High-speed rail seismic data volume wave extraction method

Abstract

The invention discloses a high-speed rail seismic data volume wave extraction method, and the method comprises the following specific steps: 1, giving a high-speed rail seismic source, laying a measuring line, and carrying out the forward modeling of the high-speed rail seismic data recorded by the measuring line based on a three-dimensional elastic wave wave equation for further processing and analysis; step 2, selecting high-speed rail seismic data in a t'time period meeting a stable phase condition from the high-speed rail seismic data recorded by the measuring line obtained in the step 1; 3, F-K filtering is carried out on the high-speed rail seismic data which are obtained in the step 2 and meet the stable-phase condition, and preprocessed high-speed rail seismic data are obtained; step 4, obtaining a virtual shot record; step 5, carrying out band-pass filtering on the virtual shot record obtained in the step 4 to obtain a filtered virtual shot record; and step 6, superposing the virtual shot records obtained by the N high-speed rails to obtain a superposed virtual shot record. According to the method, relatively high-quality body wave signals are successfully extracted from the high-speed rail seismic data.

Description

Technical Field

[0001] This invention belongs to the field of geophysical exploration technology, specifically relating to a method for extracting volume waves from high-speed rail seismic data. Background Technology

[0002] High-speed trains running on viaducts generate vibrations, which in turn trigger seismic waves that propagate through the earth's strata. While once considered a source of traffic noise, high-speed trains have now become a unique type of seismic source. Analysis of numerous high-speed rail seismic events reveals a close correlation between the characteristics of the seismic wave fields generated by high-speed trains and changes in the underground medium. This indicates that effectively discovering and utilizing the information contained in high-speed rail seismic data is of significant practical importance for understanding the underground environment surrounding railways.

[0003] In recent years, significant progress has been made in the application of high-speed rail seismic data in underground exploration, primarily through methods such as full waveform inversion and seismic interferometry. A key challenge in applying high-speed rail seismic data to underground exploration is its interferometric characteristics. Compared to full waveform inversion, seismic interferometry can significantly reduce the impact of these interferometric effects. Seismic interferometry is an effective tool in seismology, capable of extracting useful waveform information hidden within background noise. By interferometric superposition between seismic traces, virtual shot records can be constructed, effectively transforming existing receiver points into new sources and receiver points.

[0004] While some studies have touched upon the discussion of body wave signals in high-speed rail seismic data, our goal is to conduct a more comprehensive and systematic study on the extraction of body wave signals from this data. Compared to surface waves, body waves typically have greater penetration depth, making them suitable for deeper exploration. Furthermore, body waves usually contain higher frequency components, allowing for more detailed characterization of subsurface stratigraphic structures. Additionally, body waves are well-suited for multi-parameter inversion (e.g., simultaneously estimating P-wave and S-wave velocities). However, in high-speed rail seismic data, body waves are largely masked by surface waves, posing a challenge to the reliable direct utilization of body waves for subsurface exploration. Therefore, a systematic study of body wave signal extraction from high-speed rail seismic data is of great significance for achieving deeper and more detailed subsurface exploration.

[0005] For the extraction of body wave signals from high-speed rail seismic data, where body waves are largely masked by surface wave signals, overcoming the influence of surface wave signals on body waves is the key to successfully extracting body wave signals from high-speed rail seismic data. Summary of the Invention

[0006] The purpose of this invention is to provide a method for extracting body waves from high-speed rail seismic data. This method transforms high-speed rail seismic data to the FK domain, which can present the velocity differences and frequency distribution differences between body waves and surface waves in the high-speed rail seismic data. Thus, a reasonable data processing flow is designed to suppress the influence of surface wave signals on body wave signal extraction in high-speed rail seismic data, and successfully extracts relatively high-quality body wave signals from high-speed rail seismic data.

[0007] The technical solution adopted in this invention is a method for extracting volume waves from high-speed rail seismic data, and the specific steps are as follows:

[0008] Step 1: Given the high-speed rail seismic source and set up the survey line, simulate the high-speed rail seismic data recorded by the survey line based on the three-dimensional elastic wave equation for further processing and analysis;

[0009] Step 2: Select high-speed rail seismic data within the time period t′ that meets the steady-phase condition from the high-speed rail seismic data recorded in Step 1.

[0010] Step 3: Apply FK filtering to the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2 to obtain preprocessed high-speed rail seismic data;

[0011] Step 4: Obtain the record of the fake cannon shot;

[0012] Step 5: Perform bandpass filtering on the virtual shot records obtained in Step 4 to obtain the filtered virtual shot records;

[0013] Step 6: Overlay the virtual shooting records obtained from N high-speed trains to obtain the superimposed virtual shooting records.

[0014] The invention is further characterized in that:

[0015] In step 1, the survey line consists of g detectors;

[0016] In step 1, the expression for the high-speed rail seismic data within time period t recorded by the survey line, based on the forward modeling of the three-dimensional elastic wave equation, is as follows: Among them, u x (x i ,x s ,t), where x is the source of the high-speed rail earthquake. s When excited at coordinate position x i The x-component of high-speed rail seismic data recorded by the i-th geophone within time period t; u y (x i ,x s ,t), where x is the source of the high-speed rail earthquake. s When excited at coordinate position x i The y-component of high-speed rail seismic data recorded by the i-th geophone within time period t; u z (x i ,xs ,t) represents the high-speed rail seismic source at x s When excited at coordinate position x i The z-component of high-speed rail seismic data recorded by the i-th geophone within the time interval t; for ease of representation, let be denoted as . That is, the high-speed rail epicenter is at x s When the location is excited, the high-speed rail seismic data recorded by the i-th geophone within the time interval t; where, [·] T Let's denote the transpose of a vector; then the high-speed rail seismic data recorded by the survey line simplifies to... The following statements all use the following methods. replace This represents the high-speed rail seismic data recorded by the survey line within the time period t.

