Method and system for separating longitudinal and transverse waves based on reflection coefficient and stress gradient to explore water

Abstract

The application provides a longitudinal and transverse wave separation water exploration method and system based on a reflection coefficient and a stress gradient, and the method comprises the following steps: collecting original seismic record data of a tunnel site and performing pretreatment; a longitudinal and transverse wave separation method is used to separate longitudinal waves and transverse waves from the pretreated seismic wave data; wherein, F-K filtering separates wave fields with different apparent velocities through frequency-wavenumber domain transformation, and realizes preliminary separation of longitudinal waves and transverse waves; for the overlapping part of the longitudinal waves and the transverse waves remaining in the F-K domain; linear Radon transformation is used to map the data from the time-space domain to the ray parameter domain, and further separate the wave fields with similar apparent velocities; a polarization filter is used to finally separate the longitudinal waves and the transverse waves by using the polarization characteristics; based on the separated longitudinal waves and the transverse waves, reflection coefficient imaging and stress gradient imaging are calculated respectively; and according to the reflection coefficient imaging result and the stress gradient imaging result, the underground water occurrence condition is identified. The identification precision of the underground water occurrence condition is improved.

Description

Technical Field

[0001] This invention belongs to the field of advanced geological exploration of tunnels, and in particular relates to a method and system for water exploration based on the separation of longitudinal and transverse waves using reflection coefficient and stress gradient. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the rapid development of tunnel engineering, complex groundwater environments have become a major bottleneck restricting safe tunnel construction. Advanced geological exploration technology for tunnels, as an important means to ensure construction safety and efficiency, is crucial in terms of accuracy and reliability. However, existing groundwater exploration technologies still have many limitations under complex geological conditions.

[0004] Traditional tunnel advanced geological exploration often employs electromagnetic methods for groundwater identification, while elastic wave methods are primarily used to detect large geological structures such as faults. However, electromagnetic methods often fall short of the requirements when encountering irregular geological structures, strong stress gradients, and complex hydrological conditions. Elastic wave methods frequently suffer from inaccurate results due to crosstalk between P-waves and S-waves, making it difficult to accurately distinguish groundwater from other geological anomalies. Furthermore, insufficient separation accuracy between P-waves and S-waves leads to unreliable results, thus requiring improvement in P-wave and S-wave separation methods. Additionally, elastic wave methods often utilize a single parameter for imaging and geological interpretation, resulting in a high risk of multiple interpretations.

[0005] Therefore, in the elastic wave method, how to construct water body identification criteria through multi-parameter joint imaging and more accurate P-wave and S-wave separation methods to improve the detection sensitivity and accuracy of groundwater bodies has become an urgent problem to be solved in tunnel advanced geological exploration technology. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, this invention provides a method and system for P-wave and S-wave separation for water exploration based on reflection coefficient and stress gradient. The P-wave and S-wave separation is achieved through multi-stage filtering, and the dual-parameter imaging of reflection coefficient and stress gradient is combined to significantly improve the accuracy and reliability of groundwater detection in tunnels, making it suitable for complex geological conditions.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0008] The first aspect of this invention provides a method for separating longitudinal and transverse waves for water exploration based on reflection coefficient and stress gradient;

[0009] Water exploration methods based on reflection coefficient and stress gradient for separating P-waves and S-waves include:

[0010] Collect raw seismic wave data at the tunnel site and perform preprocessing;

[0011] A multi-method combined approach is employed to separate P-waves and S-waves from preprocessed seismic data. This method includes FK filtering, linear Radon transform, and polarization filtering. FK filtering separates wavefields with different apparent velocities through frequency-wavenumber domain transformation, achieving initial separation of P-waves and S-waves. For the overlapping P-waves and S-waves remaining in the FK domain, linear Radon transform is used to map the preprocessed data from the time-space domain to the ray parameter domain, separating wavefields with similar apparent velocities. Finally, polarization filtering utilizes polarization characteristics to perform the final separation of P-waves and S-waves.

[0012] Based on the separated longitudinal and transverse waves, reflection coefficient imaging and stress gradient imaging are calculated respectively;

[0013] The groundwater occurrence is determined by combining the reflection coefficient imaging results and the stress gradient imaging results.

[0014] As a further technical solution, raw seismic record data from the tunnel site is collected and preprocessed; the preprocessing includes data preprocessing and waveform processing; the data preprocessing includes data format conversion, gather editing, and observation system definition;

[0015] The waveform processing includes bandpass filtering, first arrival pickup and seismic time base correction, inter-channel and intra-channel energy equalization, and inverse Q filtering.

