Coal thickness prediction method based on seismic channel wave frequency

Abstract

The invention belongs to the technical field of coal seam detection, and particularly relates to a coal thickness prediction method based on seismic channel wave frequency. According to the method, the channel wave frequency is used as a coal thickness prediction parameter, the applicability of the method is judged through the matching of a theoretical effective frequency band and an actual effective frequency band, the fixed seismic channel wave speed is determined by using a frequency dispersion curve abrupt drop point or an Erie phase extreme point, and the fixed seismic channel wave speed is used as a channel wave frequency pickup reference. And finally realizing the inversion of the thickness of the coal seam by combining the CT tomography and actual measurement data of the picked slot wave frequency data body. The coal thickness prediction method has full coal thickness applicability, and the adopted theoretical and actual effective frequency band matching evaluation improves the accuracy of full coal thickness prediction of the stope face.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of coal seam exploration, and particularly relates to a coal thickness prediction method based on seismic channel wave frequency. BACKGROUND

[0002] Seismic channel wave exploration is a geophysical prospecting method with development potential and application prospect. Seismic channel wave has frequency dispersion characteristics and is very sensitive to the change of coal seam thickness. The change of coal seam thickness can be detected by using the seismic channel wave dispersion curve. In the existing channel wave exploration coal thickness prediction method, the channel wave velocity at a certain frequency is used to construct a coal thickness quantitative prediction model according to the actual geological results. Chinese patent CN111077572A discloses a coal thickness quantitative prediction method based on transmission channel wave dispersion curve inversion. The velocity characteristics of the coal seam and the surrounding rock of the top and bottom plates are directly inverted through the analysis of the transmission channel wave dispersion curve data, and the quantitative detection result of the coal seam thickness on the path through which the transmission channel wave signal passes is obtained. Chinese patent CN112363210A discloses a coal thickness quantitative prediction method based on joint inversion of transmission channel wave velocity and attenuation coefficient. The coal thickness quantitative prediction method based on joint inversion of transmission channel wave velocity and attenuation coefficient is provided. The coal seam thickness is detected by using the joint inversion method through the analysis of the drilling data, transmission channel wave velocity and attenuation coefficient and other data. Chinese patent CN117631025A discloses an exploration method for interpreting coal seam thickness based on seismic channel wave multi-frequency joint. The method can freely select the frequency points of the dispersion travel time, and realizes fine detection of the coal seam thickness.

[0003] In the above-mentioned prior art solutions, the coal seam thickness detection is performed by tomographic imaging of the seismic channel wave velocity, and the empirical relationship between the channel wave velocity and the coal seam thickness is used for interpretation. However, in theory, the channel wave velocity and the coal seam thickness are not a one-to-one function. Within a certain coal thickness range, the channel wave velocity and the coal thickness show a negative correlation, but below the coal thickness range, the difference between the channel wave velocities of different coal thicknesses is very small, and above the coal thickness range, the corresponding relationship between the channel wave velocity and the coal thickness becomes a positive correlation. Therefore, the use of channel wave velocity can only effectively predict a certain range of coal thickness, and the application of multi-frequency channel wave velocity expands the coal thickness prediction range, but the introduction of frequency band overlap leads to velocity inversion multi-solution, which still has great limitations. In addition, the existing solutions do not consider the applicability of frequency dispersion analysis. The extraction of channel wave dispersion curve depends on the integrity of the data in the effective frequency band. If the actual observation frequency band does not match the theoretical prediction frequency band, the dispersion curve may be missing, i.e. the theoretical high frequency band or low frequency band is missing in the actual data, which leads to the inversion result of the coal seam being thicker or thinner. The existing solutions only rely on subjective judgment of the frequency band range, lack of quantitative matching standard, and the accuracy of the inversion result cannot be guaranteed. SUMMARY

[0004] In view of the deficiencies of the prior art, the technical problem to be solved by the present application is to provide a coal thickness prediction method based on seismic channel wave frequency, which utilizes the monotonic relationship between channel wave frequency and coal thickness in the full coal thickness range to realize mapping from the frequency field to the coal thickness field, and accurately predict the full coal thickness inside the mining face.

