High-speed railway seismic data body wave extraction method

Abstract

The application discloses a high-speed rail seismic data body wave extraction method, and specific steps are as follows: step 1, a high-speed rail seismic source is given and a survey line is laid out, and high-speed rail seismic data recorded by the survey line are simulated based on a three-dimensional elastic wave wave equation forward modeling to be further processed and analyzed; step 2, high-speed rail seismic data in a t' time period meeting a stable phase condition are selected from the high-speed rail seismic data recorded by the survey line obtained in step 1; step 3, F-K filtering is performed on the high-speed rail seismic data meeting the stable phase condition obtained in step 2, and pretreated high-speed rail seismic data are obtained; step 4, virtual shot records are obtained; step 5, band-pass filtering is performed on the virtual shot records obtained in step 4, and filtered virtual shot records are obtained; step 6, the virtual shot records obtained by N high-speed rails are stacked to obtain stacked virtual shot records. The method successfully extracts relatively high-quality body wave signals from high-speed rail seismic data.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of geophysical exploration, and particularly relates to a high-speed rail seismic data body wave extraction method. BACKGROUND

[0002] High-speed rail running on viaducts can generate vibrations, which excite seismic waves and propagate through the strata. High-speed rail was once considered a source of traffic noise, but now it has become a special new type of seismic source. Analysis of a large number of high-speed rail seismic events shows that the characteristics of the seismic wave field excited by high-speed rail are closely related to the changes in the underground medium. This shows that effectively discovering and utilizing the information contained in high-speed rail seismic data has important practical significance for understanding the underground environment around the railway.

[0003] In recent years, the application of high-speed rail seismic data in underground exploration has also made many progress, and the main methods include full waveform inversion and seismic interferometry. One of the key challenges of applying high-speed rail seismic data to underground exploration is its interference characteristics. Compared with full waveform inversion, seismic interferometry can significantly reduce the influence of these interference effects. Seismic interferometry is an effective tool in seismology that can extract useful waveform information hidden in background noise. Through the interference stacking between seismic traces, virtual shot records can be constructed, effectively transforming the original receiving points into new sources and receiving points.

[0004] At present, although some work has involved the discussion of body wave signals in high-speed rail seismic data, our goal is to conduct a more comprehensive and systematic study of the extraction of body wave signals in high-speed rail seismic data. Compared with surface waves, body waves usually have greater penetration depth and are suitable for deeper exploration. In addition, body waves usually contain higher frequency components, which can more finely depict the underground stratum structure. In addition, body waves are very suitable for multi-parameter inversion (e.g., simultaneously estimating P-wave and S-wave velocities, etc.). However, for high-speed rail seismic data, the body waves therein are largely masked by surface waves, which poses a challenge for directly using body waves for reliable underground exploration. In order to utilize high-speed rail seismic data to achieve deeper and more fine-grained underground exploration, it is of great significance to conduct a systematic study of the signal extraction of body waves in high-speed rail seismic data.

[0005] For the extraction of body wave signals in high-speed rail seismic data, how to overcome the influence of surface wave signals on body waves is the key to successfully extracting body wave signals from high-speed rail seismic data in the case that body waves are largely masked by surface wave signals. SUMMARY

[0006] The application aims to provide a high-speed railway seismic data body wave extraction method, which can present the velocity difference and frequency distribution difference of body waves and surface waves in high-speed railway seismic data by transforming the high-speed railway seismic data to the F-K domain, so as to design a reasonable data processing flow to realize the suppression of the influence of surface wave signals on body wave signal extraction in high-speed railway seismic data, and successfully extract relatively high-quality body wave signals from high-speed railway seismic data.

[0007] The technical scheme adopted by the application is a high-speed railway seismic data body wave extraction method, and the specific steps are as follows:

[0008] Step 1, a high-speed seismic source is given and a survey line is laid out, and high-speed seismic data recorded by the survey line are simulated based on a three-dimensional elastic wave wave equation forward modeling for further processing and analysis;

[0009] Step 2, high-speed seismic data in a t' time period meeting the stable phase condition are selected from the high-speed seismic data recorded by the survey line obtained in step 1;

[0010] Step 3, F-K filtering is performed on the high-speed seismic data meeting the stable phase condition obtained in step 2 to obtain preprocessed high-speed seismic data;

[0011] Step 4, virtual shot records are obtained;

[0012] Step 5, band-pass filtering is performed on the virtual shot records obtained in step 4 to obtain filtered virtual shot records;

[0013] Step 6, the virtual shot records obtained by N high-speed railways are stacked to obtain stacked virtual shot records.

