A multi-source wave velocity structure fusion method and device, electronic equipment and storage medium

Abstract

The application discloses a multi-source wave velocity structure fusion method, comprising: obtaining original data sources, including a large-range wave velocity structure data set covering the range where the engineering structure is located, a surface geology lithology distribution map and engineering site drilling exploration information; for the surface geology lithology distribution map, classifying the rocks through image recognition, and setting the wave velocity based on the rock categories; for the remaining original data sources, removing outliers through data cleaning and standardization processing respectively to determine the corresponding wave velocities; for the wave velocities determined based on the engineering site drilling exploration information, converting the one-dimensional wave velocities into three-dimensional wave velocities by adding transition zones around the drilling points; performing data enhancement on the three-dimensional wave velocities corresponding to each original data source through an interpolation method; and performing weight fusion on each type of wave velocity after data enhancement to obtain a fused wave velocity structure. The application improves the precision and efficiency of wave velocity structure modeling, and enables the wave velocity structure modeling to be matched with wideband ground motion numerical simulation of a required calculation frequency.

Description

Technical Field

[0001] This invention belongs to the field of earthquake engineering technology, specifically relating to a multi-source wave velocity structure fusion method, device, electronic equipment, and storage medium. Background Technology

[0002] Seismic design of structures includes three steps: (1) determining the design ground motion parameters; (2) structural seismic response analysis; and (3) engineering safety evaluation. Among these, reasonable ground motion input parameters are a prerequisite for seismic design. For the seismic design of major projects, it is necessary to determine reasonable ground motion parameters through specialized seismic hazard analysis, such as peak ground acceleration corresponding to a given exceedance probability level and design response spectrum. Currently, the commonly used seismic hazard analysis methods are mainly probabilistic seismic hazard analysis (PSHA) and deterministic seismic hazard analysis (DSHA). Both PSHA and DSHA generally use empirical ground motion attenuation relationships to determine the ground motion parameters of the target site. The determination of empirical ground motion attenuation relationships depends on seismic record data. However, for most regions, seismic record data is relatively scarce, and the existing seismic record data is not rich enough for establishing empirical ground motion models. In particular, for major earthquakes, which are more important for seismic research on major projects, the frequency of occurrence is extremely low, and the existing near-field record data of major earthquakes is particularly scarce. The prediction results of empirical ground motion models for the ground motion parameters of major earthquakes may have a large degree of uncertainty. Compared with empirical ground motion models, deterministic numerical simulation methods based on physical mechanisms can comprehensively consider the effects of the source rupture process, propagation path and local site conditions, and therefore have received increasing attention from researchers.

[0003] Numerical simulations of seismic ground motion based on physical mechanisms can comprehensively consider the influence of wave velocity structure and topographic conditions. However, the accuracy of the simulation results is also constrained by the rationality of the modeling. The wave velocity (P-wave velocity Vp, S-wave velocity Vs) structure of the subsurface medium (especially shallow sedimentary layers) is a major factor controlling the propagation path, amplitude, frequency components, and duration of seismic waves. It is one of the most fundamental and important input parameters in numerical simulations (such as the finite element method, finite difference method, and spectral element method). For topographic conditions, a large number of remote sensing technologies have been developed that can provide digital elevation models with meter-level or even higher accuracy, far exceeding the resolution required for computation. However, due to insufficient understanding of subsurface structures, high-precision, high-resolution wave velocity structures are currently lacking in most areas.

[0004] Existing research has established some global and national-scale wave velocity structures based on seismic inversion techniques. However, the horizontal resolution of these wave velocity structures is often only around 100 km or 50 km, which is far from meeting the needs of simulation modeling. In addition, some wave velocity structure information often exists in surface geological data and engineering geological surveys, but there is currently no effective method to comprehensively consider this multi-source wave velocity structure information.