[0016] As a further technical solution, the FK filter represents the seismic wave data as a binary function of distance and time, and obtains the frequency wavenumber spectrum through a two-dimensional Fourier transform; the spectrum transformation relationship is discretized to obtain a two-dimensional frequency wavenumber spectrum; the apparent velocity is obtained based on the wavenumber and frequency of the two-dimensional frequency wavenumber spectrum; and preliminary separation is performed based on the apparent velocity.

[0017] As a further technical solution, the process of mapping data from the time-space domain to the ray parameter domain using the linear Radon transform, and further separating wavefields with similar apparent velocities, is as follows:

[0018] Will t - x The original seismic records in the domain are based on a fixed slope P With intercept t Summation of straight lines; express Earthquake signals in the region Indicates the converted The conversion principle between the seismic signals in the region and the two is as follows:

[0019]

[0020]

[0021] In the formula: Indicates to Hilbert transform of the function.

[0022] As a further technical solution, a polarization filter is used to perform final separation of longitudinal and transverse waves based on polarization characteristics, including:

[0023] Select sampling points for seismic wave data and construct the covariance matrix of the seismic wave data;

[0024] Calculate the polarization parameters based on the obtained covariance matrix;

[0025] The polarization parameters are processed using the Poline polarization filter function to obtain the output results of the seismic wave along the three coordinate axes.

[0026] As a further technical solution, the process of calculating the reflection coefficient imaging and stress gradient imaging based on the separated longitudinal and transverse waves includes:

[0027] Reflection coefficient imaging is calculated using the difference in wave impedance, and the formula is as follows:

[0028]

[0029] In the formula, R is the reflection coefficient. A R and A I The amplitude value. Z 1 and Z 2 represents wave impedance; V represents wave velocity; ρ represents density;

[0030] Stress gradient imaging extracts the instantaneous amplitude and frequency of seismic signals based on the Hilbert-Huang transform, and calculates the stress gradient using the following formula:

[0031]

[0032] In the formula: The rock mass stress gradient; These represent the instantaneous amplitude and instantaneous frequency of the seismic signal, respectively. , represents the average values ​​of instantaneous amplitude and instantaneous frequency, respectively; n and m represent the weights of the changes in instantaneous amplitude and instantaneous frequency on the stress gradient.

[0033] As a further technical solution, the groundwater occurrence is jointly identified based on the reflection coefficient imaging results and stress gradient imaging results. For example, if the longitudinal wave reflection coefficient of a certain interval is negative and the absolute value of the transverse wave reflection coefficient is larger or tends to -1, it is determined to be a water-bearing body.

[0034] If the stress gradient in a certain interval changes abruptly, it is determined that the rock mass is fractured and may contain water;

[0035] Based on the combined anomaly characteristics of reflection coefficient and stress gradient, the water-bearing areas are divided into high-confidence, medium-confidence, and low-confidence regions.

[0036] The second aspect of the present invention provides a longitudinal and transverse wave separation water exploration system based on reflection coefficient and stress gradient.

[0037] A P-wave and S-wave separation water exploration system based on reflection coefficient and stress gradient includes:

[0038] The data acquisition module is configured to: acquire raw seismic record data at the tunnel site and perform preprocessing;

[0039] The P-wave and S-wave separation module is configured to use a multi-method combined P-wave and S-wave separation approach to separate P-waves and S-waves from preprocessed seismic wave data. This multi-method combined P-wave and S-wave separation approach includes FK filtering, linear Radon transform, and polarization filtering. FK filtering separates wavefields with different apparent velocities through frequency-wavenumber domain transformation, achieving initial separation of P-waves and S-waves. For the overlapping portion of P-waves and S-waves remaining in the FK domain, linear Radon transform is used to map the data from the time-space domain to the ray parameter domain, further separating wavefields with similar apparent velocities. Finally, a polarization filter is used to perform the final separation of P-waves and S-waves based on polarization characteristics.

[0040] The imaging module is configured to calculate reflection coefficient imaging and stress gradient imaging based on the separated longitudinal and transverse waves, respectively.

[0041] The groundwater occurrence determination module is configured to jointly identify the groundwater occurrence based on the reflection coefficient imaging results and the stress gradient imaging results.

[0042] A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of the longitudinal and transverse wave separation water exploration method based on reflection coefficient and stress gradient as described in the first aspect of the present invention.

[0043] A fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the longitudinal and transverse wave separation water exploration method based on reflection coefficient and stress gradient as described in the first aspect of the present invention.

