Geophysical prospecting system and method for seismic survey

Abstract

The invention relates to the field of seismic survey, in particular to a geophysical prospecting system and method for seismic survey, and the method comprises the steps: collecting earth surface information, and constructing an earth surface model; setting a virtual shot point in the earth surface model; simulation is carried out in the earth surface model, and forward modeling of seismic waves is carried out; an area where scattering interference generated by forward modeling internal seismic waves is larger than a preset value is extracted as a noise dense area, micro-logging adapting to the surface layer earth surface is set according to the earth surface model, the micro-logging is used for detecting the geological component structure of the noise dense area, and when the complexity of the geological component structure exceeds the preset value, the noise dense area is determined. Changing the position of a virtual shot point, triggering time and generated seismic wave parameters, and repeating simulation; and when the geological component structure complexity does not exceed a preset value, setting a compensation strategy corresponding to the noise dense area based on the geological component structure. According to the technical scheme of the invention, the method is used for reducing the superposition area of the wave interference noise and the complex geological noise of the superficial layer underground of the overlying earth surface, and improving the seismic survey effect.

Description

Technical Field

[0001] The present invention relates to the field of seismic surveying, and in particular to a geophysical prospecting system and method for seismic surveying. Background Art

[0002] With the deepening and improvement of exploration work under simple geological conditions in some areas, a large amount of seismic exploration work for minerals, oil and gas resources has been carried out in areas with undulating surfaces. However, seismic exploration work in areas with undulating surfaces has always faced some special problems, such as difficult data acquisition and poor data quality, serious scattering interference, inaccurate static correction, poor imaging effect or even no imaging. Due to the complexity of geological conditions and the lack of support from a large amount of forward simulation data, the effectiveness and pertinence of seismic data acquisition in areas with undulating surfaces are relatively poor. Traditional seismic exploration theories and processing technologies are based on the assumption that the surface is horizontal. Static correction is often used to deal with undulating surface problems. However, even with the use of detailed static correction technology, it is difficult to achieve good imaging effects in areas with severe surface undulations. At the same time, the geological structure of the shallow underground is usually more complex, with non-uniform media such as weathering layers and loose sediments, which leads to irregular propagation paths of seismic waves and affects the imaging quality.

[0003] In the prior art, the seismic waves generated by the undulating surface are simulated by numerical simulation of wave equations and ray tracing methods to simulate the first arrival wave, first wave, diffraction wave, transmission wave, reflection wave, multiple reflection wave, conversion wave, etc., so as to obtain the noise interference caused by the mutual influence between waves. However, in addition to the mutual influence between waves, complex geological structures and components will also cause interference. If the two are superimposed, the complex waveforms generated will be more difficult to compensate and clean. Summary of the invention

[0004] To solve the above problems, the present invention provides a geophysical exploration system and method for seismic survey, which are used to reduce the superposition area of ​​wave interference noise and complex geological noise in the shallow underground of the ground surface, and improve the seismic survey effect.

[0005] In order to achieve the above object, the technical solution of the present invention is as follows: A geophysical method for seismic survey, comprising:

[0006] Step 1: detect the surface interface, collect surface information and build a surface model;

[0007] Step 2: setting virtual shot points in the surface model, and setting the triggering time of the virtual shot points and the generated seismic wave parameters;

[0008] Step 3: simulate in the surface model, and perform forward modeling of seismic waves based on the curved grid method of coordinate transformation method. The forward modeling includes the first arrival wave, first wave, diffraction wave, transmission wave, reflection wave, multiple reflection wave and conversion wave generated by seismic waves;

[0009] Step 4: extracting the area where the scattering interference generated by the seismic wave in the forward simulation is greater than the preset value as the noise-intensive area, and setting the micro-well logging adapted to the surface according to the surface model, and the micro-well logging is used to detect the geological component structure of the noise-intensive area;

[0010] Step 5. After the geological component structure is detected, when the complexity of the geological component structure exceeds the preset value, the position of the virtual shot point, the trigger time and the generated seismic wave parameters are changed, and steps 3 and 4 are repeated; when the complexity of the geological component structure does not exceed the preset value, a compensation strategy for the corresponding noise-intensive area is set based on the geological component structure.