[0017] Step 1 is as follows:

[0018] Step 1.1: Given a high-speed rail seismic source, specifically: when a high-speed train passes over an elevated bridge, the high-speed rail seismic source is represented as:

[0019]

[0020] In the formula, Q represents the total number of wheelsets in a high-speed train; J represents the number of piers of the viaduct. This indicates that when the high-speed train is traveling at speed v, the distance L between it and the first bridge pier is... q The qth pair of wheels arrives at a distance K from the first pier. j The loading function for the j-th pier within time period t;

[0021] Step 1.2: Lay out the survey lines, such as... Figure 2 As shown, specifically: a survey line consisting of g detectors is laid out on the ground below the viaduct, and the survey line is parallel to the viaduct; the coordinate positions of the 1st detector, the 2nd detector, ..., the gth detector are x1, x2, ..., xg, respectively. g ;

[0022] Step 1.3: Forward modeling of high-speed railway seismic data recorded by survey lines based on three-dimensional elastic wave equations. The specific form of the three-dimensional elastic wave equation is as follows:

[0023]

[0024] In the formula, u x (x,x s ,t) represents the high-speed rail seismic source at x s When the location is excited, the x-component of the high-speed rail seismic data within the time interval t corresponding to the x-coordinate position; u y (x,x s ,t) represents the high-speed rail seismic source at x sWhen the location is excited, the y-component of the high-speed rail seismic data within the time interval t corresponding to the x-coordinate position; u z (x,x s ,t) represents the high-speed rail seismic source at x s The z-component of high-speed rail seismic data within time interval t at the x-coordinate location when the earthquake is triggered; ρ is the density of the subsurface medium; P xx (x, xs, t) represents the high-speed rail seismic source at x s When the point is excited, the normal stress component in the x-direction during the time interval t corresponding to the x-coordinate position; P yy (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the normal stress component in the y direction at the x-coordinate position within the time interval t; P zz (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the normal stress component in the z-direction within the time interval t corresponding to the x-coordinate position; P xy (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the shear stress components in the x and y directions within time interval t at the x-coordinate position; P xz (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the shear stress components in the x and z directions within time interval t at the x-coordinate position; P yz (x,x s ,t) represents the high-speed rail seismic source at x s When excited, the shear stress components in the y and z directions at the x-coordinate position within the time interval t; λ and μ are the components related to the longitudinal wave velocity v. P and transverse wave velocity v S The relevant Lamé parameters, λ and μ, are expressed as follows:

[0025]

[0026] In addition, to simulate surface waves in high-speed rail seismic data using free surface boundaries during forward modeling, the specific implementation of free surface boundaries is as follows:

[0027]

[0028] Where, ρ free ρ represents the density ρ at the boundary of the free surface; λ represents the density ρ at the boundary of the free surface. free λ represents the value at the boundary of the free surface; μ represents the value at the boundary of the free surface. free μ represents the boundary of a free surface; P represents the z-direction normal stress component on the boundary of the free surface. zz;

[0029] Under the constraints of (2) and (3), the high-speed railway seismic data recorded by the survey line can be obtained by solving the differential equation shown in (2). Essentially, it is a matrix composed of high-speed rail seismic data recorded by g detectors.

[0030] Step 2 involves obtaining high-speed rail seismic data from the survey lines recorded in Step 1. Select high-speed rail seismic data within the time interval t′ that meets the steady-phase condition. To ensure effective superposition of signals during interference, t′ is a subset of t; where, The epicenter of the high-speed rail was in x s When excited at coordinate position x i The high-speed rail seismic data within time period t′ corresponding to the i-th geophone at location i, satisfying the steady-phase condition; u′ x (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The x-component of high-speed rail seismic data within time interval t′ corresponding to the i-th geophone at location i, satisfying the steady-phase condition; u′ y (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The y-component of high-speed rail seismic data within time interval t′ corresponding to the i-th geophone at location i, satisfying the steady-phase condition; u′ z (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The z-component of high-speed rail seismic data within the time interval t′ corresponding to the i-th geophone at the location, which satisfies the steady-phase condition.

[0031] Step 2 is as follows:

[0032] Step 2.1: First, determine the distribution area of ​​the high-speed rail seismic source that satisfies the phase stability condition with the survey line; the phase stability condition means that the convergence of the correlation function to the Green's function requires the existence of a source or scatterer collinear with the two detectors; when the high-speed rail seismic source is located in the area on both sides of the first and g-th detectors in the survey line, the high-speed rail seismic data recorded by the survey line satisfies the phase stability condition.

[0033] Step 2.2: Then, determine the time period t′ when the high-speed rail seismic source travels through the area on both sides of the first and g-th geophones along the survey line, based on the high-speed rail seismic data. High-speed rail seismic data satisfying the steady-phase condition are obtained by extracting data within the time interval t′.

[0034] Step 3 involves processing the high-speed rail seismic data obtained in Step 2 that meets the steady-phase condition. Implement FK filtering to filter out High-frequency surface wave signals were used to obtain preprocessed high-speed rail seismic data. in, The epicenter of the high-speed rail was in x s When excited at coordinate position x i The preprocessed high-speed rail seismic data within the time interval t′ corresponding to the i-th detector at location; u″ x (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The preprocessed x-component high-speed rail seismic data within the time interval t′ corresponding to the i-th detector at location; u″ y (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The preprocessed y-component high-speed rail seismic data within the time interval t′ corresponding to the i-th detector; u″ z (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The z-component high-speed rail seismic data within the preprocessed time period t′ corresponding to the i-th geophone at location ;

[0035] Step 3 specifically involves:

[0036] Step 3.1: First, process the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2. Transform to the FK domain to clarify The velocity and frequency distribution differences between mid-surface waves and volume waves determine the filtering range v1 to v2 of the FK filter; where v1 is the lower limit of the FK filter, and generally v1 is slightly higher than v2. The velocity of mid-surface waves is lower than The velocity of the mid-body wave; v2 is the upper limit of the FK filter, generally v2 is higher than... The velocity of midbody waves;

[0037] Step 3.2: Then, based on the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2... The velocity difference between mid-surface waves and volume waves Perform FK filtering to filter out High-frequency surface wave signals were used to obtain preprocessed high-speed rail seismic data.

