Surface survey modeling method and device, equipment and storage medium

Abstract

The invention relates to a surface survey modeling method and device, equipment and a storage medium, and the method comprises the steps: obtaining the surface data of a target work area, and enabling the surface data to be sub-meter precision data; selecting surface survey control points from the grid units of the surface data of the target work area, and obtaining surface model parameters of the surface survey control points; according to the earth surface data of the target work area, determining geographic position information of a surface survey control point and a shot point detection point; according to the surface layer model parameters of the surface layer survey control points and the geographic position information of the surface layer survey control points and the shot point detection points, the surface layer model parameters of the shot point detection points are determined and used for constructing a surface layer model, and the surface layer survey surface layer model precision can be improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of surface exploration, and in particular, to a surface exploration modeling method, device, equipment, and storage medium. Background Art

[0002] Static correction is to eliminate the delay effect of the low-velocity layer and the velocity-decreasing layer near the surface on seismic waves, and correct the reflected waves to an environment equivalent to that without a low-velocity zone and a velocity-decreasing zone and with excitation and reception on a horizontal plane. Static correction not only serves the pre-data-processing link of eliminating the influence of the low-velocity and velocity-decreasing zones on seismic data, but also provides a high-precision surface model for prestack depth migration, and plays an important role in data imaging in some areas. This requires the establishment of a geophysical model of the low-velocity zone and the velocity-decreasing zone. Currently, the common methods for establishing a surface model include tomography, refraction method, layer relationship coefficient method, etc. Among them, the tomography and refraction methods are based on the first arrivals of large shots, and the established models have better time-domain equivalence, but their authenticity needs to be improved. The layer relationship coefficient method is based on the interpretation results of surface exploration control points (such as small refraction, micro-logging, VSP, etc.). In theory, a surface model closer to the true structure can be obtained, but there are too many influencing factors, and the accuracy of the established model is difficult to meet the requirements. In order to achieve better results in seismic data imaging, it is often required to establish surface models by multiple means and select the best one for use. Therefore, improving the authenticity of the surface model has always been the pursuit in the industry.

[0003] Surface exploration is a method for modeling the low-velocity and velocity-decreasing zones. The established model can provide correction amounts and also provide a high-precision constrained surface model for tomographic inversion. The layout and modeling of conventional surface exploration are based on the shot-receiver data grid, which is the surface data obtained by interpolating and smoothing discrete data relative to the true surface. It is difficult to accurately grasp the surface, landform, and the changing positions of the low-velocity and velocity-decreasing zones when laying out control points under the guidance of this data volume. After obtaining the velocity and thickness information of the control points, the surface model is still established based on the layer relationship coefficient modeling method on this discrete data. Therefore, the accuracy of the established model is affected. Especially in places where the surface undulates violently and there is no shot-receiver control, the accuracy is often not high and it is difficult to meet the requirements of high-precision modeling. Summary of the Invention

[0004] To solve the above technical problems or at least partially solve the above technical problems, embodiments of the present disclosure provide a surface exploration modeling method, device, equipment, and storage medium.

[0005] In a first aspect, embodiments of the present disclosure provide a surface exploration modeling method, the method comprising:

[0006] Obtain surface data of a target work area, wherein the surface data is sub-meter accuracy data;

[0007] Select surface survey control points from the grid cells of the surface data of the target work area, and obtain the surface model parameters of the surface survey control points;

[0008] Determine the geographical location information of the surface survey control points and the shot-receiver points according to the surface data of the target work area;

[0009] Determine the surface model parameters of the shot-receiver points according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot-receiver points, for constructing the surface model.

[0010] In a possible implementation manner, the selecting surface survey control points from the grid cells of the surface data of the target work area includes:

[0011] Determine the mountain-valley line of the target work area according to the surface data of the target work area;

[0012] For each grid cell in the surface data of the target work area, determine the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of the mountain-valley line;

[0013] Select the target grid cell from the grid cells of the surface data of the target work area as the surface survey control point according to the elevation difference.

