Near-surface velocity modeling method and device

Abstract

The invention discloses a near-surface velocity modeling method and device. The method comprises the following steps: establishing a three-dimensional grid of a research area, and obtaining an initial speed model; determining first arrival travel time data corresponding to the current speed model by using a discontinuous Galerkin solution method based on the eikonal equation; determining a residual error between the current first arrival travel time data and the first arrival travel time data picked up based on the seismic record, and judging whether the current residual error meets a residual error threshold value or not; if not, the real detection point serves as a seismic source point, the real seismic source point serves as a detection point, the current residual error is subjected to back propagation through discontinuous Galerkin solution of the eikonal equation, the updating gradient of the speed model is determined, the updating step length is determined by combining a setting method, the speed model is updated, and first arrival travel time data is subjected to forward modeling again; and if yes, determining the current speed model as the speed model of the research area. According to the method, a high-precision discontinuous Galerkin travel time calculation method and an accompanying state inversion framework are combined, and the near-surface speed modeling precision is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of petroleum seismic exploration, and in particular to a near-surface velocity modeling method and device. Background Art

[0002] In the field of petroleum geophysical exploration, the importance of near-surface velocity models cannot be underestimated, especially in complex mountainous areas. The complexity of the surface conditions and subsurface structures in these areas makes high-precision imaging extremely challenging, hindering accurate representation of the subsurface. Therefore, solving the problem of near-surface velocity modeling is a key factor in overcoming the difficulties of seismic exploration in complex areas. The accuracy of near-surface velocity models is crucial for both time-domain denoising and depth-domain imaging.

[0003] Near-surface velocity modeling is crucial for imaging complex structures, and a variety of techniques are used to build near-surface models. From the early use of seismic refraction to create crude refraction models, to the emergence of revolutionary ray tomography, the accuracy of near-surface velocity models has been greatly improved, supporting the continued development of subsequent static correction and depth-domain imaging. Summary of the Invention

[0004] In order to enrich product types, enrich process routes, and increase selection space, an embodiment of the present invention provides a near-surface velocity modeling method and device, which combines a high-precision discontinuous Galerkin travel time calculation method and an adjoint state inversion framework to improve the accuracy of near-surface velocity modeling.

[0005] In a first aspect, an embodiment of the present invention provides a near-surface velocity modeling method, comprising:

[0006] Establishing a three-dimensional grid for a study area and obtaining an initial velocity model under the three-dimensional grid;

[0007] Based on the Eikonal equation, the discontinuous Galerkin solution method is used to determine the first arrival travel time data corresponding to the current velocity model.

[0008] Determine the residual between the current first arrival travel time data and the first arrival travel time data picked based on the earthquake record, and judge whether the current residual meets the residual threshold;

[0009] If not, take the real detection point as the source point, take the real source point as the detection point, back-propagate the current residual through the discontinuous Galerkin solution of the Eikonal equation, determine the update gradient of the velocity model, determine the update step size of the velocity model in combination with the setting method, update the velocity model, return to execute the discontinuous Galerkin solution method based on the Eikonal equation, and determine the first arrival traveltime data corresponding to the current velocity model;

[0010] If so, the current velocity model is determined as the velocity model of the study area.

[0011] In a second aspect, an embodiment of the present invention provides a near-surface velocity modeling device, comprising:

[0012] An initial velocity model acquisition module is used to establish a three-dimensional grid in the study area and obtain an initial velocity model under the three-dimensional grid;

[0013] The first arrival travel time forward modeling module is used to determine the first arrival travel time data corresponding to the current velocity model based on the Eikonal equation using the discontinuous Galerkin solution method;

[0014] A judgment module is used to determine the residual between the current first arrival travel time data and the first arrival travel time data picked based on the earthquake record, and to judge whether the current residual meets the residual threshold;

[0015] a velocity model updating module, configured to, if the judgment module determines that the result is negative, use the actual detection point as the source point, reversely propagate the current residual error through the discontinuous Galerkin solution of the eikonal equation, determine the updated gradient of the velocity model, determine the updated step size of the velocity model in combination with a setting method, and update the velocity model; and the first arrival traveltime forward modeling module is further configured to determine the first arrival traveltime data corresponding to the updated velocity model.