[0014] The application is further characterized in that:

[0015] In step 1, the survey line is composed of g geophones;

[0016] In step 1, the expression of the high-speed seismic data recorded by the survey line in a t time period based on the three-dimensional elastic wave wave equation forward modeling is wherein u x (x i ,x s ,t) is the x component high-speed seismic data recorded by the i th geophone at the coordinate position x s at the time t when the high-speed seismic source is excited at x i ; u y (x i ,x s ,t) is the y component high-speed seismic data recorded by the i th geophone at the coordinate position x s at the time t when the high-speed seismic source is excited at x i ; and 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 epicenter of the high-speed rail 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-iron seismic data of the line record is obtained by solving the differential equation shown in (2) The essence is a matrix composed of high-iron seismic data recorded by g detectors.

[0030] Step 2: Select the high-iron seismic data in the t' time period that meets the stable phase condition from the high-iron seismic data of the line record obtained in step 1 Ensure the effective superposition of signals in the interference process, t' is a subset of t; wherein, is the high-iron seismic data in the t' time period that meets the stable phase condition corresponding to the i-th detector at the coordinate position x s when the high-iron source is excited at x i ; u' x (x i ,x s ,t′) is the x component high-iron seismic data in the t' time period that meets the stable phase condition corresponding to the i-th detector at the coordinate position x s when the high-iron source is excited at x i ; u' y (x i ,x s ,t′) is the y component high-iron seismic data in the t' time period that meets the stable phase condition corresponding to the i-th detector at the coordinate position x s when the high-iron source is excited at x i ; u' z (x i ,x s ,t′) is the z component high-iron seismic data in the t' time period that meets the stable phase condition corresponding to the i-th detector at the coordinate position x s when the high-iron source is excited at x i .

[0031] Step 2 is specifically:

[0032] Step 2.1: First, determine the distribution area of the high-iron source that meets the stable phase condition with the line; the stable phase condition means that there needs to be a source or scatterer that is collinear with the two detectors for the correlation function to converge to the Green's function; when the high-iron source is located in the area on both sides of the 1st detector and the gth detector of the line, the high-iron seismic data of the line record meets the stable phase condition;

[0033] Step 2.2: Then, determine the time period t' when the high-iron source travels in the area on both sides of the 1st detector and the gth detector of the line from the high-iron 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 is as follows:

[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: H 1i (x i Transform the virtual gun 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 obtain the superimposed virtual shot record by superimposing the virtual shot records obtained by the N high-speed rails wherein, is the coordinate position x i is the virtual shot record in the t' time period after superimposition of the virtual shot records obtained by the N high-speed rails corresponding to the i th geophone at the coordinate position x is the x-component virtual shot record in the t' time period after superimposition of the virtual shot records obtained by the N high-speed rails corresponding to the i th geophone at the coordinate position x i is the x-component virtual shot record in the t' time period after superimposition of the virtual shot records obtained by the N high-speed rails corresponding to the i th geophone at the coordinate position x is the y-component virtual shot record in the t' time period after superimposition of the virtual shot records obtained by the N high-speed rails corresponding to the i th geophone at the coordinate position x i is the y-component virtual shot record in the t' time period after superimposition of the virtual shot records obtained by the N high-speed rails corresponding to the i th geophone at the coordinate position x is the z-component virtual shot record in the t' time period after superimposition of the virtual shot records obtained by the N high-speed rails corresponding to the i th geophone at the coordinate position x i is the z-component virtual shot record in the t' time period after superimposition of the virtual shot records obtained by the N high-speed rails corresponding to the i th geophone at the coordinate position x

[0047] Step 6 is specifically:

