A Geologically Constrained Method and System for Coal Thickness Detection via In-Bore Elastic Waves

Abstract

This application discloses a method and system for detecting coal thickness in boreholes using elastic waves based on geological constraints, relating to the field of geophysical exploration. The specific steps are as follows: acquiring raw elastic wave signals from the borehole and preprocessing the raw elastic wave signals; constructing a geologically constrained adaptive variational mode empirical decomposition model based on the preprocessed signal and constraint conditions, and solving it to output intrinsic mode functions; the constraint conditions include bandwidth constraints, reconstruction constraints, and geological prior constraints; identifying coal seam reflection modes based on the intrinsic mode functions and extracting the reception time difference of the reflection signals at the top and bottom interfaces of the coal seam; calculating the coal seam thickness based on the reception time difference of the reflection signals at the top and bottom interfaces of the coal seam and the P-wave velocity of the coal seam. This application not only improves the robustness of detection in low signal-to-noise ratio and complex interference environments but also enhances the consistency between the signal processing process and the geophysical mechanism.

Description

Technical Field

[0001] This application relates to the field of geophysical exploration, and in particular to a method and system for detecting coal thickness in boreholes using elastic waves based on geological constraints. Background Technology

[0002] Currently, driven by the demand for safe and efficient coal mining and accurate resource evaluation, high-precision detection of coal seam thickness has become a key technical link in the field of geophysical exploration. Traditional methods such as core drilling, conventional logging and surface seismic exploration are difficult to meet the requirements of fine detection in front of roadway excavation or inside mining areas due to high cost, low efficiency, insufficient vertical resolution or strong near-surface interference.

[0003] Among them, the reflection detection technology based on elastic waves in the borehole has become an important means of coal thickness detection due to its high vertical resolution and engineering applicability. However, the actual acquired signals have significant non-stationarity and strong noise interference characteristics. Existing signal decomposition methods, such as empirical mode decomposition and its improved algorithms, suffer from mode aliasing and endpoint effects. Variational mode decomposition relies on manually preset parameters and lacks a geological prior information fusion mechanism, resulting in unstable extraction of effective reflection features and limited accuracy of coal thickness inversion.

[0004] Therefore, how to integrate prior geological knowledge, adaptively suppress non-target frequency band interference, and robustly extract high-fidelity decomposition methods for coal seam interface reflection signals under strong noise environments is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides a method and system for detecting coal thickness in boreholes using elastic waves based on geological constraints, which overcomes the above-mentioned defects.

[0006] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a method for detecting coal thickness in boreholes using elastic waves based on geological constraints, the specific steps of which are as follows: The raw elastic wave signal in the acquisition hole is collected and preprocessed. Based on the preprocessed signal and constraints, a geologically constrained adaptive variational mode empirical decomposition model is constructed and solved to output the intrinsic mode functions; the constraints include bandwidth constraints, reconstruction constraints and geological prior constraints. Based on the intrinsic mode function, the coal seam reflection mode is identified, and the reception time difference of the reflected signal at the top and bottom interfaces of the coal seam is extracted; The thickness of the coal seam is calculated based on the time difference between the received reflected signals at the top and bottom interfaces of the coal seam and the longitudinal wave velocity of the coal seam.

[0007] Optionally, the preprocessing specifically includes: The original elastic wave signal is subjected to mean removal processing, and the amplitude of the original elastic wave signal after mean removal processing is normalized to obtain the preprocessed signal.

[0008] Optionally, the expression for the geologically constrained adaptive variational mode empirical decomposition model is: ; In the formula, These are bandwidth control parameters; The preset total number of modes; It is the Dirac function; The imaginary unit; It is a time variable; For the first One eigenmode function to be solved; For the first The central angular frequency corresponding to each mode; Weights for signal reconstruction errors; This is the preprocessed original elastic wave signal; This is the geological constraint strength coefficient; These are geological a priori constraints. This is a convolution operation.

[0009] Optionally, the expression for the geological prior constraint term is: ; In the formula, For the first The center frequency of the mode; , This represents the typical frequency boundary of coal seam reflected waves.