[0038] Step 4: Using the preprocessed high-speed rail seismic data obtained in Step 3 corresponding to the first geophone. For the reference trace, the normalized cross-correlation between the preprocessed seismic data corresponding to the 1st, 2nd, ..., gth geophones and the reference trace is calculated to obtain the virtual shot record. in, The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the x component within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the y component within the time interval t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the z component within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location.

[0039] Step 4 specifically involves:

[0040] Step 4.1: First, calculate the high-speed rail seismic source obtained in Step 3 at x s When excited at coordinate position x i The preprocessed seismic data u″ corresponding to the i-th detector at position i (x i ,x s Fourier transform U(x,t′) i ,x s ,ω); where i=1,2,…,g; ω represents the angular frequency;

[0041] Step 4.2: In the Fourier domain, calculate the normalized cross-correlation between the preprocessed seismic data and the reference trace corresponding to the i-th detector, where i = 1, 2, ..., g. The expression for the normalized cross-correlation is as follows:

[0042]

[0043] Where, ε 2 U is a damping factor to ensure the stability of the relevant results; * (x1,x s ,ω) represents the high-speed rail seismic source at x s The preprocessed seismic data u″1(x1,x) corresponding to the first geophone at coordinate position x1 when the device is excited. s Fourier transform U(x1, x, t′) s The complex conjugate of ,ω);

[0044] Step 4.3: Transfer H 1i (x i Transform the virtual shot record (x1, ω) from the Fourier domain to the time domain, where i = 1, 2, ..., g. Finally, the virtual shot records corresponding to the 1st detector, 2nd detector, ..., i-th detector, ..., g-th detector are combined to form...

[0045] Step 5 specifically involves: processing the virtual shot records obtained in Step 4. Bandpass filtering was performed with a passband range of 18Hz to 60Hz to obtain the filtered virtual shot record. Further suppress surface wave signals; among which, The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location and performing bandpass filtering. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The preprocessed high-speed rail seismic data corresponding to the i-th geophone at point is normalized cross-correlation and bandpass filtered to obtain the filtered virtual shot record of the x component in the time interval t′. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the y component in the time interval t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location and performing bandpass filtering. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The preprocessed high-speed rail seismic data corresponding to the i-th geophone at point is used to calculate the normalized cross-correlation and perform bandpass filtering to obtain the z-component filtered virtual shot record within the time interval t′.

[0046] Step 6 is to overlay the virtual shooting records obtained from N high-speed trains to obtain the overlaid virtual shooting records. in, x is the coordinate position i The virtual shot record within the time period t′ obtained by superimposing the virtual shot records of the N high-speed trains corresponding to the i-th detector at the location; x is the coordinate position i The x-component virtual shot record within the time period t′ obtained by superimposing the x-component virtual shot records of the N high-speed trains corresponding to the i-th detector at the location; x is the coordinate position i The y-component virtual shot record within the time period t′ obtained by superimposing the y-component virtual shot records of the N high-speed trains corresponding to the i-th detector at the location; x is the coordinate position i The z-component virtual shot records obtained from the N high-speed trains corresponding to the i-th detector at the location are superimposed within the time period t′.

[0047] Step 6 specifically involves:

[0048] Step 6.1: First, adjust the high-speed rail operating speed v from Step 1 (ensuring multiple operating speeds v have different values; depending on the actual high-speed rail operating speed, v can be between 55 m / s and 97 m / s) to obtain N sets of high-speed rail seismic data; then, sequentially perform steps 2 to 5 on the N sets of high-speed rail seismic data to obtain the corresponding virtual shot records; here, for ease of representation, the filtered virtual shot records obtained by sequentially performing steps 2 to 5 on the N sets of high-speed rail seismic data are respectively denoted as...

[0049] Step 6.2: Then, the N sets of filtered virtual shot records obtained in Step 6.1 are superimposed to obtain the preliminary superimposed seismic virtual shot records. The specific mathematical expression is as follows:

[0050]

[0051] The beneficial effects of this invention are:

[0052] (1) The method of this invention: First, starting from a linear model, high-speed rail seismic data is simulated using forward modeling of the three-dimensional elastic wave equation. Second, seismic data that meets the steady-phase condition is selected from the original high-speed rail seismic data to ensure effective signal superposition during the interferometry process. Third, FK filtering is applied to the selected high-speed rail seismic data that meets the steady-phase condition to filter out some high-frequency surface waves, reducing the influence of high-frequency surface waves on volume wave extraction. Then, through normalized cross-correlation, the interferometry process of different detectors on the recorded high-speed rail seismic data is realized to reduce the influence of the correlation of high-speed rail sources on the interferometry results. In addition, bandpass filtering is applied to the virtual shot records to further reduce the influence of low-frequency surface waves on the volume wave signal. Finally, the virtual shot records corresponding to different high-speed rail seismic events are superimposed to further improve the quality of the volume wave signal.

[0053] (2) The method of this invention can significantly reduce the influence of high-energy surface waves on the extraction of body waves from high-speed rail seismic data. The reason for this advantage is that: firstly, the screening of seismic data that meets the steady-phase condition ensures effective signal superposition during the interferometry process. Secondly, analysis of the high-speed rail seismic data in the FK domain highlights the characteristic differences between body waves and surface waves in the data. Based on these differences, surface waves in the high-speed rail seismic data are effectively filtered out and suppressed, thus enabling the extraction of high-quality body wave signals from the data. Attached Figure Description

[0054] Figure 1 This is a flowchart of the method of the present invention;

[0055] Figure 2 This explains the mechanism by which high-speed trains generate seismic waves when running on viaducts;

[0056] Figure 3 It is a three-dimensional linear model (longitudinal wave velocity);

[0057] Figure 4 It is a three-dimensional linear model (transverse wave velocity);

[0058] Figure 5 This is a schematic diagram (top view) of the observation system;

[0059] Figure 6(a) shows the x-component high-speed rail seismic data;

[0060] Figure 6(b) shows the y-component high-speed rail seismic data;

[0061] Figure 6(c) shows the z-component high-speed rail seismic data;

[0062] Figure 7(a) shows the FK spectrum of the x-component high-speed rail seismic data;

[0063] Figure 7(b) shows the FK spectrum of the y-component high-speed rail seismic data;

[0064] Figure 7(c) shows the FK spectrum of the x-component high-speed rail seismic data;