[0016] The velocity model determining module is configured to determine the current velocity model as the velocity model of the study area if the determination module determines that the current velocity model is yes.

[0017] In a third aspect, an embodiment of the present invention provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and when the computer executable instructions are executed by a processor, the above-mentioned near-surface velocity modeling method is implemented.

[0018] In a fourth aspect, an embodiment of the present disclosure provides a server comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned near-surface velocity modeling method when executing the program.

[0019] The beneficial effects of the above technical solutions provided by the embodiments of the present invention include at least:

[0020] The near-surface velocity modeling method provided by the embodiment of the present invention combines the discontinuous Galerkin method forward travel time with the adjoint state inversion framework. The forward modeling process avoids the drawbacks of ray tracing and improves the accuracy of travel time calculation. At the same time, the inversion efficiency is not affected by the number of detection points, thereby improving the accuracy and efficiency of modeling.

[0021] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0022] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0024] Figure 1 This is a flow chart of a near-surface velocity modeling method according to an embodiment of the present invention;

[0025] Figure 2 A schematic diagram of a three-dimensional grid established in an embodiment of the present invention;

[0026] Figure 3 Schematic diagram of the initial velocity model in an embodiment of the present invention;

[0027] Figure 4 Schematic diagram of the three-dimensional travel time field in an embodiment of the present invention;

[0028] Figure 5 Schematic diagram of the inversion velocity model in an embodiment of the present invention;

[0029] Figure 6 Schematic diagram of the structure of the near-surface velocity modeling device in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0031] It should be understood that the terms described in the present invention are only for describing special embodiments and are not intended to limit the present invention. Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which the present invention pertains. Although the present invention has only described preferred methods and materials, any methods and materials similar or equivalent to those described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods and / or materials associated with the documents. In the event of any conflict with any incorporated document, the content of this specification shall prevail.

[0032] During their work, the inventors discovered that under complex underground geological conditions, the traditional ray tracing algorithm used for near-surface velocity modeling cannot accurately simulate the propagation path of seismic waves. Consequently, it suffers from inherent disadvantages such as low precision and ray shadowing, which directly restrict the accuracy of near-surface velocity modeling. Furthermore, at the inversion level, ray tracing tomography requires the calculation of Frechet derivatives and the establishment of a set of inversion equations. Large-scale data acquisition and observation systems inevitably lead to a large set of equations and a massive amount of computation.

[0033] To overcome the shortcomings of current seismic ray tracing and ray tracing tomographic inversion algorithms and improve the accuracy of velocity modeling, the inventors conducted further research and proposed improvements at both the forward modeling and inversion levels, resulting in the present invention. This embodiment of the present invention provides a near-surface velocity modeling method and apparatus that combines a high-precision discontinuous Galerkin traveltime calculation method with an adjoint state inversion framework to improve the accuracy of near-surface velocity modeling.

[0034] Example

[0035] The embodiment of the present invention provides a near-surface velocity modeling method, the process of which is as follows Figure 1 As shown, the following steps are included:

[0036] Step S11: Establish a three-dimensional grid in the study area and obtain an initial velocity model under the three-dimensional grid.

[0037] According to the topography of the study area and the inversion target depth, a set grid generation method, such as hexahedral or tetrahedral grid generation method, is used to establish a three-dimensional grid of the study area.

[0038] To build a grid, you must first establish a geometric shape, and then use an algorithm to generate a grid to approximate the geometric shape. For near-surface velocity modeling, the geometric shape is generally simple. The top surface is generally the terrain, and the bottom surface is determined according to the inversion target depth, generally a plane 2000 to 3000 meters away from the top surface. The other four planes are determined according to the acquisition range of the observation system to form a hexahedron. The hexahedron is meshed. Tetrahedral meshes are more suitable for describing irregular shapes. They are generally generated using the Delaunay triangulation algorithm, but the calculation accuracy and stability may be defective; the hexahedral mesh scheme is computationally stable and is sufficient to describe terrain changes in exploration seismic. There are many generation algorithms, and the mapping method and adaptive method have mature algorithms. In actual use, you can rely on the open source software gmsh or other software to carry out grid construction. See Figure 2 As shown in Figure 2, a schematic diagram of the established three-dimensional grid is shown.