[0048] Step 6.1: first, adjust the running speed v of the high-speed rail in step 1 (ensure that the values of the plurality of running speeds v are different; according to the actual running speed of the high-speed rail, v can be taken between 55 m / s and 97 m / s) to obtain N groups of high-speed rail seismic data; then, sequentially implement steps 2 to 5 on the N groups of high-speed rail seismic data to obtain the corresponding virtual shot records; here, for the convenience of representation, the N groups of high-speed rail seismic data sequentially implement steps 2 to 5 to obtain the corresponding filtered virtual shot records are respectively denoted as

[0049] Step 6.2: then, superimpose the N groups of filtered virtual shot records obtained in step 6.1 to obtain the preliminary superimposed seismic virtual shot record The specific mathematical expression is as follows:

[0050]

[0051] The beneficial effects of the present application are:

[0052] (1) The method of the present application: first, starting from the linear model, the high-speed rail seismic data is simulated by three-dimensional elastic wave equation forward modeling. Secondly, the seismic data meeting the stable phase condition is selected from the original high-speed rail seismic data to ensure the effective superposition of the signal in the interference process. Thirdly, the selected high-speed rail seismic data meeting the stable phase condition is subjected to F-K filtering to filter out part of the high-frequency surface wave and reduce the influence of the high-frequency surface wave on the extraction of body wave. Then, by normalizing the cross-correlation, the interference process of the high-speed rail seismic data recorded by different geophones is realized to reduce the influence of the correlation of the high-speed rail source on the interference result. In addition, the virtual shot record is subjected to band-pass filtering to further reduce the influence of the low-frequency surface wave on the body wave signal. Finally, the virtual shot records corresponding to different high-speed rail seismic events are stacked to further improve the quality of the body wave signal.

[0053] (2) The method of the present application can significantly reduce the influence of strong energy surface wave on the extraction of body wave from high-speed rail seismic data. The reason why the method has the above advantages is that: first, the selection of seismic data meeting the stable phase condition ensures the effective superposition of the signal in the interference process. Secondly, in the F-K domain, the high-speed rail seismic data is analyzed, and the characteristic difference between the body wave and the surface wave in the high-speed rail seismic data is highlighted. According to the characteristic difference between the surface wave and the body wave signal, the surface wave in the high-speed rail seismic data is effectively filtered and suppressed, so that the body wave signal with high quality can be extracted from the high-speed rail seismic data. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 is a flow chart of the method of the present application;

[0055] Figure 2 is the mechanism of the earthquake wave generated by the high-speed rail running on the viaduct;

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

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

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

[0059] Fig. 6(a) is the x-component high-speed rail seismic data;

[0060] Fig. 6(b) is the y-component high-speed rail seismic data;

[0061] Fig. 6(c) is the z-component high-speed rail seismic data;

[0062] Fig. 7(a) is the F-K spectrum of the x-component high-speed rail seismic data;

[0063] Fig. 7(b) is the F-K spectrum of the y-component high-speed rail seismic data;

[0064] Figure 7(c) is the F-K spectrum of the x-component high-iron seismic data;

[0065] Figure 8(a) is the F-K spectrum of the x-component high-iron seismic data that meets the stable phase condition;

[0066] Figure 8(b) is the F-K spectrum of the y-component high-iron seismic data that meets the stable phase condition;

[0067] Figure 8(c) is the F-K spectrum of the z-component high-iron seismic data that meets the stable phase condition;

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

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

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

[0071] Figure 10(a) is the x-component virtual shot record finally obtained by the method of the present application;

[0072] Figure 10(b) is the y-component virtual shot record finally obtained by the method of the present application;

[0073] Figure 10(c) is the z-component virtual shot record finally obtained by the method of the present application; DETAILED DESCRIPTION

[0074] The present application will be described in detail below in conjunction with the drawings and specific embodiments.

