Spatial phase velocity inversion method and system of array surface wave, terminal and readable storage medium

Abstract

The invention belongs to the technical field of data processing, and discloses a space phase velocity inversion method and system for array surface waves, a terminal and a readable storage medium, and the method comprises the steps: obtaining array detection data, generating sub arrays, and extracting the frequency dispersion curve data of each sub array according to the array detection data; according to the frequency dispersion curve data of each sub-array, inverting frequency dispersion curve data of a detection space; and reconstructing the frequency dispersion curve of the detection space according to the frequency dispersion curve data of the detection space. According to the method, inversion is carried out according to the data of the sub-array, and the whole frequency dispersion curve in the detection space is reconstructed, so that the problems that no observation data exists in the outermost circle of the sub-array detection area in the array surface wave method and the observation data of the sub-array has deviation are solved, and the accuracy and the resolution of the array surface wave are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method, system, terminal and readable storage medium for inverting spatial phase velocity of array surface waves. Background Art

[0002] Surface wave imaging technology based on background noise is one of the most important methods for detecting the internal structure of the earth developed in geophysics in recent years. The core idea is to measure the phase velocity or group velocity dispersion curve of the surface wave when it passes through the underground structure from the noise cross-correlation function, and to invert the relationship between the underground structure and the dispersion curve to obtain the underground velocity structure.

[0003] The dispersion curve measurement methods can be mainly divided into two categories: the ray-based dual-station dispersion curve measurement method and the array-based dispersion curve measurement method.

[0004] Compared with the ray-based dual-station dispersion curve measurement method, the array-based dispersion curve measurement method has higher dispersion curve measurement accuracy and is easier to measure high-order modes of the dispersion curve.

[0005] When performing three-dimensional velocity structure imaging, array-type surface wave methods usually need to divide the study area into several overlapping sub-arrays, extract the dispersion curve of each sub-array and invert it to obtain the corresponding one-dimensional velocity structure as the underground structure below the array center point (including the arithmetic mean of the sub-array coordinates), and finally obtain the three-dimensional velocity structure by interpolating these one-dimensional velocity structures.

[0006] The velocity structure obtained by this method through splicing the center points of the array often has a certain deviation from the actual velocity structure (due to the average effect, the observed velocity must be greater than the minimum velocity in the sub-array and less than the maximum velocity in the sub-array), and there will be no observation data in the outermost circle of the detection area (approximately half the scale of the sub-array). The above factors make the spatial resolution of the array-like surface wave method weaker. Summary of the invention

[0007] The purpose of the present invention is to provide a spatial phase velocity inversion method, system, terminal and readable storage medium for array surface wave, aiming to solve the problem of weak spatial resolution of the prior art array surface wave method.

[0008] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0009] The present invention provides a method for inverting the spatial phase velocity of an array surface wave, the method comprising:

[0010] Acquiring array detection data, generating sub-arrays, and extracting dispersion curve data of each sub-array based on the array detection data;

[0011] Inverting the dispersion curve data of the detection space according to the dispersion curve data of each of the sub-arrays;

[0012] The dispersion curve of the detection space is reconstructed according to the dispersion curve data of the detection space.

[0013] Furthermore, the acquisition of array detection data specifically includes:

[0014] Acquire original noise data of the array, and sequentially remove the mean, remove the trend, remove the instrument response, and segment the original noise data to obtain a plurality of segmented data;

[0015] For each of the cut data, calculating the cross-correlation data of the station pairs formed by all the stations in the cut data;

[0016] At each of the station pairs, all corresponding cross-correlation data are superimposed as detection data of the corresponding station pair;

[0017] The combination of the detection data of all station pairs is taken as the array detection data.

[0018] Furthermore, the generating of the sub-arrays and extracting dispersion curve data of each sub-array according to the array detection data specifically includes:

[0019] Generate multiple graphics through spatial segmentation, and generate sub-arrays according to each graphics;

[0020] The phase velocities of different orders and different Hertz of each of the sub-arrays are extracted, and the phase velocities of different orders and different Hertz corresponding to each sub-array are used as dispersion curve data.