[0039] The initial velocity model can be transformed from the refraction model, or a gradient model can be established that gradually increases from the surface downwards. Figure 3 The figure shows the schematic diagram of the initial velocity model.

[0040] Step S12: Based on the Eikonal equation, the discontinuous Galerkin solution method is used to determine the first arrival travel time data corresponding to the current velocity model.

[0041] Forward modeling is the basis of inversion and also the guarantee of inversion accuracy. In the embodiment of the present invention, the discontinuous Galerkin method is used to solve the eikonal equation to ensure the accuracy of travel time calculation. The discontinuous Galerkin method (DGM) is a finite element method (FEM), but it has certain advantages over the conventional finite element method when solving partial differential equations and difference equations. DGM is a discontinuous method that allows the solution to have jumps between finite element units. This means that the value of the solution can be discontinuous on the unit boundary. This makes DGM very suitable for dealing with problems containing discontinuities, such as shock waves, fractures, etc. Conventional finite elements usually use continuous basis functions, requiring the solution to be continuous between finite element units. This makes conventional FEM more suitable for dealing with smooth problems and less suitable for dealing with jumps or discontinuities.

[0042] Therefore, the discontinuous Galerkin method is particularly suitable for calculating problems involving complex underground media and complex surfaces (boundaries). It solves the Eikonal equation on a discrete grid and can adapt to dramatically undulating surfaces and complex underground structures.

[0043] First, the eikonal equation must be converted to a difference scheme, which divides time and space into discrete computational units. At each time or space step, an initial solution is assumed, and then the difference scheme is used to compute the solution for the next time or space step. This process is repeated until the required accuracy or convergence criteria are achieved.

[0044] Based on the Eikonal equation and the current velocity model, the discontinuous Galerkin solution method is used. After several scanning iterations, the first arrival travel time data obtained by the current scan meets the convergence conditions, and the first arrival travel time data corresponding to the current velocity model is obtained.

[0045] Based on the discontinuous Galerkin solution of the Eikonal equation, the single shot travel time field is obtained. By extracting the travel time from the detection point position, the first arrival travel time data can be obtained. Figure 4 As shown in Figure 1, the first arrival travel time data obtained is a schematic diagram of the three-dimensional travel time field.

[0046] Furthermore, the first arrival travel time data obtained by the current scan meets the convergence condition, which can be that the difference between the first arrival travel time data obtained by the current scan and the first arrival travel time data obtained by the previous scan is less than a set threshold.

[0047] Step S13: Determine the residual between the current first arrival travel time data and the first arrival travel time data picked based on the earthquake record, and judge whether the current residual meets the residual threshold.

[0048] For the same shot point and the same receiver point position, the difference between the first arrival travel time extracted from the current first arrival travel time data and the first arrival travel time picked based on the seismic record is determined to obtain the residual between the current first arrival travel time data and the first arrival travel time data picked based on the seismic record.

[0049] The first arrival travel time residual represents the travel time difference caused by the error between the current velocity model and the true velocity model.

[0050] If the answer of step S13 is yes, go to step S15; if the answer of step S13 is no, go to step S14.

[0051] Step S14: Taking the real detection point as the source point, backpropagating the current residual through the discontinuous Galerkin solution of the Eikonal equation, determining the update gradient of the velocity model, determining the update step size of the velocity model in combination with the setting method, and updating the velocity model.

[0052] The velocity model update gradient is solved by the adjoint state method. After the gradient calculation is completed, only the direction of the velocity update is determined, and the update step size also needs to be calculated.

[0053] A variety of methods can be used, such as L-bfgs, steepest descent method, etc., to calculate the appropriate update step size through certain judgment criteria (such as the Wolfe criterion).