[0075] The present application provides a high-iron seismic data body wave extraction method, as shown in the accompanying drawings, the specific steps are as follows: Figure 1

[0076] Step 1, given a high-iron seismic source and layout of the survey line (wherein the survey line is composed of g geophones), based on the three-dimensional elastic wave equation forward modeling of the high-iron seismic data recorded by the survey line for further processing and analysis;

[0077] In step 1, the expression of the high-iron seismic data recorded by the survey line in the t time period based on the three-dimensional elastic wave equation forward modeling is Wherein, u x (x i ,x s ,t) is the x-component high-iron seismic data recorded by the i-th geophone at the coordinate position x s when the high-iron seismic source is excited at x i ; u y (x i ,x s ,t) is the x-component high-iron seismic data recorded by the i-th geophone at the coordinate position x s when the high-iron seismic source is excited at x​i the y-component high-speed train seismic data recorded by the i-th geophone at the coordinate position x z (x i ,x s ,t) is the z-component high-speed train seismic data recorded by the i-th geophone at the coordinate position x s when the high-speed train source is excited at the coordinate position x i ; for convenience of representation, let (x s ) (i.e. the high-speed train seismic data recorded by the i-th geophone in the t time period when the high-speed train source is excited at the coordinate position x T ) ; where [·] q represents the transpose of a vector; then the high-speed train seismic data recorded by the survey line is simplified as In the following expressions, instead of , the following is used to represent the high-speed train seismic data recorded by the survey line in the t time period;

[0078] Step 1 is specifically as follows:

[0079] Step 1.1: Given the high-speed train source, specifically, when a high-speed train passes under a viaduct, the high-speed train source is represented as:

[0080]

[0081] In the formula, Q represents the total number of wheel pairs contained in a high-speed train; J represents the number of piers of the viaduct; represents the loading function of the q-th wheel pair of the high-speed train, which is L q away from the 1st pier, to the t time period corresponding to the j-th pier which is K j away from the 1st pier, when the high-speed train travels at a speed v;

[0082] Step 1.2: Layout of the survey line, as shown in Figure 2 , specifically, a survey line composed of g geophones is laid on the ground under the viaduct, and the survey line is parallel to the viaduct; the coordinate positions of the 1st geophone, the 2nd geophone, …, the gth geophone are x g 1, x x 2, …, x s g respectively.

[0083] Step 1.3: Based on the three-dimensional elastic wave equation, the high-speed train seismic data recorded by the survey line is forward modeled The specific form of the three-dimensional elastic wave equation is as follows:

[0084]

[0085] In the formula, u x (x s ,x sx-component high-speed seismic data in the t time period corresponding to the x-coordinate position when the high-speed seismic source is excited at x y (x,x s ,t) is the y-component high-speed seismic data in the t time period corresponding to the x-coordinate position when the high-speed seismic source is excited at x s (x,x z ,t) is the z-component high-speed seismic data in the t time period corresponding to the x-coordinate position when the high-speed seismic source is excited at x s (x,x s ,t) is the z-component high-speed seismic data in the t time period corresponding to the x-coordinate position when the high-speed seismic source is excited at x xx (x,xs,t) is the x-direction normal stress component in the t time period corresponding to the x-coordinate position when the high-speed seismic source is excited at x s (x,x yy ,t) is the y-direction normal stress component in the t time period corresponding to the x-coordinate position when the high-speed seismic source is excited at x s (x,x s ,t) is the y-direction normal stress component in the t time period corresponding to the x-coordinate position when the high-speed seismic source is excited at x zz (x,x s ,t) is the z-direction normal stress component in the t time period corresponding to the x-coordinate position when the high-speed seismic source is excited at x s (x,x xy ,t) is the z-direction normal stress component in the t time period corresponding to the x-coordinate position when the high-speed seismic source is excited at x s (x,x s ,t) is the shear stress component in the t time period corresponding to the x-direction and the y-direction of the x-coordinate position when the high-speed seismic source is excited at x xz (x,x s ,t) is the shear stress component in the t time period corresponding to the x-direction and the z-direction of the x-coordinate position when the high-speed seismic source is excited at x s (x,x yz ,t) is the shear stress component in the t time period corresponding to the y-direction and the z-direction of the x-coordinate position when the high-speed seismic source is excited at x s (x,x s ,t) is the shear stress component in the t time period corresponding to the y-direction and the z-direction of the x-coordinate position when the high-speed seismic source is excited at x P λ and μ are Lame parameters related to the longitudinal wave velocity v S and the transverse wave velocity v free , and the expressions of λ and μ are as follows:

[0086]

[0087] In addition, in order to simulate the surface wave in the high-speed seismic data, a free surface boundary is used in the forward simulation, and the specific implementation of the free surface boundary is as follows:

[0088]

