A method, system, terminal and readable storage medium for array surface wave imaging based on sampling inversion

Abstract

The present invention relates to the technical field of data processing, and discloses a method, system, terminal and readable storage medium for array surface wave imaging based on sampling inversion. The method includes: repeatedly extracting station pairs from all station pairs to form a station pair combination; extracting single-mode dispersion curve data for each group of the station pair combinations; obtaining inversion dispersion curve data according to the multiple single-mode dispersion curve data, and establishing a spatial dispersion curve according to the inversion dispersion curve data. The present invention aims to solve the problem that in the case of a small number of stations, the method based on array surface waves cannot perform three-dimensional velocity structure imaging. When measuring the dispersion curve, instead of using all station pairs inside the array for dispersion curve measurement, multiple random samplings are carried out, and the difference in the dispersion curves extracted by different station pair combinations is used to inversely calculate the spatial phase velocity distribution, so as to observe the phase velocity distribution inside the array in the case of a small array.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a method, system, terminal and readable storage medium for array surface wave imaging based on sampling inversion. Background Art

[0002] The surface wave imaging technology based on ambient noise is one of the important methods for detecting the internal structure of the earth. Its core idea is to measure the phase velocity or group velocity dispersion curve of surface waves passing through the underground structure from the noise cross-correlation function, and to invert the underground velocity structure through the relationship between the underground structure and the dispersion curve.

[0003] Among them, the measurement methods of the dispersion curve can be mainly divided into two categories: the two-station dispersion curve measurement method based on rays and the dispersion curve measurement method based on an array. Compared with the two-station method, the dispersion curve measurement method of the array type uses the cross-correlation function of all station pairs inside the array to measure the dispersion curve, and its measurement accuracy of the dispersion curve is higher, and it is easier to measure the higher-order modes of the dispersion curve. And under many conditions (such as when the station spacing is small), the two-station method cannot observe the dispersion curve, but the array method is not restricted by this. However, the array surface wave method can only obtain one dispersion curve representing the average underground structure below the array from an array, so as to obtain the one-dimensional velocity structure below the array. When performing three-dimensional velocity structure imaging, usually the array surface wave method needs to divide the research area into multiple overlapping sub-arrays for imaging. However, in many cases, it is often limited by the detection area and cost, and the stations in the detection work area are limited (such as less than 100 stations), and it is difficult to divide the area to obtain enough effective sub-arrays to obtain the dispersion curve. In this case, this method can only detect the one-dimensional velocity structure and is difficult to meet the demand for detecting the underground three-dimensional structure. Summary of the Invention

[0004] The purpose of the present invention is to provide a method, system, terminal and readable storage medium for array surface wave imaging based on sampling inversion, aiming to solve the problem that the existing technology's dispersion curve measurement method based on an array is difficult to meet the demand for detecting the underground three-dimensional structure when the number of stations is small.

[0005] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0006] The present invention provides a method for array surface wave imaging based on sampling inversion, and the method for array surface wave imaging based on sampling inversion includes:

[0007] Repeatedly extracting station pairs from all station pairs to form station pair combinations;

[0008] Extracting single dispersion curve data for each group of the station pair combinations;

[0009] Obtain the inversion dispersion curve data based on the multiple single dispersion curve data, and establish a spatial dispersion curve according to the inversion dispersion curve data.

[0010] Further, the extraction of the single dispersion curve data for each group of the station pair combinations specifically includes:

[0011] Divide the detection space into multiple grids;

[0012] Extract the weights corresponding to each grid and each station pair combination, and calculate the average phase slowness corresponding to all grids and each station pair combination; use the average phase slowness and weight corresponding to each station pair combination as the single dispersion curve data corresponding to the station pair combination.

[0013] Further, the extraction of the weights corresponding to each grid and each station pair combination specifically includes:

[0014] Obtain the dispersion curve rays corresponding to each station pair in each station pair combination;

[0015] Obtain the ray length of each dispersion curve ray and the passing length in each grid passed through by the ray;

[0016] Calculate the weight of each grid corresponding to the corresponding station pair combination according to the ray length and the passing length of all the dispersion curve rays included in each station pair combination.

