, the second relationship data can be expressed as:

[0095]

[0096] Among them, t i (f) represents the theoretical travel time of the single-frequency surface wave component of frequency f in the ith shot pair, γ kn represents the interpolation coefficient of the surface wave component group velocity at the midpoint of the k-th ray path segment generated by the bicubic B-spline interpolation method based on the single-frequency surface wave component group velocity of the f-th node in the second grid,

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

[0098] Step 205: The electronic device constructs 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 detection pair.

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

[0100] (1) Electronic equipment determines the traveltime error between the observed traveltime and the theoretical traveltime.

[0101] For each shot-detection pair, the electronic device determines the difference between the observed traveltime and the theoretical traveltime of each single-frequency surface wave component in the shot-detection pair to obtain the traveltime error.

[0102] One thing that needs to be explained is that the observed travel time is obtained through the collected seismic data, and the theoretical travel time is calculated through the initial shear wave velocity model. There is inevitably a certain error between the two, which is the travel time error.

[0103] (2) The electronic device determines a first sensitivity, a second sensitivity, and a 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 shear wave velocity, the longitudinal wave velocity, and the density at each depth at each node in the second grid.

[0104] Among them, the first sensitivity is used to represent the rate of change of the group velocity of the single-frequency surface wave component relative to the shear wave velocity in the depth direction, the second sensitivity is used to represent the rate of change of the group velocity of the single-frequency surface wave component relative to the longitudinal wave velocity in the depth direction, and the third sensitivity is used to represent the rate of change of the group velocity of the single-frequency surface wave component 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 the node relative to the shear wave velocity in the depth direction to obtain a first sensitivity; determines the rate of change of the group velocity of each single-frequency surface wave component of the node relative to the longitudinal wave velocity in the depth direction to obtain a second sensitivity; determines the rate of change of the group velocity of each single-frequency surface wave component of the node relative to the density in the depth direction to obtain a third sensitivity.

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

[0107] Among them, the fifth relationship data is used to represent the relationship between the change in the group velocity of the f-frequency single-frequency surface wave component of the n-th node in the second grid, the change in the shear wave velocity, the first sensitivity, the second sensitivity and the third sensitivity, and the sixth relationship 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 n-th node in the second grid.

[0108] In the embodiment of the present application, the fifth relationship data can be expressed as:

[0109]

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

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

[0112]

[0113] Among them, Δt i (f) represents the travel time error, represents the theoretical travel time of the single-frequency surface wave component of frequency f in the ith shot pair, represents the observed travel time of the single-frequency surface wave component of frequency f in the ith shot pair.

[0114] The electronic device converts Δυ in the fifth relationship datan (f) Substituting into the sixth relationship data, the part other than the travel time error and the shear wave velocity variation is determined as the first sensitivity matrix.

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

[0116] In the embodiment of the present application, the electronic device constructs the objective function based on the first sensitivity matrix, the travel time error and the shear wave velocity variation: d=Gm;

[0117] Where d represents the travel time error vector of Q single-frequency surface wave components on P shot-detection pairs, which is composed of multiple travel time errors, Q is the total number of frequencies, P is the total number of shot-detection pairs, d = [Δt 1 (f 1 ), ..., Δt p (f 1 ), Δt 1 (f 2 ), ..., Δt p (f 2 ), ..., Δt 1 (f Q ), ..., Δt p (f Q )] T m represents the disturbance vector of the shear wave velocity at H depths at N nodes in the second grid, which is 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 travel time error source of a single-frequency surface wave vector on a shot-detection 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 a preset condition, thereby obtaining a target shear wave velocity model.

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

[0120] (1) The electronic device determines the change in shear 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 equation system, and the electronic device can use the LSQR (least squares QR decomposition) algorithm to solve the objective function to obtain the shear wave velocity change 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 shear wave velocity change at each depth at each node in the second grid to obtain an 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 shear wave velocity at the depth at the node is increased by the shear wave velocity change at the depth at the node to obtain an updated shear wave velocity at the depth at the node, thereby obtaining an 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 detection 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, thereby obtaining the target shear wave velocity model.