[0014] In a possible implementation manner, the determining the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of the mountain-valley line includes:

[0015] When the coordinates of the current grid cell are (x3, y3, z3), and the coordinates of the two nearest shot-receiver points on both sides of the current grid cell are (x1, y1, z1) and (x2, y2, z2) respectively, calculate the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of it through the following expression:

[0016] Δh = (z1 - z2) * sqrt((x2 - x3)2 + (y2 - y3)2) / sqrt((x2 - x1)2 + (y2 - y1)2)) + (z2 - z3)

[0017] Where, Δh is the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of it.

[0018] In a possible implementation manner, the selecting the target grid cell from the grid cells of the surface data of the target work area as the surface survey control point according to the elevation difference includes:

[0019] Calculate the time difference caused by the elevation difference according to the elevation difference of the current grid cell and the average surface velocity;

[0020] Compare the quarter period of the effective wave at the current grid cell with this time difference, and select, from the surface data of the target work area, the grid cells where the quarter period of the effective wave is less than this time difference as the first grid cells;

[0021] Select second grid cells from the first grid cells according to the subsurface data and geomorphic data of the target work area as the surface survey control points.

[0022] In a possible implementation manner, the surface model parameters include formation velocity and formation thickness.

[0023] In a possible implementation manner, the determining the surface model parameters of the shot-receiver points according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot-receiver points includes:

[0024] When the surface model parameter is the formation thickness, calculate the interlayer relationship coefficient at the surface control points according to the formation thickness at the surface control points;

[0025] Based on the geographical location information of the surface survey control points and the shot-receiver points, obtain the interlayer relationship coefficient at the shot-receiver points through interpolation calculation;

[0026] Perform interpolation calculation on the formation thickness at the surface control points to obtain the initial formation thickness at the shot-receiver points;

[0027] Take the product of the initial formation thickness at the shot-receiver points and the interlayer relationship coefficient corresponding to the shot-receiver points as the formation thickness of the shot-receiver points.

[0028] In a possible implementation manner, the determining the surface model parameters of the shot-receiver points according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot-receiver points includes:

[0029] When the surface model parameter is the formation velocity, based on the geographical location information of the surface survey control points and the shot-receiver points, obtain the formation velocity at the shot-receiver points through interpolation calculation.

[0030] In a second aspect, an embodiment of the present disclosure provides a surface survey modeling device, including:

[0031] An acquisition module, configured to acquire the surface data of the target work area, where the surface data is sub-meter accuracy data;

[0032] A selection module, configured to select surface survey control points from the grid cells of the surface data of the target work area and acquire the surface model parameters of the surface survey control points;

[0033] The first determination module is configured to determine the geographical location information of the surface survey control points and the shot point - geophone points according to the surface data of the target work area;

[0034] The second determination module is configured to determine the surface model parameters of the shot point - geophone points according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot point - geophone points, for constructing a surface model.

[0035] In a third aspect, an embodiment of the present disclosure provides an electronic device, including a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus;

[0036] The memory is used to store a computer program;

[0037] The processor is configured to implement the above - mentioned surface survey modeling method when executing the program stored on the memory.

[0038] In a fourth aspect, an embodiment of the present disclosure provides a computer - readable storage medium, on which a computer program is stored. The computer program, when executed by a processor, implements the above - mentioned surface survey modeling method.

[0039] The above - mentioned technical solutions provided by the embodiments of the present disclosure have at least some or all of the following advantages compared with the prior art:

[0040] For the surface survey modeling method described in the embodiments of the present disclosure, surface data of the target work area is obtained, where the surface data is sub - meter - level precision data; surface survey control points are selected from the grid cells of the surface data of the target work area, and the surface model parameters of the surface survey control points are obtained; the geographical location information of the surface survey control points and the shot point - geophone points is determined according to the surface data of the target work area; the surface model parameters of the shot point - geophone points are determined according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot point - geophone points, for constructing a surface model, which can improve the accuracy of the surface model in surface surveys. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings herein are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure.