[0005] The core idea of the technical scheme of the present application is to take the matching of the theoretical effective frequency band and the actual effective frequency band as the basis, first evaluate the method applicability of the data, and under the condition that the data meets the method applicability, use the steep drop point of the dispersion curve or the extreme value point of the Eri phase to determine the fixed seismic channel wave velocity, and take the fixed seismic channel wave velocity as the picking reference of the channel wave frequency, and finally realize the coal seam thickness inversion by combining the CT tomography of the picked channel wave frequency data body and the measured data constraint. Specifically, the steps include:

[0006] Step S1, collect and arrange the exposed coal thickness data, seismic channel wave data and existing coal rock geophysical parameters of the mining face;

[0007] Step S2, determine the actual effective frequency band range using the seismic channel wave data, calculate the theoretical effective frequency band range based on the dispersion formula, and evaluate the matching degree of the actual effective frequency band range and the theoretical effective frequency band range to determine the method applicability;

[0008] Step S3, if it is determined in step S2 that the data meets the method applicability, calculate the fixed seismic channel wave velocity using the seismic channel wave group velocity formula, otherwise the process is terminated;

[0009] Step S4, extract the channel wave frequency data body according to the fixed seismic channel wave velocity obtained in step S3;

[0010] Step S5, perform CT tomography on the channel wave frequency data body obtained in step S4 to obtain a working face frequency distribution map;

[0011] Step S6, pick the frequency value of the key position in the working face frequency distribution map obtained in step S5, combine the corresponding key position measured coal thickness data to construct a "frequency-coal thickness" data set, and then fit a "frequency-coal thickness" mathematical function from the "frequency-coal thickness" data set through mathematical statistical analysis;

[0012] Step S7, substitute the frequency value of each node in the working face frequency distribution map obtained in step S5 into the "frequency-coal thickness" mathematical function obtained in step S6 to calculate the coal thickness value, and generate an initial working face coal thickness distribution map;

[0013] Step S8, constrain and correct the initial working face coal thickness distribution map obtained in step S7 using the exposed coal thickness data obtained in step S1 to generate a final working face coal thickness distribution map.

[0014] Preferably, in step S1, data on coal seam thickness revealed by tunneling and drilling at the longwall face, seismic channel wave data, and existing coal and rock geophysical parameters are collected, and the coal seam thickness d and coal seam density ρ are obtained by combining empirical formulas. c Coal seam shear wave velocity v c Density of surrounding rock ρ r and the surrounding rock shear wave velocity v r Geophysical parameters of coal and rock required for seismic trough wave dispersion analysis.

[0015] Preferably, in step S2, spectral analysis is performed on the seismic trough wave data to obtain a "frequency-energy" spectrum; time-frequency analysis is performed on the seismic trough wave data to obtain a "frequency-velocity" energy spectrum; combining the "frequency-energy" spectrum and the "frequency-velocity" energy spectrum, the frequency band where the trough wave energy is ≥ 10% of the maximum trough wave energy is determined as the effective frequency band, and the lowest and highest frequencies of the effective frequency band are denoted as f. 实min and f 实max Thus, the actual effective frequency band range of the seismic trough wave data is determined to be f. 实min ~f 实max .

[0016] Preferably, in step S2, the seismic trough wave frequency f is used as a variable, and the coal seam thickness d and coal seam density ρ obtained in step S1 are used as variables. c Coal seam shear wave velocity v c Density of surrounding rock ρ r and the surrounding rock shear wave velocity v r For quantitative purposes, the seismic trough wave group velocity formula U = F(d, ρ) is used. c , v c , ρ r , v r The group velocity is simplified to U = F(f), meaning the group velocity is simplified to a function of the single variable of frequency; the minimum value d of the exposed coal thickness is selected respectively. min and maximum value d max To quantify this, the theoretical maximum value f of the frequency required for identifying coal seam thickness using seismic channel waves was calculated using either the first-order or second-order derivative of U = F(f). 计max and theoretical minimum value f 计min Therefore, the theoretical effective frequency band range f required for seismic channel wave identification of coal seam thickness is determined. 计min ~f 计max The specific method for finding the first or second derivative of U = F(f) is as follows:

[0017] Calculation Method 1: The first-order derivative method can be used to obtain the Airy phase frequency corresponding to the Airy phase extremum point of the dispersion curve, for d=d min and d=d maxThe seismic channel wave Airy phase frequency when the first derivative of the channel wave group velocity formula is 0 is calculated, that is, the frequency f' corresponding to U' = F'(f) = 0;

[0018] Calculation Method 2: The second-order derivative method can obtain the frequency corresponding to the steep drop point of the dispersion curve, for d=d min and d=d max The frequency of the fastest change in seismic trough wave velocity when the second derivative of the trough wave group velocity formula is 0 is calculated, i.e., the frequency f'' corresponding to U'' = F''(f) = 0. When the seismic trough wave dispersion curve in the "frequency-velocity" energy spectrum is continuous, calculation method 1 or calculation method 2 is used. If the seismic trough wave dispersion curve is discontinuous, calculation method 1 is used.