[0005] In summary, existing wave velocity-structure fusion methods lack a systematic fusion framework, often resorting to simple splicing or subjective interpolation. They struggle to effectively integrate data from different scales (from regional kilometer-level to site meter-level), resolutions, accuracies, and sources (geophysical, geological, empirical). When fusing regional models with high-resolution site models, discontinuities or inconsistencies frequently occur in the transition zone. Furthermore, they fail to consider the varying sensitivity of different frequency bands of seismic waves to the different scale characteristics of wave velocity-structure. Finally, the fusion results often fail to simultaneously meet the accuracy requirements for both low-frequency and high-frequency ground motion simulations. Summary of the Invention

[0006] To address one or more of the aforementioned problems in the existing technology, this invention aims to provide an efficient and robust multi-source wave velocity structure fusion method, device, electronic device, and storage medium. This method can integrate wave velocity structure information from multiple sources (geophysical exploration, geological data, background models, empirical relationships, etc.) at different scales and resolutions, significantly improving the efficiency, accuracy, and reliability of broadband ground motion numerical simulation. Furthermore, it enables the simulation to be matched with the broadband ground motion numerical simulation of the required calculation frequency, thereby making its application in earthquake engineering more effective and standardized.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] The first aspect of this invention provides a multi-source wave velocity structure fusion method, the obtained fused wave velocity structure being used for multi-scale numerical simulation of seismic motion from source to medium to site. The fusion method includes:

[0009] Obtain the original data source, which should include at least a large-scale wave velocity structure dataset covering the area where the engineering structure is located, a surface geological lithology distribution map, and borehole exploration information of the engineering site.

[0010] The wave velocity of each original data source was determined. Specifically, for the surface geological lithology distribution map, rocks were classified through image recognition, and the wave velocity was set based on the rock category. For the remaining original data sources, outliers were removed through data cleaning and standardization to determine the corresponding wave velocity.

[0011] For wave velocities determined based on borehole exploration information at engineering sites, a transition zone is added around the borehole points to convert one-dimensional wave velocities into three-dimensional wave velocities; then, the three-dimensional wave velocities corresponding to each original data source are augmented using interpolation methods.

[0012] The weights of various data sources are defined based on their confidence level, spatial resolution, consistency, and whether they are actual measured data. The various wave velocities after data augmentation are then fused to obtain the fused wave velocity structure.

[0013] In some embodiments, the resolution of the large-scale wave velocity structure dataset is on the order of 50 km to 100 km; and / or

[0014] The number of data points in the horizontal direction shall not be less than 9; and / or

[0015] At least two large-scale wave velocity structure datasets must be obtained; and / or

[0016] The length and width of the area covered by the large-scale wave velocity structure should not be less than 100 km, and the depth should not be less than 30 km.

[0017] In some embodiments, the borehole exploration information at the engineering site includes data including underground wave velocity, which includes borehole Vs / Vp profiles, dense array surface wave inversion results, and seismic reflection / refraction profiles.

[0018] In some embodiments, determining wave velocity based on a surface geological lithology distribution map includes:

[0019] Remove auxiliary information, including text labels and contour lines, from the surface geological lithology distribution map;

[0020] The surface geological lithology distribution map is extracted by image recognition method. Based on the RGB value of each pixel, rocks represented by the same color are classified. The wave velocity and density of different rocks are respectively used as the wave velocity and density of each type of rock.

[0021] In some embodiments, before performing data cleaning on the large-scale wave velocity structure dataset, pre-interpolation is also performed.

[0022] In some embodiments, the conversion of one-dimensional wave velocity into three-dimensional wave velocity by adding a transition zone around the borehole point for the wave velocity determined based on borehole exploration information at the engineering site includes:

[0023] Centered on the borehole location, the distance from the transition boundary to the center is set. The wave velocity structure at the outer boundary is consistent with the large-scale wave velocity structure, the wave velocity structure at the center is consistent with the one-dimensional wave velocity of the engineering borehole, and the rest is transitioned through linear interpolation.

[0024] In some embodiments, the data enhancement of the three-dimensional wave velocities corresponding to each original data source through interpolation includes:

[0025] Determine depth The wave velocity corresponding to various data sources is resampled onto the target computation grid; among them, for depths of 0~ In some parts, Kriging interpolation is used to generate wave velocity structures; for depth... The following section uses linear interpolation;

[0026] The two wave velocity structures are merged to obtain an equally spaced matrix wave velocity structure.

[0027] The second aspect of this invention provides a multi-source wave velocity structure fusion device, the resulting fused wave velocity structure being used for multi-scale numerical simulation of seismic motion from the source-medium-site. The fusion device includes:

[0028] The first module is configured to acquire raw data sources, including at least a large-scale wave velocity structure dataset covering the area where the engineering structure is located, a surface geological lithology distribution map, and borehole exploration information of the engineering site.