[0089] wherein, ρfree 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 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 seismic data recorded by the shown survey line meets the stable phase condition;

[0093] Step 2.2: Then, the time period t' when the high-speed seismic source travels in the area located on both sides of the 1st geophone and the gth geophone of the shown survey line is determined (t' can be calculated according to the departure time, departure position and running speed of the high-speed seismic source), and the high-speed seismic data in the t' time period is intercepted from the high-speed seismic data Figure 2 to obtain the high-speed seismic data meeting the stable phase condition

[0094] Step 3, the high-speed seismic data meeting the stable phase condition obtained in step 2 is subjected to F-K filtering to filter out the high-frequency surface wave signals in to obtain the preprocessed high-speed seismic data wherein, is the preprocessed high-speed seismic data corresponding to the i th geophone at the coordinate position x s when the high-speed seismic source is excited at x i ; u" x (x i ,x s ,t′) is the x-component high-speed seismic data in the t' time period after preprocessing corresponding to the i th geophone at the coordinate position x s when the high-speed seismic source is excited at x i ; u" y (x i ,x s ,t′) is the y-component high-speed seismic data in the t' time period after preprocessing corresponding to the i th geophone at the coordinate position x s when the high-speed seismic source is excited at x i ; u" z (x i ,x s ,t′) is the z-component high-speed seismic data in the t' time period after preprocessing corresponding to the i th geophone at the coordinate position x s when the high-speed seismic source is excited at x i ;

[0095] Step 3 is specifically: Step 3.1: First, the high-speed seismic data meeting the stable phase condition obtained in step 2 is transformed into the F-K domain to clearly show the velocity difference and frequency distribution difference between the surface wave and the body wave in , and the filtering range v1-v2 of the F-K filter is determined; wherein v1 is the lower limit of the F-K filter, which is generally slightly higher than the velocity of the surface wave in but lower than the velocity of the body wave in ; v2 is the upper limit of the F-K filter, which is generally slightly lower than the velocity of the body wave in ;​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: 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 4A three-dimensional linear model (elastic medium containing P and S waves) is shown. The velocity of the three-dimensional linear model increases linearly with depth, the length of x and y directions are both 1.6 km, the depth of z direction is 0.4 km, and the spatial sampling interval of all directions is 4 m. During the implementation, the observation system is as shown in Figure 5 As shown, the high-speed train runs along the positive direction of the x axis on the viaduct on the surface of the linear model from point O, and the survey line composed of 300 geophones is close to and parallel to the viaduct. The length of the survey line is 1200 m, and the first geophone is located at (400 m, 40 m, 0 m) and is arranged along the positive direction of the x axis. The distance between adjacent geophones in the survey line is 4 m. In the specific implementation process, a high-speed train with 16 carriages is used, each carriage is 25 m long, each carriage has 4 pairs of wheels, and the distance from each pair of wheels to the front end of the carriage is 4 m, 6.5 m, 18.5 m, and 21 m, respectively. A Ricker wavelet with a peak frequency of 15 Hz is used as the loading function of each group of wheels (corresponding to f in formula (1)). wherein the running speed v of the high-speed train is 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 synthetic high-speed train source is obtained. The observation time is 30 s, and the time sampling interval is 1 ms.

[0110] The x-component, y-component, and z-component high-speed train seismic data obtained by step 1 of the method proposed in the application when the running speed of the high-speed train is 83 m / s are shown in FIGS. 6(a), 6(b), and 6(c), respectively. The corresponding F-K spectra of FIGS. 6(a), 6(b), and 6(c) are shown in FIGS. 7(a), 7(b), and 7(c), respectively. It can be seen that there are both surface waves and body waves in the high-speed train seismic data. The seismic data satisfying the stable phase condition obtained by step 2 of the method proposed in the application is shown in FIGS. 8(a), 8(b), and 8(c), and the F-K spectra corresponding to the seismic data satisfying the stable phase condition are shown in FIGS. 9(a), 9(b), and 9(c), respectively. It can be seen that the energy of the interference signal in the seismic data satisfying the stable phase condition is reduced, and the energy of the surface wave and body wave signals is relatively enhanced. The x-component, y-component, and z-component virtual shot records obtained by steps 3 to 5 of the method proposed in the application are shown in FIGS. 9(a), 9(b), and 9(c), respectively. It can be seen that there are partial body wave signals, such as refracted P waves, direct P waves, and refracted S waves, in the x-component and z-component virtual shot records. The x-component, y-component, and z-component virtual shot records containing high-quality body wave signals obtained by step 6 of the method proposed in the application are shown in FIGS. 10(a), 10(b), and 10(c), respectively. It can be seen that the relatively high-quality body wave signals are successfully extracted from the high-speed train seismic data by steps 1 to 6 of the method proposed in the application, which proves the effectiveness of the method proposed in the application.