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0043] Figure 1Schematically shows a schematic flowchart of a surface survey modeling method according to an embodiment of the present disclosure;

[0044] Figure 2 Schematically shows a schematic diagram of the elevation difference of the valley bottom position according to an embodiment of the present disclosure;

[0045] Figure 3 Schematically shows a structural block diagram of a surface survey modeling device according to an embodiment of the present disclosure;

[0046] Figure 4 Schematically shows a structural block diagram of an electronic device according to an embodiment of the present disclosure. Detailed implementation manners

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Apparently, the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present disclosure without creative efforts shall fall within the scope of protection of the present disclosure.

[0048] See Figure 1 , embodiments of the present disclosure provide a surface survey modeling method, including the following steps:

[0049] S1. Obtain surface data of a target work area, where the surface data is sub-meter accuracy data.

[0050] In this embodiment, the surface data can be obtained by high-precision lidar aerial survey. A drone-borne portable navigation device can be used to perform high-density (0.2m * 0.2m) sampling on the surface to form high-precision image data as the surface data. Among them, the surface data can also be any one of meter-level, decimeter-level, and centimeter-level accuracy data.

[0051] S2. Select surface survey control points from the grid cells of the surface data of the target work area, and obtain surface model parameters of the surface survey control points.

[0052] In this embodiment, the surface model parameters include formation velocity and formation thickness.

[0053] S3. Determine the geographical location information of the surface survey control points and shot-geophone points according to the surface data of the target work area.

[0054] According to the surface data of the target work area, extract the coordinate information of the grid cells in the surface data along the mountain peaks and valley lines on the surface data, so as to obtain the geographical location information of the surface survey control points and shot-geophone points.

[0055] S4. Determine the surface model parameters of the shot-receiver points based on the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot-receiver points, for constructing the surface model.

[0056] In this embodiment, in step S2, the selecting the surface survey control points from the grid cells of the surface data of the target work area includes:

[0057] Determine the mountain-valley line of the target work area according to the surface data of the target work area;

[0058] For each grid cell in the surface data of the target work area, determine the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of the current grid cell on the mountain-valley line;

[0059] Select the target grid cell from the grid cells of the surface data of the target work area as the surface survey control point according to the elevation difference.

[0060] In this embodiment, the determining the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of the current grid cell on the mountain-valley line includes:

[0061] When the coordinates of the current grid cell are (x3, y3, z3), and the coordinates of the two nearest shot-receiver points on both sides of the current grid cell are (x1, y1, z1) and (x2, y2, z2) respectively, calculate the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of the current grid cell through the following expression:

[0062] Δh = (z1 - z2) * sqrt((x2 - x3)2 + (y2 - y3)2) / sqrt((x2 - x1)2 + (y2 - y1)2)) + (z2 - z3)

[0063] where Δh is the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of the current grid cell.

[0064] In this embodiment, the determining the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of the current grid cell on the mountain-valley line for each grid cell in the surface data of the target work area includes:

[0065] For each grid cell in the surface data of the target work area, extract the mountain and valley lines by calculating its slope, aspect and terrain change curvature;

[0066] Spread the shot-receiver points on the mountain and valley lines, and obtain the elevation difference between the two nearest shot-receiver points on both sides of the mountain and valley lines and the valley bottom or mountain top.

[0067] Such as Figure 2As shown, according to the surface data, the coordinate of a valley bottom position is (x3, y3, z3), and the coordinates of the two nearest shot points are S(x1, y1, z1) and r(x2, y2, z2) respectively. If there is no measured data for the valley, the valley bottom will be interpolated into a point with coordinates (x3, y3, z3 + Δh), and the elevation of the valley bottom increases by Δh, which will bring errors to the modeling. Among them, Δh can be obtained by the relationship between the position and elevation of the conventional measured coordinates and the surface data coordinates: Δh = Δh1 + Δh2 = Δh1 + (z2 - z3) = (z1 - z2) * sqrt((x2 - x3)^2 + (y2 - y3)^2) / sqrt((x2 - x1)^2 + (y2 - y1)^2)) + (z2 - z3)

[0068] In this embodiment, the selecting the target grid unit from the grid units of the surface data of the target work area according to the elevation difference as the surface investigation control point includes:

[0069] Calculating the time difference caused by the elevation difference according to the elevation difference of the current grid unit and the surface average velocity;

[0070] Comparing the quarter period of the effective wave at the current grid unit with the time difference, and selecting, from the surface data of the target work area, the grid unit whose quarter period of the effective wave is less than the time difference as the first grid unit;

[0071] Selecting a second grid unit from the first grid units according to the underground data and geomorphic data of the target work area as the surface investigation control point, wherein, preferably, the grid unit with obvious characteristics in the corresponding underground data and geomorphic data at the grid unit in the historical data is selected.

[0072] In this embodiment, the surface average velocity can be determined according to the historical surface investigation data and the large gun data, and the effective wave can be determined according to the historical seismic data.

[0073] In this embodiment, if the main frequency of the effective wave in the historical seismic data at a certain valley bottom position is 20 Hz and the period T is 50 ms, then the quarter period is 12.5 ms; if the surface average velocity v at this place is 2000 m / s and Δh / v is greater than 12.5 ms, that is, Δh is greater than 25 m, then this valley bottom is used as the surface investigation control point.

[0074] In the surface investigation modeling method of the present disclosure, by calculating the slope, aspect, and terrain change curvature, valleys and peaks are extracted, and positions with surface mutations and no shot point control are found to ensure the optimization of the layout of the investigation control points. After further obtaining the optimized interpretation result of the surface investigation control points, using high-precision surface data to calculate the interlayer relationship coefficient of the work area, a high-precision surface model can be obtained.

[0075] In this embodiment, in step S4, determining the surface layer model parameters of the shot point and geophone point according to the surface layer model parameters of the surface layer survey control points and the geographical location information of the surface layer survey control points and the shot point and geophone point includes:

[0076] When the surface layer model parameter is the formation thickness, calculating the interlayer relationship coefficient at the surface layer control point according to the formation thickness at the surface layer control point;

[0077] Based on the geographical location information of the surface layer survey control points and the shot point and geophone point, obtaining the interlayer relationship coefficient at the shot point and geophone point through interpolation calculation;

[0078] Performing interpolation calculation on the formation thickness at the surface layer control point to obtain the initial formation thickness at the shot point and geophone point;

[0079] Taking the product of the initial formation thickness at the shot point and geophone point and the interlayer relationship coefficient corresponding to the shot point and geophone point as the formation thickness of the shot point and geophone point.

[0080] In this embodiment, in step S4, determining the surface layer model parameters of the shot point and geophone point according to the surface layer model parameters of the surface layer survey control points and the geographical location information of the surface layer survey control points and the shot point and geophone point includes:

[0081] When the surface layer model parameter is the formation velocity, based on the geographical location information of the surface layer survey control points and the shot point and geophone point, obtaining the formation velocity at the shot point and geophone point through interpolation calculation.

[0082] In the actual application scenario, the western Altyn Tagh area in the Qaidam Basin belongs to an area with extremely complex terrain. The geomorphic altitude is 2,800 - 3,700 meters, the mountain is steep, the gullies are crisscrossed, the mountain body is broken, 50 - 300 - meter cliffs can be seen everywhere, and there are a large number of karst caves and hidden ditches, which are prone to safety accidents such as vehicle sinking and personnel stepping into empty spaces. In the 3D Yingxiongling in the Qaidam Basin, the surface layer survey and modeling method of the present disclosure is used for near - surface modeling. By accurately arranging points indoors, it not only ensures the rationality of the surface layer survey control points but also eliminates the time consumption of on - site point running. At the same time, using high - density surface mapping information to calculate the interlayer relationship coefficient for modeling further improves the accuracy of the surface layer model, solves the problems of on - site point running, unreasonable layout positions of the surface layer survey control points, and low accuracy of the surface layer model during the surface layer survey in the extremely complex mountain area of the Qaidam Basin, and has achieved good results in solving the serious static correction problem and low - signal - to - noise ratio pre - stack depth migration imaging problem in the 3D Yingxiongling.