[0021] Furthermore, the inverting the dispersion curve data of the detection space according to the dispersion curve data of each of the sub-arrays specifically includes:

[0022] Divide the detection space into multiple grids;

[0023] Calculating the phase slowness of each grid point according to the dispersion curve data of each sub-array;

[0024] The set of phase slowness of each grid point is used as dispersion curve data of the detection space.

[0025] Furthermore, the phase slowness of each grid point is calculated according to the dispersion curve data of each sub-array, specifically including:

[0026] Obtain the relationship matrix between the phase velocity of the sub-array and the phase slowness of the detection space;

[0027] The phase slowness of each of the grid points is calculated according to the relationship matrix and the dispersion curve data of each of the sub-arrays.

[0028] Furthermore, the number of the sub-arrays is greater than the number of the grids.

[0029] Further, the reconstructing the dispersion curve of the detection space according to the dispersion curve data of the detection space specifically includes:

[0030] For each grid, obtain the phase slowness of each grid point constituting the grid;

[0031] Interpolation is performed according to the phase slowness of each grid point constituting the grid to obtain a dispersion curve of the grid space;

[0032] The dispersion curves of all grid spaces are combined to obtain the dispersion curve of the detection space.

[0033] In addition, to achieve the above-mentioned purpose, the present invention also provides a spatial phase velocity inversion system for array surface waves, the spatial phase velocity inversion system for array surface waves comprising:

[0034] A detection and extraction module, which obtains array detection data, generates sub-arrays, and extracts dispersion curve data of each sub-array based on the array detection data;

[0035] A dispersion inversion module, which inverts the dispersion curve data of the detection space according to the dispersion curve data of each of the sub-arrays;

[0036] The space reconstruction module reconstructs the dispersion curve of the detection space according to the dispersion curve data of the detection space.

[0037] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, which includes: a memory, a processor, and a spatial phase velocity inversion program of an array surface wave stored in the memory and executable on the processor, wherein when the spatial phase velocity inversion program of an array surface wave is executed by the processor, the terminal is controlled to implement the steps of the spatial phase velocity inversion method of an array surface wave as described above.

[0038] In addition, to achieve the above-mentioned purpose, the present invention also provides a readable storage medium, which stores a spatial phase velocity inversion program for an array surface wave. When the spatial phase velocity inversion program for an array surface wave is executed by a processor, the steps of the spatial phase velocity inversion method for an array surface wave as described above are implemented.

[0039] The present invention adopts the above technical solution to achieve the following effects:

[0040] The present invention reconstructs the entire dispersion curve in the detection space by inverting based on the data of the sub-array, thereby solving the problem that the array surface wave method has no observation data in the outermost circle of the sub-array detection area and the observation data of the sub-array has deviations, thereby improving the accuracy and resolution of the array surface wave. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flow chart of the steps of a method for inverting the spatial phase velocity of an array surface wave in a preferred embodiment of the present invention;

[0042] Figure 2 It is an automatic flow chart of a spatial phase velocity inversion method of an array surface wave in a preferred embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of the stations for the array surface wave method;

[0044] Figure 4 A grid diagram in a preferred embodiment of the present invention;

[0045] Figure 5 A schematic diagram of neutron array generation and extraction in a preferred embodiment of the present invention;

[0046] Figure 6 Schematic diagram of the checkerboard test;

[0047] Figure 7 It is a schematic structural diagram of a spatial phase velocity inversion system of an array surface wave in a preferred embodiment of the present invention;

[0048] Figure 8 A schematic diagram of an operating environment of a preferred embodiment of a terminal of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0050] Embodiment 1

[0051] Specifically, see Figure 1 and Figure 2 Embodiment 1 of the present application is a method for inverting the spatial phase velocity of an array surface wave, which comprises the steps of:

[0052] S1. Acquire array detection data, generate sub-arrays, and extract dispersion curve data of each sub-array based on the array detection data.

[0053] Specifically, the acquisition of array detection data first involves acquiring Figure 3The original noise data of the array shown, and then the original noise data is processed. The processing of the original noise data includes removing the mean, detrending, removing the instrument response, and segmenting and cutting. In this embodiment, specifically, the processed noise data is cut according to days, and the processed noise data is cut into the cut data of each day.