[0010] Optionally, the geologically constrained adaptive variational modal empirical decomposition model is solved using the alternating direction multiplier method, including iterative update execution: The eigenmode functions of each mode are updated in the frequency domain, and their expressions are as follows: ; The expression for updating the center angular frequency is: ; The Lagrange multipliers are updated using the following expression: ; In the formula, Fourier transform; For the first The eigenmode function at the th Frequency domain representation of the next iteration; Fourier transform of the preprocessed original elastic wave signal; For the first The mode in the th ... Frequency domain representation of the next iteration; For frequency domain variables; For the first The mode in the th ... The central angular frequency of the next iteration; For the first The Lagrange multiplier spectrum of the next iteration; For A frequency band window function centered on the frequency band; For the first The Lagrange multiplier spectrum of the next iteration; It is a relaxation factor.

[0011] Optionally, the formula for calculating coal seam thickness is: ; In the formula, Coal seam thickness; This refers to the longitudinal wave propagation velocity in the coal seam. This refers to the time difference in receiving reflected signals from the top and bottom interfaces of the coal seam.

[0012] Secondly, this application provides a geologically constrained in-hole elastic wave coal thickness detection system, comprising: The signal preprocessing module is used to acquire the original elastic wave signal in the hole and preprocess the original elastic wave signal. The model building module is used to construct an objective functional containing bandwidth constraints, reconstruction constraints, and geological prior constraints based on the preprocessed signal, which serves as a geologically constrained adaptive variational mode empirical decomposition model. The mode decomposition module is used to solve the geologically constrained adaptive variational mode empirical decomposition model using the alternating direction multiplier method algorithm, and output the intrinsic mode functions. A reflection mode identification unit is used to identify the coal seam reflection mode based on the intrinsic mode function and extract the reception time difference of the reflected signal at the top and bottom interfaces of the coal seam. The coal thickness calculation module is used to calculate the coal seam thickness based on the time difference between the received reflected signals at the top and bottom interfaces of the coal seam and the longitudinal wave velocity of the coal seam.

[0013] Optionally, the signal preprocessing module includes: The mean-removing unit is used to perform mean-removing processing on the original elastic wave signal to obtain a mean-removed signal; The normalization unit is used to perform amplitude normalization processing on the mean-removed signal to obtain the preprocessed signal.

[0014] According to the specific embodiments provided in this application, this application has the following technical effects: This application embeds the frequency band prior determined by the acoustic properties of coal and rock into a variational decomposition framework to form a physically guided time-frequency decomposition mechanism, which effectively suppresses spurious modes in non-coal seam frequency bands; it integrates empirical mode initialization and variational optimization to balance the sensitivity of transient reflected waves with the mathematical stability of time-frequency decomposition; and it achieves robust coal seam reflection feature extraction under high-noise environments by adaptively adjusting the geological constraint strength. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the overall method flow provided in one embodiment of this application; Figure 2 This is a diagram of the original elastic wave signal provided in an embodiment of this application; Figure 3 This is a schematic diagram of the decomposition results of a geologically constrained adaptive variational mode empirical decomposition model provided in an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] This implementation discloses a method for detecting coal thickness in boreholes using elastic waves based on geological constraints, such as... Figure 1 As shown, the specific steps are as follows: S1. Collect the original elastic wave signal in the acquisition hole and preprocess the original elastic wave signal; S2. Based on the preprocessed signal and constraints, construct a geologically constrained adaptive variational mode empirical decomposition model and solve it to output the intrinsic mode functions; the constraints include bandwidth constraints, reconstruction constraints and geological prior constraints. S3. Identify coal seam reflection modes based on intrinsic mode functions and extract the reception time difference of reflected signals from the top and bottom interfaces of the coal seam; S4. Calculate the coal seam thickness based on the time difference between the received reflected signals at the top and bottom interfaces of the coal seam and the longitudinal wave velocity of the coal seam.

[0020] In one embodiment, the preprocessing steps are as follows: The original elastic wave signal is subjected to mean-reduction processing to eliminate DC offset; The amplitude of the mean-reduced signal (i.e., the mean-reduced signal) is normalized to make its energy distribution uniform, which facilitates subsequent stability control of the decomposition.

