Near-surface longitudinal wave velocity modeling method and device based on micro-motion exploration

Abstract

The invention relates to a near-surface longitudinal wave velocity modeling method and device based on micro-motion exploration, and the method comprises the steps: obtaining a surface survey-based ground geological map of a target work area, and correcting a geological boundary of the surface survey-based ground geological map; according to stratum, fault and stratum occurrence information provided by the corrected ground geological map, a geological cross section is drawn along a seismic survey line, and a shallow ground structure model of the target work area is obtained; obtaining the shallow surface shear wave velocity of each preset measuring point in the target work area, and converting the shallow surface shear wave velocity of each preset measuring point into a longitudinal wave velocity; with the shallow ground structure model as a constraint, spatial interpolation is carried out on the longitudinal wave velocity of each preset measuring point to obtain a near-surface longitudinal wave velocity model based on the shallow ground structure model and a shallow velocity field based on the shallow ground structure model, the inversion velocity is close to the stratum velocity, and the precision is high; and a good near-surface longitudinal wave velocity model is provided for subsequent pre-stack depth migration.

Description

Technical Field

[0001] The present disclosure relates to the technical field of seismic data processing, and particularly to a method and device for near-surface longitudinal wave velocity modeling based on microtremor exploration. Background Art

[0002] Shallow velocity modeling is one of the key links in seismic data processing, which seriously affects the quality of static correction, migration imaging, and reservoir prediction. However, the shallow velocity is affected by various factors such as surface structure and lithology, with a relatively fast longitudinal velocity change, low accuracy in near-surface velocity modeling, unreasonable trends and shapes, and large well-seismic errors.

[0003] Currently, the microtremor exploration technology has been recently adopted to detect the near-surface velocity with good results. However, the microtremor exploration inversely obtains the shear wave velocity, which needs to be converted into the longitudinal wave velocity. The common method is to calculate the shear wave velocity ratio according to the geological age horizons using a small number of micro-logging and indoor core tests, and then convert the shear wave velocity of different horizons into the longitudinal wave velocity based on a simple layered model. The acquisition of the shear wave velocity ratio is only based on experience and simply stratifies according to the shear wave velocity range. The shallow structure morphology is often not a simple layered model but is controlled by the regional structure. The simple spatial model and layered model cannot meet the requirements of near-surface velocity modeling, with large errors and unable to meet the requirements of high-precision seismic data processing. Summary of the Invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, embodiments of the present disclosure provide a method and device for near-surface longitudinal wave velocity modeling based on microtremor exploration.

[0005] In a first aspect, embodiments of the present disclosure provide a method for near-surface longitudinal wave velocity modeling based on microtremor exploration, the method comprising:

[0006] Obtain a ground geological map based on surface survey of the target work area, and correct the geological boundaries of the ground geological map based on surface survey to obtain a corrected ground geological map;

[0007] According to the formation, fault, and formation attitude information provided by the corrected ground geological map, draw a geological cross-section along the seismic survey line to obtain a shallow ground structure model of the target work area;

[0008] Obtain the shallow surface shear wave velocity of each preset measurement point in the target work area, and convert the shallow surface shear wave velocity of each preset measurement point into the longitudinal wave velocity;

[0009] With the shallow ground structure model as a constraint, perform spatial interpolation on the longitudinal wave velocity of each preset measurement point to obtain a near-surface longitudinal wave velocity model based on the shallow ground structure model.

[0010] In a possible implementation manner, the correction of the geological boundaries of the ground geological map based on surface surveys to obtain a corrected ground geological map includes:

[0011] Obtain high-precision ground data of the target work area using lidar, and correct the geological boundaries of the ground geological map based on surface surveys according to the geological boundaries in the high-precision ground data to obtain a corrected ground geological map, where the resolution of the high-precision ground data is not less than 0.1m * 0.1m.