[0054] After that, according to the cut data of each day, the cross-correlation data between every two of all stations of each day is calculated, and the cross-correlation data of each day is superimposed to obtain the array detection data. For example, if stations A, B, and C record data for half a month, then they are respectively cut into 1-day data. The cross-correlation data of AB, BC, and AC are calculated for the segmented data of each day, and the 15-day cross-correlation data of AB, BC, and AC are respectively superimposed to obtain the array detection data and store it.

[0055] After that, please refer to Figure 4 , the detection space is gridded into nx grid columns in the x direction of the abscissa, and the coordinates are x 0 , x 1 ,..., x nx , where x 0 is the abscissa of the origin, x 1 is the abscissa of the first column of the grid, x nx is the abscissa of the nx-th column of the grid. The detection space is gridded into ny grid rows in the y direction of the ordinate, and the coordinates are y 0 , y 1 ,..., y ny , where y 0 is the ordinate of the origin, y 1 is the ordinate of the first row of the grid, y ny is the ordinate of the ny-th row of the grid. The detection area of the array is divided into nx*ny grid points. The spacing between grid points can refer to the approximate station spacing. Specifically, it can be estimated by calculating the spacing between each station and the nearest station and taking the average. Among them, the division of grid points does not need to be very strict, as long as it roughly conforms.

[0056] In addition, although in this embodiment, for the convenience of calculation, a square grid division method is specifically adopted, the grid division of the present invention is not limited to a square, nor is it limited to a quadrilateral. By using various topological pattern division methods, the inversion effect to be achieved by the present invention can also be achieved through interpolation.

[0057] After the grid points are divided, a sub-array is generated by a spatial partitioning method. Specifically, in this embodiment, sub-arrays are generated by multiple Thiessen polygon partitionings, and dispersion curve data of each sub-array is extracted from the sub-array by the array surface wave method. A sub-array is a subset of an array, and each sub-array includes data from multiple stations. The dispersion curve data of the sub-array is generated from the data from these multiple stations.

[0058] It is worth noting that the number of sub-arrays It should be greater than nx*ny to ensure that the inversion is overdetermined. In addition, it is also necessary to ensure that the generated sub-stations can cover all the stations in the study area. For this reason, this embodiment uses the Thiessen polygon method to generate sub-stations multiple times.

[0059] Thiessen polygons are a method of partitioning space. Figure 5 As shown in the figure, by generating Thiessen polygons repeatedly and randomly, enough sub-arrays can be obtained to fully cover the study area.

[0060] Afterwards, for each sub-array, the dispersion curve data of each sub-array is obtained based on the array detection data contained in the sub-array, that is, the cross-correlation data between all sub-stations. When obtaining the dispersion curve data, it is necessary to fix the frequency point extracted each time. For example, if the dispersion curve frequency range is 1 to 5 Hz, then for each sub-array, the dispersion curve phase velocities of 1, 1.1, 1.2…4.9 and 5 Hz can be saved. At the same time, there are differences in surface waves of different orders, so the corresponding order needs to be marked at the same time, and the station number used by each sub-array is saved. The serial number, order and phase velocities of different hertz of the included stations are used as the dispersion curve data.

[0061] S2. Inverting the dispersion curve data of the detection space according to the dispersion curve data of each of the sub-arrays.

[0062] In this embodiment, the phase velocity c at each frequency of the dispersion curve observed by the array surface wave is constructed. obs The relationship between the actual phase velocity distribution c(x, y) in the detection area is then inverted to obtain c(x, y) from multiple different sub-array observations through the inversion method.

[0063] Specifically, for each order and frequency of the phase velocity, the phase velocity of the grid point in the ith x-direction and the jth y-direction, i.e., the grid point in the ith column and the jth row, is found from the saved data. Among them, s i,jIt represents the phase slowness of the grid point in the i-th column and the j-th row, which is defined as the inverse of the phase velocity. It can be understood that the phase slowness between the i-th column to the i+1-th column and the j-th row to the j+1-th row can be obtained by interpolation. In this embodiment, bilinear interpolation is specifically adopted:

[0064] s(x, y) = s i,j ω i,j (x, y)-s i+1，j ω i+1，j (x, y)-s i,j+1 ω i,j+1 (x,y)+s i+1,j+1 ω i+1，j+1 (x, y);