[0021] In one embodiment, constructing a geologically constrained adaptive variational mode empirical decomposition model specifically includes: Set the total number of modes Initialize the center frequencies of each mode. ; Construct a joint optimization objective functional containing three terms: ; In the formula, This is a bandwidth control parameter, with a value range of 1000~5000, used to constrain the spectral compactness of each mode; The total number of modes is usually set to 5 to 8 based on the complexity of the elastic wave signal in the hole; It is the Dirac function; , is the imaginary unit; It is a time variable; For the first One eigenmode function to be solved; For the first The center angular frequency (unit: rad / s) corresponding to each mode; The signal reconstruction error weights are set with values ​​ranging from 500 to 2000, balancing fidelity and decomposition sparsity. This is the pre-processed elastic wave signal in the hole; This is the geological constraint strength coefficient, with a value ranging from 200 to 1000, used to suppress non-coal seam frequency band modes; This is a geological prior constraint term used to suppress modal energy in the response frequency band of non-coal seams; This is a convolution operation.

[0022] In one embodiment, geological prior constraints Defined as: ; In the formula, , for the first The center frequency of each mode, in Hz; , The typical frequency boundary of coal seam reflected waves is determined by the physical prior determined by the difference in acoustic impedance between coal and rock. The function of this constraint term is: when the center frequency of a certain mode falls within the effective response frequency band of the coal seam, no penalty is imposed; otherwise, its energy is penalized twice, thereby guiding the decomposition process to focus on the geologically effective reflected signal.

[0023] Furthermore, the alternating direction multiplier method is used to solve the geologically constrained adaptive variational mode empirical decomposition model, which includes the following iterative update steps: Update each mode in the frequency domain : ; In the formula, Fourier transform; For the first The eigenmode function at the th Frequency domain representation of the next iteration; Fourier transform of the preprocessed elastic wave signal in the hole (i.e., the original elastic wave signal); For the first The mode in the th ... Frequency domain representation of the next iteration; For frequency domain variables; For the first The mode in the th ... The central angular frequency of the next iteration; For the first The Lagrange multiplier spectrum of the next iteration; For A frequency band window function centered on the frequency band is used for local spectrum focusing; The expression for the frequency band window function is: ; In the formula, The parameters for controlling the window width are set based on the signal sampling rate and the expected modal bandwidth, and are generally adopted as follows: , This is a proportionality coefficient, ranging from 0.5 to 1.5; The frequency difference is represented by a frequency window function multiplied by a Lagrange multiplier in the frequency domain to achieve energy focusing on the target frequency band.

[0024] Update center angular frequency : ; Update the Lagrange multipliers: ; In the formula, For the first The Lagrange multiplier spectrum of the next iteration; , which is a relaxation factor used to improve the convergence stability of the algorithm.

[0025] In one embodiment, the formula for calculating the coal seam thickness is: ; In the formula, Coal seam thickness; The longitudinal wave propagation velocity of the coal seam can be obtained from nearby well logging data or laboratory measurements. This refers to the time difference in receiving reflected signals from the top and bottom interfaces of the coal seam.

[0026] Furthermore, the longitudinal wave propagation velocity of the coal seam can be obtained from the acoustic logging curves of adjacent boreholes. By finding a location at the same depth as the target coal seam, the longitudinal wave velocity value recorded at that location can be directly read. The longitudinal wave velocity value in the acoustic logging curve data is the conventional output result. Alternatively, a cylindrical rock core sample taken from the coal seam can be placed in an ultrasonic device in the laboratory, and the time required for the sound wave to pass through the entire rock core can be measured. The longitudinal wave velocity can then be obtained by dividing the rock core length by the time.

[0027] In one embodiment, the above method is further illustrated by a specific example, as follows: First, the elastic wave signal in the hole is acquired and preprocessed: In the borehole, an elastic wave was excited using a piezoelectric source with a center frequency of 2 kHz. Eight elastic wave detectors were deployed along the borehole depth, with a sampling frequency of 50 kHz and a recording duration of 10 ms. A total of 100 single-channel reflection signals s(t) were acquired, such as... Figure 2 As shown.

[0028] Subsequently, the original signal (i.e., the elastic wave signal in the hole) is preprocessed: First, calculate the mean of the entire signal and subtract it from each sampling point to eliminate DC offset; then, divide the signal amplitude by the maximum absolute value to normalize it, compressing the signal amplitude range to [ ]. The interval is [1,1].