[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 is determined whether the travel time error meets the preset conditions. If the preset conditions are met, the updated shear wave velocity model is used as the target shear wave velocity model. If the preset conditions are not met, the objective function is reconstructed, and the shear wave velocity change at each depth at each node in the second grid is re-determined based on the reconstructed objective function. The shear wave velocity model is updated again based on the re-determined shear wave velocity change. The above steps are repeated until the travel time error meets the preset conditions, and the shear wave velocity model corresponding to the travel time error meeting the preset conditions is used as the target shear wave velocity model. See Figure 7 , Figure 7 is a schematic diagram of the target shear wave velocity model finally obtained. Figure 7 The shear wave velocities at different depths are shown in Figure .

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

[0127] In order to more clearly illustrate the solution of this application, Figure 8 and Fig. 9 See Figure 8Based on the first seismic data, the electronic device calculates the observed travel time of each single-frequency surface wave component in each shot-detection pair according to the shot-detection pair cycle, determines whether the current shot-detection pair is the last shot-detection pair, and if it is the last shot-detection pair, obtains the observed travel time of all single-frequency surface wave components. In addition, based on the first seismic data, the electronic device performs multi-channel transient surface wave analysis on the receiving line closest to the shot point according to the shot point cycle to obtain the depth-transverse wave velocity structure of the target position, determines whether the current shot point is the last shot point, and if it is the last shot point, performs three-dimensional space interpolation to obtain the initial transverse wave velocity model. In addition, the electronic device also performs triangulated surface interpolation based on the measurement results of the shot points and the detection points to generate a three-dimensional surface undulation surface.

[0128] Based on the initial shear wave velocity model, the electronic device forward models the surface wave group velocity dispersion curve to obtain the group velocity of all surface wave components, and then performs three-dimensional surface undulation ray tracing for all gun inspection pairs according to the surface wave component cycle, calculates the ray path segment and theoretical travel time of the single-frequency surface wave component, and constructs the first sensitivity matrix. Determine whether the current single-frequency surface wave component is the last frequency component. If it is the last frequency component, calculate the travel time error vector based on the observed travel time and the theoretical travel time, establish and solve the objective function, and determine whether the travel time error meets the preset conditions. If it does not meet the preset conditions, update the shear wave velocity model until the conditions are met to obtain the target shear wave velocity model.

[0129] See also Fig. 9 The electronic device extracts single-shot seismic data from the first seismic data, and then determines the observed travel time of the single-frequency surface wave component and constructs an initial shear wave velocity model based on the single-shot seismic data. A target function is constructed based on the observed travel time and the initial shear wave velocity model, and a target shear wave velocity model is obtained by solving the target function and iteratively updating it.

[0130] According to the above content, the process of determining the target shear wave velocity model involves the following processes: constructing a three-dimensional surface undulation, constructing an initial shear wave velocity model, determining the observed travel time of all single-frequency surface wave components, determining the theoretical travel time of all single-frequency surface wave components, constructing a target function, and updating the shear wave velocity model. In practical applications, electronic devices can implement the corresponding processes through different functional modules, see Fig.10 .

[0131] In summary, this application is based on the principle that the near-surface shear wave velocity structure is closely related to the surface wave dispersion. It uses the surface wave data collected by oil and gas seismic exploration to perform travel time inversion, uses the measurement results of shot points and detection points to establish a three-dimensional surface undulation surface, and performs surface ray tracing to obtain the theoretical travel time. By solving the travel time error inversion equation, that is, the objective function iteration approximates the true near-surface shear wave velocity structure, and obtains the target shear wave velocity model. The resolution of this model in the depth direction depends on the thickness of the layer in the depth direction, and the resolution in the horizontal direction depends on the spacing of the detection points, and has the same horizontal resolution as the seismic data. This model can be used to calculate the static correction of shear waves in multi-wave and converted wave exploration, and can also be used for near-surface shear wave velocity modeling of pre-stack depth migration.

[0132] An embodiment of the present application provides a seismic data processing method, which first determines an initial shear wave velocity model based on the seismic data of a target work area, then determines the observed travel time of a single-frequency surface wave component based on the seismic data, determines the theoretical travel time of the single-frequency surface wave component based on the initial shear wave velocity model, constructs an objective function through the observed travel time and the theoretical travel time, and iteratively updates the initial shear wave velocity model based on the objective function, so as to continuously approximate the actual shear wave velocity structure and finally obtain the target shear wave velocity model.

