A high-density seismic surface wave detection method and apparatus

Abstract

The application relates to a high-density seismic surface wave detection method and device, which comprises the following steps: collecting signals for multiple times of coverage; arranging seismic signals obtained along a survey line to obtain a common midpoint signal pair arrangement, wherein all signal pairs in the common midpoint signal pair arrangement have the same center coordinates of the connecting lines of the receiving points; performing FFT forward and inverse transformation on each signal pair in the common midpoint signal pair arrangement to obtain a time variable cross-correlation curve of each frequency of the signal pair; then performing coordinate transformation on the time variable cross-correlation curve of each frequency of the signal pair according to the distance between the common midpoint signal pairs to obtain a velocity variable cross-correlation curve corresponding to each frequency; and calculating the surface wave velocity according to the sum of the velocity variable cross-correlation curves corresponding to all frequencies to obtain the surface wave dispersion curve of the center point position of the common midpoint signal pair arrangement. The application has the advantages of convenient and fast calculation, high precision, high density and the like, and greatly improves the detection efficiency.

Description

Technical Field

[0001] This invention relates to the field of seismic surface wave detection and exploration technology, and in particular to a high-density seismic surface wave detection method and apparatus. Background Technology

[0002] With the rapid development of my country's infrastructure construction, surface wave exploration now occupies an important position in engineering geophysical methods. The dispersion curves calculated from the measured surface wave signals can directly stratify the site and further calculate the shear wave velocity (Vs) of each layer, leading to numerous applications in engineering and geology. Furthermore, the surface wave method has very relaxed requirements on the test site and instruments used; signals from seismic arrays received by multichannel seismographs to two-channel signals received by virtual instruments can all be used for surface wave dispersion curve calculation and interpretation. However, while surface wave applications possess many advantages, a key challenge remains: how to achieve high-precision, high-density, and high-efficiency surface wave detection and exploration. Summary of the Invention

[0003] The purpose of this invention is to provide a high-density seismic surface wave detection method and apparatus to solve the problems existing in the prior art.

[0004] In a first aspect, the present invention provides a high-density seismic surface wave detection method, comprising:

[0005] Perform multiple coverage signal acquisitions;

[0006] The seismic signals acquired along the survey line are arranged to obtain a common center point signal pair arrangement, wherein the center coordinates of the line connecting the receiving points of all signal pairs in the common center point signal pair arrangement are the same;

[0007] For each signal pair in the common center point signal pair arrangement, perform forward and inverse FFT transformations to obtain the time-variable cross-correlation curves of each frequency of the signal pair. Then, based on the distance between the common center point signal pairs, perform coordinate transformations on the time-variable cross-correlation curves of each frequency of the signal pair to obtain the velocity-variable cross-correlation curves corresponding to each frequency. Finally, calculate the surface wave velocity based on the sum of the velocity-variable cross-correlation curves corresponding to all frequencies, thereby solving for the surface wave dispersion curve at the center point of the common center point signal pair arrangement.

[0008] Furthermore, the multiple coverage signal acquisitions are performed using a wireless distributed seismograph, which includes a signal acquisition unit, a detector, and a computer.

[0009] The signal acquisition unit includes three or more acquisition units, each with four or more independent channels, and the computer serves as the main control platform for the wireless distributed seismograph.

[0010] The collectors are numbered independently in sequence. When each collector moves forward, it automatically generates a common shot point arrangement signal based on the received signal according to the collector number. Based on the record of multiple coverage of common shot point signals, it extracts and arranges common center point signal pairs. The common center point is located at the center of two adjacent detector points, and the point spacing is equal to the channel spacing.

[0011] The detector is a broadband accelerometer or other type of sensor. It uses the FFT bandpass filtering method, employs the low-frequency components of the signal for surface wave detection, and uses the high-frequency components of the signal for reflection wave exploration.

[0012] Furthermore, in each signal pair of the common center point signal pair arrangement, the two signals have the same excitation point, and each arrangement consists of multiple signal pairs, among which two or more signal pairs have different measurement point spacings.