[0017] Further, the obtaining of the dispersion curve rays corresponding to each station pair in each station pair combination specifically includes:

[0018] Obtain the detection data of the two stations of each station pair in each station pair combination, and calculate the cross-correlation data corresponding to each station pair according to all the detection data;

[0019] Calculate the corresponding dispersion curve rays according to each of the cross-correlation data.

[0020] Further, the calculation of the cross-correlation data corresponding to each station pair according to all the detection data specifically includes:

[0021] Perform mean removal, trend removal, instrument response removal, and segmented cutting on all the detection data in sequence to obtain a plurality of cut data;

[0022] Calculate the segmented cross-correlation data of each of the cut data;

[0023] Superimpose all the segmented cross-correlation data corresponding to the station pair as the cross-correlation data of the corresponding station pair.

[0024] Further, obtaining the inversion dispersion curve data based on the multiple single dispersion curve data specifically includes:

[0025] Calculating the inversion phase slowness of each grid according to the average phase slowness of each single dispersion curve and each weight:

[0026] ;

[0027] Wherein, is the weight matrix, represents the vector composed of the inversion phase slownesses of all grids, represents the vector composed of each average phase slowness;

[0028] Taking the set of all the inversion phase slownesses as the inversion dispersion curve data.

[0029] Further, establishing the spatial dispersion curve based on the inversion dispersion curve data specifically includes:

[0030] Calculating the one-dimensional spatial dispersion curve of the entire detection space according to the inversion phase slowness of each grid;

[0031] Establishing the three-dimensional spatial dispersion curve of the detection space based on the one-dimensional spatial dispersion curve.

[0032] In addition, to achieve the above object, the present invention further provides an array surface wave imaging system based on sampling inversion, and the array surface wave imaging system based on sampling inversion includes:

[0033] A combined extraction module, configured to repeatedly extract station pairs from all station pairs to form a station pair combination;

[0034] A data extraction module, configured to extract the single dispersion curve data of each group of the station pair combinations;

[0035] A data inversion module, obtaining the inversion dispersion curve data based on the multiple single dispersion curve data, and establishing the spatial dispersion curve based on the inversion dispersion curve data.

[0036] In addition, to achieve the above object, the present invention further provides a terminal, and the terminal includes: a memory, a processor, and an array surface wave imaging program based on sampling inversion stored on the memory and executable on the processor. When the array surface wave imaging program based on sampling inversion is executed by the processor, it controls the terminal to implement the steps of the above-mentioned method for obtaining multiple solutions of filter synthesis based on multiple objectives.

[0037] In addition, to achieve the above object, the present invention further provides a readable storage medium storing a program for array surface wave imaging based on sampling inversion. When the program for array surface wave imaging based on sampling inversion is executed by a processor, the steps of the method for array surface wave imaging based on sampling inversion as described above are implemented.

[0038] The present invention adopts the above technical solutions and has the following effects:

[0039] To solve the problem that in the case of a small number of stations, the method based on array surface waves cannot perform three-dimensional velocity structure imaging, when measuring the dispersion curve, instead of using all station pairs inside the array to measure the dispersion curve, multiple random samplings are performed, and the difference in the dispersion curve extracted by different station pairs is used to invert the spatial phase velocity distribution, so as to observe the phase velocity distribution inside the array in the case of a small number of arrays. Description of the Drawings

[0040] Figure 1 is a flowchart of the steps of a method for array surface wave imaging based on sampling inversion in a preferred embodiment of the present invention;

[0041] Figure 2 is a detailed flowchart of a method for array surface wave imaging based on sampling inversion in a preferred embodiment of the present invention;

[0042] Figure 3 is a schematic diagram of extracting the dispersion curve by sampling station pairs in a preferred embodiment of the present invention;

[0043] Figure 4 is a schematic diagram of grid division in a preferred embodiment of the present invention;

[0044] Figure 5 is a schematic diagram of the result of a checkerboard test in a preferred embodiment of the present invention;

[0045] Figure 6 is a schematic diagram of the structure of a system for array surface wave imaging based on sampling inversion in a preferred embodiment of the present invention;

[0046] Figure 7 Schematic diagram of the operating environment of a preferred embodiment of the terminal of the present invention. Detailed Description of the Preferred Embodiments

[0047] To make the object, technical solutions and advantages of the present invention clearer and more definite, the following further describes the present invention in detail with reference to the accompanying drawings and by way of examples. It should be understood that the specific examples described herein are only used to explain the present invention and are not used to limit the present invention.