[0065] Among them, s(x, y) represents the function of phase slowness and the horizontal coordinate x and the vertical coordinate y, ω i,j (x, y) represents the phase slowness s i,j The function of the relationship between the horizontal coordinate x and the vertical coordinate y, s i+1，j represents the phase slowness of the grid point in the i+1th column and jth row, ω i+1，j (x, y) represents the phase slowness s i+1，j The function of the relationship between the horizontal coordinate x and the vertical coordinate y, s i，j+1 represents the phase slowness of the grid point in the i-th column and the j+1-th row, ω i,j+1 (x, y) represents the phase slowness s i,j+1 The function of the relationship between the horizontal coordinate x and the vertical coordinate y, s i+1，j+1 represents the phase slowness of the grid point at the i+1th column and j+1th row, ω i+1，j+1 Indicates phase slowness s i+1，j+1 A function that relates the horizontal coordinate x to the vertical coordinate y.

[0066] Among them, ω i,j (x, y), ω i+1，j (x, y), ω i,j+1 (x, y) and ω i+1，j+1 The definition of (x, y) is as follows:

[0067]

[0068] Among them, x i represents the horizontal coordinate of the i-th column, x i+1 Indicates the horizontal coordinate of the i+1th column, y i Indicates the ordinate of the jth row, y i+1 Indicates the vertical coordinate of the j+1th row.

[0069] The dispersion curve extracted from a sub-array can be approximated as the average of the dispersion curves measured by all stations in the sub-array for the ray, and the phase slowness of the dispersion curve measured by a sub-array can be obtained by averaging the phase slowness on the ray path:

[0070]

[0071] in is the phase slowness measured by the sub-array, L is the length of the ray, and dl is the differential of the ray.

[0072] Among them, the phase slowness measured by the sub-array can be expanded as:

[0073]

[0074] It can be noted that ∫ω i，j (x, y)dl is a constant, so the relationship between the phase slowness measured by each sub-array and the phase slowness at the grid point can be obtained:

[0075]

[0076] Among them, w i，j For i，j The coefficients satisfy ∑w i，j =1.

[0077] Furthermore, the phase slowness of all rays of a sub-array can be averaged to obtain the phase slowness of the dispersion curve observed by the sub-array. i，j Flatten into a one-dimensional vector of length nx*ny Then for The phase velocity vector d observed by the sub-array is expressed as:

[0078]

[0079] Among them, A is the relationship matrix between the phase velocity of the sub-array and the phase slowness of the detection space, which is A matrix with nx rows and ny columns, each row corresponds to a sub-array, and each column corresponds to a grid point.

[0080] From the above content, it is not difficult to find that after calculating the relationship matrix A, the phase slowness s of each grid point can be calculated by the inversion method through the dispersion curve data d of each sub-array i，j , the set of phase slownesses of all grid points is taken as the dispersion curve data of the detection space.

[0081] Specifically, in this embodiment, a loss function is constructed:

[0082]

[0083] in, is the loss value, α is the regularization factor, and L is the spatial gradient operator.

[0084] This embodiment uses the gradient inversion method such as the Quasi-Newton Method (BFGS) to invert Thus, the phase slowness s of each grid point is obtained i，j .

[0085] S3. Reconstructing the dispersion curve of the detection space according to the dispersion curve data of the detection space.

[0086] Afterwards, according to the previous formula, the true spatial distribution of the phase velocity can be obtained from the phase velocity observed by the sub-array, so that the phase velocity at each spatial grid point can be obtained at each frequency for each order dispersion curve. Through the above formula, the inverted phase velocity at each grid point can be further combined into a dispersion curve. The one-dimensional velocity structure under each spatial grid point can be obtained by inverting the dispersion curve. Further, we can combine these one-dimensional velocity structures into a three-dimensional velocity structure.

[0087] In addition, please refer to Figure 6 The technical solution of the present invention has an advantage that it can conveniently implement a checkerboard test to verify the inversion effect of the phase velocity dispersion curve, such as spatial resolution, recovery degree of different regions, etc.