[0044] The above one or more technical solutions have the following beneficial effects:

[0045] This invention improves the accuracy of P-wave and S-wave separation based on a multiple filtering method, and establishes water body interpretation criteria based on the separated P-wave and S-wave information. It breaks through the limitation of low sensitivity of traditional elastic wave method for groundwater detection, and significantly improves accuracy through multi-parameter joint imaging.

[0046] Compared with traditional single-parameter elastic wave advance detection methods, this invention comprehensively uses multi-parameter imaging results formed by reflection coefficient, stress gradient, P-wave, and S-wave parameters for geological interpretation, which can improve the accuracy of identifying adverse geological conditions and further effectively reduce the ambiguity of elastic wave geological exploration.

[0047] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0048] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0049] Figure 1 This is a flowchart of the method in the first embodiment.

[0050] Figure 2 This is a system structure diagram of the second embodiment. Detailed Implementation

[0051] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0052] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0053] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0054] Example 1

[0055] This embodiment discloses a method for separating longitudinal and transverse waves for water exploration based on reflection coefficient and stress gradient;

[0056] like Figure 1 As shown, the P-wave and S-wave separation water exploration method based on reflection coefficient and stress gradient includes:

[0057] Step S1: Collect raw seismic record data at the tunnel site and perform preprocessing;

[0058] First, raw seismic record data was collected at the tunnel site using seismic wave method advanced geological prediction equipment.

[0059] Furthermore, the acquired raw seismic record data undergoes data preprocessing, including data format conversion, gather editing, and observation system definition. In addition, waveform processing is performed, including bandpass filtering, first arrival picking and seismic time base correction, inter-trace / intra-trace energy equalization, and inverse Q filtering.

[0060] Step S2 involves using a multi-method combined P-wave and S-wave separation approach to separate P-waves and S-waves from the preprocessed seismic wave data. This multi-method combined P-wave and S-wave separation approach includes FK filtering, linear Radon transform, and polarization filtering. FK filtering separates wavefields with different apparent velocities through frequency-wavenumber domain transformation, achieving initial separation of P-waves and S-waves. For the overlapping portion of P-waves and S-waves remaining in the FK domain, linear Radon transform is used to map the data from the time-space domain to the ray parameter domain, further separating wavefields with similar apparent velocities. Finally, a polarization filter is used to perform the final separation of P-waves and S-waves based on their polarization characteristics.

[0061] For the FK filtering method, seismic records can be represented as a bivariate function of distance and time. g ( x , t Its frequency wavenumber spectrum can be obtained through two-dimensional Fourier transform. G ( k , f The expression is as follows:

[0062]

[0063] In the formula: k is the wave number corresponding to distance x; f is the frequency corresponding to time t.

[0064] The discretized spectrum transformation relationship is as follows:

[0065]

[0066] In the formula: m =0, 1, ..., M -1; n =0, 1, ..., N -1; For a periodic sequence where X=M△ and T=N△; It is a two-dimensional frequency wavenumber spectrum; p and q are index values ​​in the frequency domain, representing the spatial frequency components in the horizontal and vertical directions, respectively.

[0067] Two-dimensional frequency wavenumber spectrum The independent variables, wavenumber k and frequency f, are respectively:

[0068]

[0069] The ratio of frequency to wavenumber is the apparent velocity, and their relationship can be expressed by the following formula:

[0070]

[0071] In the formula, For apparent speed.

[0072] FK filtering separates wavefields with different apparent velocities through a frequency-wavenumber domain transformation. Since P-wave velocities are typically higher than S-wave velocities, they exhibit different slope regions in the FK domain. Therefore, filters can be designed to retain or suppress waves within specific velocity ranges, thus initially separating P-waves and S-waves. However, when the apparent velocity ranges of P-waves and S-waves overlap, complete separation is difficult, and high-frequency noise or scattered waves may interfere with the velocity domain division. Therefore, after FK filtering, the linear Radon transform (… Transformation can map data from the time-space domain to the ray parameter domain, further separating wave fields with similar apparent velocities and processing the overlapping parts of residual transverse and longitudinal waves in the FK domain.

[0073] The Radon transform is a coordinate transformation of a signal based on a specific integration path to achieve signal reconstruction. Based on the differences in the integration transformation path, commonly used Radon transforms are mainly divided into three categories. The most commonly used method for tunnel advanced geological prediction is the linear Radon transform, which has significant advantages in extracting negative apparent velocity phase axes and suppressing surface wave interference.