[0048] Example 1

[0049] Embodiment 1 of the present application is a method for array surface wave imaging based on sampling inversion. Specifically, please refer to Figure 1 and Figure 2 . A method for array surface wave imaging based on sampling inversion in this embodiment includes the steps:

[0050] S1. Repeatedly extract station pairs from all station pairs to form station pair combinations.

[0051] In order to solve the problem that the three-dimensional velocity structure imaging cannot be performed by the method based on array surface waves when the number of stations is small, a new three-dimensional velocity structure imaging method for arrays based on sampling of station pairs within the array is proposed.

[0052] The core idea of this method is that when measuring the dispersion curve, instead of using all station pairs within the array for dispersion curve measurement, multiple random samplings are performed, and the difference in the dispersion curves extracted by different station pair combinations is used to invert the spatial phase velocity distribution, so as to observe the phase velocity distribution inside the array from a single array, and further invert to obtain the three-dimensional velocity structure.

[0053] Please refer to Figure 3 . Taking the dispersion curve observed from the actual array data in this embodiment as an example, Figure 3 a in Figure 3 shows the station pairs composed of all stations, Figure 3 b in Figure 3 shows the dispersion spectra extracted from all station pairs inside the array,

[0054] From Figure 3 , it can be seen that the quality of the dispersion spectra extracted twice is quite the same, but there are slight differences in the positions of the dispersion curves. This difference is mainly caused by different station pair combinations, and this combination reflects the differences in the underground structures passed through by the connection lines of each station pair.

[0055] It is not difficult to find from the above that as long as the relationship between the structure and the phase velocity of the observed dispersion curve is quantified, the distribution of the phase velocity inside the array can be inverted by repeatedly and randomly sampling the station pairs to extract the dispersion spectra, so as to further invert the underground three-dimensional velocity structure.

[0056] Therefore, in this embodiment, station pairs are repeatedly extracted from all station pairs to form station pair combinations, so that in the subsequent steps, the dispersion curves can be extracted for each station pair respectively, and the difference in the dispersion curves extracted by different station pair combinations is used to invert the spatial phase velocity distribution, so as to observe the phase velocity distribution inside the array from a single array, and further invert to obtain the three-dimensional velocity structure.

[0057] It should be noted that the proportion and quantity of the number of station pairs extracted each time do not need to be the same. In this embodiment, considering that too few stations result in too low quality of the extracted dispersion spectrum, leading to too large errors in the dispersion curve, and too many stations result in the extracted dispersion spectrum being too close to the dispersion spectrum extracted from all data due to the averaging effect, making it difficult to distinguish the structural differences in the inversion. Therefore, in this embodiment, each time when extracting, 40%-70% of the total number of station pairs are extracted.

[0058] It should be noted that the more times of extraction, the more accurate the final inversion result will be, but the corresponding calculation will be more cumbersome. The specific number of times is determined according to needs, but it needs to be at least greater than the number of spatial grids.

[0059] S2. Extract the single - time dispersion curve data of each group of the station - pair combinations.

[0060] Specifically, in this embodiment, first, data pre - processing is performed to obtain the original noise data of each station. Then, the original noise data is processed. The processing of the original noise data includes de - meaning, de - trending, removing instrument response, and segmenting and cutting. The segmenting and cutting process can be to cut the continuous 5 - day data into 1 - hour segments for storage.

[0061] After that, the segmented cross - correlation data of all station pairs for each segment is calculated. For each station pair, the segmented cross - correlation data of each segment is superimposed to obtain the cross - correlation data of this station pair.

[0062] In this embodiment, to control the quality of cross - correlation, cross - correlation data screening is set. Specifically, the cross - correlation signal - to - noise ratio range can be set, and the segmented cross - correlation data outside the range is discarded. Or directly discard the set proportion of the segmented cross - correlation data with the lowest cross - correlation signal - to - noise ratio.

[0063] After that, for all station pairs, the dispersion curve is extracted by the array method according to the cross - correlation function to obtain the reference dispersion curve. This step is mainly to prepare for the subsequent order, each order frequency band, and phase velocity range.

