Anisotropic elastic medium Rayleigh surface wave frequency dispersion curve inversion method

Abstract

The invention relates to an anisotropic elastic medium Rayleigh surface wave frequency dispersion curve inversion method, which comprises the steps of collecting near-earth surface wave exploration seismic data, obtaining a Rayleigh surface wave frequency dispersion energy diagram based on a phase shift method, and extracting a frequency dispersion curve from the frequency dispersion energy diagram based on a convolutional neural network artificial intelligence method; constructing a near-surface anisotropic elastic parameter initial model; calculating to obtain a theoretical Rayleigh surface wave dispersion curve by using a Rayleigh surface wave dispersion curve forward modeling method according to the current elastic parameter model; designing a loss function according to the observed Rayleigh surface wave dispersion curve and the theoretically calculated Rayleigh surface wave dispersion curve, and calculating and judging whether the loss function reaches a set threshold value or converges to a minimum value; if yes, outputting a current near-surface shear wave velocity model; if the conditions are not met, updating the shear wave velocity model by adopting a quasi-Newton method; and outputting the near-surface shear wave velocity model and the sensitive function of the Rayleigh surface wave frequency dispersion curve to the anisotropic elastic parameter after the loss function meets the condition.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, and in particular to the field of seismic inversion technology. Specifically, the present invention proposes an inversion method for Rayleigh surface wave dispersion curve of anisotropic elastic medium. Background Art

[0002] Surface wave exploration is a method of geophysical exploration that mainly uses surface waves in seismic waves to detect underground structures and properties. It has a wide range of applications in seismic exploration, engineering geology, environmental geology, and earthquake disaster assessment.

[0003] Rayleigh surface waves propagate along the surface and are highly sensitive to the elastic parameters of the underground medium. Rayleigh surface wave dispersion curve inversion is to obtain the underground elastic medium parameters by analyzing the dispersion curve of Rayleigh surface waves.

[0004] Geological media in nature often have anisotropic properties. Processes such as rock deposition, metamorphism, and tectonic movement can cause their physical properties to differ in different directions. Sedimentary rocks, metamorphic rocks, and igneous rocks exhibit anisotropy due to the directional arrangement of minerals or the presence of cracks.

[0005] In the current surface wave exploration inversion calculation, some algorithms are based on the isotropic assumption. However, this simplified processing is difficult to reflect the actual characteristics of complex strata, often resulting in significant deviations between the inversion results and the actual geological conditions, making it difficult to meet the needs of accurate modeling.

[0006] Another type of inversion method introduces anisotropy in the forward modeling, such as simulated annealing and Monte Carlo random inversion. However, these methods rely on a large number of annealing calculations or random sampling, resulting in high computational costs. When searching for the global optimal solution, it is usually necessary to go through a large number of iterations, and the convergence efficiency is low. Especially when the number of iterations is insufficient, the inversion results often lack stability and are difficult to meet the actual needs of fast and accurate inversion of near-surface structures. Summary of the invention

[0007] In view of the above problems, the purpose of the present invention is to provide a Rayleigh surface wave dispersion curve inversion method suitable for anisotropic elastic media. Compared with the existing technology, this method significantly improves the calculation efficiency, can quickly obtain high-precision near-surface shear wave velocity structure information, and meet the needs of accurate modeling in complex geological environments.

[0008] To achieve the above object, the present invention adopts the following technical solutions:

[0009] In a first aspect, the present invention provides a method for inverting a Rayleigh surface wave dispersion curve of an anisotropic elastic medium, the method comprising:

[0010] S1, collects near-surface surface wave exploration seismic data, calculates Rayleigh surface wave dispersion energy map based on phase shift method, and extracts Rayleigh surface wave observation dispersion curve based on convolutional neural network artificial intelligence method;

[0011] S2, constructing an initial elastic parameter model of the near-surface anisotropic elastic medium;

[0012] S3, according to the current elastic parameter model, the theoretical Rayleigh surface wave dispersion curve is calculated using the Rayleigh surface wave dispersion curve forward modeling method;