[0133] Fig.11 is a structural diagram of a seismic data processing device provided in an embodiment of the present application, see Fig.11 , the device comprises:

[0134] A division module 1101 is used to divide the target work area into grids to obtain a first grid and a second grid; wherein the second grid is obtained by thinning the first grid;

[0135] A first determination module 1102 is used to obtain first seismic data of a target work area, and determine an initial shear wave velocity model of the target work area based on the first seismic data, wherein the initial shear wave velocity model is used to represent an initial shear wave velocity distribution at each depth at each node in the second grid;

[0136] A second determination module 1103 is used to determine the observed travel time of each single-frequency surface wave component in each shot-check pair based on the first seismic data;

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

[0138] A construction 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 detection pair, wherein the objective function is used to represent the relationship between the travel time error and the shear wave velocity variation, and the travel time error is the difference between the observed travel time and the theoretical travel time;

[0139] The updating 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 condition, thereby obtaining the target shear wave velocity model.

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

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

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

[0143] The second determination module 1103 is used to perform top 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-detection pairs; perform time-frequency analysis on the second seismic sub-data corresponding to each shot-detection pair to obtain the observed travel time of each single-frequency surface wave component in each shot-detection pair.

[0144] In another possible implementation, the third determination module 1104 is used to determine each single-frequency surface wave component group velocity of each node in the second grid based on the initial shear wave velocity model; determine each single-frequency surface wave component group velocity of each node in the first grid based on the first relationship data and each single-frequency surface wave component group velocity of each node in the second grid; wherein the first relationship data is used to represent 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, j is a positive integer, f>0; project the shot point coordinates and the detection point coordinates of each shot-detection pair onto the surface undulation surface; wherein the surface undulation surface is generated on the basis of the first grid; for each A shot-detection pair, based on the group velocity of each single-frequency surface wave component of each node in the first grid, determining a plurality of ray path segments corresponding to each single-frequency surface wave component in the shot-detection pair on the undulating curved surface of the ground; wherein the ray path segments are used to represent the distance from the shot point to the detection point in the shot-detection pair; based on the plurality of ray path segments corresponding to each shot-detection pair, the group velocity of each single-frequency surface wave component of each node in the second grid and the second relationship data, determining the theoretical travel time of each single-frequency surface wave component in each shot-detection pair; wherein the second relationship data is used to represent the relationship between the theoretical travel time of the f-frequency single-frequency surface wave component in the ith shot-detection pair, the plurality of ray path segments corresponding to the ith shot-detection pair and the group velocity of the f-frequency single-frequency surface wave component of each node in the second grid, wherein i is a positive integer.

[0145] In another possible implementation, the third determination 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 relationship data to obtain the longitudinal wave velocity at each depth at each node in the second grid; wherein the third relationship data is used to represent the relationship between the shear wave velocity and the longitudinal wave velocity; substitute the longitudinal wave velocity at each depth at each node in the second grid into the fourth relationship data to obtain the density at each depth at each node in the second grid; wherein the fourth relationship data is used to represent the relationship between the longitudinal 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, longitudinal wave velocity and density at each depth at each node in the second grid; 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 determination module 1104 is used to determine the travel time error between the observed travel time and the theoretical travel time; based on each single-frequency surface wave component group velocity of each node in the second grid, the shear wave velocity, the longitudinal wave velocity and the density at each depth at each node in the second grid, respectively determine the first sensitivity, the second sensitivity and the third sensitivity at each depth at each node in the second grid; 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 longitudinal wave velocity in the depth direction. The rate of change of density in the depth direction; construct a first sensitivity matrix based on the fifth relationship data, the sixth relationship data, the first sensitivity, the second sensitivity and the third sensitivity at each depth at each node in the second grid; wherein the fifth relationship data is used to represent the relationship between the change in the group velocity of the f-frequency single-frequency surface wave component of the n-th node in the second grid, the change in the shear wave velocity, the first sensitivity, the second sensitivity and the third sensitivity, and the sixth relationship 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 n-th node in the second grid, and n is a positive integer; construct an objective function based on the first sensitivity matrix, the travel time error and the change in the shear wave velocity.

[0147] In another possible implementation, the updating module 1106 is used to determine the amount of shear wave velocity change 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 amount of shear wave velocity change at each depth at each node in the second grid to obtain an updated shear wave velocity model; use the updated shear wave velocity model as the initial shear wave velocity model, and repeatedly perform the steps of determining the theoretical travel time of each single-frequency surface wave component in each shot-detection pair based on the initial shear wave velocity model, the first grid, and the second grid until the travel time error meets a preset condition, thereby obtaining a target shear wave velocity model.