[0074] Its principle is to t - x The original seismic records in the domain are based on a fixed slope P With intercept t Summing the sum of the lines. express Earthquake signals in the region Indicates the converted The conversion principle between seismic signals in the region and those in the seismic field can be expressed by the following formula:

[0075]

[0076]

[0077] In the formula: Indicates to Hilbert transform of the function.

[0078] Seismic signals in the domain A domain has the following characteristics: Points in the domain Transform it into a straight line; conversely, A straight line in the domain Transform it into a point; Hyperbolic meridian in the domain Transform it into an elliptical arc.

[0079] because Different types of signals in the domain have different apparent velocities. The differences are amplified after transformation. Based on this characteristic or rule, effective signals can be extracted and interference signals can be filtered out.

[0080] Linear Radon filtering in While the velocity domain further refines and separates the wave field to compensate for the limitations of the FK domain in terms of apparent velocity resolution, it still cannot handle polarization differences and carries the risk of incomplete separation between longitudinal and transverse waves. Therefore, this invention proposes to utilize Poline polarization filtering for further processing. Based on the polarization difference between longitudinal waves (where the particle vibration direction is consistent with the propagation direction) and transverse waves (where the vibration direction is perpendicular to the propagation direction), the data processed in the first two steps is further separated, resolving the overlapping portion of transverse and longitudinal waves that cannot be distinguished by the velocity domain and suppressing residual noise.

[0081] Specifically, for longitudinal waves and transverse waves, the trajectories of particle motion during propagation differ significantly, i.e., their polarization characteristics are different. Polarization characteristics are an external manifestation of the spatiotemporal features of the wave field and one of the most sensitive characteristics of the wave field.

[0082] Polarization filtering is a signal processing method based on the difference in polarization direction between P-waves and S-waves. The projections of the full vector wave field along the three coordinate axes in space are recorded in sensors with different components. The XYZ system is the most widely used coordinate system in seismic exploration.

[0083] The Poline polarization filtering method, based on the covariance matrix, has shown good results in the analysis of three-component seismic records from tunnels. Its core principle is the calculation of polarization parameters from the covariance matrix, and the accurate acquisition of these parameters directly affects filter design and the effective identification of different types of wavefield information. Therefore, this invention considers the propagation characteristics of three-component elastic waves and designs a polarization filter using wavefield polarization properties such as the covariance matrix and polarization coefficients.

[0084] (1) Covariance matrix

[0085] In the XYZ coordinate system, a certain time window of the three-component seismic record is selected. within N If each sampling point is taken as the research object, then each point has three components. , , The mean within a fixed time window can be expressed as follows:

[0086]

[0087] In the formula: , , These are the average values ​​of the seismic records for the three components within the time window; N Given the number of sampling points for a given time window, , These are the sampling points corresponding to the start and end points of the time window, and their relationship with the sampling rate ∆ is... t Between full .

[0088] The covariance matrix corresponding to this earthquake record can then be constructed:

[0089]

[0090] In the formula: It is the covariance matrix; ; ; .

[0091] Its eigenvalues ​​can be obtained by solving the matrix. l 1. l 2. l 3 and eigenvectors A 1. A 2. A 3. Among them, the signal energy is mainly concentrated on the largest eigenvalue, and the direction of its corresponding eigenvector is the main polarization direction.

[0092] (2) Polarization coefficient and ellipsoidal index

[0093] The major, minor, and intermediate axes of a particle's trajectory can be determined by eigenvalues:

[0094]

[0095] In the formula: a, b, and c are the values ​​of the major, medium, and minor semi-axes of the particle's trajectory, respectively; m is approximately taken as... .

[0096] Further define the polarization coefficient T :

[0097]

[0098] In the formula: e 21 , e 31These are the principal ellipsoidal indices and the secondary ellipsoidal indices, respectively. Ellipsoidal indices can be obtained through eigenvalues. l 1. l 2. l 3. We obtain:

[0099]

[0100] The polarization coefficient ranges from 0 to 1, and its value can be used to determine the degree of polarization of the seismic signal.

[0101] (3) Determination of polarization direction and filter function

[0102] Based on the corresponding spatial geometric relationships, the cosines of the three polarization directions can be calculated using the following formula:

[0103]

[0104] Based on the analysis of polarization coefficient and polarization direction, this invention employs a Poline polarization filter function with spatial orientation filtering characteristics:

[0105]

[0106] In the formula: T The polarization coefficient; i ( t The angle between the principal eigenvector and the filter axis; the exponent. p , q These respectively characterize the weighting of polarization degree and polarization direction, and are relevant to engineering applications. p The value ranges from 0.5 to 1. q The value ranges from 1 to 2.