[0012] In a possible implementation manner, the drawing of a geological cross-section along the seismic survey line according to the formation, fault, and formation attitude information provided by the corrected ground geological map to obtain a shallow ground structure model of the target work area includes:

[0013] According to the corrected ground geological map, determine the positions of geological interfaces and fault developments and the dip directions of fault developments at the seismic survey line positions in the target work area, and delimit each geological age and formation attitude on the corrected ground geological map according to the positions of geological interfaces and fault developments and the dip directions of fault developments;

[0014] Within the range of the ground elevation at the seismic survey line position and the top surface of the high-velocity layer, interpret the geological layer planes and faults according to each geological age and formation attitude;

[0015] Enclose the interpreted geological layer plane and fault data into different geological blocks, and use the spatial topological relationship containing reverse faults and horizons to construct a shallow ground structure model of the target work area according to different geological blocks.

[0016] In a possible implementation manner, the top surface of the high-velocity layer is obtained through geophysical data, surface low-velocity zone surveys, and regional geological data of the target work area.

[0017] In a possible implementation manner, the obtaining of the shallow surface shear wave velocity of each preset measuring point in the target work area and the conversion of the shallow surface shear wave velocity of each preset measuring point into a compressional wave velocity include:

[0018] Use the microtremor exploration technology to obtain the shallow surface shear wave velocity of each preset measuring point in the target work area;

[0019] Obtain the compressional wave to shear wave velocity ratio of each geological horizon according to the surface velocity survey, compressional and shear wave logging data, and laboratory core tests within the target work area;

[0020] Convert the shallow surface shear wave velocity of each preset measuring point into a compressional wave velocity according to the compressional wave to shear wave velocity ratio of each geological horizon.

[0021] In a possible implementation manner, the use of the microtremor exploration technology to obtain the shallow surface shear wave velocity of each preset measuring point in the target work area includes:

[0022] Based on a stationary random process, extract the surface wave dispersion curve from the micro-motion signal, and obtain the shear wave velocity structure of the subsurface medium in the target work area through the inversion of the dispersion curve;

[0023] Extract the shallow surface shear wave velocity of each preset measuring point from the shear wave velocity structure.

[0024] In a possible implementation manner, with the shallow surface structure model as a constraint, perform spatial interpolation on the longitudinal wave velocity of each preset measuring point to obtain a near-surface longitudinal wave velocity model based on the shallow surface structure model, including:

[0025] Input the longitudinal wave velocity of each preset measuring point into the shallow surface structure model, perform velocity interpolation, and obtain a near-surface longitudinal wave velocity model based on the shallow surface structure model.

[0026] In a second aspect, an embodiment of the present disclosure provides a near-surface longitudinal wave velocity modeling device based on micro-motion exploration, including:

[0027] A correction module, configured to obtain a ground geological map based on surface investigation of the target work area, correct the geological boundaries of the ground geological map based on surface investigation, and obtain a corrected ground geological map;

[0028] A drawing module, configured to draw a geological cross-section along the seismic survey line according to the formation, fault, and formation attitude information provided by the corrected ground geological map, and obtain a shallow surface structure model of the target work area;

[0029] A conversion module, configured to obtain the shallow surface shear wave velocity of each preset measuring point in the target work area, and convert the shallow surface shear wave velocity of each preset measuring point into a longitudinal wave velocity;

[0030] An interpolation module, configured to perform spatial interpolation on the longitudinal wave velocity of each preset measuring point with the shallow surface structure model as a constraint, and obtain a near-surface longitudinal wave velocity model based on the shallow surface structure model.

[0031] 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, wherein the processor, the communication interface, and the memory complete communication with each other through the communication bus;

[0032] The memory is used for storing a computer program;

[0033] The processor is configured to implement the above-mentioned near-surface longitudinal wave velocity modeling method based on micro-motion exploration when executing the program stored in the memory.

[0034] Fourthly, an embodiment of the present disclosure provides a computer-readable storage medium, on which a computer program is stored, and characterized in that when the computer program is executed by a processor, the above-mentioned near-surface longitudinal wave velocity modeling method based on microtremor exploration is implemented.