[0148] An embodiment of the present application provides a seismic data processing device, which first determines an initial shear wave velocity model based on the seismic data of a target work area, then determines the observed travel time of a single-frequency surface wave component based on the seismic data, determines the theoretical travel time of the single-frequency surface wave component based on the initial shear wave velocity model, constructs an objective function through the observed travel time and the theoretical travel time, and iteratively updates the initial shear wave velocity model based on the objective function, so as to continuously approximate the actual shear wave velocity structure and finally obtain the target shear wave velocity model.

[0149] refer to Fig.12 , Fig.12The structure block diagram of a terminal 1200 provided by an exemplary embodiment of the present application is shown. The terminal 1200 may be a portable mobile terminal, such as a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 player (Moving Picture Experts Group Audio Layer IV), a laptop computer or a desktop computer. The terminal 1200 may also be called a user device, a portable terminal, a laptop terminal, a desktop terminal or other names.

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

[0151] The processor 1201 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 1201 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 1201 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 1201 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 1201 may also include an AI (Artificial Intelligence) processor, which is used to process computing 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 a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 1202 is used to store at least one program code, which is used to be executed by the processor 1201 to implement the seismic data processing method provided in the method embodiment of the present application.

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

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

[0155] The radio frequency circuit 1204 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 1204 communicates with the communication network and other communication devices through electromagnetic signals. The radio frequency circuit 1204 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the radio frequency 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, and the like. The radio frequency circuit 1204 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: the World Wide Web, a metropolitan area network, an intranet, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 1204 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0156] The display screen 1205 is used to display a UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 1205 is a touch display screen, the display screen 1205 also has the ability to collect touch signals on the surface or above the surface of the display screen 1205. The touch signal can be input to the processor 1201 as a control signal for processing. At this time, the display screen 1205 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the display screen 1205 can be one, set on the front panel of the terminal 1200; in other embodiments, the display screen 1205 can be at least two, respectively set on different surfaces of the terminal 1200 or in a folding design; in other embodiments, the display screen 1205 can be a flexible display screen, set on a curved surface or a folding surface of the terminal 1200. Even, the display screen 1205 can also be set to a non-rectangular irregular shape, that is, a special-shaped 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 capture images or videos. Optionally, the camera assembly 1206 includes a front camera and a rear camera. Typically, the front camera is arranged on the front panel of the terminal, and the rear camera is arranged on the back of the terminal. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, a wide-angle camera, and a telephoto camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, the fusion of the main camera and the wide-angle camera to realize the panoramic shooting and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 1206 may also include a flash. The flash can be a monochrome temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold 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, and convert the sound waves into electrical signals and input them into the processor 1201 for processing, or input them into the radio frequency circuit 1204 to achieve voice communication. For the purpose of stereo acquisition or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the terminal 1200. The microphone may also be an array microphone or an omnidirectional acquisition microphone. The speaker is used to convert the electrical signal from the processor 1201 or the radio frequency circuit 1204 into sound waves. The speaker may be a traditional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 1207 may also include a headphone jack.

[0159] The power supply 1208 is used to power various components in the terminal 1200. The power supply 1208 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the 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 charged through a wired line, and a wireless rechargeable battery is a battery charged through 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] The acceleration sensor 1210 can detect the magnitude of acceleration on the three coordinate axes of the coordinate system established by the terminal 1200. For example, the acceleration sensor 1210 can be used to detect the components of gravity acceleration on the three coordinate axes. The processor 1201 can control the display screen 1205 to display the user interface in a horizontal view or a vertical view based on the gravity acceleration signal collected by the acceleration sensor 1210. The acceleration sensor 1210 can also be used to collect motion data of games or users.

[0162] The gyro sensor 1211 can detect the body direction and rotation angle of the terminal 1200, and the gyro sensor 1211 can cooperate with the acceleration sensor 1210 to collect the user's 3D actions on the terminal 1200. Based on the data collected by the gyro sensor 1211, the processor 1201 can implement the following functions: motion sensing (such as changing the UI based on the user's tilt operation), image stabilization during shooting, game control, and inertial navigation.