[0088] Figure 6 a in is the phase velocity distribution of the chessboard, Figure 6 b is the phase velocity distribution inverted according to the method of the present invention.

[0089] Embodiment 2

[0090] See also Figure 7 Based on the above method, the present invention also provides a spatial phase velocity inversion system for array surface waves, the spatial phase velocity inversion system for array surface waves comprising:

[0091] A detection and extraction module, which obtains array detection data, generates sub-arrays, and extracts dispersion curve data of each sub-array based on the array detection data;

[0092] A dispersion inversion module, which inverts the dispersion curve data of the detection space according to the dispersion curve data of each of the sub-arrays;

[0093] The space reconstruction module reconstructs the dispersion curve of the detection space according to the dispersion curve data of the detection space.

[0094] Furthermore, the acquisition of array detection data specifically includes:

[0095] Acquire original noise data of the array, and sequentially remove the mean, remove the trend, remove the instrument response, and segment the original noise data to obtain a plurality of segmented data;

[0096] For each of the cut data, calculating the cross-correlation data of the station pairs formed by all the stations in the cut data;

[0097] At each of the station pairs, all corresponding cross-correlation data are superimposed as detection data of the corresponding station pair;

[0098] The combination of the detection data of all station pairs is taken as the array detection data.

[0099] Furthermore, the generating of the sub-arrays and extracting dispersion curve data of each sub-array according to the array detection data specifically includes:

[0100] Generate multiple graphics through spatial segmentation, and generate sub-arrays according to each graphics;

[0101] The phase velocities of different orders and different Hertz of each of the sub-arrays are extracted, and the phase velocities of different orders and different Hertz corresponding to each sub-array are used as dispersion curve data.

[0102] Furthermore, the inverting the dispersion curve data of the detection space according to the dispersion curve data of each of the sub-arrays specifically includes:

[0103] Divide the detection space into multiple grids;

[0104] Calculating the phase slowness of each grid point according to the dispersion curve data of each sub-array;

[0105] The set of phase slowness of each grid point is used as dispersion curve data of the detection space.

[0106] Furthermore, the phase slowness of each grid point is calculated according to the dispersion curve data of each sub-array, specifically including:

[0107] Obtain the relationship matrix between the phase velocity of the sub-array and the phase slowness of the detection space;

[0108] The phase slowness of each of the grid points is calculated according to the relationship matrix and the dispersion curve data of each of the sub-arrays.

[0109] Furthermore, the number of the sub-arrays is greater than the number of the grids.

[0110] Further, the reconstructing the dispersion curve of the detection space according to the dispersion curve data of the detection space specifically includes:

[0111] For each grid, obtain the phase slowness of each grid point constituting the grid;

[0112] Interpolation is performed according to the phase slowness of each grid point constituting the grid to obtain a dispersion curve of the grid space;

[0113] The dispersion curves of all grid spaces are combined to obtain the dispersion curve of the detection space.

[0114] Embodiment 3

[0115] See also Figure 8 Based on the above method, the present invention further provides a terminal, which 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 components shown, and more or fewer components may be implemented instead.

[0116] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed in the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a spatial phase velocity inversion program 40 of a station array surface wave is stored on the memory 20, and the spatial phase velocity inversion program 40 of the station array surface wave can be executed by the processor 10, thereby realizing the terminal in the present application.

[0117] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing the relevant programs of the spatial phase velocity inversion method of the array surface wave.

[0118] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface.

[0119] In one embodiment, when the processor 10 executes the spatial phase velocity inversion program 40 of an array surface wave in the memory 20, the steps of the spatial phase velocity inversion method of an array surface wave as described above are implemented.

[0120] Embodiment 4

[0121] This embodiment provides a storage medium, wherein the readable storage medium stores a spatial phase velocity inversion program for an array surface wave, and when the spatial phase velocity inversion program for an array surface wave is executed by a processor, the steps of the spatial phase velocity inversion method for an array surface wave as described above are implemented.

[0122] In summary, the present invention reconstructs the entire dispersion curve in the detection space by inverting according to the data of the sub-array, thereby solving the problem that the array surface roll method has no observation data in the outermost circle of the sub-array detection area and the observation data of the sub-array has deviations, thereby improving the accuracy and resolution of the array surface roll.