[0111] Example 2

[0112] A high-speed rail seismic data body wave extraction method, the specific steps are as follows:

[0113] Step 1, given a high-speed rail source and layout the measuring line, based on the three-dimensional elastic wave equation forward modeling of the high-speed rail seismic data recorded by the measuring line for further processing and analysis; Step 2, select the high-speed rail seismic data in the t' time period that meets the stable phase condition from the high-speed rail seismic data recorded by the measuring line obtained in step 1; Step 3, F-K filtering is performed on the high-speed rail seismic data obtained in step 2 that meets the stable phase condition, to obtain the preprocessed high-speed rail seismic data; Step 4, obtain the virtual shot record; Step 5, band-pass filtering is performed on the virtual shot record obtained in step 4 to obtain the filtered virtual shot record; Step 6, stack the virtual shot records obtained by N high-speed rails to obtain the stacked virtual shot record.

[0114] Example 3

[0115] The difference from example 2 is that in step 1, the measuring line is composed of g geophones;

[0116] Example 4

[0117] The difference from example 3 is that step 1 is specifically: step 1.1: given a high-speed rail source; step 1.2: layout the measuring line; step 1.3: based on the three-dimensional elastic wave equation forward modeling of the high-speed rail seismic data recorded by the measuring line;

[0118] Example 5

[0119] The difference from example 4 is that step 2 is specifically: step 2.1: first, determine the distribution area of the high-speed rail source that meets the stable phase condition with the measuring line; step 2.2: then, determine the time period t' when the first geophone and the gth geophone on both sides of the measuring line in the driving process of the high-speed rail source, and obtain the high-speed rail seismic data that meets the stable phase condition by cutting the data in the t' time period from the high-speed rail seismic data.

[0120] Example 6

[0121] The difference from example 5 is that step 3 is specifically: step 3.1: first transform the high-speed rail seismic data obtained in step 2 that meets the stable phase condition to the F-K domain to clearly show the velocity difference and frequency distribution difference between the surface wave and the body wave; step 3.2: then, according to the velocity difference between the surface wave and the body wave in the high-speed rail seismic data obtained in step 2 that meets the stable phase condition, perform F-K filtering to filter out the high-frequency surface wave signal in the middle, 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 that meet the steady-phase condition from the survey line records obtained in Step 1. High-speed rail earthquake data within the specified time period; Step 2 involves obtaining high-speed rail seismic data from the survey lines recorded in Step 1. Select those that satisfy the stable phase condition. High-speed rail earthquake data within a time period To ensure effective signal superposition during the interference process, yes t A subset of; in which, That is, the epicenter of the high-speed rail is in When the point is activated, the first i Recorded by each detector t High-speed rail earthquake data within the specified time period; i =1,2,…,g; g is the number of detectors; For the high-speed rail epicenter in When excited at coordinate position The first i Each detector corresponds to a condition that satisfies the steady-state condition. High-speed rail earthquake data within the specified time period; For the high-speed rail epicenter in When excited at coordinate position The first i Each detector corresponds to a condition that satisfies the steady-state condition. within the time period x High-speed rail seismic data; For the high-speed rail epicenter in When excited at coordinate position The first i Each detector corresponds to a condition that satisfies the steady-state condition. within the time period y High-speed rail seismic data; For the high-speed rail epicenter in When excited at coordinate position The first i Each detector corresponds to a condition that satisfies the steady-state condition. within the time period z High-speed rail seismic data; 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 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. From high-speed rail earthquake data Extracting from the middle Data within a specific time period was used to obtain high-speed rail seismic data that met the steady-phase condition. ; 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 survey line records are simulated based on the forward modeling of the three-dimensional elastic wave equation. t The expression for high-speed rail seismic data within a time period is: ,in, The epicenter of the high-speed rail earthquake was located in When excited at coordinate position The first i Recorded by each detector t within the time period x High-speed rail seismic data; The epicenter of the high-speed rail earthquake was located in When excited at coordinate position The first i Recorded by each detector t within the time period y High-speed rail seismic data; For the high-speed rail epicenter in When excited at coordinate position The first i Recorded by each detector t within the time period z High-speed rail seismic data in components; for ease of representation, let's call them... That is, the epicenter of the high-speed rail is in When the point is activated, the first i Recorded by each detector t High-speed rail seismic data within the specified time period; among which, Let's denote the transpose of a vector; then the high-speed rail seismic data recorded by the survey line simplifies to... ; in the following statements, the following expressions shall be used. replace Indicates the survey line record t Earthquake data for high-speed rail within a specific time period.