[0029] The second module is configured to determine the wave velocity of each original data source. Specifically, for the surface geological lithology distribution map, rocks are classified through image recognition, and wave velocities are set based on rock categories. For the remaining original data sources, outliers are removed through data cleaning and standardization to determine the corresponding wave velocity.

[0030] The third module is configured to convert one-dimensional wave velocities into three-dimensional wave velocities by adding a transition zone around the borehole points for wave velocities determined based on borehole exploration information at the engineering site; then, the three-dimensional wave velocities corresponding to each original data source are augmented using interpolation methods.

[0031] The fourth module is configured to define the weights of various data sources based on their confidence level, spatial resolution, consistency, and whether they are measured data, and then perform weighted fusion of the various wave velocities after data augmentation to obtain a fused wave velocity structure.

[0032] A third aspect of the present invention provides an electronic device comprising:

[0033] At least one processor, and a memory communicatively connected to said at least one processor;

[0034] The memory stores instructions executable by the at least one processor, the instructions being configured to perform the fusion method according to any embodiment of the first aspect of the present invention.

[0035] A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to perform the fusion method according to any embodiment of the first aspect of the present invention.

[0036] Features and beneficial effects of the present invention:

[0037] This invention provides an efficient and robust method, apparatus, electronic device, and storage medium for fusing multi-source wave velocity structures. It integrates wave velocity structure information from multiple sources (geophysical exploration, geological data, background models, empirical relationships, etc.) at different scales and resolutions. By establishing reasonable fusion rules, it ensures the spatial continuity and physical rationality of the fused wave velocity structure. Considering the physical mechanism of broadband seismic wave propagation, the fused wave velocity structure can more accurately support numerical simulations of seismic motions from low to high frequencies. This significantly improves the efficiency, accuracy, and reliability of broadband seismic motion numerical simulations, making its application in earthquake engineering more effective and standardized. Attached Figure Description

[0038] Figure 1 A flowchart illustrating a multi-source wave velocity structure fusion method provided in the first aspect of the present invention;

[0039] Figure 2 This is a schematic diagram of the final wave velocity structure generated in an embodiment of the present invention;

[0040] Figure 3 (a), (b), and (c) are schematic diagrams of the earthquake motion time histories in the x, y, and z directions obtained by calculating the wave velocity structure generated using the method of the embodiments of the present invention.

[0041] Figure 4 This is a schematic diagram of the structure of an electronic device provided in a third aspect embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application. The following solutions are merely illustrative of the inventive concept, and specific solutions are not limited thereto. Furthermore, for ease of description, the accompanying drawings show only the parts relevant to the present invention, not the entire process.

[0043] Conversely, this application covers any alternatives, modifications, equivalent methods, and schemes made within the spirit and scope of this application as defined by the claims. Furthermore, to provide the public with a better understanding of this application, certain specific details are described in detail below. However, this application can be fully understood by those skilled in the art even without these detailed descriptions.

[0044] See Figure 1 The first aspect of this invention provides a multi-source wave velocity structure fusion method. The fused wave velocity structure is used for multi-scale numerical simulation of seismic motion from the source to the medium to the site. The fusion method of this embodiment includes the following steps:

[0045] Step S1: Obtain the original data sources provided by different entities, including at least a large-scale publicly available wave velocity structure dataset covering the area where the engineering structure is located, surface geological lithology distribution maps, and borehole exploration information of the engineering site;

[0046] Step S2: Determine the wave velocity of each original data source; for the surface geological lithology distribution map, rocks are classified by image recognition, and wave velocities are set based on rock categories; for the remaining original data sources, outliers are removed by data cleaning and standardization to determine the corresponding wave velocity.

[0047] Step S3: For the wave velocity determined based on the borehole exploration information of the engineering site, the one-dimensional wave velocity is converted into a three-dimensional wave velocity by adding a transition zone around the borehole point; then the three-dimensional wave velocity corresponding to each original data source is augmented by interpolation method.

[0048] Step S4: Define the weights of various data sources based on their confidence level, spatial resolution, consistency, and whether they are measured data. Then, perform weighted fusion of the various wave velocities after data augmentation to obtain a fused wave velocity structure that matches the required broadband ground motion numerical simulation.