[0054] For example, the line-search method is used to update the step size, that is, multiple update step sizes are set, and for each update step size, the corresponding first arrival travel time residual is determined to obtain multiple arrays containing the update step size and the corresponding first arrival travel time residual. The update step size corresponding to the minimum first arrival travel time residual is determined by the curve fitting method as the update step size of the velocity model.

[0055] Furthermore, for each update step, the corresponding first arrival traveltime residual is determined, including, for each update step, updating the velocity model according to the update gradient and the update step; based on the eikonal equation, using the discontinuous Galerkin solution method, determining the first arrival traveltime data corresponding to the updated velocity model; determining the residual between the first arrival traveltime data and the first arrival traveltime data picked up based on the seismic record as the first arrival traveltime residual corresponding to the update step.

[0056] See also Figure 5 The figure shows the inversion, i.e. the updated velocity model schematic.

[0057] After step S14, the process returns to step S12.

[0058] Step S15: Determine the current velocity model as the velocity model of the study area.

[0059] If the current initial arrival travel time residual satisfies the residual threshold, the current velocity model is determined to be sufficiently accurate and is used as the velocity model for the study area.

[0060] The near-surface velocity modeling method provided by the embodiment of the present invention combines the discontinuous Galerkin method forward travel time with the adjoint state inversion framework. The forward modeling process avoids the drawbacks of ray tracing and improves the accuracy of travel time calculation. At the same time, the inversion efficiency is not affected by the number of detection points, thereby improving the accuracy and efficiency of modeling.

[0061] Based on the inventive concept of the present invention, an embodiment of the present invention further provides a near-surface velocity modeling device, the structure of which is as follows: Figure 6 Shown, including:

[0062] An initial velocity model acquisition module 61 is used to establish a three-dimensional grid of a study area and obtain an initial velocity model under the three-dimensional grid;

[0063] The first arrival travel time forward modeling module 62 is used to determine the first arrival travel time data corresponding to the current velocity model based on the Eikonal equation using the discontinuous Galerkin solution method;

[0064] A judgment module 63 is used to determine the residual between the current first arrival travel time data and the first arrival travel time data picked based on the earthquake record, and to determine whether the current residual meets the residual threshold;

[0065] The velocity model updating module 64 is configured to, if the judgment module 63 determines that the result is negative, use the actual detection point as the source point, reversely propagate the current residual error through the discontinuous Galerkin solution of the eikonal equation, determine the updated gradient of the velocity model, determine the updated step size of the velocity model in combination with the set method, and update the velocity model. The first arrival traveltime forward modeling module 62 is also configured to determine the first arrival traveltime data corresponding to the updated velocity model.

[0066] The velocity model determining module 65 is configured to determine the current velocity model as the velocity model of the study area if the determination module 63 determines that the current velocity model is the velocity model of the study area.

[0067] In some embodiments, the first arrival traveltime forward modeling module 62 uses the discontinuous Galerkin solution method based on the eikonal equation to determine the first arrival traveltime data corresponding to the current velocity model, which is used to:

[0068] Based on the Eikonal equation and the current velocity model, the discontinuous Galerkin solution method is used. After several scanning iterations, the first arrival travel time data obtained by the current scan meets the convergence conditions, and the first arrival travel time data corresponding to the current velocity model is obtained.

[0069] In some embodiments, the velocity model updating module 64, which determines the update step size of the velocity model by combining the setting method, is used to:

[0070] Set multiple update step sizes, determine the corresponding first arrival travel time residual for each update step size, and obtain multiple arrays containing update step sizes and corresponding first arrival travel time residuals. Use the curve fitting method to determine the update step size corresponding to the minimum first arrival travel time residual, which is used as the update step size of the velocity model.

[0071] In some embodiments, the velocity model updating module 64 determines the corresponding first arrival travel time residual for each update step, which is used to:

[0072] For each update step, the velocity model is updated according to the update gradient and the update step. Based on the Eikonal equation, the discontinuous Galerkin solution method is used to determine the first arrival traveltime data corresponding to the updated velocity model. The residual between the first arrival traveltime data and the first arrival traveltime data picked up based on the seismic record is determined as the first arrival traveltime residual corresponding to the update step.