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: （1） In the formula, Q This indicates the total number of wheelsets in a high-speed train. J Indicates the number of piers of the viaduct; Indicates that high-speed rail is based on speed v When driving, the distance to the first bridge pier The q The distance between the wheels and the first pier The j The corresponding bridge pier t Load functions within a time period; Step 1.2: Laying out the survey line, specifically: [The text abruptly ends here, likely due to an incomplete sentence or a formatting error.] g A survey line consisting of several detectors is laid out on the ground beneath the viaduct, parallel to the viaduct. The coordinates of the first, second, ..., g-th detectors are as follows: , ,…, ; 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: （2） In the formula, For the high-speed rail epicenter in When the site is stimulated, The corresponding coordinate position t within the time period x High-speed rail seismic data; For the high-speed rail epicenter in When the site is stimulated, The corresponding coordinate position t within the time period y High-speed rail seismic data; For the high-speed rail epicenter in When the site is stimulated, The corresponding coordinate position t within the time period z High-speed rail seismic data; The density of the underground medium; For the high-speed rail epicenter in When the site is stimulated, The corresponding coordinate position t within the time period x Directional normal stress component; For the high-speed rail epicenter in When the site is stimulated, The corresponding coordinate position t within the time period y Directional normal stress component; For the high-speed rail epicenter in When the site is stimulated, The corresponding coordinate position t within the time period z Directional normal stress component; For the high-speed rail epicenter in When the site is stimulated, The corresponding coordinate position x direction and y Direction t Shear stress components over a time period; For the high-speed rail epicenter in When the site is stimulated, The corresponding coordinate position x direction and z Direction t Shear stress components over a time period; For the high-speed rail epicenter in When the site is stimulated, The corresponding coordinate position y Direction and z-direction t Shear stress components over a time period; and To match the longitudinal wave velocity and transverse wave velocity The relevant Lamé parameters, and The expression is as follows: （3） 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: （4） in, Density at the boundary of a free surface ; Represents the boundary of a free surface ; Represents the boundary of a free surface ; Represents the boundary of a free surface z Directional normal stress components ; 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 1, 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, For the high-speed rail epicenter in When excited at coordinate position The first i Preprocessed data corresponding to each detector High-speed rail earthquake data within the specified time period; For the high-speed rail epicenter in When excited at coordinate position The first i Preprocessed data corresponding to each detector within the time period x High-speed rail seismic data; For the high-speed rail epicenter in When excited at coordinate position The first i Preprocessed data corresponding to each detector within the time period y High-speed rail seismic data; For the high-speed rail epicenter in When excited at coordinate position The first i Preprocessed data corresponding to each detector within the time period z High-speed rail seismic data; 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 are used to determine the filtering range of the FK filter. v 1~ v 2; among which, v 1 represents the lower limit of the FK filter. v 1 higher than The velocity of mid-surface waves is lower than The velocity of mid-body waves; v 2 is the upper limit of the FK filter. v 2 higher than The velocity of mid-body 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. .