[0013] Further, performing forward and inverse FFT transformations on each signal pair in the common center point signal pair arrangement includes:

[0014] Spectrum refinement is achieved by adding zeros to the signal data to increase the signal length, thereby improving analysis accuracy.

[0015] The computational accuracy is improved by introducing a window function into the formula and then performing an inverse FFT transform on each frequency signal.

[0016] Further, the step of performing coordinate transformation on the time-variable cross-correlation curves of each frequency of the signal pair to obtain the velocity-variable cross-correlation curves corresponding to each frequency includes:

[0017] The surface wave signal travels between two measurement points and corresponds to a certain peak on the cross-correlation curve of the time variable. When the distance between the two measurement points is less than one wavelength, it corresponds to the first peak. After coordinate transformation, the surface wave velocity also corresponds to a certain peak on the cross-correlation curve of the velocity variable for each frequency.

[0018] Furthermore, the step of then determining the surface wave velocity based on the sum of the cross-correlation curves of the velocity variables corresponding to all frequencies includes:

[0019] For all common center point signals at a certain frequency, sum the corresponding velocity variable cross-correlation curves. At the surface wave velocity point, sum the corresponding peaks on each velocity variable cross-correlation curve to obtain the maximum value. The velocity value corresponding to the maximum value on the obtained cross-correlation summation curve is the surface wave velocity.

[0020] The velocity value corresponding to the maximum value on the cross-correlation summation curve obtained for each frequency is also the surface wave velocity of the signal at that frequency. The surface wave velocity corresponding to all frequencies can be obtained by summing the cross-correlation curves of the velocity variables corresponding to all frequencies.

[0021] Furthermore, the step of solving for the surface wave dispersion curve of the common center point signal pair at the center point of the arrangement includes:

[0022] Based on the effective frequency range and velocity variation interval of the surface wave signal, a planar coordinate system is established with the X and Y axes representing velocity and frequency, respectively. The cross-correlation summation curves obtained for each frequency are plotted sequentially in the plane. Then, the velocity values ​​corresponding to the maximum values ​​on the cross-correlation summation curves are connected sequentially according to the frequency variation from small to large, resulting in a frequency-velocity variation curve, which is the surface wave dispersion curve of the center point of the common center point signal pair arrangement.

[0023] Alternatively, the cross-correlation summation curve values ​​obtained for each frequency in the planar plot can be represented by different colors, with larger values ​​resulting in darker colors, thus obtaining a surface wave cross-correlation summation curve chromatogram. Based on the line connecting each frequency with the velocity point corresponding to the darkest color in the surface wave cross-correlation summation curve chromatogram, the surface wave frequency versus velocity variation curve can be obtained, which is the surface wave dispersion curve of the center point of the common center point signal pair arrangement.

[0024] In a second aspect, the present invention provides a high-density seismic surface wave detection device, comprising:

[0025] The signal acquisition module is used to acquire signals over multiple coverages.

[0026] The signal arrangement module is used to arrange the seismic signals acquired along the survey line to obtain a common center point signal pair arrangement, wherein the center coordinates of the line connecting the receiving points of all signal pairs in the common center point signal pair arrangement are the same.

[0027] The surface wave solution module performs forward and inverse FFT transformations on each signal pair in the common center point signal pair arrangement to obtain the time-variable cross-correlation curves of each frequency of the signal pair. Then, based on the distance between the common center point signal pairs, it performs coordinate transformation on the time-variable cross-correlation curves of each frequency of the signal pair to obtain the velocity-variable cross-correlation curves corresponding to each frequency. Finally, it calculates the surface wave velocity based on the sum of the velocity-variable cross-correlation curves corresponding to all frequencies, thereby solving for the surface wave dispersion curve at the center point of the common center point signal pair arrangement.