[0083] The surface layer survey and modeling method of the present disclosure uses high - definition image data to achieve accurate indoor layout during the layout of control points, and then uses high - precision surveying and mapping data to calculate the interlayer relationship coefficient for modeling after obtaining the surface layer survey results.

[0084] The surface survey modeling method of the present disclosure achieves a 100% accurate point rate for laying out surface survey control points indoors, avoiding on-site offsets and point selection. The layout position does not depend on shot-receiver point data, thus achieving the optimal layout of the true surface. The accuracy of the interlayer relationship coefficient calculated using the true surface data is greatly improved, and finally a high-precision surface survey model can be obtained.

[0085] Refer to Figure 3 , an embodiment of the present disclosure provides a surface survey modeling device, including:

[0086] An acquisition module 11, configured to acquire surface data of a target work area, where the surface data is sub-meter accuracy data;

[0087] A selection module 12, configured to select surface survey control points from grid cells of the surface data of the target work area, and acquire surface model parameters of the surface survey control points;

[0088] A first determination module 13, configured to determine the geographical location information of surface survey control points and shot-receiver points according to the surface data of the target work area;

[0089] A second determination module 14, configured to determine the surface model parameters of the shot-receiver points according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot-receiver points, for constructing a surface model.

[0090] The implementation processes of the functions and roles of each unit in the above device are specifically detailed in the implementation processes of the corresponding steps in the above method, and will not be elaborated here.

[0091] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the present invention. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0092] In the above embodiments, any combination of the acquisition module 11, the selection module 12, the first determination module 13, and the second determination module 14 can be combined and implemented in one module, or any one of them can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. At least one of the acquisition module 11, the selection module 12, the first determination module 13, and the second determination module 14 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on substrate, a system on package, an application specific integrated circuit (ASIC), or any other reasonable way of integrating or packaging circuits, etc., implemented by hardware or firmware, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in an appropriate combination of any several of them. Alternatively, at least one of the acquisition module 11, the selection module 12, the first determination module 13, and the second determination module 14 can be at least partially implemented as a computer program module, which can execute the corresponding functions when the computer program module is run.

[0093] Referring to Figure 4 As shown, the electronic device provided by the embodiment of the present disclosure includes a processor 1110, a communication interface 1120, a memory 1130, and a communication bus 1140. Among them, the processor 1110, the communication interface 1120, and the memory 1130 complete communication with each other through the communication bus 1140;

[0094] The memory 1130 is used to store computer programs;

[0095] When the processor 1110 executes the program stored on the memory 1130, the following surface survey modeling method is implemented:

[0096] Obtain the surface data of the target work area, where the surface data is sub-meter accuracy data;

[0097] Select surface survey control points from the grid cells of the surface data of the target work area, and obtain the surface model parameters of the surface survey control points;

[0098] According to the surface data of the target work area, determine the geographical location information of the surface survey control points and the shot point geophones;

[0099] According to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot point geophones, determine the surface model parameters of the shot point geophones for constructing the surface model.

[0100] The aforementioned communication bus 1140 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 1140 may be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience in representation, only a thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0101] The communication interface 1120 is used for communication between the aforementioned electronic device and other devices.

[0102] The memory 1130 may include a Random Access Memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory 1130 may also be at least one storage device located far from the aforementioned processor 1110.

[0103] The aforementioned processor 1110 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0104] Embodiments of the present disclosure also provide a computer-readable storage medium. A computer program is stored on the aforementioned computer-readable storage medium, and when the computer program is executed by a processor, the surface investigation modeling method as described above is implemented.

[0105] The computer-readable storage medium may be included in the device / device described in the above embodiments; it may also exist alone without being assembled into the device / device. The aforementioned computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the surface investigation modeling method according to the embodiments of the present disclosure is implemented.

[0106] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device.

[0107] It should be noted that in this text, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the said element.

[0108] The above are only specific embodiments of the present disclosure, enabling those skilled in the art to understand or implement the present disclosure. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to these embodiments shown herein, but rather will conform to the broadest scope consistent with the principles and novel features claimed herein.