5. The method for extracting volume waves from high-speed rail seismic data according to claim 1, 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, For coordinate position The preprocessed high-speed rail seismic data corresponding to the first geophone at the location and the coordinate position The first i The normalized cross-correlation of preprocessed high-speed rail seismic data corresponding to each detector was obtained by calculating the normalized cross-correlation. Records of false shots within a given time period; For coordinate position The preprocessed high-speed rail seismic data corresponding to the first geophone at the location and the coordinate position The first i The normalized cross-correlation of preprocessed high-speed rail seismic data corresponding to each detector was obtained by calculating the normalized cross-correlation. within the time period x Quantity-based false recording; For coordinate position The preprocessed high-speed rail seismic data corresponding to the first geophone at the location and the coordinate position The first i The normalized cross-correlation of preprocessed high-speed rail seismic data corresponding to each detector was obtained by calculating the normalized cross-correlation. within the time period y Quantity-based false recording; For coordinate position The preprocessed high-speed rail seismic data corresponding to the first geophone at the location and the coordinate position The first i The normalized cross-correlation of preprocessed high-speed rail seismic data corresponding to each detector was obtained by calculating the normalized cross-correlation. within the time period z Quantity-based false recording; Step 4 is as follows: Step 4.1: First, calculate the high-speed rail seismic source obtained in Step 3. When excited at coordinate position The first i Preprocessed seismic data corresponding to each detector Fourier transform ;in, i =1, 2, …,g; Indicates angular frequency; Step 4.2: In the Fourier domain, calculate the first... i The preprocessed seismic data corresponding to each detector are cross-correlated with the normalized reference trace, where, i =1, 2, …, g, the normalized cross-correlation expression is as follows: （5） in, This serves as a damping factor to ensure the stability of the relevant results; For the high-speed rail epicenter in When excited at coordinate position The preprocessed seismic data corresponding to the first detector at the location Fourier transform The complex conjugate; Step 4.3: [The text appears to be incomplete and contains several grammatical errors. A more accurate translation would require From the Fourier domain to the time domain, where... i =1, 2, …, g, obtain the virtual cannon record. Finally, the first detector, the second detector, ..., the... i The virtual shot records corresponding to the g-th detector, ..., g-th detector are composed of... .

6. The method for extracting volume waves from high-speed rail seismic data according to claim 5, 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. This further suppresses surface wave signals; among which, For coordinate position The preprocessed high-speed rail seismic data corresponding to the first geophone at the location and the coordinate position The first i The preprocessed high-speed rail seismic data corresponding to each detector was obtained after calculating normalized cross-correlation and performing bandpass filtering. Records of false shots within a given time period; For coordinate position The preprocessed high-speed rail seismic data corresponding to the first geophone at the location and the coordinate position The first i The preprocessed high-speed rail seismic data corresponding to each detector was obtained after calculating normalized cross-correlation and performing bandpass filtering. within the time period x Virtual shot record after component filtering; For coordinate position The preprocessed high-speed rail seismic data corresponding to the first geophone at the location and the coordinate position The first i The preprocessed high-speed rail seismic data corresponding to each detector was obtained after calculating normalized cross-correlation and performing bandpass filtering. within the time period y Virtual shot record after component filtering; For coordinate position The preprocessed high-speed rail seismic data corresponding to the first geophone at the location and the coordinate position The first i The preprocessed high-speed rail seismic data corresponding to each detector was obtained after calculating normalized cross-correlation and performing bandpass filtering. within the time period z Virtual shot records after component filtering.

7. The method for extracting volume waves from high-speed rail seismic data according to claim 6, 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, coordinate position The first i The superposition of virtual shot records obtained from N high-speed trains corresponding to each detector Records of false shots within a given time period; coordinate position The first i The results of N high-speed trains corresponding to one detector x After superposition of component virtual shot records within the time period x Quantity-based false recording; coordinate position The first i The results of N high-speed trains corresponding to one detector y After superposition of component virtual shot records within the time period y Quantity-based false recording; coordinate position The first i The results of N high-speed trains corresponding to one detector z After superposition of component virtual shot records within the time period z The data is recorded as a fictitious sample.

8. The method for extracting volume waves from high-speed rail seismic data according to claim 7, characterized in that, Step 6 specifically involves: Step 6.1: First, adjust the operating speed of the high-speed train from Step 1. N sets of high-speed rail seismic data are obtained; then, steps 2 to 5 are sequentially performed 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: （6）。

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