[0011] The above scheme has the following beneficial effects:

[0012] 1. In this scheme, the undulating surface is constructed by detecting the surface interface. Due to the particularity of its geological structure, the undulating surface is greatly disturbed by the terrain and has strong noise during seismic surveys. In addition, it will be superimposed with the interference caused by complex geological components, resulting in waveform distortion that affects data accuracy and even data failure. The undulating surface is on the surface of the ground, which is convenient for collecting information and modeling. By setting the shot point to simulate the seismic wave, it is possible to understand the first arrival wave, first wave, diffraction wave, transmission wave, reflection wave, multiple reflection wave and conversion wave of the seismic wave that is not affected by geological components but only by the terrain, so that users can plan the shot point and change the interaction point between seismic waves, thereby optimizing the noise distribution.

[0013] 2. In this scheme, in addition to the scattering interference generated by seismic waves, it is also affected by the geological composition structure. Complex geological structures will also generate noise. The purpose of seismic survey itself is to explore geological structures. In theory, it is difficult to obtain detailed information about geological structures before conducting seismic surveys, so as to deal with the impact of geological structures. However, after locating the noise-intensive areas, micro-logging can be used to explore shallow geological areas to observe whether there are complex geological structures in the noise-intensive areas. According to the exploration results, the planning of the shot points can be changed to avoid complex geological structures in the noise-intensive areas generated by seismic waves, reduce the unpredictable changes caused by the superposition of noise, and improve the quality of subsequent large-scale seismic surveys.

[0014] Furthermore, the curved grid method based on the coordinate transformation method includes gridding the surface model, and establishing a corresponding relationship between the surface model grid and the physical space coordinates through a mapping function. The mapping function is:

[0015]

[0016] Among them, xz is the physical space in the Cartesian coordinate system, ξ- is the computational space in the curved coordinate system, and z 0 (ξ) is a function describing the shape of the surface, η maxis the maximum coordinate in the η direction in the ξ-η coordinate system;

[0017] The finite difference method is used to solve the problem in the physical space grid, and the calculation results are mapped from the calculation space to the corresponding grid nodes in the physical space through the mapping function.

[0018] Beneficial effects: The mapping function is used to longitudinally stretch or compress the curved grid in the physical space to obtain a square grid in the calculation space, or to longitudinally compress or stretch the square grid in the calculation space to obtain a curved grid in the physical space. The curved grid method can adapt to the undulating surface, so as to better simulate and calculate the travel time of seismic waves in the undulating surface environment.

[0019] Furthermore, the forward modeling adopts one of the upwind difference method, the unequal distance difference method, and the linear interpolation method.

[0020] Beneficial effects: Forward modeling can use one of the upwind difference method, the unequal distance difference method, and the linear interpolation method, all of which can perform forward modeling on the seismic waves generated under the curved grid undulating surface.

[0021] Furthermore, in step 4, the noise-intensive area is simulated by two-dimensional surface ground undulation forward modeling, and in step 5, when the complexity of the geological composition structure does not exceed the preset value, it is simulated based on three-dimensional surface ground undulation forward modeling, and a compensation strategy corresponding to the noise-intensive area is designed according to the forward simulation results.

[0022] Beneficial effects: Currently, both two-dimensional and three-dimensional simulations of seismic waves are mature. Three-dimensional simulation can improve the simulation effect and the degree of restoration, but it requires higher computing power. In step five, multiple simulations are required for screening. Therefore, two-dimensional simulation is used to reduce the amount of calculation to quickly find geological areas that initially meet the conditions, and then three-dimensional simulation is used to improve the simulation accuracy and verify the geological areas, thereby reducing the amount of calculation.

[0023] Furthermore, in step 4, the noise-intensive area is simulated by 2.5D surface ground undulation forward modeling based on the Fourier transform method.

[0024] Beneficial effects: The 2.5D surface undulation forward simulation based on the Fourier transform method can combine the advantages and disadvantages of two-dimensional simulation and three-dimensional simulation. Its accuracy and computing power requirements are between those of two-dimensional simulation and three-dimensional simulation. Therefore, the use of 2.5D simulation can meet the requirements of reducing computing power and accuracy.