[0049] In some embodiments, in step S1, a publicly available large-scale wave velocity structure dataset is composed of coarse-resolution publicly available large-scale wave velocity structures. These publicly available large-scale wave velocity structures are generally provided by publicly published papers from research institutions and can be obtained through online download or by contacting the paper authors. Such wave velocity structures include regional or global scale background wave velocity structure model data such as CRUST1.0, whose resolution is often on the order of 50km to 100km. At least nine data points are selected in the horizontal direction for subsequent interpolation processing. To reduce the uncertainty of large-scale wave velocity structures, at least two large-scale wave velocity structure datasets should be collected, including the coordinates and wave velocities of the subsurface medium within the region. The length and width of the area covered by the large-scale wave velocity structure should not be less than 100km, and the depth should not be less than 30km.

[0050] In some embodiments, in step S1, the surface geological lithology distribution map can be obtained from the China Geological Archives.

[0051] In some embodiments, in step S1, the wave velocity structure of a local area can be obtained based on the borehole exploration information at the engineering site. The borehole exploration information at the engineering site is obtained from engineering geological survey data provided by the engineering design unit or construction unit, and should include data including underground wave velocities, specifically including borehole Vs / Vp profiles, surface wave inversion results from dense arrays, and high-resolution seismic reflection / refraction profiles, etc.

[0052] It is understandable that the original data sources of different resolutions obtained through step S1 in the embodiments of the present invention include comprehensive possible data sources, provide multi-source wave velocity structures of different scales, and at the same time, enable the wave velocity structure subsequently established to encompass the entire fault and the engineering site in a sufficiently economical manner, and the model size is also sufficient when performing local analysis of the engineering site.

[0053] In some embodiments, step S2 includes:

[0054] Step S201: For the surface geological lithology distribution map obtained in step S1, firstly, delete the auxiliary information in the map, mainly including text labels and contour lines, etc. Then, extract the pixels of the surface geological lithology distribution map through image recognition methods, and then classify the rocks represented by the same color according to the RGB value of each pixel. The wave velocity and density parameters of different rocks provided by existing literature are used as the wave velocity and density parameters of each type of rock.

[0055] Step S202: For the large-scale wave velocity structure dataset obtained in step S1, a certain degree of pre-interpolation should be performed first to avoid abrupt changes in parameters of adjacent points during the interpolation process. It is recommended to interpolate the resolution to below the recommended interpolation value of 10km.

[0056] The pre-interpolated large-scale wave velocity structure dataset and the borehole exploration information from the engineering site were preprocessed as follows: First, data cleaning was performed; then, the wave velocity variations with depth of multiple wave velocity structures within the same data source were compared, the standard deviation of each wave velocity structure relative to the average wave velocity structure was calculated, and a threshold was defined. Outliers are removed based on this threshold to obtain the wave velocity corresponding to various data sources, i.e., the wave velocity at different resolutions.

[0057] In some embodiments, step S3 includes:

[0058] Step S301: For the one-dimensional wave velocity determined based on the borehole exploration information of the engineering site, with the borehole location as the center, the distance from the transition boundary to the center is set to 2km. The wave velocity structure at the outer boundary is consistent with the large-scale wave velocity structure, the wave velocity structure at the center is consistent with the one-dimensional wave velocity of the engineering borehole, and the rest is transitioned by linear interpolation.

[0059] Step S302: Determine the depth , The wave velocity should be greater than the thickness of the low-velocity region and the fault depth, and the wave velocity corresponding to various data sources should be resampled onto the target computational grid; for depths of 0~ In this part, Kriging interpolation is used to generate the wave velocity structure. For each target calculation grid point, at least 3*3*3 sample points around it should be selected for interpolation; for depth... The following part, due to its high wave velocity and distance from the ground surface, has a smaller impact on the response of the ground station. Linear interpolation can be used to reduce the interpolation workload. Finally, the two wave velocity structures are merged to obtain an equally spaced matrix wave velocity structure. In order to adapt to the influence of undulating terrain and changing wave velocity, the horizontal spacing of the obtained wave velocity structure should not be greater than 2km and the vertical spacing should not be less than 500m.

[0060] In some embodiments, step S4 includes:

[0061] Step S401, Weight Setting

[0062] Fusion weights The calculation should be based on one or more of the following factors: (1) uncertainty / confidence of the data source, data with high confidence has high weight; (2) spatial resolution of the data source, high-resolution data has high weight when representing small-scale features; low-resolution data has high weight when representing large-scale background or constraining deep structures; (3) when multiple independent data sources have good consistency, their comprehensive weight can be increased; (4) the location with actual measured data, actual measured data has the highest weight.