[0107] In summary, through polarization filtering analysis, the output results of the three components of the seismic record are as follows:

[0108]

[0109] This technical solution utilizes FK filtering to provide initial velocity separation, but is limited by apparent velocity overlap and noise. Therefore, a linear Radon filter is proposed for further analysis. While velocity-domain refinement separation compensates for the limitations of FK methods in apparent velocity resolution, it still cannot handle polarization differences. Therefore, further polarization filtering is used to utilize polarization characteristics for final separation, addressing the fundamental differences that velocity-domain methods cannot handle. This invention combines the advantages of both velocity and polarization domains, gradually overcoming the shortcomings of previous methods, and is suitable for wavefield separation under complex geological conditions.

[0110] Step S3: Based on the separated longitudinal and transverse waves, calculate the reflection coefficient imaging and stress gradient imaging respectively;

[0111] Specifically, the reflection coefficient is the core of the elastic wave reflection method:

[0112]

[0113] In the formula, R is the reflection coefficient. A R and A I The amplitude value. Z 1 and Z 2 represents wave impedance.

[0114] The reflection coefficient represents the energy of the reflected wave when an elastic wave is incident perpendicularly on an interface. In particular, since transverse waves cannot propagate in gaseous or liquid media, incident transverse waves cannot penetrate water-bearing bodies, while longitudinal waves can propagate in solid-liquid-gas three-phase media. Theoretically, the energy of longitudinal wave reflection at the interface is less than that of transverse wave reflection.

[0115] Assuming the underground rock mass is under non-uniform stress, the density of the rock mass can be further differentiated based on the principle of mutual mapping between the instantaneous attribute parameters of elastic waves and the normal of the rock mass structural surface. The degree of rock fragmentation is closely related to the surrounding rock stress and groundwater flow and convergence, providing a basis for groundwater detection based on the surrounding rock stress state. Furthermore, the concept of stress gradient is introduced. Based on seismic gather records and fused with the Hilbert-Huang instantaneous attribute extraction algorithm, accurate surrounding rock stress gradient parameters are obtained. The specific calculation method is as follows:

[0116] (1) Stress gradient calculation method:

[0117] The reflection coefficient of a vertically incident wave under prestressed conditions is:

[0118]

[0119] In the formula, Z is the reflection coefficient of a vertically incident wave under prestressed conditions; Z and These are the wave impedances in stress-free and prestressed half-space strata, respectively. Angular frequency;

[0120] The scaling factor for hydrostatic pressure in the stress half-space can be expressed as:

[0121]

[0122] Where: P is the proportionality coefficient between stress space and hydrostatic pressure; m * This is the shear modulus.

[0123] Considering the weak correlation between the elastic modulus and stress change under discrete medium conditions, and given that the wave impedance values ​​remain almost unchanged under stress-free and prestressed conditions, the above equation can be further simplified:

[0124]

[0125] Pressure changes at any two points on the reflective interface for:

[0126]

[0127] In the formula: A The amplitude of the signal; oh The signal frequency.

[0128] In the above formula, the amplitude and frequency are expressed in the form of analytic signals. Therefore, the quantitative relationship between the stress gradient, instantaneous amplitude, and instantaneous frequency can be expressed as:

[0129]

[0130] In the formula The rock mass stress gradient; , These represent the instantaneous amplitude and instantaneous frequency of the seismic signal, respectively. , represents the average values ​​of instantaneous amplitude and instantaneous frequency, respectively; n and m represent the weights of the changes in instantaneous amplitude and instantaneous frequency on the stress gradient.

[0131] The above calculation of stress gradient utilizes the concept of reflection coefficient, specifically the formula for the reflection coefficient of a vertically incident wave under prestressed conditions, which is one of the foundations of stress gradient calculation. Through a series of derivations, considering factors such as the weak correlation between elastic modulus and stress change under discrete medium conditions, the quantitative relationship between stress gradient and instantaneous amplitude and instantaneous frequency is gradually derived from the reflection coefficient formula. This indicates that, at the computational level, the reflection coefficient is a crucial element in obtaining the stress gradient.

[0132] (2) The principle and implementation path of Hilbert-Huang transform:

[0133] The key to solving stress gradient imaging lies in the accurate extraction of instantaneous attributes of seismic signals. An analytical signal corresponding to the seismic trace is established based on a linear combination of the Hilbert transform signal and the seismic signal, allowing the calculation of instantaneous attributes (instantaneous amplitude, instantaneous phase, instantaneous amplitude) for a given time series. However, Hilbert transformation is only applicable to single-component seismic signals, while seismic records from tunnel advanced geological exploration are mostly multi-component data (i.e., containing multiple frequency components at the same time). Based on complex seismic signals, the instantaneous frequency result after Hilbert transformation shows a negative frequency, which contradicts basic facts; therefore, directly solving for the instantaneous frequency based on the seismic signal is meaningless.