[0013] S4, designing a loss function based on the observed Rayleigh surface wave dispersion curve and the theoretically calculated Rayleigh surface wave dispersion curve, and calculating and judging whether the loss function reaches a set threshold or converges to a minimum value;

[0014] S5, if the loss function satisfies the conditions in S4, the current near-surface shear wave velocity model is output; if the loss function does not meet the conditions, the quasi-Newton method is used to update the shear wave velocity model, and the process returns to S3 and S4 until the loss function meets the conditions;

[0015] S6, the sensitivity function of the near-surface shear wave velocity model and Rayleigh surface wave dispersion curve to the anisotropic elastic parameters after the output loss function meets the conditions.

[0016] In one implementation, the expression for calculating the Rayleigh surface wave dispersion energy diagram using the phase shift method is:

[0017]

[0018] Where ω is the angular frequency, c is the scanning phase velocity, N is the number of Rayleigh surface wave seismic recording detectors, and x n is the distance from the nth detector to the earthquake source, u(x n ,ω) is the Rayleigh surface wave seismic record u(x n ,t) is obtained by performing one-dimensional Fourier transform along the time direction, where i is an imaginary unit.

[0019] In one implementation, in S2, an initial model of near-surface elastic parameters is constructed based on near-surface drilling information, including formation density, vertical P- and S-wave velocities, and Thomsen anisotropy parameters ε and δ.

[0020] In one implementation, in S3, the theoretical Rayleigh surface wave dispersion curve is calculated by a transfer matrix algorithm;

[0021] The expression is:

[0022] D(ω,c)=det(U′T1T2…T n V)=0

[0023] Among them, U' represents the upper boundary condition, that is, the free surface, T represents the transfer matrix, and V represents the lower boundary condition, that is, the semi-infinite space. The root obtained by solving the above dispersion equation is the theoretical dispersion curve of Rayleigh surface wave.

[0024] In one implementation, the loss function is:

[0025]

[0026] Where m is the total number of modes of the observed Rayleigh surface wave dispersion curve, n e is the total number of discrete dispersion points of the observed Rayleigh surface wave dispersion curve in the eth mode, is the phase velocity of the theoretical Rayleigh surface wave dispersion curve at the i-th frequency of the e-th mode, is the phase velocity at frequency i of the eth mode of the Rayleigh surface wave dispersion curve.

[0027] In one implementation, the loss function gradient is:

[0028]

[0029]

[0030] in, j is the layer number, is the vertical shear wave velocity of the jth layer, z j is the depth of the jth interface, k is the wave number, U is the group velocity, ρ is the density, and r1 and r2 are the Rayleigh surface wave eigendisplacement functions.

[0031] In one implementation, the line search descent direction is calculated using the quasi-Newton method, and the expression for updating the vertical shear wave velocity by the line search is:

[0032] x b+1 =x b +αd b

[0033] Among them, x b+1 is the vertical shear wave velocity of the b+1th iteration, α is the update step size, d b is in x b The expression for calculating the direction of gradient descent is:

[0034]

[0035] Among them, D b is in x b The approximate Hessian matrix at g b is the loss function for x b The gradient of b-1 =x b -xb-1 ,y b-1 =g b -g b-1 .

[0036] In one implementation, after S5, the method further includes: calculating the theoretical Rayleigh surface wave dispersion curve corresponding to the inversion model by a forward modeling method, and then calculating the sensitivity function of the theoretical Rayleigh surface wave dispersion curve to the inversion model, analyzing the sensitivity of the theoretical Rayleigh surface wave dispersion curve to the inversion model, and quantitatively evaluating the credibility of the inversion result; wherein the sensitivity function calculation formula is:

[0037]

[0038] In addition, the present invention also provides the sensitivity functions of the Rayleigh surface wave dispersion curve to the vertical longitudinal wave velocity, density, Thomsen parameters ε and δ, which are:

[0039]

[0040]

[0041] in S ρ , S ε and S δ are the sensitivity functions of the Rayleigh surface wave dispersion curve to the vertical shear wave velocity, vertical longitudinal wave velocity, density, and Thomsen anisotropy parameters ε and δ, respectively.