[0025] Furthermore, the detection target of the micro-well logging in step 4 is the noise-intensive area at a depth of 5-50m underground.

[0026] Beneficial effects: The geological structure of shallow underground is usually more complex, and the cost of micro-well logging that is too deep is high. Therefore, a noise-intensive area with a depth of 5-50m is selected for overlapping verification to control costs and be targeted.

[0027] Furthermore, the forward simulation adopts a linear interpolation method based on optimization of the trained convolutional neural network. The convolutional neural network is trained based on the travel times of seismic waves at different surface interfaces. The convolutional neural network is used to add additional difference nodes to the linear interpolation method so that the travel times of seismic waves simulated by the forward simulation can be fitted to similar travel times in the training model.

[0028] Beneficial effects: Conventional linear interpolation can fit curves, but it is easily affected by grid accuracy, resulting in deviations. Based on the convolutional neural network, the fitting process of the linear interpolation method is trained to extract the nodes where the linear interpolation method deviates, and based on the original grid accuracy, the fitting process is corrected using additional difference nodes to obtain better fitting results.

[0029] Furthermore, in step 4, when the area ratio of the noise-intensive area is greater than a preset value, the position, triggering time and generated seismic wave parameters of the virtual shot point are changed, and step 3 is repeated.

[0030] Beneficial effects: In addition to the overlap of noise-intensive areas and complex geological areas, which will reduce the quality of seismic surveys, too many noise-intensive areas will also affect the quality of seismic surveys.

[0031] Furthermore, in step three, the forward simulation uses multi-GPU parallel computing.

[0032] Beneficial effects: Multi-GPU parallel computing can improve the computing speed and facilitate the rapid design and analysis of virtual gun points.

[0033] A geophysical exploration system for seismic survey, comprising:

[0034] Surface scanning module: used to scan the surface interface to collect surface information and build a surface model;

[0035] Seismic wave simulation module: used to set virtual shot points in the surface model. The virtual shot points are provided with positions, triggering times and generated seismic wave parameters. The seismic wave simulation module is used to perform forward simulation of seismic waves by using a curved grid method based on a coordinate transformation method, and extract areas where the scattering interference generated by seismic waves in the forward simulation is greater than a preset value as noise-intensive areas;

[0036] Micro-logging module: used to detect the geological composition structure of noise-intensive areas through micro-logging, and determine whether the complexity of the geological composition structure exceeds the preset value. When the complexity of the geological composition structure exceeds the preset value, the position, trigger time and generated seismic wave parameters of the virtual shot point are changed, and the forward simulation of the seismic wave is re-performed; when the complexity of the geological composition structure does not exceed the preset value, the compensation strategy for the corresponding noise-intensive area is output based on the geological composition structure.

[0037] Beneficial effect: By using micro-logging modules in the shallow underground, the overlap of noise-intensive areas and areas with complex geological composition structures can be avoided, thereby improving the quality of seismic surveys.

[0038] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic diagram of the steps of an embodiment of a geophysical prospecting method for seismic survey according to the present invention;

[0040] Figure 2 A logical schematic diagram of a linear interpolation method optimized by a convolutional neural network in an embodiment of a geophysical prospecting method for seismic surveying according to the present invention;

[0041] Figure 3 It is a module schematic diagram of an embodiment of a geophysical exploration system for seismic survey according to the present invention. DETAILED DESCRIPTION

[0042] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0044] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0045] The following is further described in detail through specific implementation methods:

[0046] Embodiment 1:

[0047] As attached Figure 1-Figure 3 A geophysical method for seismic surveying, comprising:

[0048] Step 1: Detect the surface interface, collect surface information and construct a surface model.

[0049] Step 2: Set virtual shot points in the surface model, and set the triggering time of the virtual shot points and the generated seismic wave parameters.

[0050] Step 3: simulate in the surface model, and perform forward modeling of seismic waves based on the curved grid method of coordinate transformation method, including gridding the surface model, and establishing a corresponding relationship between the surface model grid and the physical space coordinates through a mapping function. The mapping function is:

[0051]

[0052] Among them, xz is the physical space in the Cartesian coordinate system, ξ-η is the computational space in the curved coordinate system, and z 0 (ξ) is a function describing the shape of the surface, η max is the maximum coordinate in the η direction in the ξ-η coordinate system.