[0035] The above 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:

[0036] For the near-surface longitudinal wave velocity modeling method based on microtremor exploration described in the embodiments of the present disclosure, a ground geological map based on surface investigation of the target work area is obtained, the geological boundaries of the ground geological map based on surface investigation are corrected to obtain a corrected ground geological map; according to the formation, fault and formation attitude information provided by the corrected ground geological map, a geological cross-section is drawn along the seismic survey line to obtain a shallow ground structure model of the target work area; the near-surface shear wave velocity of each preset measuring point in the target work area is obtained, and the near-surface shear wave velocity of each preset measuring point is converted into a longitudinal wave velocity; with the shallow ground structure model as a constraint, the longitudinal wave velocity of each preset measuring point is spatially interpolated to obtain a near-surface longitudinal wave velocity model based on the shallow ground structure model, and the formation velocity is filled on the shallow ground structure model to construct a near-surface longitudinal wave velocity model. Based on the shallow velocity field of the shallow ground structure model, the inverted velocity is close to the formation velocity and has high accuracy, providing a good near-surface longitudinal wave velocity model for subsequent prestack depth migration. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings here are incorporated into the specification and constitute 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.

[0038] 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.

[0039] Figure 1 Schematically shows a flow chart of the near-surface longitudinal wave velocity modeling method based on microtremor exploration according to an embodiment of the present disclosure;

[0040] Figure 2 Schematically shows a schematic diagram of the corrected ground geological map of lidar ground data according to an embodiment of the present disclosure;

[0041] Figure 3 Schematically shows a schematic diagram of the topographic line and the bottom boundary of the low-velocity layer (top surface of the high-velocity layer) in the target work area according to an embodiment of the present disclosure;

[0042] Figure 4Schematic diagram showing a geological block determined based on a geological horizon boundary according to an embodiment of the present disclosure;

[0043] Figure 5 Schematic diagram showing a geological cross-section drawn along a seismic survey line determined based on a geological horizon boundary according to an embodiment of the present disclosure;

[0044] Figure 6 Schematic diagram showing the interpretation result of the microtremor measurement point WD108 in the target work area according to an embodiment of the present disclosure;

[0045] Figure 7 Schematic diagram showing the interpretation result of the microtremor measurement point WD122 in the target work area according to an embodiment of the present disclosure;

[0046] Figure 8 Schematic diagram showing a near-surface P-wave velocity model based on a shallow subsurface structure model according to an embodiment of the present disclosure;

[0047] Figure 9 Schematic diagram showing a flow chart of a near-surface P-wave velocity modeling method based on microtremor exploration according to another embodiment of the present disclosure;

[0048] Figure 10 Schematic block diagram showing a near-surface P-wave velocity modeling device based on microtremor exploration according to an embodiment of the present disclosure; and

[0049] Figure 11 Schematic block diagram showing an electronic device according to an embodiment of the present disclosure. Detailed implementation manners

[0050] 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 of the present disclosure without creative efforts shall fall within the protection scope of the present disclosure.

[0051] See Figure 1 , embodiments of the present disclosure provide a near-surface P-wave velocity modeling method based on microtremor exploration, and the method includes:

[0052] S1, obtaining a ground geological map based on surface surveys of a target work area, and correcting the geological boundaries of the ground geological map based on surface surveys to obtain a corrected ground geological map.

[0053] In this embodiment, the stratigraphic boundaries on the ground geological map based on surface surveys are inferred. It is necessary to combine the regional geological background and use high-precision ground lidar data, i.e., lidar maps, to identify the ground geological conditions. Strata of different ages have different lithologies and lithological combinations, which appear as combinations of different color bands on the lidar map. Identify the main geological interfaces and trends, correct the geological horizons, and revise the geological boundaries of the ground geological map based on surface surveys, so as to obtain an accurate ground geological map, such as Figure 2 as shown

[0054] S2. According to the stratigraphic, fault, and stratigraphic attitude information provided by the revised ground geological map, draw a geological cross-section along the seismic line to obtain a shallow ground structure model of the target work area.

[0055] S3. Obtain the shallow surface shear wave velocity of each preset measuring point in the target work area and convert the shallow surface shear wave velocity of each preset measuring point into a compressional wave velocity.