[0029] Its advantages lie in improving the numerical stability of subsequent decomposition algorithms and eliminating the interference of instrument baseline drift on reflection feature recognition.

[0030] Next, a geologically constrained adaptive variational mode empirical decomposition model is constructed: Based on on-site geological data, the surrounding rocks above and below the target coal seam are known to be mainly sandy mudstone, and the longitudinal wave velocity of the coal seam is approximately 2100 m / s. Combining historical logging experience, the effective frequency range of coal seam reflection is determined to be... to Set the total number of modes K=6, and the bandwidth control parameters... =2000, Reconstruct error weights =1000, initial strength of geological constraint =500, relaxation factor =1.5.

[0031] The preprocessed signal was coarsely decomposed using a standard empirical mode decomposition method. The dominant frequency of the third-order characteristic mode (IMF) was extracted as the initial center frequency, and two boundary frequencies of 0.1 kHz and 7.5 kHz were added to complete the initialization of six modes. This modeling process explicitly embeds the coal and rock acoustic priors into the optimization objective, ensuring that the decomposition results focus on the geologically effective reflection frequency band.

[0032] Then, solve the geologically constrained adaptive variational mode empirical decomposition model: Iterative optimization is performed using the alternating direction multiplier method, updating each mode sequentially. , and The maximum number of iterations is set to 100, and the convergence threshold is set to 10. 6 In each iteration, the spectrum, center frequency, and Lagrange multipliers of each mode are updated sequentially. After 42 iterations, the algorithm converges, outputting 6 intrinsic mode functions. Upon inspection, among them The center frequency is 4.13 kHz, falling within the effective frequency band, and its time-domain waveform exhibits two clear polarity reversals, suggesting that it contains reflection information from the top and bottom interfaces of the coal seam. Figure 3 As shown.

[0033] Finally, the coal seam reflection modes were identified and the coal seam thickness was calculated. right Envelope extraction is performed to obtain its amplitude envelope sequence. Then, the first strong polarity reversal point is searched within the envelope sequence, and its corresponding sampling index is [index missing]. and Converted to time =0.42×10 -3 s; The longitudinal wave velocity of the coal seam is known. The velocity is 2100 m / s. Substituting this into the coal thickness calculation formula yields the coal thickness. It is 0.441m.

[0034] Among them, for The specific steps for envelope extraction are as follows: right Perform a Hilbert transform to obtain its analytic signal. ,in, Represents the Hilbert transform; The imaginary unit is used. Then, the modulus of the analytic signal, i.e., the amplitude envelope sequence, is calculated: For amplitude envelope sequences A peak detection algorithm is applied, with the minimum peak height set to 15% of the maximum envelope value and the minimum peak spacing set to 30 sampling points to eliminate weak noise fluctuations. The number of sampling points corresponding to the first two detected valid peaks is recorded as follows: and .

[0035] Among them, by and The expression for converting to time is: ; In the formula, The sampling frequency is 50kHz in this embodiment.

[0036] This embodiment also discloses a geologically constrained in-hole elastic wave coal thickness detection system, comprising: The signal preprocessing module is used to acquire the raw elastic wave signal in the hole and preprocess the raw elastic wave signal. The model building module is used to construct an objective functional containing bandwidth constraints, reconstruction constraints, and geological prior constraints based on the preprocessed signal, which serves as a geologically constrained adaptive variational mode empirical decomposition model. The mode decomposition module is used to solve the geologically constrained adaptive variational mode empirical decomposition model using the alternating direction multiplier method algorithm, and output the intrinsic mode functions. The reflection mode identification unit is used to identify the coal seam reflection mode based on the intrinsic mode function and extract the reception time difference of the reflected signal at the top and bottom interfaces of the coal seam. The coal thickness calculation module is used to calculate the coal seam thickness based on the time difference between the received reflected signals from the top and bottom interfaces of the coal seam and the longitudinal wave velocity of the coal seam.

[0037] In one embodiment, the signal preprocessing module includes: The mean-removing unit is used to perform mean-removing processing on the original elastic wave signal to obtain a mean-removed signal; The normalization unit is used to perform amplitude normalization on the mean-removed signal to obtain a preprocessed signal.