[0042] Compared with the prior art, the beneficial effects of the present invention include:

[0043] 1. The near-surface underground medium often has anisotropic characteristics. The traditional surface wave dispersion curve inversion method is based on the assumption of isotropic medium, which will cause errors in the inversion shear wave velocity model. The present invention is based on anisotropic elastic theory, which more truly reflects the properties of the underground medium and can obtain a high-precision near-surface shear wave velocity structure, providing more reliable and accurate guidance for earthquake safety evaluation, foundation treatment effect evaluation and engineering survey;

[0044] 2. The present invention derives an analytical expression of the gradient of the Rayleigh surface wave dispersion curve to the vertical shear wave velocity, and develops a gradient-based surface wave inversion method and technology in anisotropic media; compared with the existing elastic anisotropic Rayleigh surface wave dispersion curve inversion method (such as Monte Carlo random inversion and simulated annealing), the method of the present invention accelerates the convergence process of the loss function by quickly identifying the decreasing direction of the vertical shear wave velocity, and significantly improves the convergence speed and computational efficiency. This method can efficiently complete the inversion of the near-surface shear wave velocity structure, meeting the requirements of both speed and accuracy in practical engineering applications.

[0045] 3. The present invention analyzes the response characteristics of the dispersion curve to different physical parameters by analyzing and calculating the sensitivity functions of the Rayleigh surface wave dispersion curve to density, vertical longitudinal and transverse wave velocity, and Thomsen anisotropy parameters. Based on sensitivity analysis, it can not only effectively evaluate the credibility of the inversion results, but also provide a scientific basis for the interpretation of the results, and provide reliable support for subsequent geological analysis and engineering decision-making, further improving the practicality and guiding value of near-surface geophysical exploration methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a flow chart of a method for gradient inversion of Rayleigh surface wave dispersion curve of near-surface anisotropic elastic medium in an embodiment of the present invention;

[0047] Figure 2 It is the surface wave exploration seismic data obtained by simulating the near-surface anisotropic elastic geological model in Table 1 through the finite difference method in the embodiment of the present invention;

[0048] Figure 3 The Rayleigh surface wave dispersion energy diagram calculated by the phase shift method and the extracted observed dispersion curve in the embodiment of the present invention;

[0049] Figure 4 is a near-surface shear wave velocity model obtained by inverting the Rayleigh surface wave dispersion curve L-BFGS-B of anisotropic elastic medium in an embodiment of the present invention;

[0050] Figure 5 A comparison diagram of the dispersion curve predicted by the near-surface shear wave velocity model obtained by inverting the near-surface Rayleigh surface wave dispersion curve L-BFGS-B of anisotropic elastic medium in an embodiment of the present invention and the observed dispersion curve;

[0051] Figure 6 This is a comparison chart between the theoretical dispersion curve and the observed dispersion curve based on the traditional surface wave inversion of isotropic elastic media. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] In view of the problems of the prior art, the present invention provides a method for inverting Rayleigh surface wave dispersion curves of anisotropic elastic media, the method comprising:

[0054] S1, collects near-surface surface wave exploration seismic data, calculates Rayleigh surface wave dispersion energy map based on phase shift method, and extracts dispersion curve from dispersion energy map based on convolutional neural network artificial intelligence method;

[0055] Specifically, surface wave seismic data is obtained by acquisition or numerical simulation, and the Rayleigh surface wave dispersion energy map is calculated by the phase shift method, and the Rayleigh surface wave observation dispersion curve is extracted from it based on the convolutional neural network artificial intelligence method. The expression for calculating the Rayleigh surface wave dispersion energy map by the phase shift method is:

[0056]

[0057] Where ω is the angular frequency, c is the scanning phase velocity, N is the number of Rayleigh surface wave seismic recording detectors, and x n is the distance from the nth detector to the earthquake source, u(x n ,ω) is the Rayleigh surface wave seismic record u(x n ,t) is obtained by performing one-dimensional Fourier transform along the time direction, where i is an imaginary unit.