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

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

[0165] The proximity sensor 1214, also called a distance sensor, is usually arranged on the front panel of the terminal 1200. The proximity sensor 1214 is used to collect 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 the screen-on state to the 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 the screen-off state to the screen-on state.

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

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

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

[0169] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0170] The above description is only for the purpose of facilitating those skilled in the art to understand the technical solution of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for processing seismic data, characterized in that: The method comprises: Divide the target work area into grids to obtain a first grid and a second grid; wherein the second grid is obtained by thinning the first grid; Acquire first seismic data of the target work area, and determine an initial shear wave velocity model of the target work area based on the first seismic data, wherein the initial shear wave velocity model is used to represent an initial shear wave velocity distribution at each depth at each node in the second grid; Determining the observed travel time of each single-frequency surface wave component in each shot-check pair based on the first seismic data; Determining a theoretical travel time of each single-frequency surface wave component in each shot-detection pair based on the initial shear wave velocity model, the first grid, and the second grid; Based on the observed traveltime, theoretical traveltime and shear wave velocity variation of each single-frequency surface wave component in each shot detection pair, constructing an objective function, wherein the objective function is used to represent the relationship between the traveltime error and the shear wave velocity variation, and the traveltime error is the difference between the observed traveltime and the theoretical traveltime; Based on the objective function, the initial shear wave velocity model is iteratively updated until the travel time error meets a preset condition, thereby obtaining a 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 a plurality of shot points, wherein the first seismic sub-data is surface wave data collected by a detection point on a receiving line closest to the shot point; The determining, based on the first seismic data, an initial shear wave velocity model of the target work area comprises: For each shot point, a dispersion spectrum analysis is performed on the first seismic sub-data corresponding to the shot point to obtain a phase velocity dispersion curve; Inverting the phase velocity dispersion curve to obtain a shear wave velocity structure at a target position; wherein the target position is the midpoint position of the receiving line, and the shear wave velocity structure is used to represent the shear wave velocities corresponding to different depths; Based on the spatial coordinates of the target position, projecting the shear wave velocity structure at the target position into the second grid to obtain a 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 a plurality of shot points, wherein the first seismic sub-data is surface wave data collected by a detection point on a receiving line closest to the shot point; The step of determining the observed travel time of each single-frequency surface wave component in each shot-check pair based on the first seismic data comprises: For each shot point, top-cutting and bottom-cutting are performed on the first seismic sub-data corresponding to the shot point to obtain second seismic sub-data; wherein the first seismic sub-data includes second seismic sub-data of multiple shot-detection pairs; A time-frequency analysis is performed on the second seismic sub-data corresponding to each shot-detection pair to obtain the observed travel time of each single-frequency surface wave component in each shot-detection pair.

4. The method according to claim 1, characterized in that The step of determining the theoretical travel time of each single-frequency surface wave component in each shot-detection pair based on the initial shear wave velocity model, the first grid, and the second grid comprises: determining, based on the initial shear wave velocity model, a group velocity of each single-frequency surface wave component of each node in the second grid; Determine the group velocity of each single-frequency surface wave component of each node in the first grid based on the first relationship data and the group velocity of each single-frequency surface wave component of each node in the second grid; wherein the first relationship data is used to represent the relationship between the group velocity of the single-frequency surface wave component of the frequency f of the j-th node in the first grid and the group velocity of the single-frequency surface wave component of the frequency f of each node in the second grid, j is a positive integer, and f>0; Projecting the shot point coordinates and the detection point coordinates of each shot-detection pair onto a undulating curved surface; wherein the undulating curved surface is generated based on the first grid; For each shot-detection pair, based on the group velocity of each single-frequency surface wave component of each node in the first grid, a plurality of ray path segments corresponding to each single-frequency surface wave component in the shot-detection pair are determined on the surface undulation surface; wherein the ray path segments are used to represent the distance from the shot point to the detection point in the shot-detection pair; Based on the multiple ray path segments corresponding to each shot inspection pair, the group velocity of each single-frequency surface wave component of each node in the second grid and the second relationship data, the theoretical travel time of each single-frequency surface wave component in each shot inspection pair is determined; wherein the second relationship data is used to represent the relationship between the theoretical travel time of the f-frequency single-frequency surface wave component in the ith shot inspection pair, the multiple ray path segments corresponding to the ith shot inspection pair and the group velocity of the f-frequency single-frequency surface wave component of each node in the second grid, and i is a positive integer.