[0028] As can be seen from the above technical solution, the high-density seismic surface wave detection method and device provided by this invention acquires a very dense array of common midpoint signal pairs, with the number of signals at each common midpoint far exceeding the number of signals at the common shot points. A high-precision surface wave dispersion curve can be calculated for each common midpoint signal pair. This method offers advantages such as convenient and fast dispersion curve calculation, high accuracy, and high-density distribution, greatly improving detection efficiency. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a flowchart of a high-density seismic surface wave detection method according to an embodiment of the present invention;

[0031] Figure 2 This is a schematic diagram of the operation of a data acquisition unit (4 channels) according to an embodiment of the present invention;

[0032] Figure 3 This is a schematic diagram of three data acquisition units (12 channels) and a conventional surface wave according to an embodiment of the present invention;

[0033] Figure 4 This is a schematic diagram of a high-density surface wave using three data acquisition units (12 channels) according to an embodiment of the present invention;

[0034] Figure 5 This is a schematic diagram of CMC signal acquisition according to an embodiment of the present invention;

[0035] Figure 6 This is a flowchart of the calculation of dispersion curve of measured CMC signal according to an embodiment of the present invention;

[0036] Figure 7 This is a schematic diagram of the structure of a high-density seismic surface wave detection device according to an embodiment of the present invention. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] When seismic waves excited by a hammer or other device propagate through underground space, they generate a special but common wave, called a "Rayleigh surface wave" or "rolling wave," along the Earth's surface (a special free surface). This wave is generated due to the interference of P-waves and SV-waves, and is found only at the Earth's surface. Commonly referred to as a "surface wave," Rayleigh surface waves propagate outward from the seismic source, with the vibration of surface wave particles exhibiting both vertical and horizontal components. The trajectory of this vibration is a counter-clockwise rotating ellipse at the Earth's surface. When a low-velocity overburden or layered medium exists at the surface, surface waves exhibit dispersion, meaning their velocity changes with frequency. The wave velocity curves corresponding to different frequency signals are called dispersion curves, and their determination is a crucial component of surface wave exploration. In surface wave exploration, half the signal wavelength is generally used as the detection depth. Based on the wavelength calculation formula (λ = V / f), the surface wave dispersion curve (fV) is obtained. R This can be converted into the depth wave velocity variation curve (HV) required for engineering. R ).

[0039] The early two-channel phase difference method was simple and easy to implement, requiring fewer detectors. However, when calculating the phase difference, it was necessary to expand the folded phase (φ = 2nπ + Δφ). When expanding the folded phase, the value of n in the formula could not be directly calculated and determined. It was necessary to judge the value of n and the velocity to be obtained based on experience, which had certain limitations.

[0040] Currently, the most commonly used methods for calculating dispersion curves include FK and τ-P methods (based on multi-channel arrangement of signals from common shot points). These methods eliminate the problem of folded phase difference that the phase difference method cannot solve, and are widely used in engineering. However, due to the limitations of the methods themselves (the instrument should generally have no fewer than 12 channels), during signal acquisition, only one dispersion curve can be calculated and extracted from the unfolded signal record of each common shot point, directly affecting work efficiency. On the other hand, each dispersion curve obtained is an average reflection of the arrangement area, resulting in poor curve positioning accuracy.

[0041] As the above analysis shows, surface wave detection plays an important role in engineering geological exploration and in-situ testing. On the other hand, due to the limitations of currently commonly used methods, it directly affects work efficiency and the accuracy of results.

[0042] This invention provides a high-density seismic surface wave detection method and apparatus, which can quickly obtain high-precision surface wave dispersion curves and realize high-density surface wave detection and exploration.

[0043] Figure 1 This is a flowchart of a high-density seismic surface wave detection method according to an embodiment of the present invention, with reference to... Figure 1 The high-density seismic surface wave detection method provided in this embodiment of the invention includes:

[0044] Step 110: Perform multiple coverage signal acquisitions;

[0045] Step 120: Arrange the seismic signals acquired along the survey line to obtain a common center point signal pair arrangement, wherein the center coordinates of the line connecting the receiving points of all signal pairs in the common center point signal pair arrangement are the same.

[0046] Step 130: Perform forward and inverse FFT transformations on each signal pair in the common center point signal pair arrangement to obtain the time variable cross-correlation curve of each frequency of the signal pair. Then, based on the distance between the common center point signal pairs, perform coordinate transformation on the time variable cross-correlation curve of each frequency of the signal pair to obtain the velocity variable cross-correlation curve corresponding to each frequency. Then, calculate the surface wave velocity based on the sum of the velocity variable cross-correlation curves corresponding to all frequencies, thereby solving for the surface wave dispersion curve at the center point of the common center point signal pair arrangement.