[0019] Preferably, in step S2, the actual effective frequency band range f of the seismic trough wave data is compared. 实min ~f 实max and theoretical effective frequency band range f 计min ~f 计max If the theoretical effective frequency band is within the actual effective frequency band, that is (f 计min ~f 计max )∈(f 实min ~f 实max If the condition is met, the method is deemed applicable; otherwise, the process terminates.

[0020] Preferably, in step S2, the intersection frequency band of the theoretical effective frequency band range and the actual effective frequency band range is obtained, i.e. (f 实min ~f 实max )∩(f 计min ~f 计max Let ω be a weighting factor, taking values ​​from 0.6 to 0.8. If (f 实min ~f 实max )∩(f 计min ~f 计max )≥ω(f 计min ~f 计max If the condition is not met, the process will terminate.

[0021] Preferably, in step S3, d is taken as the average thickness of the exposed coal seam. The calculation method 1 or calculation method 2 described in step S2 is used, that is, by U' = F'(f) = 0 or U'' = F''(f) = 0, the Airy phase frequency f' or the frequency f'' with the fastest change in trough wave velocity is obtained. Substituting f' or f'' into the seismic trough wave group velocity formula U = F(f) in step S2, a fixed seismic trough wave velocity U0 is obtained for picking up the seismic trough wave frequency.

[0022] Preferably, in step S4, the fixed seismic trough wave velocity U0 obtained in step 3 is used as the velocity lateral baseline. On the frequency-velocity energy spectrum obtained in step S2, the frequency corresponding to the point with the strongest trough wave energy at velocity U0 is picked up, thereby obtaining the seismic trough wave frequency data volume between different shot points and receiver points.

[0023] Preferably, in step S5, CT tomography is performed on the seismic channel wave frequency data volumes between different shot points and receiver points obtained in step S4. Based on the channel wave propagation path, a ray model of the shot point-receiver point pair is established. The frequency values ​​of each node are inverted using SIRT synchronous iterative reconstruction technology or LSQR algorithm. Then, Kriging interpolation is performed on the inversion results to generate a continuous frequency distribution map, i.e., the working face frequency distribution map A. f。

[0024] Preferably, in step S6, the working surface frequency distribution map A obtained in step S5... f Frequency values ​​at key points such as transport roadways, return airways, and cut-off statistical points are picked up. Combined with the exposed coal thickness values ​​at the above key points, the picked frequency values ​​and exposed coal thickness values ​​are paired to construct a "frequency-coal thickness" dataset. Then, the "frequency-coal thickness" dataset is fitted with a mathematical function through linear, polynomial, exponential, or logarithmic models to obtain the mathematical function between "frequency" and "coal thickness".

[0025] The beneficial effects obtained by adopting the above technical solution are as follows:

[0026] (1) By utilizing the monotonic functional relationship between the channel wave frequency and the coal thickness, the full coal thickness of the longwall face was predicted by using the channel wave frequency as the coal thickness prediction parameter.

[0027] (2) The applicability of the method is evaluated based on the degree of matching between the theoretical frequency band and the actual frequency band, so as to avoid the absence of theoretical high frequency band or low frequency band in actual data, which would lead to the coal seam inversion result being too thick or too thin, thus improving the accuracy of coal thickness prediction. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the process flow of the method of the present invention.

[0029] Figure 2 This is a flowchart illustrating the feasibility analysis of the method of the present invention.

[0030] Figure 3 This is a frequency distribution diagram of the working surface.

[0031] Figure 4 This is a map showing the coal thickness distribution at the working face. Detailed Implementation

[0032] The technical solution of the present invention will now be described more clearly and completely with reference to the accompanying drawings.