[0058] S2, constructing an initial elastic parameter model of the anisotropic elastic medium;

[0059] Specifically, an initial model of near-surface elastic parameters is constructed based on near-surface drilling information, including formation density, vertical P- and S-wave velocities, and Thomsen anisotropy parameters ε and δ.

[0060] S3, according to the current anisotropic elastic parameter model, the theoretical dispersion curve is calculated using the Rayleigh surface wave dispersion curve forward modeling method applicable to anisotropic elastic media;

[0061] Specifically, the forward calculation method is based on the transfer matrix algorithm.

[0062] The expression is:

[0063] D(ω,c)=det(U'T1T2…T n V)=0

[0064] Among them, U' represents the upper boundary condition, that is, the free surface, T represents the transfer matrix, and V represents the lower boundary condition, that is, the semi-infinite space.

[0065] S4, designing a loss function according to the observed Rayleigh surface wave dispersion curve and the theoretical Rayleigh surface wave dispersion curve, and calculating and judging whether the loss function reaches a set threshold or converges to a minimum value;

[0066] Specifically, the loss function is:

[0067]

[0068] Where m is the total number of modes of the observed Rayleigh surface wave dispersion curve, n e is the total number of discrete dispersion points of the observed Rayleigh surface wave dispersion curve in the eth mode, is the phase velocity of the theoretical Rayleigh surface wave dispersion curve at the i-th frequency of the e-th mode, is the phase velocity at frequency i of the eth mode of the Rayleigh surface wave dispersion curve.

[0069] S5, if the loss function satisfies the conditions in S4, the current near-surface shear wave velocity model is output; if the loss function does not meet the conditions, the near-surface shear wave velocity model is updated using the quasi-Newton method, and the process returns to S3 and S4 until the loss function meets the conditions;

[0070] Specifically, the loss function is calculated, and it is determined whether the loss function reaches a set threshold or converges to a minimum value; if the conditions are met, the near-surface shear wave velocity structure model is output; if the conditions are not met, the gradient of the loss function with respect to the vertical shear wave velocity (hereinafter referred to as the gradient of the loss function) is calculated, and the vertical shear wave velocity model is updated using line search, and the line search descent direction calculation method includes but is not limited to the gradient descent method, Newton's method, and the quasi-Newton method, and the step length calculation method includes but is not limited to the precise line search, direct search, and inexact line search.

[0071] Among them, the gradient of the loss function is:

[0072]

[0073] in, j is the layer number, is the vertical shear wave velocity of the jth layer, z j is the depth of the jth interface, k is the wave number, U is the group velocity, ρ is the density, r1 and r2 are the Rayleigh surface wave eigendisplacement functions;

[0074] The line search descent direction is calculated using the quasi-Newton method, and the expression for updating the vertical shear wave velocity in the line search is:

[0075] x b+1 =x b +αd b

[0076] Among them, x b+1 is the vertical shear wave velocity of the b+1th iteration, α is the update step size, d b is in x b The expression for calculating the direction of gradient descent is:

[0077]

[0078] Among them, D b is in x bThe approximate Hessian matrix at g b is the loss function for x b The gradient of b-1 =x b -x b-1 ,y b-1 =g b -g b-1 .

[0079] Furthermore, the theoretical Rayleigh surface wave dispersion curve corresponding to the inverted near-surface shear wave velocity model is calculated by the forward modeling method, and then the sensitivity function of the theoretical Rayleigh surface wave dispersion curve to the inverted near-surface shear wave velocity model is calculated, and the sensitivity of the theoretical Rayleigh surface wave dispersion curve to the inversion model is analyzed to ensure the credibility of the inversion result.

[0080] The sensitivity function calculation formula is:

[0081]

[0082] In addition, the present invention also provides the sensitivity functions of the Rayleigh surface wave dispersion curve to the vertical longitudinal wave velocity, density, Thomsen parameters ε and δ, which are:

[0083]

[0084]

[0085] in S ρ , S ε and S δ are the sensitivity functions of the Rayleigh surface wave dispersion curve to the vertical shear wave velocity, vertical longitudinal wave velocity, density, and Thomsen anisotropy parameters ε and δ, respectively.