[0134] Secondly, the Hilbert transform requires the signal to be narrowband and stationary, but tunnel seismic signals do not meet these conditions. To effectively utilize the Hilbert transform, the nonlinear stationary signal needs to be converted into a stationary signal. The Hilbert-Huang transform preprocesses the complex seismic signal using empirical mode decomposition (EMD) and then performs the Hilbert transform on the decomposed intrinsic mode functions. This approach cleverly solves the problem of not being able to directly obtain the instantaneous properties of complex signals. Therefore, this invention processes seismic signals using the Hilbert-Huang transform method to analyze their instantaneous property parameters.

[0135] The principle of the EMD (Experience Module Decomposition) method is as follows:

[0136]

[0137] In the formula: This is the original seismic signal; After decomposition k One intrinsic mode function; For the original seismic signal and IMF The residual term of the signal.

[0138] The Hilbert conversion principle is as follows:

[0139]

[0140] In the formula: The result is the Hilbert transform. .

[0141] Therefore, the complex signal of this seismic signal can be defined. Z (t) is:

[0142]

[0143] In the formula: A(t) is the instantaneous amplitude; φ(t) is the instantaneous phase, and its expression is:

[0144]

[0145]

[0146] The instantaneous frequency is the derivative of the instantaneous phase with respect to time, and its expression is as follows:

[0147]

[0148] From an imaging methodology perspective, combining reflection coefficient and stress gradient for water exploration is a more effective approach. The reflection coefficient reflects the energy characteristics of reflected waves at the interface of a water-bearing body from the perspective of impedance differences, while the stress gradient, closely related to the degree of rock fragmentation, surrounding rock stress, and groundwater flow and convergence, can provide clues about the presence of groundwater from the perspective of rock stress state. Combining reflection coefficient and stress gradient provides effective theoretical support for scientifically predicting and determining the distribution patterns of groundwater within rock masses, thereby improving the accuracy of groundwater occurrence identification and reducing the ambiguity of geological predictions.

[0149] From the perspective of the polarization characteristics of elastic waves, transverse waves cannot propagate in gaseous and liquid phase media, meaning they cannot penetrate aquifers; most of their energy is reflected at the interface. Longitudinal waves, on the other hand, can propagate in a three-phase medium (solid-liquid-gas). Therefore, the amplitude energy of the reflected wave at the boundary of an aquifer structure is significantly less than that of the reflected transverse wave. Based on the difference in how longitudinal and transverse waves "reflect" aquifers, an effective separation method for longitudinal and transverse waves provided in the second aspect of this invention is used to perform separate imaging of longitudinal and transverse waves (specifically including longitudinal wave reflection coefficient imaging, transverse wave reflection coefficient imaging, longitudinal wave stress gradient imaging, and transverse wave stress gradient imaging). By combining and interpreting the longitudinal wave imaging results with the transverse wave imaging results, the occurrence of aquifers ahead of the excavation face can be inferred, enriching the interpretation results of geological exploration.

[0150] Specifically, a method for separating longitudinal and transverse waves for water exploration that combines reflection coefficient and stress gradient involves first effectively separating longitudinal and transverse waves, and then performing reflection coefficient imaging of longitudinal waves, reflection coefficient imaging of transverse waves, stress gradient imaging of longitudinal waves, and stress gradient imaging of transverse waves, respectively.

[0151] Furthermore, for reflection coefficient imaging, if negative reflection occurs at the front end of a certain interval and positive reflection occurs at the rear end of the interval, then the interval is inferred to be a water-bearing characteristic model. Alternatively, if negative reflection occurs in the longitudinal wave imaging (reflection coefficient less than 0) and negative reflection also occurs in the transverse wave imaging (reflection coefficient less than 0, and the absolute value is larger than the longitudinal wave reflection coefficient, or even tends to -1), then the interval is inferred to be a water-bearing characteristic model.

[0152] Furthermore, for stress gradient imaging, if a sudden change in stress occurs within a certain interval, it is inferred that the rock mass within that interval is fractured and may contain water.

[0153] Step S4: Based on the reflection coefficient imaging results and stress gradient imaging results, jointly identify the groundwater occurrence.