Claims

1. A surface survey modeling method, characterized in that, the method includes: Obtain the surface data of the target work area, wherein the surface data is sub-meter accuracy data; Select surface survey control points from the grid cells of the surface data of the target work area, and obtain the surface model parameters of the surface survey control points; Determine the geographical location information of the surface survey control points and the shot-receiver points according to the surface data of the target work area; Determine the surface model parameters of the shot-receiver points according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot-receiver points, for constructing the surface model.

2. The method according to claim 1, characterized in that, the selecting surface survey control points from the grid cells of the surface data of the target work area includes: Determine the mountain-valley line of the target work area according to the surface data of the target work area; For each grid cell in the surface data of the target work area, determine the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of the mountain-valley line; Select the target grid cell from the grid cells of the surface data of the target work area as the surface survey control point according to the elevation difference.

3. The method according to claim 2, characterized in that, the determining the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of the mountain-valley line includes: When the coordinates of the current grid cell are (x3, y3, z3), and the coordinates of the two nearest shot-receiver points on both sides of the current grid cell are (x1, y1, z1) and (x2, y2, z2) respectively, calculate the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of it through the following expression: Δh = (z1 - z2) * sqrt((x2 - x3)2 + (y2 - y3)2) / sqrt((x2 - x1)2 + (y2 - y1)2)) + (z2 - z3) where Δh is the elevation difference between the current grid cell and the two nearest shot-receiver points on both sides of it.

4. The method according to claim 2, characterized in that, the selecting the target grid cell from the grid cells of the surface data of the target work area as the surface survey control point according to the elevation difference includes: Calculate the time difference caused by the elevation difference according to the elevation difference of the current grid cell and the average surface velocity; Compare the quarter period of the effective wave at the current grid cell with this time difference, and select the grid cells with the quarter period of the effective wave less than this time difference from the surface data of the target work area as the first grid cells; Select the second grid cells from the first grid cells as the surface survey control points according to the underground data and the geomorphic data of the target work area.

5. The method according to claim 1, characterized in that, the surface model parameters include formation velocity and formation thickness.

6. The method according to claim 5, characterized in that, the determining the surface model parameters of the shot-receiver points according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot-receiver points includes: When the surface model parameter is the formation thickness, calculate the interlayer relationship coefficient at the surface control point according to the formation thickness at the surface control point; Based on the geographical location information of the surface survey control points and the shot point - geophone points, through interpolation calculation, the inter - layer relationship coefficient at the shot point - geophone points is obtained; Interpolate and calculate the formation thickness at the surface control points to obtain the initial formation thickness at the shot point - geophone points; Take the product of the initial formation thickness at the shot point - geophone points and its corresponding inter - layer relationship coefficient at the shot point - geophone points as the formation thickness of the shot point - geophone points.

7. The method according to claim 5, wherein, The determination of the surface model parameters of the shot point - geophone points according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot point - geophone points includes: When the surface model parameter is the formation velocity, based on the geographical location information of the surface survey control points and the shot point - geophone points, through interpolation calculation, the formation velocity at the shot point - geophone points is obtained.

8. A surface survey modeling device, wherein, comprising: An acquisition module for acquiring surface data of a target work area, wherein the surface data is sub - meter - accuracy data; A selection module for selecting surface survey control points from the grid cells of the surface data of the target work area and acquiring the surface model parameters of the surface survey control points; A first determination module for determining the geographical location information of the surface survey control points and the shot point - geophone points according to the surface data of the target work area; A second determination module for determining the surface model parameters of the shot point - geophone points according to the surface model parameters of the surface survey control points and the geographical location information of the surface survey control points and the shot point - geophone points, for constructing a surface model.

9. An electronic device, wherein, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory complete communication with each other through the communication bus; The memory is used for storing a computer program; The processor, when executing the program stored on the memory, implements the surface survey modeling method according to any one of claims 1 - 7.

10. A computer - readable storage medium, on which a computer program is stored, wherein, The computer program, when executed by a processor, implements the surface survey modeling method according to any one of claims 1 - 7.

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