5. The method according to claim 4, characterized in that The determining, based on the initial shear wave velocity model, a group velocity of each single-frequency surface wave component of each node in the second grid comprises: Determining the shear wave velocity at each depth at each node in the second grid based on the initial shear wave velocity model; Substituting the shear wave velocity at each depth at each node in the second grid into the third relationship data to obtain the longitudinal wave velocity at each depth at each node in the second grid; wherein the third relationship 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 relationship data to obtain the density at each depth at each node in the second grid; wherein the fourth relationship data is used to represent the relationship between the P-wave velocity and the density; determining a surface wave group velocity dispersion curve for each node in the second grid based on the shear wave velocity, the longitudinal wave velocity and the density at each depth at 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 based on the surface wave group velocity dispersion curve of each node in the second grid.

6. The method according to claim 5, 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 detection pair, including: determining a traveltime error between the observed traveltime and the theoretical traveltime; Based on the group velocity of each single-frequency surface wave component of each node in the second grid, the shear wave velocity, the longitudinal wave velocity and the density at each depth at each node in the second grid, respectively determine the first sensitivity, the second sensitivity and the third sensitivity at each depth at each node in the second grid; wherein the first sensitivity is used to represent the rate of change of the group velocity of the single-frequency surface wave component relative to the shear wave velocity in the depth direction, the second sensitivity is used to represent the rate of change of the group velocity of the single-frequency surface wave component relative to the longitudinal wave velocity in the depth direction, and the third sensitivity is used to represent the rate of change of the group velocity of the single-frequency surface wave component relative to the density in the depth direction; A first sensitivity matrix is ​​constructed based on the fifth relationship data, the sixth relationship data, the first sensitivity, the second sensitivity and the third sensitivity at each depth at each node in the second grid; wherein the fifth relationship data is used to represent the relationship between the change in the group velocity of the single-frequency surface wave component of the f frequency at the n-th node in the second grid, the change in the shear wave velocity, the first sensitivity, the second sensitivity and the third sensitivity; and the sixth relationship data is used to represent the relationship between the travel time error and the change in the group velocity of the single-frequency surface wave component of the f frequency at the n-th 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 shear wave velocity variation.

7. The method according to claim 1, characterized in that The iterative updating of the initial shear wave velocity model based on the objective function until the travel time error satisfies a preset condition to obtain a target shear wave velocity model comprises: Based on the objective function, determining a change in shear wave velocity at each depth at each node in the second grid; Based on the shear wave velocity variation at each depth at each node in the second grid, updating the initial shear wave velocity model to obtain an updated shear wave velocity model; The updated shear wave velocity model is used as the initial shear wave velocity model, and the step of determining the theoretical travel time of each single-frequency surface wave component in each shot-detection pair based on the initial shear wave velocity model, the first grid, and the second grid is repeatedly performed until the travel time error meets a preset condition, thereby obtaining the target shear wave velocity model.

8. A seismic data processing device, characterized in that: The device comprises: A division module, used for dividing the target work area into grids to obtain a first grid and a second grid; wherein the second grid is obtained by thinning the first grid; A first determination module is used to obtain first seismic data of the target work area, and determine an initial shear wave velocity model of the target work area based on the first seismic data, wherein the initial shear wave velocity model is used to represent an initial shear wave velocity distribution at each depth at each node in the second grid; A second determination module is used to determine the observed travel time of each single-frequency surface wave component in each shot-check pair based on the first seismic data; A third determination module is used to determine the theoretical travel time of each single-frequency surface wave component in each shot-detection pair based on the initial shear wave velocity model, the first grid and the second grid; A construction module, configured to construct an objective function based on the observed traveltime, theoretical traveltime and shear wave velocity variation of each single-frequency surface wave component in each shot detection pair, wherein the objective function is used to represent the relationship between the traveltime error and the shear wave velocity variation, and the traveltime error is the difference between the observed traveltime and the theoretical traveltime; An updating module is used to iteratively update the initial shear wave velocity model based on the objective function until the travel time error meets a preset condition, thereby obtaining a target shear wave velocity model.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one program code, and the at least one program code is loaded and executed by the processor to implement the seismic data processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one program code, and the at least one program code is loaded and executed by a processor to implement the seismic data processing method according to any one of claims 1 to 7.

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