[0154] Furthermore, by comparing the results of reflectance coefficient imaging and stress gradient imaging, if both infer a certain interval as a water-bearing characteristic model, then that interval is judged as a high-confidence water-bearing area. If only one infers a water-bearing characteristic model, then that interval is judged as a medium-confidence water-bearing area. Areas where neither reflectance coefficient nor stress gradient shows anomalies are judged as low-confidence / non-water-bearing areas.

[0155] Example 2

[0156] This embodiment discloses a longitudinal and transverse wave separation water exploration system based on reflection coefficient and stress gradient;

[0157] like Figure 2 As shown, the P-wave and S-wave separation water exploration system based on reflection coefficient and stress gradient includes:

[0158] The data acquisition module is configured to: acquire raw seismic record data at the tunnel site and perform preprocessing;

[0159] The P-wave and S-wave separation module is configured to use a multi-method combined P-wave and S-wave separation approach to separate P-waves and S-waves from preprocessed seismic wave data. This multi-method combined P-wave and S-wave separation approach includes FK filtering, linear Radon transform, and polarization filtering. FK filtering separates wavefields with different apparent velocities through frequency-wavenumber domain transformation, achieving initial separation of P-waves and S-waves. For the overlapping portion of P-waves and S-waves remaining in the FK domain, linear Radon transform is used to map the data from the time-space domain to the ray parameter domain, further separating wavefields with similar apparent velocities. Finally, a polarization filter is used to perform the final separation of P-waves and S-waves based on polarization characteristics.

[0160] The imaging module is configured to calculate reflection coefficient imaging and stress gradient imaging based on the separated longitudinal and transverse waves, respectively.

[0161] The groundwater occurrence determination module is configured to jointly identify the groundwater occurrence based on the reflection coefficient imaging results and the stress gradient imaging results.

[0162] Example 3

[0163] The purpose of this embodiment is to provide a computer-readable storage medium.

[0164] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the longitudinal and transverse wave separation water exploration method based on reflection coefficient and stress gradient as described in Example 1.

[0165] Example 4

[0166] The purpose of this embodiment is to provide an electronic device.

[0167] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the longitudinal and transverse wave separation water exploration method based on reflection coefficient and stress gradient as described in Example 1.

[0168] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0169] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0170] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for separating P-waves and S-waves for water exploration based on reflection coefficient and stress gradient, characterized in that, include: Collect raw seismic data at the tunnel site and perform preprocessing; A multi-method combined approach is employed to separate P-waves and S-waves from preprocessed seismic data. This method includes FK filtering, linear Radon transform, and polarization filtering. FK filtering separates wavefields with different apparent velocities through frequency-wavenumber domain transformation, achieving initial separation of P-waves and S-waves. For the overlapping P-waves and S-waves remaining in the FK domain, linear Radon transform is used to map the preprocessed data from the time-space domain to the ray parameter domain, separating wavefields with similar apparent velocities. Finally, polarization filtering utilizes polarization characteristics to perform the final separation of P-waves and S-waves. Based on the separated longitudinal and transverse waves, reflection coefficient imaging and stress gradient imaging are calculated respectively; Based on the reflection coefficient imaging results and stress gradient imaging results, the groundwater occurrence is jointly identified. If the P-wave reflection coefficient of a certain interval is negative and the absolute value of the S-wave reflection coefficient is larger or tends to -1, it is determined to be a water-bearing body. If the stress gradient of a certain interval shows a sudden change, it is determined to be a fractured rock mass with a probability of water content. Combining the abnormal characteristics of reflection coefficient and stress gradient, the interval is divided into high-confidence water-bearing areas, medium-confidence water-bearing areas, and low-confidence water-bearing areas. If both of a certain interval are inferred to be water-bearing characteristic models, the current interval is determined to be a high-confidence water-bearing area. If only one is inferred to be a water-bearing characteristic model, the current interval is determined to be a medium-confidence water-bearing area. If neither the reflection coefficient nor the stress gradient is abnormal, the current interval is determined to be a low-confidence or non-water-bearing area.

2. The method for separating P-waves and S-waves for water exploration based on reflection coefficient and stress gradient as described in claim 1, characterized in that, Raw seismic record data is collected from the tunnel site and preprocessed; the preprocessing includes data preprocessing and waveform processing; the data preprocessing includes data format conversion, gather editing, and observation system definition; The waveform processing includes bandpass filtering, first arrival pickup and seismic time base correction, inter-channel and intra-channel energy equalization, and inverse Q filtering.