[0053] The finite difference method is used to solve the problem in the physical space grid, and the calculation results are mapped from the calculation space to the corresponding grid nodes in the physical space through the mapping function.

[0054] The forward modeling includes the first arrival wave, head wave, diffraction wave, transmission wave, reflection wave, multiple reflection wave and conversion wave generated by seismic waves. The forward modeling adopts one of the upwind difference method, unequal distance difference method and linear interpolation method.

[0055] Step 4: extract the area where the scattering interference generated by the seismic waves in the forward simulation is greater than the preset value as the noise-intensive area, and set the micro-logging adapted to the surface according to the surface model. The micro-logging is used to detect the geological component structure of the noise-intensive area.

[0056] Step 5. After the geological component structure is detected, when the complexity of the geological component structure exceeds the preset value, the position of the virtual shot point, the trigger time and the generated seismic wave parameters are changed, and steps 3 and 4 are repeated; when the complexity of the geological component structure does not exceed the preset value, a compensation strategy for the corresponding noise-intensive area is set based on the geological component structure.

[0057] The specific implementation process is as follows: The undulating surface is constructed by detecting the surface interface. Due to the particularity of its geological structure, the undulating surface is greatly disturbed by the terrain and has strong noise during seismic surveys. In addition, it will be superimposed with the interference caused by complex geological components, resulting in waveform distortion that affects data accuracy and even data failure. The undulating surface is on the surface of the ground, which is convenient for collecting information and modeling. By setting the shot point to simulate the seismic wave, it is possible to understand the first arrival wave, first wave, diffraction wave, transmission wave, reflection wave, multiple reflection wave and conversion wave of the seismic wave that is not affected by geological components but only affected by terrain, so that users can plan the shot point and change the interaction points between seismic waves, thereby optimizing the noise distribution. This simulation is difficult to restore the travel time of seismic waves in real seismic exploration, because there are still complex geological influences, and the geological components are unknown during simulation, so it is difficult to improve the quality of seismic exploration only through simulation.

[0058] In addition to being disturbed by the scattering generated by seismic waves, it is also affected by the structure of geological components. Complex geological structures will also generate noise, and the purpose of seismic survey itself is to explore geological structures. In theory, it is difficult to obtain detailed information about geological structures before conducting seismic surveys, so as to deal with the impact of geological structures. However, after locating the noise-intensive areas, micro-logging can be used to explore shallow geological areas to observe whether there are complex geological structures in the noise-intensive areas. According to the exploration results, the planning of the shot points can be changed to avoid complex geological structures in the noise-intensive areas generated by seismic waves, reduce the unpredictable changes caused by the superposition of noise, and improve the quality of subsequent large-scale seismic surveys.

[0059] Micro-logging is a miniature detection method with low cost. Its detection range is only tens of centimeters to several meters around the logging area. By improving the blasting points, the area of ​​noise-intensive areas generated can be reduced, thereby satisfying the conditions for users to judge whether there are complex geological structures in the noise-intensive areas.

[0060] The mapping function is used to longitudinally stretch or compress the curved grid in the physical space to obtain a square grid in the computational space, or to longitudinally compress or stretch the square grid in the computational space to obtain a curved grid in the physical space. The curved grid method can adapt to the undulating surface, so as to better simulate and calculate the travel time of seismic waves in the undulating surface environment.

[0061] Forward modeling can use one of the upwind difference method, the unequal distance difference method, and the linear interpolation method, all of which can perform forward modeling of the seismic waves generated under the curved grid undulating surface.

[0062] Embodiment 2:

[0063] The difference from the above embodiment is that in step 4, the noise-intensive area is simulated by two-dimensional surface surface undulation forward simulation, and in step 5, when the complexity of the geological composition structure does not exceed the preset value, it is simulated based on three-dimensional surface surface undulation forward simulation, and a compensation strategy corresponding to the noise-intensive area is designed according to the forward simulation results.