[0064] Then, for each station pair, the dispersion curve is extracted according to the cross - correlation data. When obtaining the dispersion curve, the frequency points extracted each time need to be fixed. For example, if the frequency range of the dispersion curve is from 1 to 5 Hz, then for each station pair to extract the dispersion curve, the phase velocity of the dispersion curve at 1, 1.1, 1.2 … 4.9, and 5 Hz can be saved. At the same time, there are also differences in surface waves of different orders. Therefore, the corresponding order needs to be marked, and the station numbers used by each sub - array are saved simultaneously. Save the station numbers, orders, and phase velocities at different Hertz included.

[0065] Then, please refer toFigure 4 As shown, in this embodiment, the detection space is first divided horizontally into meshes, and the phase velocity of the th mesh is denoted as , where the phase velocity refers to the velocity at a certain order and a certain frequency under the dispersion curve. The phase slowness of the th mesh is denoted as . For example, the phase slowness of the first mesh is denoted as , the phase slowness of the second mesh is denoted as , and the phase slowness of the th mesh is denoted as , where , the phase slowness is the reciprocal of the velocity at a certain order and a certain frequency under the dispersion curve. The phase velocities of each mesh are combined into a vector , and the phase slownesses of each mesh are combined into a vector .

[0066] Among them, for the division of the meshes, it can be in the form of average triangulation, triangular triangulation, Thiessen polygon, etc. In this embodiment, the average triangulation method is specifically adopted. It should be noted that the meshes after triangulation are two-dimensional meshes obtained by multiplying rows and columns. The spacing between the meshes can refer to the approximate station spacing. Specifically, it can be estimated by calculating the distance between each station and the nearest station and taking the average. Among them, the division of the meshes does not need to be very strict, as long as it roughly conforms. In this embodiment, for the needs of calculation and explanation, the two-dimensional mesh is flattened into a one-dimensional form for recording.

[0067] For the rd pair of stations, its ray length and its length in each penetrated mesh can be obtained, where represents the first mesh penetrated by the ray of the rd pair of stations, represents the second mesh penetrated by the ray of the rd pair of stations, represents the th mesh penetrated by the ray of the rd pair of stations, and the length of the th pair of stations in each penetrated mesh is recorded, where represents the passing length of the ray of the rd pair of stations in the first penetrated mesh, represents the passing length of the ray of the rd pair of stations in the second penetrated mesh, The ray of the station pair passes through the th grid, and the passing length in the grid is considered. Then, the average phase slowness of this station pair is:

[0068] ;

[0069] Among them, represents the average phase slowness of the th station pair.

[0070] Actually, the above formula is equivalent to writing the average phase slowness of the ray of the th station pair as a weighted average of the phase slownesses of each grid. Among them, the weight of the grid not passed by the ray is 0, and the weight of the grid passed by the ray is the length of the passed part of the ray / the total ray length. If there are nr station pairs in total used to extract the dispersion curve, then the finally extracted dispersion curve data can be expressed as the average of the dispersion curves in these regions.

[0071] It should be noted that in this embodiment, the number of nr can be not fixed, as long as the reliable quality dispersion curve can be extracted.

[0072] Substituting the phase slowness of each ray, the dispersion curve data extracted from nr station pairs can be expressed as a weighted average combination of the dispersion curves on the

[0073] ;

[0074] Among them, represents the weight of the th grid, which is calculated according to the rays of each station pair, represents the phase slowness corresponding to the corresponding frequency and order. The weights of each grid and the average phase slowness of all grids are used as the single - time dispersion curve data.

[0075] S3. Obtain the inversion dispersion curve data according to multiple pieces of the single - time dispersion curve data, and establish a spatial dispersion curve according to the inversion dispersion curve data.

[0076] Specifically, if a total of valid combinations of station pairs for observing the dispersion curve are randomly selected, for the phase slowness observations of a certain frequency and a certain order, they form a vector , among which, the vector contains elements , , …, , represents the phase slowness observed for the first time, represents the phase slowness observed for the second time, represents the If the inversed slowness is observed for the first time, then the inversed slowness on each grid can be constructed. And the relationship with the slowness vector observed each time:

[0077] ;

[0078] Among them, is a weight matrix with rows and columns. The -th row represents the weight vector calculated according to the -th station pair combination, and the -th column represents the weight value corresponding to the -th grid.