[0047] In the embodiments of the present invention, it should be noted that the solutions provided by the present invention include:

[0048] S1, such as Figure 2 As shown, multiple coverage signal acquisitions are performed using a wireless distributed seismograph. The instrument system consists of multiple acquisition units, each with four independent channels (or more channels).

[0049] S2. Arrange the seismic signals acquired along the survey line to obtain a common center point signal pair arrangement (CMC). All signals in the CMC arrangement must have the same center coordinates (points) of the line connecting their receiving points.

[0050] S3. Perform forward and inverse FFT transformations on each signal pair (i) in the CMC arrangement to obtain the signal frequency (f) k Cross-correlation curves of time variables Then, based on the distance between CMC signal pairs, a coordinate transformation can be performed on the time variable cross-correlation curve to obtain the velocity variable cross-correlation curve corresponding to each frequency. Then according to Directly calculate each frequency (f) k The corresponding surface wave velocity V R Furthermore, the surface wave dispersion curve (fV) at the center point of the CMC can be solved. R ).

[0051] The aforementioned signal collector features Wi-Fi wireless data transmission capability, which is more efficient compared to conventional wired connection methods that require multiple coverage passes. Figure 3As shown, the multiple coverage signal acquisitions are performed using multiple acquisition devices. After each single-sided or double-sided excitation signal acquisition is completed, the acquisition device at the back of the measurement line is moved to the front of the line. The movement step is the product of the number of acquisition device channels and the channel spacing (dx). Each time the line is moved, the conventional surface wave method calculates a dispersion curve with the center of the line as the measurement point. The distance between the measurement points on the dispersion curve is the movement step. If one acquisition device (4 channels) is moved each time, the distance between the measurement points on the dispersion curve is 4dx; if two acquisition devices are moved each time, the distance between the measurement points is 8dx.

[0052] In the aforementioned Common Center Point (CMC) signal pair arrangement, the two signals in each signal pair must have the same excitation point (i.e., common shot point signal); the center coordinates (point positions) of the lines connecting all signals to their receiving points must be the same, but their excitation points can be different. For example... Figure 4 As shown, the centers of two adjacent detector points are taken sequentially along the survey line as the CMC arrangement center Xc. Then, all CMC signals that meet the conditions are generated into a file, and the dispersion curve at the measurement point Xc (i.e., Xc is a surface wave measurement point) can be calculated based on this. The distance between the dispersion curve measurement points is the channel spacing (dx), which is independent of the moving step distance.

[0053] If one data acquisition unit (4 channels) is moved each time, the density of dispersion curve measurement points is four times that of the conventional method; if two data acquisition units are moved each time, the density of dispersion curve measurement points is eight times that of the conventional method. On the other hand, selecting any surface wave measurement point (j) on the survey line yields 20 signals (10 signal pairs) for its concentric point signal pair, including 2 pairs in the first arrangement, 6 pairs in the second arrangement, and 2 pairs in the third row. That is, except for a few measurement points at both ends of the survey line, the number of signals participating in the calculation is far greater than that of the conventional method (12 common shot point arrangement signals), which can effectively improve the accuracy of surface wave dispersion curve calculation.

[0054] The CMC signal is subjected to FFT forward and inverse transformation, such as... Figure 5 As shown, let x11 / x12 be any common center point signal pair in the CMC arrangement. According to the principles of vibration, the measured signal is composed of multiple frequency signals. Using FFT transformation, the various frequency signals it contains can be separated. Its mathematical expression is as follows:

[0055] X 11 (f)=∫x 11 (t)e -2π·jft dt;X 12 (f)=∫x 12 (t)e -2π·jft dt (1)

[0056] If for a certain frequency signal (f) kAfter performing conjugate multiplication and then inverse FFT, the result is the cross-correlation curve of the time variable corresponding to the frequency signal at the two measurement points, and its mathematical expression is:

[0057]

[0058] In the specific implementation process, spectrum refinement technology is applied, and a window function W(f) is introduced into the above formula. k ), that is, assuming the window width is 2w, its simplest expression is, when (f k -w≤f k ≤f k When +w), W(f) k Setting ) = 1 and all others to zero can achieve a more ideal effect.