[0063] Step S402, Wave speed fusion

[0064] Weighted fusion wave velocity structure:

[0065]

[0066] in, To integrate wave velocity structure; It is a single wave velocity structure, corresponding to a type of wave velocity after step S3 data enhancement; In this embodiment, n=3, which represents the number of wave velocity structures. is the weight of the i-th wave speed structure.

[0067] In some embodiments, the fusion method of the present invention further includes: post-processing the obtained fused wave velocity structure, specifically:

[0068] Step S501: Smooth the fused wave velocity structure to eliminate non-physical drastic changes caused by data jumps or weight abrupt changes, especially at the boundaries of different data source coverage areas, to avoid reflection and refraction caused by wave velocity abrupt changes; smoothing methods can include linear interpolation, Gaussian filtering, etc.

[0069] Step S502: Check the physical consistency of the fused wave velocity structure: (1) Whether the Vp / Vs ratio is within the set range; (2) Whether the wave velocity increases reasonably with depth. If there is a low-velocity underground structure, a strict inspection is required to confirm whether it conforms to the actual geological conditions.

[0070] The post-processed fused wave velocity structure is used as input for multi-scale numerical simulation of seismic motion in the source-medium-site region of the target area.

[0071] An illustrative embodiment of the present invention is as follows, and this embodiment defines the following scope:

[0072] Large area: A cubic area with a horizontal range of 50km × 50km and a depth of 30km is defined with a certain high dam hydropower station as the center, including the known active fault F1 (extending to a depth of 15km).

[0073] Local area: Focusing on the near-field area of ​​the high dam hydropower station (2km×2km);

[0074] Fault model: Based on the geological survey report, fault F1 is modeled as a rupture surface with a dip angle of 60° and a strike of N45°E.

[0075] This embodiment specifically includes the following steps:

[0076] Step S1: Obtain the original data sources provided by different entities.

[0077] The large-scale wave velocity structure dataset includes two datasets, CRUST1.0 and EARA2024, which were obtained by downloading from online research papers.

[0078] Obtain surface geological lithology distribution maps through the China Geological Archives;

[0079] The wave velocity structure of the local area where the project is located is obtained through engineering design units.

[0080] Step S2: Determine the wave velocity of each original data source.

[0081] For the obtained surface geological lithology map, firstly, the auxiliary information in the map, mainly including text labels and contour lines, is removed. Then, the surface geological lithology distribution map is extracted by image recognition method. Then, based on the RGB value of each pixel, the rocks represented by the same color are classified. The wave velocity and density parameters of different rocks provided in existing literature are used as the wave velocity and density parameters of each type of rock.

[0082] Interpolation was performed on two large-scale wave velocity structure datasets, CRUST1.0 and EARA2024, with a resolution of 10km.

[0083] Data cleaning was performed on both the pre-interpolated large-scale wave velocity structure dataset and the borehole exploration information from the engineering site, and missing values ​​were added. The standard deviation of each wave velocity structure relative to the average wave velocity structure was calculated, and a standard deviation threshold of 0.5 was defined to remove outliers exceeding this threshold.

[0084] Step S3:

[0085] A transition zone is added around the borehole point to convert the one-dimensional wave velocity into a three-dimensional wave velocity. With the borehole location as the center, the distance from the transition boundary to the center is set to 2km. The wave velocity structure at the outer boundary is consistent with the large-scale wave velocity structure, the wave velocity structure at the center is consistent with the one-dimensional wave velocity of the engineering borehole, and the rest is transitioned by linear interpolation.

[0086] Data augmentation is performed on the 3D wave velocities corresponding to each original data source using interpolation methods. Depth is then determined. , The depth is 20km, which is greater than the thickness of the low-velocity zone and the fault depth. Data at different resolutions are resampled onto the target computational grid. For the 0-20km depth range, Kriging interpolation is used to generate the velocity structure. For each target computational grid point, 3*3*3 sample points around it are selected for interpolation. For the depth below 20km, since the velocity is higher and the distance from the surface is greater, the impact on the response of surface stations is smaller. Linear interpolation is used to reduce the interpolation workload. Finally, the two velocity structures are merged to obtain an equally spaced matrixed velocity structure. To adapt to the influence of undulating terrain and changing velocity, the horizontal spacing of the obtained velocity structure is 1km and the vertical spacing is 200m.