3. The method for separating P-waves and S-waves for water exploration based on reflection coefficient and stress gradient as described in claim 1, characterized in that, The FK filter represents seismic wave data as a binary function of distance and time, and obtains the frequency wavenumber spectrum through a two-dimensional Fourier transform; the spectrum transformation relationship is discretized to obtain a two-dimensional frequency wavenumber spectrum; the apparent velocity is obtained based on the wavenumber and frequency of the two-dimensional frequency wavenumber spectrum; and preliminary separation is performed based on the apparent velocity.

4. The method for separating P-waves and S-waves for water exploration based on reflection coefficient and stress gradient as described in claim 1, characterized in that, The process of mapping data from the time-space domain to the ray parameter domain using the linear Radon transform, and further separating wavefields with similar apparent velocities, is as follows: Will The original seismic records in the domain are based on a fixed slope P With intercept τ Summing the sum of the straight lines, with express Earthquake signals in the region Indicates the converted The conversion principle between seismic signals in the region and those in the seismic field is expressed by the following formula: In the formula: Indicates to Hilert transform of a function.

5. The method for separating P-waves and S-waves for water exploration based on reflection coefficient and stress gradient as described in claim 1, characterized in that, The final separation of longitudinal and transverse waves is achieved using polarization filters based on their polarization characteristics, including: Select sampling points for seismic wave data and construct the covariance matrix of the seismic wave data; Calculate the polarization parameters based on the obtained covariance matrix; The polarization parameters are processed using the Poline polarization filter function to obtain the output results of the seismic wave along the three coordinate axes.

6. The method for separating P-waves and S-waves for water exploration based on reflection coefficient and stress gradient as described in claim 1, characterized in that, The process of calculating reflection coefficient imaging and stress gradient imaging based on the separated longitudinal and transverse waves includes: Reflection coefficient imaging is calculated using the difference in wave impedance, and the formula is as follows: In the formula, R is the reflection coefficient. and The amplitude value. and Indicates wave impedance; Indicates wave speed; Indicates density; Stress gradient imaging extracts the instantaneous amplitude and frequency of seismic signals based on the Hilbert-Huang transform, and calculates the stress gradient using the following formula: In the formula The rock mass stress gradient; , These represent the instantaneous amplitude and instantaneous frequency of the seismic signal, respectively. , represents the average values ​​of instantaneous amplitude and instantaneous frequency, respectively; n and m represent the weights of the changes in instantaneous amplitude and instantaneous frequency on the stress gradient.

7. A P-wave and S-wave separation water exploration system based on reflection coefficient and stress gradient, characterized in that: include: The data acquisition module is configured to: acquire raw seismic record data at the tunnel site and perform preprocessing; The P-wave and S-wave separation module is configured to use a multi-method combined P-wave and S-wave separation approach to separate P-waves and S-waves from preprocessed seismic wave data. This multi-method combined P-wave and S-wave separation approach includes FK filtering, linear Radon transform, and polarization filtering. FK filtering separates wavefields with different apparent velocities through frequency-wavenumber domain transformation, achieving initial separation of P-waves and S-waves. For the overlapping portion of P-waves and S-waves remaining in the FK domain, linear Radon transform is used to map the data from the time-space domain to the ray parameter domain, further separating wavefields with similar apparent velocities. Finally, a polarization filter is used to perform the final separation of P-waves and S-waves based on polarization characteristics. The imaging module is configured to calculate reflection coefficient imaging and stress gradient imaging based on the separated longitudinal and transverse waves, respectively. The groundwater occurrence determination module is configured to: jointly determine the groundwater occurrence based on the reflection coefficient imaging results and stress gradient imaging results; if the P-wave reflection coefficient of a certain interval is negative and the absolute value of the S-wave reflection coefficient is larger or tends to -1, it is determined to be a water-bearing body; if the stress gradient of a certain interval shows a sudden change, it is determined to be a fractured rock mass with a probability of water content; based on the abnormal characteristics of the reflection coefficient and stress gradient, it divides the area into high-confidence water-bearing areas, medium-confidence water-bearing areas, and low-confidence water-bearing areas; if both of a certain interval are inferred to be water-bearing characteristic models, the current interval is determined to be a high-confidence water-bearing area; if only one is inferred to be a water-bearing characteristic model, the current interval is determined to be a medium-confidence water-bearing area; if neither the reflection coefficient nor the stress gradient is abnormal, the current interval is determined to be a low-confidence or non-water-bearing area.

8. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the longitudinal and transverse wave separation water exploration method based on reflection coefficient and stress gradient as described in any one of claims 1-6.

9. An electronic device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the steps in the longitudinal and transverse wave separation water exploration method based on reflection coefficient and stress gradient as described in any one of claims 1-6.

Images