[0086] S6, elastic parameter model after the output loss function meets the conditions and the sensitivity function of the Rayleigh surface wave dispersion curve to the anisotropic elastic parameters.

[0087] In combination with more detailed embodiments of the present application and its accompanying drawings, the process of the method provided by the present application is explained in further examples, and its technical effects are explained.

[0088] Example 1 discloses a method for inverting the dispersion curve of Rayleigh surface waves in elastic anisotropic media. Figure 1 As shown, the specific steps include:

[0089] Step 1, in this embodiment, seismic data is obtained by numerical simulation, and the model used is shown in Table 1. Specifically, the model is discretized into 576×651 grid points, the grid point spacing is 0.2 meters, the source and the detector are arranged on the surface, the shot offset is 11 meters, the detector channel spacing is 1 meter, a total of 100 channels, the total simulation time is 1 second, the time sampling interval is 0.05 milliseconds, the staggered grid finite difference method is used, the absorption boundary uses the C-PML boundary, the source uses the vertical force source, and the excitation function is the Ricker wavelet with a main frequency of 30 Hz. The seismic data obtained by simulation is as follows Figure 2 shown.

[0090]

[0091] Table 1

[0092] Step 2: For the simulated earthquake data u(x n ,t), and perform a one-dimensional Fourier transform along the time direction to obtain u(x n ,ω), given a reasonable scanning frequency ω and phase velocity c range, the Rayleigh surface wave dispersion energy map E(ω,c) is calculated using the phase shift method, and the Rayleigh surface wave observation dispersion curve is extracted based on the convolutional neural network artificial intelligence method. Figure 3 As shown, the background is the dispersion energy map calculated by the phase shift method, and the asterisk is the extracted dispersion curve.

[0093] Step 3: construct an initial model of anisotropic parameters, including the thickness, density, vertical P-wave velocity and S-wave velocity of each layer, and Thomsen anisotropic parameters ε and δ.

[0094] Step 4, using the transfer matrix algorithm to calculate the theoretical dispersion curve of Rayleigh surface waves corresponding to the initial model, specifically: define the stress-displacement vector for each layer, construct the transfer matrix according to the interface stress-displacement continuity condition, establish the relationship between the free surface stress-displacement and the half-space stress-displacement, and then establish the Rayleigh surface wave dispersion equation based on the conditions that the free surface stress is zero and the stress-displacement is zero at infinity in the half-space. Then use the numerical method to solve the dispersion equation and find the theoretical phase velocity corresponding to the observed frequency.

[0095] Step 5: Take the mean square error between the observed dispersion curve of the Rayleigh surface wave and the theoretical dispersion curve as the loss function and calculate the loss function value.

[0096] Step 6, calculate the gradient of the loss function with respect to the vertical shear wave velocity.

[0097] Step 7: Calculate and determine whether the loss function reaches the set threshold or converges to the minimum value. If the loss function meets the conditions, the vertical shear wave velocity is output; if the loss function does not meet the conditions, proceed to the next step.

[0098] Step 8, using line search to update the vertical shear wave velocity. In this embodiment, the line search descent direction is calculated using the quasi-Newton method, and the step size is determined based on the Wolfe criterion.

[0099] Step 9: Repeat steps 4-7 until the loss function or the loss function gradient meets the convergence condition, and output the vertical shear wave velocity. Figure 4 and Figure 5 As shown, they are respectively the shear wave velocity and dispersion curve result diagrams obtained by gradient inversion of Rayleigh surface wave dispersion curve of elastic anisotropic medium of the present invention.

[0100] Step 10, calculating the sensitivity function of the Rayleigh surface wave dispersion curve to the elastic anisotropic medium parameters.