[0079] It can be seen that in the forward step, the weight of each grid for each observation can be calculated. Therefore, the weight matrix can be calculated. is the observation of the slowness of each grid by each station pair combination. Then, the vector composed of the inversed slowness on each grid can be calculated by the inversion method.

[0080] After obtaining the inversed slowness on each grid, the dispersion curve of the entire detection space can be further established according to the inversed slowness of each grid. Specifically, in this embodiment, a one-dimensional dispersion curve of the entire detection space is first established. The slowness of all grids can be regarded as the slowness of the grid points of the grids. In this way, for any point in the entire detection space, its slowness can be obtained by interpolation calculation through the inversed slowness of the adjacent four grids.

[0081] One advantage of the technical solution of the present invention is that the checkerboard test can be conveniently implemented to verify the inversion effect of the phase velocity dispersion curve, such as the spatial resolution, the recovery degree of different regions, etc. Please refer to Figure 5 , Figure 5 which shows an example of a checkerboard test. Figure 5 In , a is the phase velocity distribution of the checkerboard, where the triangles are the positions of the station distributions. Figure 5 In , b is the inversed phase velocity distribution. Through 5000 random extractions of the station pair combinations, this embodiment realizes the imaging of the phase velocity distribution of about 50 station pairs. It can be seen from Figure 5 that the phase velocity distribution inside the array is well recovered.

[0082] Through the above method, the inversion phase velocity on each spatial grid can be obtained at each order of the dispersion curve and each frequency. The inversion phase velocities obtained on each grid are combined again into a dispersion curve. By the method of inverting the dispersion curve, the one-dimensional velocity structure under each spatial grid can be obtained, and further these one-dimensional velocity structures can be combined into a three-dimensional velocity structure.

[0083] It can be seen that in order to solve the problem that the three-dimensional velocity structure imaging cannot be performed by the method based on the array surface wave in the case of a small number of stations, when measuring the dispersion curve, instead of using all station pairs inside the array to measure the dispersion curve, multiple random samplings are performed, and the difference in the dispersion curve extracted by different combinations of station pairs is used to invert the spatial phase velocity distribution, so as to realize the observation of the phase velocity distribution inside the array in the case of a small number of arrays.

[0084] Embodiment 2

[0085] Please refer to Figure 6 , based on the above method, the present invention also provides an array surface wave imaging system based on sampling inversion, and the array surface wave imaging system based on sampling inversion includes:

[0086] A combined extraction module 51, configured to extract station pairs from all station pairs multiple times to form station pair combinations;

[0087] A data extraction module 52, configured to extract single dispersion curve data of each group of the station pair combinations;

[0088] A data inversion module 53, configured to obtain inversion dispersion curve data according to multiple pieces of the single dispersion curve data, and establish a spatial dispersion curve according to the inversion dispersion curve data.

[0089] Further, the extraction of the single dispersion curve data of each group of the station pair combinations specifically includes:

[0090] Dividing the detection space into multiple grids;

[0091] For each of the station pair combinations, extracting the weight of each of the grids, and calculating the average phase slowness of all the grids;

[0092] For all station pairs, calculating the average phase slowness by the array method.

[0093] Further, for each of the station pair combinations, extracting the weight of each of the grids, and calculating the average phase slowness of all the grids specifically includes:

[0094] For each of the station pairs, obtaining a dispersion curve ray, and obtaining the ray length and the passing length of the ray in each grid passed through according to the dispersion curve ray;

[0095] Calculate the weight of each grid according to the ray length and the passing length of all the ray of the dispersion curve.

[0096] Further, the obtaining of the ray of the dispersion curve specifically includes:

[0097] Obtain the detection data of two stations of a station pair, and calculate the cross-correlation data according to the detection data;

[0098] Calculate the ray of the dispersion curve according to the cross-correlation data.

[0099] Further, the calculating of the cross-correlation data according to the detection data specifically includes:

[0100] Perform mean removal, trend removal, instrument response removal and segmented cutting on the detection data in sequence to obtain a plurality of cut data;

[0101] For each of the cut data, calculate the segmented cross-correlation data of the station pair;

[0102] Superimpose all the cross-correlation data as the cross-correlation data.