[0065] Figure 8(a) shows the FK spectrum of the x-component high-speed rail seismic data that satisfies the steady-phase condition;

[0066] Figure 8(b) shows the FK spectrum of the y-component high-speed rail seismic data that satisfies the steady-phase condition;

[0067] Figure 8(c) shows the FK spectrum of the z-component high-speed rail seismic data that satisfies the steady-phase condition;

[0068] Figure 9(a) shows the virtual shot record of the x component obtained in step 5;

[0069] Figure 9(b) shows the virtual shot record of the y component obtained in step 5;

[0070] Figure 9(c) shows the virtual shot record of the z-component obtained in step 5;

[0071] Figure 10(a) shows the final virtual shot record of the x component obtained by the method of the present invention;

[0072] Figure 10(b) shows the final virtual shot record of the y component obtained by the method of the present invention;

[0073] Figure 10(c) shows the final z-component virtual shot record obtained by the method of the present invention; Detailed Implementation

[0074] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0075] This invention provides a method for extracting body waves from high-speed rail seismic data, such as... Figure 1 As shown, the specific steps are as follows:

[0076] Step 1: Given a high-speed rail seismic source and set up a survey line (where the survey line consists of g geophones), perform forward modeling simulation of the high-speed rail seismic data recorded by the survey line based on the three-dimensional elastic wave equation for further processing and analysis;

[0077] In step 1, the expression for the high-speed rail seismic data within time period t recorded by the survey line, based on the forward modeling of the three-dimensional elastic wave equation, is as follows: Among them, u x (x i ,x s ,t) represents the high-speed rail seismic source at x s When excited at coordinate position x i The x-component of high-speed rail seismic data recorded by the i-th geophone within time period t; u y (x i ,x s ,t) represents the high-speed rail seismic source at x s When excited at coordinate position xi The y-component of high-speed rail seismic data recorded by the i-th geophone within time period t; u z (x i ,x s ,t) represents the high-speed rail seismic source at x s When excited at coordinate position x i The z-component of high-speed rail seismic data recorded by the i-th geophone within the time interval t; for ease of representation, let be denoted as . (i.e., the high-speed rail epicenter is at x) s (When the point is excited, the high-speed rail seismic data recorded by the i-th geophone within time period t); where, [·] T Let's denote the transpose of a vector; then the high-speed rail seismic data recorded by the survey line simplifies to... The following statements all use the following methods. replace This represents the high-speed rail seismic data recorded by the survey line within time period t.

[0078] Step 1 is as follows:

[0079] Step 1.1: Given a high-speed rail seismic source, specifically: when a high-speed train passes over an elevated bridge, the high-speed rail seismic source is represented as:

[0080]

[0081] In the formula, Q represents the total number of wheelsets in a high-speed train; J represents the number of piers of the viaduct. This indicates that when the high-speed train is traveling at speed v, the distance L between it and the first bridge pier is... q The qth pair of wheels arrives at a distance K from the first pier. j The loading function for the j-th pier within time period t;

[0082] Step 1.2: Lay out the survey lines, such as... Figure 2 As shown, specifically: a survey line consisting of g detectors is laid out on the ground below the viaduct, and the survey line is parallel to the viaduct; the coordinate positions of the 1st detector, the 2nd detector, ..., the gth detector are x1, x2, ..., xg, respectively. g ;

[0083] Step 1.3: Forward modeling of high-speed railway seismic data recorded by survey lines based on three-dimensional elastic wave equations. The specific form of the three-dimensional elastic wave equation is as follows:

[0084]

[0085] In the formula, u x (x,x s ,t) represents the high-speed rail seismic source at x sWhen the location is excited, the x-component of the high-speed rail seismic data within the time interval t corresponding to the x-coordinate position; u y (x,x s ,t) represents the high-speed rail seismic source at x s When the location is excited, the y-component of the high-speed rail seismic data within the time interval t corresponding to the x-coordinate position; u z (x,x s ,t) represents the high-speed rail seismic source at x s The z-component of high-speed rail seismic data within time interval t at the x-coordinate location when the earthquake is triggered; ρ is the density of the subsurface medium; P xx (x, xs, t) represents the high-speed rail seismic source at x s When the point is excited, the normal stress component in the x-direction during the time interval t corresponding to the x-coordinate position; P yy (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the normal stress component in the y direction at the x-coordinate position within the time interval t; P zz (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the normal stress component in the z-direction within the time interval t corresponding to the x-coordinate position; P xy (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the shear stress components in the x and y directions within time interval t at the x-coordinate position; P xz (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the shear stress components in the x and z directions within time interval t at the x-coordinate position; P yz (x,x s ,t) represents the high-speed rail seismic source at x s When excited, the shear stress components in the y and z directions at the x-coordinate position within the time interval t; λ and μ are the components related to the longitudinal wave velocity v. P and transverse wave velocity v S The relevant Lamé parameters, λ and μ, are expressed as follows:

[0086]

[0087] In addition, to simulate surface waves in high-speed rail seismic data using free surface boundaries during forward modeling, the specific implementation of free surface boundaries is as follows:

[0088]

[0089] Where, ρ free ρ represents the density ρ at the boundary of the free surface; λ represents the density ρ at the boundary of the free surface.free λ represents the value at the boundary of the free surface; μ represents the value at the boundary of the free surface. free μ represents the boundary of a free surface; P represents the z-direction normal stress component on the boundary of the free surface. zz ;

[0090] Under the constraints of (2) and (3), the high-speed railway seismic data recorded by the survey line can be obtained by solving the differential equation shown in (2). Essentially, it is a matrix composed of high-speed rail seismic data recorded by g detectors.