[0101] contrast Figure 6 Based on the dispersion curve obtained by inversion based on isotropic elastic theory, it can be seen that the theoretical dispersion curve obtained by inversion based on isotropic theory does not match the observed dispersion curve, while the theoretical dispersion curve of the scheme of the present invention fits the observed dispersion curve well, indicating that the present invention considers anisotropic media to improve the accuracy of the inversion result. At the same time, the inversion method provided by the present invention is a gradient inversion method, and provides an analytical gradient of the loss function to the vertical shear wave velocity. By introducing gradient information, the inversion result is made more stable and reliable, and the calculation efficiency is higher than that of the existing inversion method, which effectively saves computing resources.

[0102] The present invention also discloses a gradient inversion method system for Rayleigh surface wave dispersion curve of elastic anisotropic medium, comprising:

[0103] An observation dispersion curve extraction module is used to calculate the Rayleigh surface wave dispersion energy diagram by a phase shift method, and extract the Rayleigh surface wave observation dispersion curve from it based on an artificial intelligence method;

[0104] Theoretical dispersion curve forward modeling module is used to calculate the theoretical dispersion curve of Rayleigh surface waves corresponding to the anisotropic elastic parameter model through the transfer matrix algorithm;

[0105] The loss function judgment module is used to calculate the loss function of the observed dispersion curve and the theoretical dispersion curve. If the loss function reaches a given threshold or converges to a minimum value, the vertical shear wave velocity is output. If the loss function does not meet the above conditions, the next module is entered;

[0106] The loss function gradient calculation module is used to calculate the gradient of the loss function with respect to the vertical shear wave velocity;

[0107] The vertical shear wave velocity update module is used to calculate the step size and gradient descent direction, update the vertical shear wave velocity through line search, calculate the theoretical dispersion curve corresponding to the updated model, and return to the loss function judgment module. This cycle is repeated until the loss function meets the convergence condition and the optimal vertical shear wave velocity is output.

[0108] The credibility assessment module calculates the theoretical Rayleigh surface wave dispersion curve corresponding to the inversion model through the forward modeling method, and then calculates the sensitivity function of the theoretical Rayleigh surface wave dispersion curve to the inversion model, analyzes the sensitivity of the theoretical Rayleigh surface wave dispersion curve to the inversion model, and thus the credibility of the inversion result is evaluated.

[0109] In the several embodiments provided by the present invention, it should be understood that the disclosed method can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0110] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (Processor) to perform some steps of the above-mentioned method of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0111] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for inverting Rayleigh surface wave dispersion curves in anisotropic elastic media, characterized in that: The method comprises: S1, collects near-surface surface wave exploration seismic data, obtains Rayleigh surface wave dispersion energy map based on phase shift method, and extracts dispersion curve from dispersion energy map based on convolutional neural network artificial intelligence method; S2, constructing the initial model of near-surface anisotropic elastic parameters; S3, according to the current elastic parameter model, the theoretical Rayleigh surface wave dispersion curve is calculated using the Rayleigh surface wave dispersion curve forward modeling method; S4, designing a loss function according to the observed Rayleigh surface wave dispersion curve and the theoretically calculated Rayleigh surface wave dispersion curve, and calculating and judging whether the loss function reaches a set threshold or converges to a minimum value; S5, if the loss function satisfies the conditions in S4, the current near-surface shear wave velocity model is output; if the loss function does not meet the conditions, the quasi-Newton method is used to update the shear wave velocity model, and the process returns to S3 and S4 until the loss function meets the conditions; S6, the sensitivity function of the near-surface shear wave velocity model and Rayleigh surface wave dispersion curve to the anisotropic elastic parameters after the output loss function meets the conditions.