[0123] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or terminal including the element.

[0124] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium, and the program can include the processes of the above-mentioned method embodiments when executed. The storage medium can be a memory, a disk, an optical disk, etc.

[0125] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for inverting the spatial phase velocity of an array surface wave, characterized in that: The spatial phase velocity inversion method of the array surface wave comprises: Acquiring array detection data, generating sub-arrays, and extracting dispersion curve data of each sub-array based on the array detection data; Inverting the dispersion curve data of the detection space according to the dispersion curve data of each of the sub-arrays; The dispersion curve of the detection space is reconstructed according to the dispersion curve data of the detection space.

2. The method for inverting the spatial phase velocity of an array surface wave according to claim 1, characterized in that: The obtaining of array detection data specifically includes: Acquire original noise data of the array, and sequentially remove the mean, remove the trend, remove the instrument response, and segment the original noise data to obtain a plurality of segmented data; For each of the cut data, calculating the cross-correlation data of the station pairs formed by all the stations in the cut data; At each of the station pairs, all corresponding cross-correlation data are superimposed as detection data of the corresponding station pair; The combination of the detection data of all station pairs is taken as the array detection data.

3. The spatial phase velocity inversion method of an array surface wave according to claim 1, characterized in that: The generating of the sub-arrays and extracting dispersion curve data of each sub-array according to the array detection data specifically includes: Generate multiple graphics through spatial segmentation, and generate sub-arrays according to each graphics; The phase velocities of different orders and different Hertz of each of the sub-arrays are extracted, and the phase velocities of different orders and different Hertz corresponding to each sub-array are used as dispersion curve data.

4. The method for inverting the spatial phase velocity of an array surface wave according to claim 3, characterized in that: The inverting the dispersion curve data of the detection space according to the dispersion curve data of each of the sub-arrays specifically includes: Divide the detection space into multiple grids; Calculating the phase slowness of each grid point according to the dispersion curve data of each sub-array; The set of phase slowness of each grid point is used as dispersion curve data of the detection space.

5. The method for inverting the spatial phase velocity of an array surface wave according to claim 4, characterized in that: Calculating the phase slowness of each grid point according to the dispersion curve data of each sub-array specifically includes: Obtain the relationship matrix between the phase velocity of the sub-array and the phase slowness of the detection space; The phase slowness of each of the grid points is calculated according to the relationship matrix and the dispersion curve data of each of the sub-arrays.

6. The method for inverting the spatial phase velocity of an array surface wave according to claim 4, characterized in that: The number of the sub-arrays is greater than the number of the grids.

7. The method for inverting the spatial phase velocity of an array surface wave according to claim 4, characterized in that: The reconstructing the dispersion curve of the detection space according to the dispersion curve data of the detection space specifically includes: For each grid, obtain the phase slowness of each grid point constituting the grid; Interpolation is performed according to the phase slowness of each grid point constituting the grid to obtain a dispersion curve of the grid space; The dispersion curves of all grid spaces are combined to obtain the dispersion curve of the detection space.

8. A spatial phase velocity inversion system for array surface waves, characterized in that: The spatial phase velocity inversion system of the array surface wave comprises: A detection and extraction module, which obtains array detection data, generates sub-arrays, and extracts dispersion curve data of each sub-array based on the array detection data; A dispersion inversion module, which inverts the dispersion curve data of the detection space according to the dispersion curve data of each of the sub-arrays; The space reconstruction module reconstructs the dispersion curve of the detection space according to the dispersion curve data of the detection space.

9. A terminal, characterized in that: The terminal comprises: a memory, a processor, and a spatial phase velocity inversion program of an array surface wave stored in the memory and executable on the processor. When the spatial phase velocity inversion program of an array surface wave is executed by the processor, the terminal is controlled to implement the steps of a spatial phase velocity inversion method of an array surface wave as claimed in any one of claims 1 to 7.

10. A readable storage medium, characterized in that: The readable storage medium stores a spatial phase velocity inversion program for an array surface wave, and when the spatial phase velocity inversion program for an array surface wave is executed by a processor, the steps of a spatial phase velocity inversion method for an array surface wave as claimed in any one of claims 1 to 7 are implemented.

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