[0064] At present, both two-dimensional and three-dimensional simulations of seismic waves are mature. Three-dimensional simulation can improve the simulation effect and the degree of restoration, but it requires higher computing power. In step five, multiple simulations are required for screening. Therefore, two-dimensional simulation is used to reduce the amount of calculation and quickly find geological areas that initially meet the conditions. Then, three-dimensional simulation is used to improve the simulation accuracy and verify the geological areas, so as to achieve the effect of reducing the amount of calculation.

[0065] Embodiment 3:

[0066] The difference from the above embodiment is that in step 4, the noise-intensive area is simulated by 2.5D surface ground undulation forward modeling based on Fourier transform method.

[0067] The 2.5D surface undulation forward simulation based on the Fourier transform method can combine the advantages and disadvantages of two-dimensional simulation and three-dimensional simulation. Its accuracy and computing power requirements are between those of two-dimensional simulation and three-dimensional simulation. Therefore, the use of 2.5D simulation can meet the requirements of reducing computing power and accuracy.

[0068] Embodiment 4:

[0069] The difference from the above embodiment is that the detection target of the micro-well logging in step 4 is the noise-intensive area at a depth of 5-50m underground. The forward simulation adopts a linear interpolation method optimized based on a trained convolutional neural network. The convolutional neural network is trained based on the travel time of seismic waves under different surface interfaces. The convolutional neural network is used to add additional difference nodes to the linear interpolation method, so that the travel time of seismic waves simulated by the forward simulation is fitted to the similar travel time in the training model.

[0070] The geological structure of shallow underground is usually more complex, and the cost of micro-logging too deep is high. Therefore, we choose the noise-intensive area at a depth of 5-50m for overlapping verification to control costs and be targeted.

[0071] Conventional linear interpolation can fit curves, but it is easily affected by grid accuracy, resulting in deviations. Based on the convolutional neural network, the fitting process of the linear interpolation method is trained to extract the nodes where the linear interpolation method deviates, and based on the original grid accuracy, the fitting process is corrected using additional difference nodes to obtain a better fitting effect.

[0072] Embodiment 5:

[0073] The difference from the above embodiment is that in step 4, when the area proportion of the noise-intensive area is greater than the preset value, the position, trigger time and generated seismic wave parameters of the virtual shot point are changed, and step 3 is repeated.

[0074] In step three, the forward simulation uses multi-GPU parallel computing.

[0075] In addition to the fact that the overlap of noise-intensive areas and complex geological areas will reduce the quality of seismic surveys, too many noise-intensive areas will also affect the quality of seismic surveys. Multi-GPU parallel computing can increase the computing speed and facilitate the rapid design and analysis of virtual shot points.

[0076] A geophysical exploration system for seismic survey, comprising:

[0077] Surface scanning module: used to scan the surface interface to collect surface information and build a surface model. The surface interface is scanned and spliced ​​by multiple laser scanners. In complex surface conditions such as urban areas.

[0078] Seismic wave simulation module: used to set virtual shot points in the surface model. The virtual shot points have positions, trigger times, and generated seismic wave parameters. Under complex surface conditions such as urban areas, the shot points need to consider the impact on urban areas. The seismic wave simulation module is used to perform forward simulation of seismic waves using the curved grid method based on the coordinate transformation method, and extract the areas where the scattering interference generated by seismic waves in the forward simulation is greater than the preset value as noise-intensive areas.

[0079] Micro-logging module: used to detect the geological composition structure of noise-intensive areas through micro-logging, and determine whether the complexity of the geological composition structure exceeds the preset value. When the complexity of the geological composition structure exceeds the preset value, the position, trigger time and generated seismic wave parameters of the virtual shot point are changed, and the forward simulation of the seismic wave is re-performed; when the complexity of the geological composition structure does not exceed the preset value, the compensation strategy for the corresponding noise-intensive area is output based on the geological composition structure.

[0080] By using micro-logging modules in the shallow underground, the overlap of noise-intensive areas and areas with complex geological composition and structure can be avoided, thereby improving the quality of seismic surveys.