2. The method for inverting Rayleigh surface wave dispersion curve of anisotropic elastic medium according to claim 1, characterized in that: In S1, the expression for calculating the Rayleigh surface wave dispersion energy diagram using the phase shift method is: Where ω is the angular frequency, c is the scanning phase velocity, N is the number of Rayleigh surface wave seismic recording detectors, and x n is the distance from the nth detector to the earthquake source, u(x n ,ω) is the Rayleigh surface wave seismic record u(x n , t) is obtained by one-dimensional Fourier transform along the time direction, i is an imaginary unit, and its expression is: U(x n ,ω)=∫u(x n ,t)e -iω dt。 3. The method for inverting Rayleigh surface wave dispersion curve of anisotropic elastic medium according to claim 1, characterized in that: In the S2, the anisotropy of the medium is manifested as vertical transverse isotropy, and an initial model of near-surface elastic parameters is constructed based on near-surface drilling information, including formation density, vertical P- and S-wave velocities, and Thomsen anisotropy parameters ε and δ.

4. The method for inverting Rayleigh surface wave dispersion curve of anisotropic elastic medium according to claim 1, characterized in that: In S3, the anisotropic elastic parameter model is used, and the theoretical Rayleigh surface wave dispersion curve is calculated by the transfer matrix algorithm, and the expression is: D(ω,c)=det(U′T1T2…T n V)=0 Among them, U′ represents the upper boundary condition, that is, the free surface, T i represents the transfer matrix of the i-th layer, V represents the lower boundary condition, that is, semi-infinite space; the root obtained by solving the above dispersion equation is the theoretical dispersion curve of Rayleigh surface wave.

5. The method for inverting Rayleigh surface wave dispersion curves of elastic anisotropic media according to claim 1, characterized in that: The loss function is: Where m is the total number of modes of the observed Rayleigh surface wave dispersion curve, n e is the total number of discrete dispersion points of the observed Rayleigh surface wave dispersion curve in the eth mode, is the phase velocity of the theoretical Rayleigh surface wave dispersion curve at the i-th frequency of the e-th mode, is the phase velocity at frequency i of the eth mode of the Rayleigh surface wave dispersion curve.

6. The method for inverting Rayleigh surface wave dispersion curve of anisotropic elastic medium according to claim 1, characterized in that: The loss function gradient is: in, j is the layer number, is the vertical shear wave velocity of the jth layer, z j is the depth of the jth interface, k is the wave number, U is the group velocity, ρ is the density, and r1 and r2 are the Rayleigh surface wave eigendisplacement functions.

7. The method for inverting Rayleigh surface wave dispersion curves of elastic anisotropic media according to claim 1, characterized in that: The descent direction of the line search is calculated using the quasi-Newton method, and the expression of the vertical shear wave velocity of the surface near the line search is: x b+1 =x b +αd b Where α is the step size, x b+1 is the near-surface vertical shear wave velocity of the b+1th iteration, d b is the gradient; the expression for calculating the direction of gradient descent is: d b =-D b g b Among them, D b is in x b The approximate Hessian matrix at g b is the loss function for x b The gradient of b-1 =x b -x b-1 ,y b-1 =g b -g b-1 .

8. The method for inverting Rayleigh surface wave dispersion curves of elastic anisotropic media according to claim 1, characterized in that: After S5, the method further includes: calculating the theoretical Rayleigh surface wave dispersion curve corresponding to the inversion model by a forward modeling method, and then calculating the sensitivity function of the theoretical Rayleigh surface wave dispersion curve to the inversion model, analyzing the sensitivity of the theoretical Rayleigh surface wave dispersion curve to the inversion model, and quantitatively evaluating the credibility of the inversion result; wherein the sensitivity function calculation formula is: In addition, the sensitivity functions of the Rayleigh surface wave dispersion curve to the vertical P-wave velocity, density, Thomsen parameters ε and δ are provided, which are: in is the sensitivity function of the Rayleigh surface wave dispersion curve to the near-surface vertical shear wave velocity, is the sensitivity function of the Rayleigh surface wave dispersion curve to the near-surface vertical longitudinal wave velocity, S ρ is the sensitivity function of the Rayleigh surface wave dispersion curve to the near-surface density, S ε and S δ They are the sensitivity functions of the Rayleigh surface wave dispersion curve to the near-surface Thomsen anisotropy parameters ε and δ respectively; the analytical expressions of the sensitivity function and the sensitivity kernel are used for sensitivity analysis to estimate the credibility of the inversion results, and can also be used for gradient method inversion.

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