[0091] Step 2: High-speed rail seismic data recorded from the survey lines obtained in Step 1. Select high-speed rail seismic data within the time interval t′ that meets the steady-phase condition. To ensure effective superposition of signals during interference, t′ is a subset of t; where, The epicenter of the high-speed rail was in x s When excited at coordinate position x i The high-speed rail seismic data within time period t′ corresponding to the i-th geophone at location i, satisfying the steady-phase condition; u′ x (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The x-component of high-speed rail seismic data within time interval t′ corresponding to the i-th geophone at location i, satisfying the steady-phase condition; u′ y (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The y-component of high-speed rail seismic data within time interval t′ corresponding to the i-th geophone at location i, satisfying the steady-phase condition; u′ z (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The z-component of high-speed rail seismic data within the time interval t′ corresponding to the i-th geophone at the location, which satisfies the phase-stable condition;

[0092] Step 2 specifically includes: Step 2.1: First, determine the relationship with... Figure 2 The survey line shown indicates the distribution area of ​​high-speed rail seismic sources that meet the steady-phase condition. The steady-phase condition implies that the convergence of the correlation function to the Green's function requires the existence of a source or scatterer collinear with both detectors. When the high-speed rail seismic source is located in... Figure 2 When the area on both sides of the first and g-th detectors in the survey line shown is... Figure 2The high-speed rail seismic data recorded by the survey line shown meets the steady-phase condition.

[0093] Step 2.2: Then, determine the location of the high-speed rail seismic source where it is traveling. Figure 2 The time interval t′ (t′ can be calculated based on the departure time, departure location, and running speed of the high-speed rail seismic source) in the area on both sides of the first and g-th geophones along the survey line is given by high-speed rail seismic data. High-speed rail seismic data satisfying the steady-phase condition are obtained by extracting data within the time interval t′.

[0094] Step 3: Process the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2. Implement FK filtering to filter out High-frequency surface wave signals were used to obtain preprocessed high-speed rail seismic data. in, The epicenter of the high-speed rail was in x s When excited at coordinate position x i The preprocessed high-speed rail seismic data within the time interval t′ corresponding to the i-th detector at location; u″ x (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The preprocessed x-component high-speed rail seismic data within the time interval t′ corresponding to the i-th detector at location; u″ y (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The preprocessed y-component high-speed rail seismic data within the time interval t′ corresponding to the i-th detector; u″ z (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The z-component high-speed rail seismic data within the preprocessed time period t′ corresponding to the i-th geophone at location ;

[0095] Step 3 specifically involves: Step 3.1: First, the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2 is processed... Transform to the FK domain to clarify The velocity and frequency distribution differences between mid-surface waves and volume waves determine the filtering range v1 to v2 of the FK filter; where v1 is the lower limit of the FK filter, and generally v1 is slightly higher than v2. The velocity of mid-surface waves is lower than The velocity of the mid-body wave; v2 is the upper limit of the FK filter, generally v2 is higher than... The velocity of midbody waves;

[0096] Step 3.2: Then, based on the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2... The velocity difference between mid-surface waves and volume waves Perform FK filtering to filter out High-frequency surface wave signals were used to obtain preprocessed high-speed rail seismic data.

[0097] Step 4: Using the preprocessed high-speed rail seismic data obtained in Step 3 corresponding to the first geophone. For the reference trace, the normalized cross-correlation between the preprocessed seismic data corresponding to the 1st, 2nd, ..., gth geophones and the reference trace is calculated to obtain the virtual shot record. in, The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the x component within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the y component within the time interval t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the z component within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location.

[0098] Step 4 specifically involves: Step 4.1: First, calculate the high-speed rail seismic source obtained in Step 3 at x s When excited at coordinate position x i The preprocessed seismic data u″ corresponding to the i-th detector at position i (x i ,x s Fourier transform U(x,t′) i ,x s ,ω); where i=1,2,…,g; ω represents the angular frequency;

[0099] Step 4.2: In the Fourier domain, calculate the normalized cross-correlation between the preprocessed seismic data and the reference trace corresponding to the i-th detector (where i = 1, 2, ..., g). The expression for the normalized cross-correlation is as follows:

[0100]

[0101] Where, ε 2 U is a damping factor to ensure the stability of the relevant results; * (x1,x s ,ω) represents the high-speed rail seismic source at x s The preprocessed seismic data u″1(x1,x) corresponding to the first geophone at coordinate position x1 when the device is excited. s Fourier transform U(x1, x, t′) s The complex conjugate of ,ω);

[0102] Step 4.3: Transfer H 1i (x i Transform the data (x1, ω) from the Fourier domain to the time domain (where i = 1, 2, ..., g) to obtain the virtual shot record. Finally, the virtual shot records corresponding to the 1st detector, 2nd detector, ..., i-th detector, ..., g-th detector are combined to form...

[0103] Step 5: Record the false shots obtained in Step 4. Bandpass filtering was performed with a passband range of 18Hz to 60Hz to obtain the filtered virtual shot record. Further suppress surface wave signals; among which, The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location and performing bandpass filtering. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The preprocessed high-speed rail seismic data corresponding to the i-th geophone at point is normalized cross-correlation and bandpass filtered to obtain the filtered virtual shot record of the x component in the time interval t′. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the y component in the time interval t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location and performing bandpass filtering. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of z component filtering in time period t′ is obtained by calculating normalized cross-correlation and bandpass filtering of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the i-th location.

[0104] Step 6: Overlay the false shooting records obtained from N high-speed trains to obtain the overlaid false shooting records. in, x is the coordinate position i The virtual shot record within the time period t′ obtained by superimposing the virtual shot records of the N high-speed trains corresponding to the i-th detector at the location; x is the coordinate position i The x-component virtual shot record within the time period t′ obtained by superimposing the x-component virtual shot records of the N high-speed trains corresponding to the i-th detector at the location; x is the coordinate position i The y-component virtual shot record within the time period t′ obtained by superimposing the y-component virtual shot records of the N high-speed trains corresponding to the i-th detector at the location; x is the coordinate position i The z-component virtual shot record within the time period t′ obtained by superimposing the z-component virtual shot records of the N high-speed trains corresponding to the i-th detector at the location;

[0105] Step 6 specifically involves: Step 6.1: First, adjust the high-speed rail operating speed v from Step 1 (ensuring multiple operating speeds of v have different values; depending on the actual high-speed rail operating speed, v can be between 55 m / s and 97 m / s) to obtain N sets of high-speed rail seismic data; then, sequentially perform steps 2 to 5 on the N sets of high-speed rail seismic data to obtain the corresponding virtual shot records. Here, for ease of representation, the filtered virtual shot records obtained by sequentially performing steps 2 to 5 on the N sets of high-speed rail seismic data are denoted as follows:

[0106] Step 6.2: Then, the N sets of filtered virtual shot records obtained in Step 6.1 are superimposed to obtain the preliminary superimposed seismic virtual shot records. The specific mathematical expression is as follows:

[0107]

[0108] Example 1

[0109] The specific implementation process of the present invention is applied to, for example Figure 3 and Figure 4The diagram shows a three-dimensional linear model (an elastic medium containing both longitudinal and transverse waves). The velocity in the three-dimensional linear model increases linearly with depth. The length in the x and y directions is 1.6 km, and the depth in the z direction is 0.4 km. The spatial sampling interval in all directions is 4 m. The observation system during implementation is as follows: Figure 5 As shown, the high-speed train runs from point O along the positive x-axis on the viaduct on the surface of the linear model. The survey line, composed of 300 detectors, is adjacent to and parallel to the viaduct. The survey line is 1200m long, and its first detector is located at (400m, 40m, 0m), and is laid out along the positive x-axis. The spacing between adjacent detectors in the survey line is 4m. The specific implementation process uses a high-speed train with 16 carriages, each carriage is 25m long, and each carriage has 4 pairs of wheels. The distances from each pair of wheels to the front end of the carriage are 4m, 6.5m, 18.5m, and 21m, respectively. The Ricker wavelet with a peak frequency of 15Hz is used as the loading function for each set of wheelsets (corresponding to the formula in formula (1)). The high-speed train's operating speed (v) was set to 71 m / s, 73 m / s, 75 m / s, 77 m / s, 79 m / s, 81 m / s, 83 m / s, and 85 m / s respectively, and a high-speed train seismic source was synthesized. The observation time was 30 s, and the time sampling interval was 1 ms.

[0110] The high-speed rail seismic data obtained through step 1 of the method proposed in this invention, when the high-speed rail is traveling at a speed of 83 m / s, are shown in Figures 6(a), 6(b), and 6(c), respectively. The FK spectra corresponding to Figures 6(a), 6(b), and 6(c) are shown in Figures 7(a), 7(b), and 7(c), respectively. It can be seen that surface waves and body waves coexist in the high-speed rail seismic data. After step 2 of the method proposed in this invention, seismic data that meets the steady-phase condition is obtained. The FK spectra corresponding to the seismic data that meets the steady-phase condition are shown in Figures 8(a), 8(b), and 8(c), respectively. It can be seen that the interference signal energy in the seismic data that meets the steady-phase condition is reduced, while the energy of surface wave and body wave signals is relatively enhanced. After steps 3 to 5 of the method proposed in this invention, the virtual shot records of the x, y, and z components are obtained, as shown in Figures 9(a), 9(b), and 9(c), respectively. It can be seen that the virtual shot records of the x and z components present some body wave signals, such as refracted P-waves, direct P-waves, and refracted S-waves. After step 6 of the method proposed in this invention, the final virtual shot records of the x, y, and z components containing high-quality body wave signals are obtained, as shown in Figures 10(a), 10(b), and 10(c), respectively. It can be seen that steps 1 to 6 of the method proposed in this invention successfully extracted relatively high-quality body wave signals from high-speed rail seismic data, demonstrating the effectiveness of the method proposed in this invention.

[0111] Example 2

[0112] The specific steps for extracting volume waves from high-speed rail seismic data are as follows:

[0113] Step 1: Given a high-speed rail seismic source and lay out the seismic lines, perform forward modeling of the high-speed rail seismic data recorded by the seismic lines based on the three-dimensional elastic wave equation for further processing and analysis; Step 2: Select high-speed rail seismic data within the time period t′ that meets the steady-phase condition from the high-speed rail seismic data obtained in Step 1; Step 3: Apply FK filtering to the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2 to obtain preprocessed high-speed rail seismic data; Step 4: Obtain virtual shot records; Step 5: Apply bandpass filtering to the virtual shot records obtained in Step 4 to obtain filtered virtual shot records; Step 6: Superimpose the virtual shot records obtained from N high-speed rail trains to obtain superimposed virtual shot records.

[0114] Example 3

[0115] The difference from Example 2 is that in step 1, the measuring line consists of g detectors;

[0116] Example 4

[0117] The difference from Example 3 is as follows: Step 1 specifically includes: Step 1.1: Given the high-speed rail seismic source; Step 1.2: Lay out the survey lines; Step 1.3: Simulate the high-speed rail seismic data recorded by the survey lines based on the forward modeling of the three-dimensional elastic wave equation;

[0118] Example 5

[0119] The difference from Example 4 is as follows: Step 2 is specifically as follows: Step 2.1: First, determine the distribution area of ​​the high-speed rail seismic source that meets the steady-phase condition with the survey line; Step 2.2: Then, determine the time period t′ of the area on both sides of the first and g-th geophones in the survey line when the high-speed rail seismic source is traveling, and extract the data within the time period t′ from the high-speed rail seismic data to obtain the high-speed rail seismic data that meets the steady-phase condition.

[0120] Example 6

[0121] The difference from Example 5 is as follows: Step 3 is specifically as follows: Step 3.1: First, transform the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2 to the FK domain to clarify the velocity difference and frequency distribution difference between surface waves and body waves; Step 3.2: Then, perform FK filtering on the velocity difference between surface waves and body waves in the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2 to filter out the high-frequency surface wave signals and obtain the preprocessed high-speed rail seismic data.

Claims

1. A method for extracting volume waves from high-speed rail seismic data, characterized in that, The specific steps are as follows: Step 1: Given the high-speed rail seismic source and set up the survey line, simulate the high-speed rail seismic data recorded by the survey line based on the three-dimensional elastic wave equation for further processing and analysis; Step 2: Select high-speed rail seismic data within the time period t′ that meets the steady-phase condition from the high-speed rail seismic data recorded in Step 1. Step 3: Apply FK filtering to the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2 to obtain preprocessed high-speed rail seismic data; Step 4: Obtain the record of the fake cannon shot; Step 5: Perform bandpass filtering on the virtual shot records obtained in Step 4 to obtain the filtered virtual shot records; Step 6: Overlay the virtual shooting records obtained from N high-speed trains to obtain the superimposed virtual shooting records.