[0056] S4. With the shallow ground structure model as a constraint, perform spatial interpolation on the compressional wave velocity of each preset measuring point to obtain a near-surface compressional wave velocity model based on the shallow ground structure model.

[0057] In this embodiment, in step S1, the revision of the geological boundaries of the ground geological map based on surface surveys to obtain a revised ground geological map includes:

[0058] Use lidar to obtain high-precision ground data of the target work area, and revise the geological boundaries of the ground geological map based on surface surveys according to the geological boundaries in the high-precision ground data to obtain a revised ground geological map, where the resolution of the high-precision ground data is not less than 0.1m * 0.1m.

[0059] In this embodiment, in step S2, the drawing of a geological cross-section along the seismic line according to the stratigraphic, fault, and stratigraphic attitude information provided by the revised ground geological map to obtain a shallow ground structure model of the target work area includes:

[0060] According to the revised ground geological map, determine the positions of geological interfaces and fault developments and the dip directions of fault developments at the seismic line positions in the target work area, and delimit the geological ages and stratigraphic attitudes of each section on the revised ground geological map according to the positions of geological interfaces and fault developments and the dip directions of fault developments;

[0061] Within the range of the ground elevation at the seismic line position and the top surface of the high-velocity layer, interpret the geological horizons and faults according to the geological ages and stratigraphic attitudes of each section, where the top surface of the high-velocity layer is as Figure 3 shown

[0062] Enclose the interpreted geological horizon and fault data into different geological blocks, such asFigure 4 As shown, by adopting the spatial topological relationship between the reverse fault and the horizon, a shallow surface structure model of the target work area is constructed according to different geological blocks, such as Figure 5 shown.

[0063] In this embodiment, the top surface of the high-velocity layer is obtained through the geophysical data of the target work area, the investigation of the surface low-velocity zone, and the regional geological data. The top surface of the high-velocity layer refers to the interface between the high-velocity layer and the low-velocity layer or the velocity-reducing layer. The low-velocity layer exists in the low-velocity area on the earth's surface. The high-velocity layer of the formation is usually related to the weathering degree, water content, and lithology of the earth's surface, and its top surface is basically a relatively smooth depth surface.

[0064] In this embodiment, in step S3, the obtaining of the shallow surface shear wave velocity of each preset measuring point in the target work area and the conversion of the shallow surface shear wave velocity of each preset measuring point into a compressional wave velocity include:

[0065] Using the microtremor exploration technology to obtain the shallow surface shear wave velocity of each preset measuring point in the target work area, such as Figure 6 and 7 shown;

[0066] According to the surface velocity survey, the compressional wave and shear wave logging data, and the indoor core test in the target work area, the compressional wave-shear wave velocity ratio of each geological horizon is obtained, as shown in Table 1 below;

[0067] According to the compressional wave-shear wave velocity ratio of each geological horizon, the shallow surface shear wave velocity of each preset measuring point is converted into a compressional wave velocity.

[0068] In this embodiment, the compressional wave velocity of each preset measuring point is the product value of the shallow surface shear wave velocity of each preset measuring point and the compressional wave-shear wave velocity ratio of the geological horizon where the preset measuring point is located.

[0069] Table 1

[0070] In this embodiment, the using of the microtremor exploration technology to obtain the shallow surface shear wave velocity of each preset measuring point in the target work area includes:

[0071] Based on the stationary random process, extracting the surface wave dispersion curve from the microtremor signal, and obtaining the shear wave velocity structure of the underground medium in the target work area through the inversion of the dispersion curve;

[0072] Extracting the shallow surface shear wave velocity of each preset measuring point from the shear wave velocity structure.

[0073] In this embodiment, in step S4, the spatially interpolating the compressional wave velocity of the preset measuring points with the shallow surface structure model as a constraint to obtain a near-surface compressional wave velocity model based on the shallow surface structure model includes:

[0074] Input the P-wave velocity of each preset measuring point into the shallow ground structure model for velocity interpolation to obtain the near-surface P-wave velocity model based on the shallow ground structure model, as Figure 8 shown.