[0059] On the other hand, for the x11 / x12 measurement points, a certain frequency signal (f) k The wave equation can be expressed as:

[0060]

[0061]

[0062] Based on the above formulas (3) and (4), the formula for calculating the cross-correlation curve is as follows:

[0063]

[0064]

[0065] Equation (6) above shows that for two periodic signals with zero mean and the same frequency, their cross-correlation function retains information about the angular frequencies and phase difference between the two signals. Furthermore, when τ = Δt1 ± nT (n = 0, 1, 2, ..., when n = 0, τ = Δt1 = τ R ),exist The curve has a maximum value, and its mathematical expression is as follows:

[0066]

[0067] According to equation (7) above, the travel time τ of the surface wave signal between the two measurement points is... R Corresponding to a certain peak on its time-varying cross-correlation curve, when the distance between two measuring points is less than the signal wavelength, τ R This corresponds to the first peak on the curve. When the distance between the two measuring points is greater than the signal wavelength, τ R For a given peak, since the surface wave signal velocity and wavelength are unknown (and need to be determined), the signal travel time cannot be directly obtained from its cross-correlation curve.

[0068] The cross-correlation curve of the time variable mentioned above Perform coordinate transformation (i.e., a certain frequency signal f in the i-th signal pair) k Let the distance between the two measuring points be ΔX. i ,application Cross-correlation curves of time variables The cross-correlation curve of velocity variables can be obtained by performing coordinate transformation. Similarly, if a surface wave CMC at a certain measuring point has N pairs of signals with common center points, then N velocity variable cross-correlation curves can be calculated using the above method. The above analysis shows that the travel time τ of the surface wave signal between the two measurement points is... R Corresponding to a certain peak on the relevant curve, the surface wave velocity after coordinate transformation... Similarly with A certain peak on the curve corresponds to this.

[0069] According to Directly calculate the surface wave velocity V R That is, first apply the formula The cross-correlation curves of N velocity variables are superimposed and summed. Since when v = V R At that time, in each The curve has a maximum value. Therefore, after adding and synthesizing multiple curves, the surface wave velocity V... R The sum of the maximum values ​​of the curves at the points where they coincide still corresponds to the maximum value on the R(v) curve. Therefore, the signal f at a certain frequency can be directly calculated from the maximum value on the R(v) curve. k The corresponding surface wave velocity V R Similarly, the surface wave velocities corresponding to all different frequencies within the effective frequency band of the CMC signal can be obtained, and the surface wave dispersion curve (fV) at the CMC center point can be solved accordingly. R Simultaneously, its chromatographic image can be drawn according to the signal frequency and velocity scanning range, and the surface wave dispersion curve can be solved more intuitively through the chromatographic image.

[0070] The above discussion is based on the assumption f k When the signal is a surface wave, the measured signal spectrum may contain multiple wave components. This issue can be effectively addressed by understanding the characteristics of surface waves. First, based on the effective frequency and velocity variation range of the surface wave, by appropriately selecting the scanning frequency and scanning wave velocity range, the influence of noise and longitudinal wave signals can be effectively overcome. Since the velocity difference between transverse waves and surface waves is very small, it cannot be eliminated by selecting a wave velocity scanning range. However, the energy of transverse waves is much smaller than that of surface waves and can be ignored. By appropriately selecting the scanning frequency (f... k By adjusting the window width and normalizing the obtained correlation energy curve R(v), weak signals can be enhanced, and the surface wave dispersion curve (fV) can be obtained more effectively.R ).