[0038] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0039] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for detecting coal thickness in boreholes using elastic waves based on geological constraints, characterized in that, The specific steps are as follows: The raw elastic wave signal in the acquisition hole is collected and preprocessed. Based on the preprocessed signal and constraints, a geologically constrained adaptive variational mode empirical decomposition model is constructed and solved to output the intrinsic mode functions; the constraints include bandwidth constraints, reconstruction constraints and geological prior constraints. Based on the intrinsic mode function, the coal seam reflection mode is identified, and the reception time difference of the reflected signal at the top and bottom interfaces of the coal seam is extracted; The thickness of the coal seam is calculated based on the time difference between the received reflected signals at the top and bottom interfaces of the coal seam and the longitudinal wave velocity of the coal seam.

2. The method for detecting coal thickness in boreholes based on geological constraints according to claim 1, characterized in that, The preprocessing specifically includes: The original elastic wave signal is subjected to mean removal processing, and the amplitude of the original elastic wave signal after mean removal processing is normalized to obtain the preprocessed signal.

3. The method for detecting coal thickness in boreholes based on geological constraints according to claim 1, characterized in that, The expression for the geologically constrained adaptive variational mode empirical decomposition model is as follows: ； In the formula, These are bandwidth control parameters; The preset total number of modes; It is the Dirac function; The imaginary unit; It is a time variable; For the first One eigenmode function to be solved; For the first The central angular frequency corresponding to each mode; Weights for signal reconstruction errors; This is the preprocessed original elastic wave signal; This is the geological constraint strength coefficient; These are geological a priori constraints. This is a convolution operation.

4. The method for detecting coal thickness in boreholes based on geological constraints according to claim 3, characterized in that, The expression for the geological prior constraints is: ； In the formula, For the first The center frequency of the mode; , This represents the typical frequency boundary of coal seam reflected waves.

5. The method for detecting coal thickness in boreholes based on geological constraints according to claim 1, characterized in that, The geologically constrained adaptive variational modal empirical decomposition model is solved using the alternating direction multiplier method, including iterative update execution. The eigenmode functions of each mode are updated in the frequency domain, and their expressions are as follows: ； The expression for updating the center angular frequency is: ； The Lagrange multipliers are updated using the following expression: ； In the formula, Fourier transform; For the first The eigenmode function at the th Frequency domain representation of the next iteration; Fourier transform of the preprocessed original elastic wave signal; For the first The mode in the th ... Frequency domain representation of the next iteration; For frequency domain variables; For the first The mode in the th ... The central angular frequency of the next iteration; For the first The Lagrange multiplier spectrum of the next iteration; For A frequency band window function centered on the frequency band; For the first The Lagrange multiplier spectrum of the next iteration; It is a relaxation factor.

6. The method for detecting coal thickness in boreholes based on geological constraints according to claim 1, characterized in that, The formula for calculating coal seam thickness is: ； In the formula, Coal seam thickness; This refers to the longitudinal wave propagation velocity in the coal seam. This refers to the time difference in receiving reflected signals from the top and bottom interfaces of the coal seam.

7. A borehole elastic wave coal thickness detection system based on geological constraints, characterized in that, include: The signal preprocessing module is used to acquire the original elastic wave signal in the hole and preprocess the original elastic wave signal. The model building module is used to construct an objective functional containing bandwidth constraints, reconstruction constraints, and geological prior constraints based on the preprocessed signal, which serves as a geologically constrained adaptive variational mode empirical decomposition model. The mode decomposition module is used to solve the geologically constrained adaptive variational mode empirical decomposition model using the alternating direction multiplier method algorithm, and output the intrinsic mode functions. A reflection mode identification unit is used to identify the coal seam reflection mode based on the intrinsic mode function and extract the reception time difference of the reflected signal at the top and bottom interfaces of the coal seam. The coal thickness calculation module is used to calculate the coal seam thickness based on the time difference between the received reflected signals at the top and bottom interfaces of the coal seam and the longitudinal wave velocity of the coal seam.

8. The borehole elastic wave coal thickness detection system based on geological constraints according to claim 7, characterized in that, The signal preprocessing module includes: The mean-removing unit is used to perform mean-removing processing on the original elastic wave signal to obtain a mean-removed signal; The normalization unit is used to perform amplitude normalization processing on the mean-removed signal to obtain the preprocessed signal.

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