[0075] In this embodiment, a certain county in a certain city in the northwest of the Sichuan Basin is used as the target work area, as Figure 6 and 7 shown in the work area. The terrain of this target work area is high in the northeast and low in the southwest, with a low-lying Tongjiang River valley in the middle. The east-west cross-section is in an asymmetric saddle shape. It belongs to the transitional area from hilly to low mountainous, and the geological structure belongs to the gentle fold area. Therefore, except for sporadic gently inclined and monoclinic low mountain terrains affected by fold structures in the area close to the north, the rest are low mountain and hilly terrains such as table-shaped, platform-shaped, and branch-shaped. The river valleys mainly develop in the north-south direction. The terrain of this target work area slopes from the high hilly and low mountain areas in the northeast above 700 meters above sea level to the middle and shallow hilly areas below 600 meters in the southwest. The highest point is a certain mountain in the northeast (altitude 911.6 meters). The lowest point is the Sanjiangkou where a certain river flows out (altitude 413 meters), with an absolute drop of 498.6 meters. The terrain cutting depth of the whole area is about 100 - 300 meters. The microtremor exploration points in this target work area are arranged according to various factors such as production requirements, exploration degree, topography, and surface lithology. The surface structure survey points in the target work area are densified on the basis of existing survey points, and it is considered to be evenly arranged in each stratum as much as possible. A total of 140 surface survey control points are arranged. Among them, the AmbiSeis software is used for microtremor data processing, mainly using the spatial autocorrelation method, and the genetic inversion algorithm is used for inversion. The amplitude and morphology of microtremor signals change with time and space, but have statistical stability within a certain time and space range, and can be described by a stationary random process in time and space. The data processing is based on the stationary random process, extracts the surface wave (Rayleigh wave) dispersion curve from the microtremor signal, and obtains the shear wave velocity structure of the underground medium through the inversion of the dispersion curve, as Figure 6 and 7 shown. According to the P-wave data obtained from the existing surface survey, calculate the petrophysical parameters of each geological horizon, and convert the shear wave velocity structure based on microtremors at each measuring point into P-wave velocity. According to the accurate ground geological map, construct the shallow ground structure model, and input the P-wave velocity of each measuring point into the shallow ground structure model for velocity interpolation, so as to obtain the near-surface P-wave velocity model based on the shallow ground structure model, as Figure 8 shown.

[0076] See Figure 9, the present disclosure calibrates the strike of geological horizons and geological boundaries based on surface surveys of geological maps and lidar data, obtains the fault attitude and the main horizon interfaces and their attitudes along the seismic survey line, thereby constructs a shallow surface structure model with the terrain line as the upper limit and the top surface of the high-velocity layer as the lower limit, uses the microtremor exploration technology to obtain the shear wave velocity structure at the measuring points, and uses the shear-wave to compress-wave velocity ratios of each horizon obtained from surface velocity surveys, micro-logging, and laboratory cores to convert the shear wave velocity of the measuring points into compressional wave velocity. Finally, a shallow compressional wave velocity model is constructed with the shallow surface structure model as a constraint. Based on the shallow velocity field of the shallow surface structure model, the inverted velocity is close to the formation velocity, and the accuracy is relatively high, providing a good near-surface compressional wave velocity model for subsequent prestack depth migration.

[0077] See Figure 10 , an embodiment of the present disclosure provides a near-surface compressional wave velocity modeling device based on microtremor exploration, including:

[0078] A correction module 11, configured to obtain a geological map of the target work area based on surface surveys, correct the geological boundaries of the geological map based on surface surveys, and obtain a corrected geological map;

[0079] A drawing module 12, configured to draw a geological cross-section along the seismic survey line according to the formation, fault, and formation attitude information provided by the corrected geological map, and obtain a shallow surface structure model of the target work area;

[0080] A conversion module 13, configured to obtain the shallow shear wave velocity of each preset measuring point in the target work area, and convert the shallow shear wave velocity of each preset measuring point into compressional wave velocity;

[0081] An interpolation module 14, configured to perform spatial interpolation on the compressional wave velocity of each preset measuring point with the shallow surface structure model as a constraint, and obtain a near-surface compressional wave velocity model based on the shallow surface structure model.