[0071] Specific examples Figure 6 As shown in .a, the CMC array consists of three signal pairs sharing a common center point, with the center point located at Xc = 10.5 m. The coordinates of the measurement points for the three signal pairs are 10 / 11, 9.5 / 11.5, and 7.5 / 13.5, respectively. After performing forward and inverse FFT transformations and coordinate transformations on each signal pair in the CMC array, the chromatographic image can be plotted based on the cross-correlation summation curve R(v) of the velocity variables corresponding to all different frequencies within the effective frequency band of the signal. Figure 6 As shown in Figure .b. The horizontal axis of the figure represents the signal power spectrum and wave velocity scanning range, and the vertical axis represents the frequency scanning range. The color of the chromatographic image is determined according to the R(v) curve (the larger the value in the figure, the darker the color), because the surface wave velocity V... R Corresponding to the maximum value of the curve, the scanning wave velocity corresponding to the darkest color in the image is the surface wave velocity V. R Based on the V corresponding to all scan frequencies in the chromatogram R This allows us to solve for (extract) the surface wave frequency dispersion curve (fV). R ).like Figure 6 As shown in .c, based on the principle of surface wave half-wavelength detection, the surface wave dispersion curve (fV) R This can be converted into the depth wave velocity variation curve (HV) required for engineering. R ).

[0072] Figure 7 This is a schematic diagram of a high-density seismic surface wave detection device provided in an embodiment of the present invention, as shown below. Figure 7 As shown, the high-density seismic surface wave detection device provided in this embodiment of the invention includes:

[0073] Signal acquisition module 710 is used to acquire signals over multiple coverages;

[0074] The signal arrangement module 720 is used to arrange the seismic signals acquired along the survey line to obtain a common center point signal pair arrangement, wherein all signals in the common center point signal pair arrangement have the same center coordinates of the line connecting their receiving points.

[0075] The surface wave solving module 730 is used to perform forward and inverse FFT transformations on each signal pair in the common center point signal pair arrangement to obtain the time variable cross-correlation curve of each frequency of the signal pair. Then, based on the distance between the common center point signal pairs, the time variable cross-correlation curve of each frequency of the signal pair is transformed to obtain the velocity variable cross-correlation curve corresponding to each frequency. Then, the surface wave velocity is calculated based on the sum of the velocity variable cross-correlation curves corresponding to all frequencies, thereby solving the surface wave dispersion curve at the center point of the common center point signal pair arrangement.

[0076] Since the high-density seismic surface wave detection device provided in this embodiment can be used to perform the high-density seismic surface wave detection method described in the above embodiment, and its working principle and beneficial effects are similar, it will not be described in detail here. For details, please refer to the description of the above embodiment.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A high-density seismic surface wave detection method, characterized in that, include: Perform multiple coverage signal acquisitions; The seismic signals acquired along the survey line are arranged to obtain a common center point signal pair arrangement, wherein the center coordinates of the line connecting the receiving points of all signal pairs in the common center point signal pair arrangement are the same; For each signal pair in the common center point signal pair arrangement, perform forward and inverse FFT transformations to obtain the time-variable cross-correlation curves of each frequency of the signal pair. Then, based on the distance between the common center point signal pairs, perform coordinate transformations on the time-variable cross-correlation curves of each frequency of the signal pair to obtain the velocity-variable cross-correlation curves corresponding to each frequency. Finally, calculate the surface wave velocity based on the sum of the velocity-variable cross-correlation curves corresponding to all frequencies, thereby solving for the surface wave dispersion curve at the center point of the common center point signal pair arrangement. The multiple coverage signal acquisitions are performed using a wireless distributed seismograph, which includes a signal acquisition unit, a detector, and a computer; wherein the signal acquisition unit includes three or more acquisition units, each with four or more independent channels. The step of performing forward and inverse FFT transformations on each signal pair in the common center point signal pair arrangement includes: achieving spectrum refinement by adding zeros to the signal data to increase the signal length and improve analysis accuracy; and improving calculation accuracy by introducing a window function in the formula and then performing an inverse FFT transformation on each frequency signal.