[0087] Step S4: Define the weights of various data sources based on their confidence level, spatial resolution, consistency, and whether they are measured data. Then, perform weighted fusion of the various wave velocities after data augmentation to obtain the fused wave velocity structure. It matches the required broadband numerical simulation of ground motion. Calculate using the formula:

[0088]

[0089] CRUST1.0 and EARA2024 datasets: These datasets have lower resolution and relatively lower confidence levels, with a weight of 0.5.

[0090] Wave velocity structure obtained from surface geological lithology distribution map: high resolution, but with errors, weight set at 0.8;

[0091] Borehole exploration information at the engineering site: measured data, with the highest confidence level, weighted at 1.0;

[0092] The final fused wave velocity structure obtained in this embodiment can be referenced. Figure 2 . Figure 3 (a), (b), and (c) are the time histories of ground motion in the x, y, and z directions obtained by using the fused wave velocity structure for numerical simulation of ground motion, respectively. The time-domain characteristics of the time histories conform to the physical laws of actual ground motion, verifying the correctness and rationality of the model.

[0093] A second aspect of the present invention provides a multi-source wave velocity structure fusion device, the resulting fused wave velocity structure being used for multi-scale numerical simulation of seismic motion from source to medium to site. The fusion device includes:

[0094] The first module is configured to acquire raw data sources, including at least a large-scale wave velocity structure dataset covering the area where the engineering structure is located, a surface geological lithology distribution map, and borehole exploration information of the engineering site.

[0095] The second module is configured to determine the wave velocity of each original data source. Specifically, for the surface geological lithology distribution map, rocks are classified through image recognition, and wave velocities are set based on rock categories. For the remaining original data sources, outliers are removed through data cleaning and standardization to determine the corresponding wave velocity.

[0096] The third module is configured to convert one-dimensional wave velocities into three-dimensional wave velocities by adding a transition zone around the borehole points for wave velocities determined based on borehole exploration information at the engineering site; then, the three-dimensional wave velocities corresponding to each original data source are augmented using interpolation methods.

[0097] The fourth module is configured to define the weights of various data sources based on their confidence level, spatial resolution, consistency, and whether they are measured data, and then perform weighted fusion of the various wave velocities after data augmentation to obtain a fused wave velocity structure.

[0098] It should be noted that the foregoing explanation of the embodiments of the multi-source wave velocity structure fusion method also applies to the multi-source wave velocity structure fusion device of this embodiment, and will not be repeated here.

[0099] To implement the above embodiments, this invention also proposes a computer-readable storage medium storing a computer program that is executed by a processor to perform the multi-source wave velocity structure fusion method of the above embodiments.

[0100] The following is for reference. Figure 4 The diagram illustrates a structural schematic of an electronic device suitable for implementing embodiments of the present invention. It should be noted that the electronic device in the embodiments of the present invention may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs, desktop computers, and servers. Figure 4 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0101] like Figure 4 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 101, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 102 or a program loaded from a storage device 108 into a random access memory (RAM) 103. The RAM 103 also stores various programs and data required for the operation of the electronic device. The processing unit 101, ROM 102, and RAM 103 are interconnected via a bus 104. An input / output (I / O) interface 105 is also connected to the bus 104.

[0102] Typically, the following devices can be connected to I / O interface 105: input devices 106 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, etc.; output devices 107 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 108 including, for example, magnetic tapes, hard disks, etc.; and communication devices 109. Communication device 109 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have instead.

[0103] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, this embodiment includes a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network via communication device 109, or installed from storage device 108, or installed from ROM 102. When the computer program is executed by processing device 101, it performs the functions defined above in the methods of embodiments of this disclosure.

[0104] It should be noted that the computer-readable medium described above in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0105] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0106] The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the aforementioned multi-source beam velocity structure fusion method.

[0107] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and Python, as well as conventional procedural programming languages ​​such as the "C-" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0108] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0109] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0110] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the function involved, as will be understood by those skilled in the art to which embodiments of this application pertain.