[0082] The implementation processes of the functions and actions of each unit in the above device are specifically described in detail in the implementation processes of the corresponding steps in the above method, and will not be elaborated here.

[0083] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can be referred to the partial description of the method embodiment. The device embodiments described above are merely 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 work.

[0084] In the above embodiments, any combination of the correction module 11, the drawing module 12, the conversion module 13, and the interpolation module 14 can be integrated into 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 correction module 11, the drawing module 12, the conversion module 13, and the interpolation 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 a chip, a system on a substrate, a system on a 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 any appropriate combination of several of them. Alternatively, at least one of the correction module 11, the drawing module 12, the conversion module 13, and the interpolation module 14 can be at least partially implemented as a computer program module, which can execute corresponding functions when the computer program module is run.

[0085] Referring to Figure 11 As shown, the electronic device provided by the fourth exemplary 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 communicate with each other through the communication bus 1140;

[0086] The memory 1130 is used to store computer programs;

[0087] When the processor 1110 executes the program stored on the memory 1130, it implements the near-surface longitudinal wave velocity modeling method based on microtremor exploration as follows:

[0088] Obtain a ground geological map based on surface surveys of the target work area, correct the geological boundaries of the ground geological map based on surface surveys to obtain a corrected ground geological map;

[0089] According to the formation, fault, and formation attitude information provided by the corrected ground geological map, draw a geological cross-section along the seismic survey line to obtain a shallow ground structure model of the target work area;

[0090] Obtain the shallow surface shear wave velocity of each preset measuring point in the target work area, and convert the shallow surface shear wave velocity of each preset measuring point into a longitudinal wave velocity;

[0091] With the shallow ground structure model as a constraint, spatially interpolate the longitudinal wave velocity of each preset measuring point to obtain a near-surface longitudinal wave velocity model based on the shallow ground structure model.

[0092] The aforementioned communication bus 1140 can be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 1140 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only a thick line is shown in the figure, but it does not mean that there is only one bus or one type of bus.

[0093] The communication interface 1120 is used for communication between the aforementioned electronic device and other devices.

[0094] The memory 1130 can include a Random Access Memory (RAM), and can also include a non-volatile memory, such as at least one disk memory. Optionally, the memory 1130 can also be at least one storage device located far from the aforementioned processor 1110.

[0095] The aforementioned processor 1110 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can 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.

[0096] Based on the same inventive concept, the fifth exemplary embodiment of the present disclosure also provides 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, it implements the near-surface longitudinal wave velocity modeling method based on microtremor exploration as described above.

[0097] The computer-readable storage medium can be included in the device / apparatus described in the above embodiments; it can also exist alone without being assembled into the device / apparatus. The aforementioned computer-readable storage medium carries one or more programs, and when the one or more programs are executed, it implements the near-surface longitudinal wave velocity modeling method based on microtremor exploration according to the embodiments of the present disclosure.

[0098] 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 memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), portable compact disk read-only memories (CD-ROMs), 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 the program may be used by or in combination with an instruction execution system, apparatus, or device.

[0099] 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 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 including 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 "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

[0100] 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 should be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for near - surface longitudinal wave velocity modeling based on micro - motion exploration, characterized in that, The method includes: Obtaining a ground geological map based on surface surveys of the target work area, and correcting the geological boundaries of the ground geological map based on surface surveys to obtain a corrected ground geological map; According to the formation, fault, and formation attitude information provided by the corrected ground geological map, drawing a geological cross-section along the seismic survey line to obtain a shallow ground structure model of the target work area; Obtaining the shallow surface shear wave velocity of each preset measuring point in the target work area, and converting the shallow surface shear wave velocity of each preset measuring point into a longitudinal wave velocity; With the shallow ground structure model as a constraint, performing spatial interpolation on the longitudinal wave velocity of each preset measuring point to obtain a near-surface longitudinal wave velocity model based on the shallow ground structure model.