[0103] Further, the obtaining of the inversion dispersion curve data according to the plurality of single dispersion curve data specifically includes:

[0104] Calculate the inversion phase slowness of each grid according to the average phase slowness of each single dispersion curve and each weight:

[0105] ;

[0106] wherein, is the weight matrix, represents the vector composed of the inversion phase slowness of all grids, represents the vector composed of each average phase slowness;

[0107] Take the set of all the inversion phase slownesses as the inversion dispersion curve data.

[0108] Further, the establishing of the spatial dispersion curve according to the inversion dispersion curve data specifically includes:

[0109] Calculate the one-dimensional spatial dispersion curve of the entire detection space according to the inversion phase slowness of each grid;

[0110] Establish the three-dimensional spatial dispersion curve of the detection space according to the one-dimensional spatial dispersion curve.

[0111] It can be seen that, in order to solve the problem that the three-dimensional velocity structure imaging cannot be performed by the method based on the array surface wave when the number of stations is small, when measuring the dispersion curve, instead of using all station pairs inside the array to measure the dispersion curve, multiple random samplings are performed, and the difference in the dispersion curve extracted by different station pairs is used to inversely calculate the spatial phase velocity distribution, so as to realize the observation of the phase velocity distribution inside the array under the condition of fewer arrays.

[0112] Embodiment III

[0113] Please refer to Figure 7 , based on the above method, the present invention also provides a terminal, and the terminal includes a processor 10, a memory 20, and a display 30. However, it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented.

[0114] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as the hard disk or memory of the terminal. In some other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the terminal. Further, the memory 20 may also include both the internal storage unit and the external storage device of the terminal. The memory 20 is used to store the application software installed on the terminal and various types of data, such as the program code for installing the terminal. The memory 20 may also be used to temporarily store the data that has been output or will be output. In one embodiment, a surface wave imaging program 40 of the array based on sampling inversion is stored on the memory 20, and the surface wave imaging program 40 of the array based on sampling inversion can be executed by the processor 10, so as to realize the terminal in the present application.

[0115] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor, or other data processing chips, and is used to run the program code stored in the memory 20 or process data, such as executing the relevant programs of the surface wave imaging method of the array based on sampling inversion.

[0116] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light Emitting Diode) toucher, etc. The display 30 is used to display the information in the terminal and to display a visual user interface.

[0117] In one embodiment, when the processor 10 executes the array surface wave imaging program 40 based on sampling inversion in the memory 20, the steps of the array surface wave imaging method based on sampling inversion as described above are implemented.

[0118] Embodiment III

[0119] This embodiment provides a storage medium. The readable storage medium stores an array surface wave imaging program based on sampling inversion. When the array surface wave imaging program based on sampling inversion is executed by a processor, the steps of the array surface wave imaging method based on sampling inversion as described above are implemented.

[0120] In summary, to solve the problem that the three-dimensional velocity structure imaging cannot be performed by the method based on array surface waves in the case of a small number of stations, when measuring the dispersion curve, instead of using all station pairs inside the array to measure the dispersion curve, multiple random samplings are performed, and the difference in the dispersion curves extracted by different station pairs is used to invert the spatial phase velocity distribution, so as to observe the phase velocity distribution inside the array in the case of a small array.

[0121] It should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or terminal. Without more limitations, the element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or terminal including the element.

[0122] Of course, those of ordinary skill in the art can understand that all or part of the processes of implementing the above method embodiments can be completed by instructing relevant hardware (such as a processor, a controller, etc.) through a computer program. The program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the above method embodiments. The storage medium can be a memory, a magnetic disk, an optical disk, etc.

[0123] It should be understood that the application of the present invention is not limited to the above examples. For those of ordinary skill in the art, improvements or transformations can be made according to the above description, and all such improvements and transformations should fall within the protection scope of the appended claims of the present invention.