2. The high-density seismic surface wave detection method according to claim 1, characterized in that, The computer serves as the main control platform for the wireless distributed seismograph. The collectors are numbered independently in sequence. When each collector moves forward, it automatically generates a common shot point arrangement signal based on the received signal according to the collector number. Based on the record of multiple coverage of common shot point signals, it extracts and arranges common center point signal pairs. The common center point is located at the center of two adjacent detector points, and the point spacing is equal to the channel spacing. The detector is a broadband accelerometer or other type of sensor. It uses the FFT bandpass filtering method, employs the low-frequency components of the signal for surface wave detection, and uses the high-frequency components of the signal for reflection wave exploration.

3. The high-density seismic surface wave detection method according to claim 1, characterized in that, The two signals in each signal pair in the common center point signal pair arrangement have the same excitation point. Each arrangement consists of multiple signal pairs, in which two or more signal pairs have different measurement point spacings.

4. The high-density seismic surface wave detection method according to claim 1, characterized in that, The coordinate transformation of the time-variable cross-correlation curve for each frequency of the signal pair to obtain the velocity-variable cross-correlation curve for each frequency includes: The surface wave signal travels between two measurement points and corresponds to a certain peak on the cross-correlation curve of the time variable. When the distance between the two measurement points is less than one wavelength, it corresponds to the first peak. After coordinate transformation, the surface wave velocity also corresponds to a certain peak on the cross-correlation curve of the velocity variable for each frequency.

5. The high-density seismic surface wave detection method according to claim 1, characterized in that, The process of then calculating the surface wave velocity based on the sum of the cross-correlation curves of the velocity variables corresponding to all frequencies includes: For all common center point signals at a certain frequency, sum the corresponding velocity variable cross-correlation curves. At the surface wave velocity point, sum the corresponding peaks on each velocity variable cross-correlation curve to obtain the maximum value. The velocity value corresponding to the maximum value on the obtained cross-correlation summation curve is the surface wave velocity. The velocity value corresponding to the maximum value on the cross-correlation summation curve obtained for each frequency is also the surface wave velocity of the signal at that frequency. The surface wave velocity corresponding to all frequencies can be obtained by summing the cross-correlation curves of the velocity variables corresponding to all frequencies.

6. The high-density seismic surface wave detection method according to claim 1, characterized in that, The method for solving the surface wave dispersion curve of the common center point signal pair at the center point of the arrangement includes: Based on the effective frequency range and velocity variation interval of the surface wave signal, a planar coordinate system is established with the X and Y axes representing velocity and frequency, respectively. The cross-correlation summation curves obtained for each frequency are plotted sequentially in the plane. Then, the velocity values ​​corresponding to the maximum values ​​on the cross-correlation summation curves are connected sequentially according to the frequency variation from small to large, resulting in a frequency-velocity variation curve, which is the surface wave dispersion curve of the center point of the common center point signal pair arrangement. Alternatively, the cross-correlation summation curve values ​​obtained for each frequency in the planar plot can be represented by different colors, with larger values ​​resulting in darker colors, thus obtaining a surface wave cross-correlation summation curve chromatogram. Based on the line connecting each frequency with the velocity point corresponding to the darkest color in the surface wave cross-correlation summation curve chromatogram, the surface wave frequency versus velocity variation curve can be obtained, which is the surface wave dispersion curve of the center point of the common center point signal pair arrangement.

7. A high-density seismic surface wave detection device, used to implement the high-density seismic surface wave detection method according to any one of claims 1-5, characterized in that, include: The signal acquisition module is used to acquire signals over multiple coverages. The signal arrangement module is used to arrange the seismic signals acquired along the survey line to obtain a common center point signal pair arrangement, wherein the center coordinates of the line connecting the receiving points of all signal pairs in the common center point signal pair arrangement are the same. The surface wave solution module performs forward and inverse FFT transformations on each signal pair in the common center point signal pair arrangement to obtain the time-variable cross-correlation curves of each frequency of the signal pair. Then, based on the distance between the common center point signal pairs, it performs coordinate transformation on the time-variable cross-correlation curves of each frequency of the signal pair to obtain the velocity-variable cross-correlation curves corresponding to each frequency. Finally, it calculates the surface wave velocity based on the sum of the velocity-variable cross-correlation curves corresponding to all frequencies, thereby solving for the surface wave dispersion curve at the center point of the common center point signal pair arrangement.

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