2. The method for extracting volume waves from high-speed rail seismic data according to claim 1, characterized in that, In step 1, the survey line consists of g detectors; In step 1, the expression for the high-speed rail seismic data within time period t recorded by the survey line, based on the forward modeling of the three-dimensional elastic wave equation, is as follows: Among them, u x (x i ,x s ,t), where x is the source of the high-speed rail earthquake. s When excited at coordinate position x i The x-component of high-speed rail seismic data recorded by the i-th geophone within time period t; u y (x i ,x s ,t), where x is the source of the high-speed rail earthquake. s When excited at coordinate position x i The y-component of high-speed rail seismic data recorded by the i-th geophone within time period t; u z (x i ,x s ,t) represents the high-speed rail seismic source at x s When excited at coordinate position x i The z-component of high-speed rail seismic data recorded by the i-th geophone within the time interval t; for ease of representation, let be denoted as . That is, the high-speed rail epicenter is at x s When the location is excited, the high-speed rail seismic data recorded by the i-th geophone within the time interval t; where, [·] T Let's denote the transpose of a vector; then the high-speed rail seismic data recorded by the survey line simplifies to... The following statements all use the following methods. replace This represents the high-speed rail seismic data recorded by the survey line within the time period t.

3. The method for extracting volume waves from high-speed rail seismic data according to claim 2, characterized in that, Step 1 is as follows: Step 1.1: Given a high-speed rail seismic source, specifically: when a high-speed train passes over an elevated bridge, the high-speed rail seismic source is represented as: In the formula, Q represents the total number of wheelsets in a high-speed train; J represents the number of piers of the viaduct. This indicates that when the high-speed train is traveling at speed v, the distance L between it and the first bridge pier is... q The qth pair of wheels arrives at a distance K from the first pier. j The loading function for the j-th pier within time period t; Step 1.2: Lay out the survey line, specifically: lay out the survey line consisting of g detectors on the ground below the viaduct, with the survey line parallel to the viaduct; the coordinates of the 1st detector, the 2nd detector, ..., the gth detector are x1, x2, ..., xg detectors, respectively. g ; Step 1.3: Forward modeling of high-speed railway seismic data recorded by survey lines based on three-dimensional elastic wave equations. The specific form of the three-dimensional elastic wave equation is as follows: In the formula, u x (x,x s ,t) represents the high-speed rail seismic source at x s When the location is excited, the x-component of the high-speed rail seismic data within the time interval t corresponding to the x-coordinate position; u y (x,x s ,t) represents the high-speed rail seismic source at x s When the location is excited, the y-component of the high-speed rail seismic data within the time interval t corresponding to the x-coordinate position; u z (x,x s ,t) represents the high-speed rail seismic source at x s When the location is excited, the z-component of the high-speed rail seismic data within the time interval t corresponding to the x-coordinate position; ρ is the density of the underground medium; P xx (x,x s ,t) represents the high-speed rail seismic source at x s When the point is excited, the normal stress component in the x-direction during the time interval t corresponding to the x-coordinate position; P yy (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the normal stress component in the y direction at the x-coordinate position within the time interval t; P zz (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the normal stress component in the z-direction within the time interval t corresponding to the x-coordinate position; P xy (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the shear stress components in the x and y directions within time interval t at the x-coordinate position; P xz (x,x s ,t) represents the high-speed rail seismic source at x s When the stress is excited, the shear stress components in the x and z directions within time interval t at the x-coordinate position; P yz (x,x s ,t) represents the high-speed rail seismic source at x s When excited, the shear stress components in the y and z directions at the x-coordinate position within the time interval t; λ and μ are the components related to the longitudinal wave velocity v. P and transverse wave velocity v S The relevant Lamé parameters, λ and μ, are expressed as follows: In addition, to simulate surface waves in high-speed rail seismic data using free surface boundaries during forward modeling, the specific implementation of free surface boundaries is as follows: Where, ρ free ρ represents the density ρ at the boundary of the free surface; λ represents the density ρ at the boundary of the free surface. free λ represents the value at the boundary of the free surface; μ represents the value at the boundary of the free surface. free μ represents the boundary of a free surface; P represents the z-direction normal stress component on the boundary of the free surface. zz ; Under the constraints of (2) and (3), the high-speed railway seismic data recorded by the survey line can be obtained by solving the differential equation shown in (2). Essentially, it is a matrix composed of high-speed rail seismic data recorded by g detectors.

4. The method for extracting volume waves from high-speed rail seismic data according to claim 3, characterized in that, Step 2 involves obtaining high-speed rail seismic data from the survey lines recorded in Step 1. Select high-speed rail seismic data within the time interval t′ that meets the steady-phase condition. To ensure effective superposition of signals during interference, t′ is a subset of t; where, The epicenter of the high-speed rail was in x s When excited at coordinate position x i The high-speed rail seismic data within time period t′ corresponding to the i-th geophone at location i, satisfying the steady-phase condition; u′ x (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The x-component of high-speed rail seismic data within time interval t′ corresponding to the i-th geophone at location i, satisfying the steady-phase condition; u′ y (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The y-component of high-speed rail seismic data within time interval t′ corresponding to the i-th geophone at location i, satisfying the steady-phase condition; u′ z (x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The z-component of high-speed rail seismic data within the time interval t′ corresponding to the i-th geophone at the location, which satisfies the steady-phase condition.

5. The method for extracting volume waves from high-speed rail seismic data according to claim 3, characterized in that, Step 2 is as follows: Step 2.1: First, determine the distribution area of ​​the high-speed rail seismic source that satisfies the phase stability condition with the survey line; the phase stability condition means that the convergence of the correlation function to the Green's function requires the existence of a source or scatterer collinear with the two detectors; when the high-speed rail seismic source is located in the area on both sides of the first and g-th detectors in the survey line, the high-speed rail seismic data recorded by the survey line satisfies the phase stability condition. Step 2.2: Then, determine the time period t′ when the high-speed rail seismic source travels through the area on both sides of the first and g-th geophones along the survey line, based on the high-speed rail seismic data. High-speed rail seismic data satisfying the steady-phase condition are obtained by extracting data within the time interval t′.