[0111] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0112] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0113] Those skilled in the art will understand that implementing all or part of the steps of the methods in the above embodiments can be accomplished by instructing related hardware through a program. The developed program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0114] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0115] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for fusing multi-source wave velocity structures, characterized in that, The obtained fused wave velocity structure is used for multi-scale numerical simulation of seismic motion from the source-medium-site, and the fusion method includes: Obtain the original data source, which should include at least a large-scale wave velocity structure dataset covering the area where the engineering structure is located, a surface geological lithology distribution map, and borehole exploration information of the engineering site. The wave velocity of each original data source was determined. Specifically, for the surface geological lithology distribution map, rocks were classified through image recognition, and the wave velocity was set based on the rock category. For the remaining original data sources, outliers were removed through data cleaning and standardization to determine the corresponding wave velocity. For wave velocities determined based on borehole exploration information at engineering sites, a transition zone is added around the borehole points to convert one-dimensional wave velocities into three-dimensional wave velocities; then, the three-dimensional wave velocities corresponding to each original data source are augmented using interpolation methods. The weights of various data sources are defined based on their confidence level, spatial resolution, consistency, and whether they are actual measured data. The various wave velocities after data augmentation are then fused to obtain the fused wave velocity structure.

2. The multi-source wave velocity structure fusion method according to claim 1, characterized in that, The resolution of the large-scale wave velocity structure dataset is in the range of 50km to 100km; and / or The number of data points in the horizontal direction shall not be less than 9; and / or At least two large-scale wave velocity structure datasets must be obtained; and / or The length and width of the area covered by the large-scale wave velocity structure should not be less than 100 km, and the depth should not be less than 30 km.

3. The multi-source wave velocity structure fusion method according to claim 1, characterized in that, The borehole exploration information at the engineering site includes data including underground wave velocity, which includes borehole Vs / Vp profiles, surface wave inversion results from dense arrays, and seismic reflection / refraction profiles.

4. The multi-source wave velocity structure fusion method according to claim 1, characterized in that, Based on the surface geological lithology distribution map, determine the wave velocity, including: Remove auxiliary information, including text labels and contour lines, from the surface geological lithology distribution map; The surface geological lithology distribution map is extracted by image recognition method. Based on the RGB value of each pixel, rocks represented by the same color are classified. The wave velocity and density of different rocks are respectively used as the wave velocity and density of each type of rock.

5. The multi-source wave velocity structure fusion method according to claim 1, characterized in that, Before performing data cleaning on the large-scale wave velocity structure dataset, pre-interpolation is also performed.

6. The multi-source wave velocity structure fusion method according to claim 1, characterized in that, The method for converting one-dimensional wave velocity into three-dimensional wave velocity by adding a transition zone around the borehole point, based on wave velocity determined from borehole exploration information at the engineering site, includes: Centered on the borehole location, the distance from the transition boundary to the center is set. The wave velocity structure at the outer boundary is consistent with the large-scale wave velocity structure, the wave velocity structure at the center is consistent with the one-dimensional wave velocity of the engineering borehole, and the rest is transitioned through linear interpolation.

7. The multi-source wave velocity structure fusion method according to claim 1, characterized in that, The data enhancement of the three-dimensional wave velocity corresponding to each original data source through interpolation methods includes: Determine depth The wave velocity corresponding to various data sources is resampled onto the target computation grid; among them, for depths of 0~ In some parts, Kriging interpolation is used to generate wave velocity structures; for depth... The following section uses linear interpolation; The two wave velocity structures are merged to obtain an equally spaced matrix wave velocity structure.

8. A multi-source wave velocity structure fusion device, characterized in that, The obtained fused wave velocity structure is used for multi-scale numerical simulation of seismic motion from the source-medium-site, and the fusion device includes: The first module is configured to acquire raw data sources, including at least a large-scale wave velocity structure dataset covering the area where the engineering structure is located, a surface geological lithology distribution map, and borehole exploration information of the engineering site. The second module is configured to determine the wave velocity of each original data source. Specifically, for the surface geological lithology distribution map, rocks are classified through image recognition, and wave velocities are set based on rock categories. For the remaining original data sources, outliers are removed through data cleaning and standardization to determine the corresponding wave velocity. The third module is configured to convert one-dimensional wave velocities into three-dimensional wave velocities by adding a transition zone around the borehole points for wave velocities determined based on borehole exploration information at the engineering site; then, the three-dimensional wave velocities corresponding to each original data source are augmented using interpolation methods. The fourth module is configured to define the weights of various data sources based on their confidence level, spatial resolution, consistency, and whether they are measured data, and then perform weighted fusion of the various wave velocities after data augmentation to obtain a fused wave velocity structure.

9. An electronic device, characterized in that, include: At least one processor, and a memory communicatively connected to said at least one processor; The memory stores instructions executable by the at least one processor, the instructions being configured to perform the fusion method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the fusion method according to any one of claims 1 to 7.

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