[0081] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A geophysical method for seismic survey, characterized in that: include: Step 1: detect the surface interface, collect surface information and build a surface model; Step 2: setting virtual shot points in the surface model, and setting the triggering time of the virtual shot points and the generated seismic wave parameters; Step 3: simulate in the surface model, and perform forward modeling of seismic waves based on the curved grid method of coordinate transformation method. The forward modeling includes the first arrival wave, first wave, diffraction wave, transmission wave, reflection wave, multiple reflection wave and conversion wave generated by seismic waves; Step 4: extracting the area where the scattering interference generated by the seismic wave in the forward simulation is greater than the preset value as the noise-intensive area, and setting the micro-well logging adapted to the surface according to the surface model, and the micro-well logging is used to detect the geological component structure of the noise-intensive area; Step 5. After the geological component structure is detected, when the complexity of the geological component structure exceeds the preset value, the position of the virtual shot point, the trigger time and the generated seismic wave parameters are changed, and steps 3 and 4 are repeated; when the complexity of the geological component structure does not exceed the preset value, a compensation strategy for the corresponding noise-intensive area is set based on the geological component structure.

2. The geophysical exploration method for seismic survey according to claim 1, characterized in that: The curved grid method based on the coordinate transformation method includes gridding the surface model and establishing a corresponding relationship between the surface model grid and the physical space coordinates through a mapping function. The mapping function is: Among them, xz is the physical space in the Cartesian coordinate system, ξ-η is the computational space in the curved coordinate system, z0(ξ) is the function describing the shape of the surface, and η max is the maximum coordinate in the η direction in the ξ-η coordinate system; The finite difference method is used to solve the problem in the physical space grid, and the calculation results are mapped from the calculation space to the corresponding grid nodes in the physical space through the mapping function.

3. The geophysical prospecting method for seismic survey according to claim 2, characterized in that: The forward simulation adopts one of the upwind difference method, unequal distance difference method and linear interpolation method.

4. The geophysical prospecting method for seismic survey according to claim 2, characterized in that: In step 4, the noise-intensive area is simulated by two-dimensional surface ground undulation forward modeling. In step 5, when the complexity of the geological composition structure does not exceed the preset value, it is simulated based on three-dimensional surface ground undulation forward modeling, and a compensation strategy corresponding to the noise-intensive area is designed according to the forward modeling results.

5. The geophysical prospecting method for seismic survey according to claim 2, characterized in that: In step 4, the noise-intensive area is simulated by 2.5D surface ground undulation forward modeling based on the Fourier transform method.

6. The geophysical prospecting method for seismic survey according to claim 5, characterized in that: The detection target of the micro-well logging in step 4 is the noise-intensive area at a depth of 5-50m underground.

7. The geophysical prospecting method for seismic survey according to claim 6, characterized in that: The forward simulation uses a linear interpolation method optimized by a trained convolutional neural network. The convolutional neural network is trained based on the travel times of seismic waves at different surface interfaces. The convolutional neural network is used to add additional difference nodes to the linear interpolation method so that the travel times of seismic waves simulated by the forward simulation can be fitted to similar travel times in the training model.

8. The geophysical prospecting method for seismic survey according to claim 7, characterized in that: In step 4, when the area ratio of the noise-intensive area is greater than the preset value, the position, trigger time and generated seismic wave parameters of the virtual shot point are changed, and step 3 is repeated.

9. The geophysical prospecting method for seismic survey according to claim 8, characterized in that: In step three, the forward simulation uses multi-GPU parallel computing.

10. A geophysical exploration system for seismic survey, based on the geophysical exploration method of claim 9, characterized in that: include: Surface scanning module: used to scan the surface interface to collect surface information and build a surface model; Seismic wave simulation module: used to set virtual shot points in the surface model. The virtual shot points are provided with positions, triggering times and generated seismic wave parameters. The seismic wave simulation module is used to perform forward simulation of seismic waves by using a curved grid method based on a coordinate transformation method, and extract areas where the scattering interference generated by seismic waves in the forward simulation is greater than a preset value as noise-intensive areas; Micro-logging module: used to detect the geological composition structure of noise-intensive areas through micro-logging, and determine whether the complexity of the geological composition structure exceeds the preset value. When the complexity of the geological composition structure exceeds the preset value, the position, trigger time and generated seismic wave parameters of the virtual shot point are changed, and the forward simulation of the seismic wave is re-performed; when the complexity of the geological composition structure does not exceed the preset value, the compensation strategy for the corresponding noise-intensive area is output based on the geological composition structure.

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