2. The method according to claim 1, characterized in that, The correcting the geological boundaries of the ground geological map based on surface surveys to obtain a corrected ground geological map includes: Using lidar to obtain high-precision ground data of the target work area, and correcting the geological boundaries of the ground geological map based on surface surveys according to the geological boundaries in the high-precision ground data to obtain a corrected ground geological map, where the resolution of the high-precision ground data is not less than 0.1m * 0.1m.

3. The method according to claim 1, characterized in that, The drawing a geological cross-section along the seismic survey line according to the formation, fault, and formation attitude information provided by the corrected ground geological map to obtain a shallow ground structure model of the target work area includes: According to the corrected ground geological map, determining the positions of geological interfaces and fault development and the dip of fault development at the seismic survey line position in the target work area, and demarcating each geological age and formation attitude on the corrected ground geological map according to the positions of geological interfaces and fault development and the dip of fault development; Within the range of the ground elevation at the seismic survey line position and the top surface of the high-velocity layer, interpreting the geological layer planes and faults according to each geological age and formation attitude; Closing the interpreted geological layer plane and fault data into different geological blocks, and constructing a shallow ground structure model of the target work area according to different geological blocks by using the spatial topological relationship containing reverse faults and horizons.

4. The method according to claim 3, characterized in that, The top surface of the high-velocity layer is obtained through geophysical data, surface low-velocity zone surveys, and regional geological data of the target work area.

5. The method according to claim 1, characterized in that, The obtaining the shallow surface shear wave velocity of each preset measuring point in the target work area and converting the shallow surface shear wave velocity of each preset measuring point into a longitudinal wave velocity includes: Using the microtremor exploration technique to obtain the shallow surface shear wave velocity of each preset measuring point in the target work area; Obtaining the shear wave to longitudinal wave velocity ratio of each geological layer according to the surface velocity survey, shear wave and longitudinal wave logging data, and indoor core tests in the target work area; According to the shear wave to longitudinal wave velocity ratio of each geological layer, converting the shallow surface shear wave velocity of each preset measuring point into a longitudinal wave velocity.

6. The method according to claim 5, characterized in that, The using the microtremor exploration technique to obtain the shallow surface shear wave velocity of each preset measuring point in the target work area includes: Based on a stationary random process, extracting the surface wave dispersion curve from the microtremor signal, and obtaining the shear wave velocity structure of the underground medium in the target work area through inversion of the dispersion curve; Extracting the shallow surface shear wave velocity of each preset measuring point from the shear wave velocity structure.

7. The method according to claim 1, characterized in that, The performing spatial interpolation on the longitudinal wave velocity of the preset measuring points with the shallow ground structure model as a constraint to obtain a near-surface longitudinal wave velocity model based on the shallow ground structure model includes: Input the P-wave velocity of each preset measurement point into the shallow ground structure model for velocity interpolation to obtain the near-surface P-wave velocity model based on the shallow ground structure model.

8. A device for near - surface longitudinal wave velocity modeling based on micro - motion exploration, characterized in that, It includes: A correction module for obtaining the ground geological map based on surface surveys of the target work area, correcting the geological boundaries of the ground geological map based on surface surveys to obtain the corrected ground geological map; A drawing module for drawing a geological cross-section along the seismic survey line according to the formation, fault, and formation attitude information provided by the corrected ground geological map to obtain the shallow ground structure model of the target work area; A conversion module for obtaining the shallow surface S-wave velocity of each preset measurement point in the target work area and converting the shallow surface S-wave velocity of each preset measurement point into a P-wave velocity; An interpolation module for spatially interpolating the P-wave velocity of each preset measurement point with the shallow ground structure model as a constraint to obtain the near-surface P-wave velocity model based on the shallow ground structure model.

9. An electronic device, characterized in that, It includes 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; The memory is used for storing computer programs; The processor, when executing the program stored on the memory, implements the near-surface P-wave velocity modeling method based on microtremor exploration described in any one of claims 1-7.

10. A computer - readable storage medium, on which a computer program is stored, characterized in that, The computer program, when executed by the processor, implements the near-surface P-wave velocity modeling method based on microtremor exploration described in any one of claims 1-7.

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