6. The method for extracting volume waves from high-speed rail seismic data according to claim 5, characterized in that, Step 3 involves processing the high-speed rail seismic data obtained in Step 2 that meets the steady-phase condition. Implement FK filtering to filter out High-frequency surface wave signals were used to obtain preprocessed high-speed rail seismic data. in, The epicenter of the high-speed rail was in x s When excited at coordinate position x i The preprocessed high-speed rail seismic data within time period t′ corresponding to the i-th geophone at location u′; x ′(x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The preprocessed x-component high-speed rail seismic data within the time interval t′ corresponding to the i-th detector at location u′; y ′(x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The preprocessed y-component high-speed rail seismic data within the time interval t′ corresponding to the i-th geophone; u′ z ′(x i ,x s ,t′) represents the high-speed rail seismic source at x s When excited at coordinate position x i The z-component high-speed rail seismic data within the preprocessed time period t′ corresponding to the i-th geophone at location ; Step 3 specifically involves: Step 3.1: First, process the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2. Transform to the FK domain to clarify The velocity and frequency distribution differences between mid-surface waves and volume waves determine the filtering range v1 to v2 of the FK filter; where v1 is the lower limit of the FK filter, and v2 is slightly higher than... The velocity of mid-surface waves is lower than The velocity of the midbody wave; v2 is the upper limit of the FK filter, v2 is higher than The velocity of midbody waves; Step 3.2: Then, based on the high-speed rail seismic data that meets the steady-phase condition obtained in Step 2... The velocity difference between mid-surface waves and volume waves Perform FK filtering to filter out High-frequency surface wave signals were used to obtain preprocessed high-speed rail seismic data.

7. The method for extracting volume waves from high-speed rail seismic data according to claim 5, characterized in that, Step 4: Using the preprocessed high-speed rail seismic data obtained in Step 3 corresponding to the first geophone. For the reference trace, the normalized cross-correlation between the preprocessed seismic data corresponding to the 1st, 2nd, ..., gth geophones and the reference trace is calculated to obtain the virtual shot record. in, The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the x component within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the y component within the time interval t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the z component within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location. Step 4 specifically involves: Step 4.1: First, calculate the high-speed rail seismic source obtained in Step 3 at x s When excited at coordinate position x i The preprocessed seismic data u corresponding to the i-th detector at position i i "(x i ,x s Fourier transform U(x,t′) i ,x s ,ω); where i=1,2,…,g; ω represents the angular frequency; Step 4.2: In the Fourier domain, calculate the normalized cross-correlation between the preprocessed seismic data and the reference trace corresponding to the i-th detector, where i = 1, 2, ..., g. The expression for the normalized cross-correlation is as follows: Where, ε 2 U is a damping factor to ensure the stability of the relevant results; * (x1,x s ,ω) represents the high-speed rail seismic source at x s The preprocessed seismic data u1″(x1,x) corresponding to the first geophone at coordinate position x1 when the device is excited. s Fourier transform U(x1, x, t′) s The complex conjugate of ,ω); Step 4.3: Transfer H 1i (x i Transform the virtual shot record (x1, ω) from the Fourier domain to the time domain, where i = 1, 2, ..., g. Finally, the virtual shot records corresponding to the 1st detector, 2nd detector, ..., i-th detector, ..., g-th detector are combined to form...

8. The method for extracting volume waves from high-speed rail seismic data according to claim 7, characterized in that, Step 5 specifically involves: processing the virtual shot records obtained in Step 4. Bandpass filtering was performed with a passband range of 18Hz to 60Hz to obtain the filtered virtual shot record. Further suppress surface wave signals; among which, The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record within the time period t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location and performing bandpass filtering. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The preprocessed high-speed rail seismic data corresponding to the i-th geophone at point is normalized cross-correlation and bandpass filtered to obtain the filtered virtual shot record of the x component in the time interval t′. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The virtual shot record of the y component in the time interval t′ is obtained by calculating the normalized cross-correlation of the preprocessed high-speed rail seismic data corresponding to the i-th geophone at the location and performing bandpass filtering. The preprocessed high-speed rail seismic data corresponding to the first geophone at coordinate position x1 and the data at coordinate position x2. i The preprocessed high-speed rail seismic data corresponding to the i-th geophone at point is used to calculate the normalized cross-correlation and perform bandpass filtering to obtain the z-component filtered virtual shot record within the time interval t′.

9. The method for extracting volume waves from high-speed rail seismic data according to claim 8, characterized in that, Step 6 is to overlay the virtual shooting records obtained from N high-speed trains to obtain the overlaid virtual shooting records. in, x is the coordinate position i The virtual shot record within the time period t′ obtained by superimposing the virtual shot records of the N high-speed trains corresponding to the i-th detector at the location; x is the coordinate position i The x-component virtual shot record within the time period t′ obtained by superimposing the x-component virtual shot records of the N high-speed trains corresponding to the i-th detector at the location; x is the coordinate position i The y-component virtual shot record within the time period t′ obtained by superimposing the y-component virtual shot records of the N high-speed trains corresponding to the i-th detector at the location; x is the coordinate position i The z-component virtual shot records obtained from the N high-speed trains corresponding to the i-th detector at the location are superimposed within the time period t′.

10. The method for extracting volume waves from high-speed rail seismic data according to claim 9, characterized in that, Step 6 specifically involves: Step 6.1: First, adjust the high-speed rail's operating speed v from Step 1 to obtain N sets of high-speed rail seismic data; then, sequentially perform Steps 2 to 5 on the N sets of high-speed rail seismic data to obtain the corresponding virtual shot records; here, for ease of representation, the corresponding filtered virtual shot records obtained by sequentially performing Steps 2 to 5 on the N sets of high-speed rail seismic data are respectively denoted as... Step 6.2: Then, the N sets of filtered virtual shot records obtained in Step 6.1 are superimposed to obtain the preliminary superimposed seismic virtual shot records. The specific mathematical expression is as follows:

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