Claims

1. A surface wave imaging method based on sampling inversion, characterized in that: The array surface wave imaging method based on sampling inversion includes: Station pairs are repeatedly extracted from all station pairs to form station pair combinations; wherein the number of extractions is greater than the number of spatial grids, and the ratio and number of stations extracted each time are inconsistent; extracting single dispersion curve data of each group of said station pair combinations; The original noise data of each station is segmented, and the segmented cross-correlation data of all station pairs in each segment are calculated according to the cut data of each segment. For each station pair, the segmented cross-correlation data of each segment are superimposed to obtain the cross-correlation data of the station pair. For all station pairs, extract dispersion curves by array method according to the cross-correlation function to obtain reference dispersion curves, and extract dispersion curves of each station pair according to the cross-correlation data; Extracting single dispersion curve data of each group of station pairs, specifically including: Divide the detection space into multiple grids; Extract the weight corresponding to each grid and each station pair combination, and calculate the average phase slowness corresponding to all grids and each station pair combination; use the average phase slowness and weight corresponding to each station pair combination as the single dispersion curve data corresponding to the station pair combination; The extracting the weight corresponding to each grid and each station pair combination specifically includes: Obtaining dispersion curve rays corresponding to each station pair in each station pair combination; Obtaining the ray length of each dispersion curve ray and the length of the ray in each mesh passed through; Calculating the weight of each grid and the corresponding station pair combination according to the ray lengths and the passing lengths of all the dispersion curve rays included in each station pair combination; Acquire inversion dispersion curve data according to the plurality of single dispersion curve data, and establish a spatial dispersion curve according to the inversion dispersion curve data; The establishing of a spatial dispersion curve according to the inverted dispersion curve data specifically includes: Calculating a one-dimensional spatial dispersion curve of the entire detection space according to the inversion phase slowness of each of the grids; Establishing a three-dimensional spatial dispersion curve of the detection space according to the one-dimensional spatial dispersion curve; The phase slowness of all grids is regarded as the phase slowness of the grid points of the grids. For any point in the entire detection space, the phase slowness of the point is calculated by interpolation using the inverted phase slowness of the four grids adjacent to the point.

2. The array surface wave imaging method based on sampling inversion according to claim 1, characterized in that: The obtaining of dispersion curve rays corresponding to each station pair in each station pair combination specifically includes: Acquire detection data of two stations of each station pair in each station pair combination, and calculate cross-correlation data corresponding to each station pair according to all the detection data; The corresponding dispersion curve rays are calculated according to the cross-correlation data.

3. The array surface wave imaging method based on sampling inversion according to claim 2, characterized in that: The step of calculating the cross-correlation data corresponding to each station pair according to all the detection data specifically includes: De-meaning, de-trending, de-instrument response and segmentation cutting are sequentially performed on all the detection data to obtain a plurality of segmentation data; Calculating the segmented cross-correlation data of each of the cutting data; All the segmented cross-correlation data corresponding to the station pair are superimposed to serve as the cross-correlation data of the corresponding station pair.

4. The array surface wave imaging method based on sampling inversion according to claim 1, characterized in that: The acquiring of inversion dispersion curve data according to the plurality of single dispersion curve data specifically comprises: The inversion phase slowness of each grid is calculated according to the average phase slowness of each single dispersion curve and each weight: ； in, is the weight matrix, represents the vector composed of the inversion phase slowness of all grids, Represents the vector composed of each average phase slowness; The set of all the inverted phase slownesses is used as the inverted dispersion curve data.

5. A sampling inversion-based array surface wave imaging system, characterized in that: The array surface wave imaging system based on sampling inversion is applied to the array surface wave imaging method based on sampling inversion according to any one of claims 1 to 4, and the array surface wave imaging system based on sampling inversion comprises: A combination extraction module is used to extract station pairs from all station pairs multiple times to form station pair combinations; A data extraction module, used for extracting single dispersion curve data of each group of station pairs; The data inversion module acquires inversion dispersion curve data according to the plurality of single dispersion curve data, and establishes a spatial dispersion curve according to the inversion dispersion curve data.

6. A terminal, characterized in that: The terminal comprises: a memory, a processor, and a sampling inversion-based array surface wave imaging program stored in the memory and executable on the processor. When the sampling inversion-based array surface wave imaging program is executed by the processor, the terminal is controlled to implement the steps of the sampling inversion-based array surface wave imaging method according to any one of claims 1 to 4.

7. A readable storage medium, characterized in that: The readable storage medium stores a sampling inversion-based array surface wave imaging program, which, when executed by a processor, implements the steps of the sampling inversion-based array surface wave imaging method according to any one of claims 1 to 4.

Images