[0073] In some embodiments, the first arrival travel forward modeling module 62 is further configured to:

[0074] Convert the eikonal equation into a differential format and divide time and space into discrete computational units.

[0075] In some embodiments, the determination module 63 determines the residual between the current first arrival travel time data and the first arrival travel time data picked based on the earthquake record, for:

[0076] For the same shot point and the same receiver point position, the difference between the first arrival travel time extracted from the current first arrival travel time data and the first arrival travel time picked based on the seismic record is determined to obtain the residual between the current first arrival travel time data and the first arrival travel time data picked based on the seismic record.

[0077] In some embodiments, the initial velocity model acquisition module 61, said establishing a three-dimensional grid of the study area, is used to:

[0078] According to the topography of the study area and the inversion target depth, a three-dimensional grid of the study area is established using hexahedron or tetrahedron meshing methods.

[0079] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0080] Based on the inventive concept of the present invention, an embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and when the computer executable instructions are executed by a processor, the above-mentioned near-surface velocity modeling method is implemented.

[0081] Based on the inventive concept of the present invention, an embodiment of the present invention further provides a server, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned near-surface velocity modeling method when executing the program.

[0082] Unless otherwise specifically stated, terms such as process, calculate, compute, determine, display, and the like may refer to the actions and / or processes of one or more processing or computing systems, or similar devices, that manipulate and convert data represented as physical (e.g., electronic) quantities within registers or memories of a processing system into other data similarly represented as physical quantities within the memories, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals may be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0083] It should be understood that the specific order or hierarchy of steps in the disclosed processes is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process can be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in an exemplary order and are not intended to be limited to the specific order or hierarchy described.

[0084] In the foregoing detailed description, various features are grouped together in a single embodiment to simplify the disclosure. This method of disclosure should not be interpreted as reflecting an intention that embodiments of the claimed subject matter require more features than are recited in each claim. On the contrary, as reflected in the appended claims, the invention comprises less than all the features of any individual disclosed embodiment. The appended claims are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate preferred embodiment of the invention.

[0085] Those skilled in the art will also appreciate that the various illustrative logic blocks, modules, circuits, and algorithmic steps described in conjunction with the embodiments herein may be implemented as electronic hardware, computer software, or a combination thereof. In order to clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described around their functions. Whether such functions are implemented as hardware or software depends on the specific application and the design constraints imposed on the entire system. A skilled person may implement the described functions in an adaptable manner for each specific application, but such implementation decisions should not be interpreted as departing from the scope of protection of this disclosure.

[0086] The steps of the methods or algorithms described in conjunction with the embodiments herein may be directly embodied as hardware, software modules executed by a processor, or a combination thereof. The software module may be located in a RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, register, hard disk, removable disk, CD-ROM, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium may also be an integral part of the processor. The processor and storage medium may be located in an ASIC. The ASIC may be located in a user terminal. Of course, the processor and storage medium may also be present in a user terminal as discrete components.

[0087] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. These software codes can be stored in a memory unit and executed by a processor. The memory unit can be implemented within the processor or external to the processor. In the latter case, it is communicatively coupled to the processor via various means, which are well known in the art.

[0088] The foregoing description includes examples of one or more embodiments. Of course, it is not possible to describe all possible combinations of components or methods for the purposes of describing the above embodiments, but one of ordinary skill in the art will recognize that the various embodiments may be further combined and arranged. Therefore, the embodiments described herein are intended to encompass all such changes, modifications and variations that fall within the scope of the appended claims. Furthermore, to the extent the term "comprising" is used in the specification or claims, the term is intended to be encompassed in a manner similar to the term "including," as explained in terms of "including," used as a transitional word in the claims. Furthermore, any use of the term "or" in the specification of the claims is intended to mean a "non-exclusive or."

Claims

1. A near-surface velocity modeling method, characterized in that: include: Establishing a three-dimensional grid for a study area and obtaining an initial velocity model under the three-dimensional grid; Based on the Eikonal equation, the discontinuous Galerkin solution method is used to determine the first arrival travel time data corresponding to the current velocity model. Determine the residual between the current first arrival travel time data and the first arrival travel time data picked based on the earthquake record, and judge whether the current residual meets the residual threshold; If not, take the real detection point as the source point, take the real source point as the detection point, back-propagate the current residual through the discontinuous Galerkin solution of the Eikonal equation, determine the update gradient of the velocity model, determine the update step size of the velocity model in combination with the setting method, update the velocity model, return to execute the discontinuous Galerkin solution method based on the Eikonal equation, and determine the first arrival traveltime data corresponding to the current velocity model; If so, the current velocity model is determined as the velocity model of the study area.

2. The method according to claim 1, wherein The method of determining the first arrival travel time data corresponding to the current velocity model based on the Eikonal equation and using the discontinuous Galerkin solution method includes: Based on the Eikonal equation and the current velocity model, the discontinuous Galerkin solution method is used. After several scanning iterations, the first arrival travel time data obtained by the current scan meets the convergence conditions, and the first arrival travel time data corresponding to the current velocity model is obtained.

3. The method according to claim 1, wherein The combination setting method for determining the update step size of the velocity model includes: Set multiple update step sizes, determine the corresponding first arrival travel time residual for each update step size, and obtain multiple arrays containing update step sizes and corresponding first arrival travel time residuals. Use the curve fitting method to determine the update step size corresponding to the minimum first arrival travel time residual, which is used as the update step size of the velocity model.

4. The method according to claim 3, wherein Determining the corresponding first arrival travel time residual for each update step size includes: For each update step, update the velocity model according to the update gradient and the update step; Based on the Eikonal equation, the discontinuous Galerkin solution method is used to determine the first arrival travel time data corresponding to the updated velocity model. The residual between the first arrival travel time data and the first arrival travel time data picked based on the earthquake record is determined as the first arrival travel time residual corresponding to the update step.

5. The method according to claim 1, wherein After the three-dimensional grid of the study area is established, the following steps are also included: Convert the eikonal equation into a differential format and divide time and space into discrete computational units.

6. The method according to any one of claims 1 to 5, wherein: Determining the residual between the current first-arrival traveltime data and the first-arrival traveltime data picked based on the seismic record includes: For the same shot point and the same receiver point position, the difference between the first arrival travel time extracted from the current first arrival travel time data and the first arrival travel time picked based on the seismic record is determined to obtain the residual between the current first arrival travel time data and the first arrival travel time data picked based on the seismic record.

7. The method according to any one of claims 1 to 5, wherein: The establishing of a three-dimensional grid of the study area includes: According to the topography of the study area and the inversion target depth, a three-dimensional grid of the study area is established using hexahedron or tetrahedron meshing methods.

8. A near-surface velocity modeling device, characterized in that: include: An initial velocity model acquisition module is used to establish a three-dimensional grid in the study area and obtain an initial velocity model under the three-dimensional grid; The first arrival travel time forward modeling module is used to determine the first arrival travel time data corresponding to the current velocity model based on the Eikonal equation using the discontinuous Galerkin solution method; A judgment module is used to determine the residual between the current first arrival travel time data and the first arrival travel time data picked based on the earthquake record, and to judge whether the current residual meets the residual threshold; a velocity model updating module, configured to, if the judgment module determines that the result is negative, use the actual detection point as the source point, reversely propagate the current residual error through the discontinuous Galerkin solution of the eikonal equation, determine the updated gradient of the velocity model, determine the updated step size of the velocity model in combination with a setting method, and update the velocity model; and the first arrival traveltime forward modeling module is further configured to determine the first arrival traveltime data corresponding to the updated velocity model. The velocity model determining module is configured to determine the current velocity model as the velocity model of the study area if the determination module determines that the current velocity model is yes.

9. A computer storage medium, characterized in that The computer storage medium stores computer executable instructions, which, when executed by a processor, implement the near-surface velocity modeling method according to any one of claims 1 to 7.

10. A server, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the near-surface velocity modeling method according to any one of claims 1 to 7 when executing the program.

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