[0033] like Figure 1 The process is as follows: In the working face transport roadway, return air roadway, or cut-off section, excitation sources, such as explosive sources or vibratory hammers, are arranged at 10m intervals to excite channel wave signals. Detectors are arranged at 10m intervals in the opposite roadway or cut-off section to record channel wave signals. The data recording sampling rate is ≥1kHz, and the recording duration is ≥1s, ensuring coverage of the main channel wave frequency band. Coal thickness measurement points are arranged every 5–20m in the roadway to observe the coal seams exposed during roadway excavation. Unexposed coal seams are also explored using boreholes. The coal thickness at each measurement point is statistically analyzed, and the minimum value d is calculated. min Maximum value d max and average values. Density ρ of collected coal. 煤 and transverse wave velocity V s,煤 Density ρ of the surrounding rock 岩 and transverse wave velocity V s,岩 Rock physical parameters, etc.

[0034] Fast Fourier Transform (FFT) is performed on seismic trough wave data recorded by a single shot to obtain a frequency-energy spectrum. The main frequency band energy concentration region is identified to determine the effective frequency band. The frequency band where the trough wave energy is ≥ 10% of the maximum trough wave energy is denoted as f. 实min ~f 实max This refers to the actual effective frequency band range of the working surface.

[0035] Time-frequency analysis was performed on the seismic trough wave data to generate a frequency-velocity energy spectrum. The dispersion curve of the trough wave was traced in the energy spectrum to identify the Airy phase, that is, the frequency-velocity pair corresponding to the point of strongest energy. In this case, it was found that the dispersion curve of the seismic trough wave in the frequency-velocity energy spectrum was discontinuous.

[0036] The theoretical effective frequency band range f is calculated below using the dispersion formula. 计min ~f 计max The simplified formula for slot wave dispersion is as follows:

[0037]

[0038] The theoretical effective frequency band range can be calculated using the following two methods: when the seismic trough wave dispersion curve in the "frequency-velocity" energy spectrum is continuous, use calculation method 1 or calculation method 2; if the seismic trough wave dispersion curve is discontinuous, use calculation method 1.

[0039] Calculation Method 1: Calculate the Airy phase frequency of the seismic trough wave when the first derivative of the dispersion formula is 0, that is, the frequency f' corresponding to U' = F'(f) = 0;

[0040] Differentiate U=F(f) and set U′=F′(f)=0 to obtain the Airy phase frequency f′;

[0041] Let d=d min Calculate the theoretical minimum maximum frequency f 计max ;

[0042] Let d=d max Calculate the theoretical maximum frequency f 计mmn ;

[0043] Calculation Method 2: Calculate the frequency at which the seismic trough wave velocity changes the fastest when the second derivative of the dispersion formula is 0, i.e., the frequency f'' corresponding to U'' = F''(f) = 0;

[0044] Since the dispersion curve of the seismic trough wave in the "frequency-velocity" energy spectrum of this embodiment is discontinuous, calculation method 1 is used to determine the theoretical effective frequency band range f of the frequency required for the seismic trough wave to identify the coal seam thickness. 计min ~f 计max The coal thickness is defined as the minimum coal thickness d revealed by boreholes in the transport roadway, return airway, cut-off roadway, bottom drainage roadway, and inside the working face. min Using the simplified seismic trough wave dispersion formula U = F(f), and setting U' = F'(f) = 0, the Airy phase frequency f' of the seismic trough wave is obtained, which is the theoretical maximum value of the frequency required for the seismic trough wave to identify the coal seam thickness. 计max Similarly, the coal thickness is taken as the maximum value d of the coal thickness revealed by boreholes in the transport roadway, return airway, cut-off roadway, bottom drainage roadway, and inside the working face. max The theoretical minimum value f of the frequency required for seismic channel wave identification of coal seam thickness was obtained. 计min Therefore, the theoretical effective frequency band f of the frequency required for identifying coal seam thickness using seismic channel waves was obtained. 计min ~f 计max .

[0045] like Figure 2 As shown, there are two conditions for determining the matching between the actual effective frequency band and the theoretical effective frequency. If neither of the following two conditions is met, then this method is deemed inapplicable:

[0046] (1)(f) 计min ~f 计max )⊆(f 实min ~f 实max )

[0047] (2)(f) 实min ~f 实max )∩(f 计min ~f 计max )≥ω(f 计min ~f 计max )

[0048] Where ω is the weighting factor, with a value of 0.6 to 0.8. The specific value depends on the quality of the seismic channel wave data and the accuracy and precision of the coal seam thickness prediction. If the quality of the seismic channel wave data is good and the accuracy and precision of the coal seam thickness prediction are required to be high, then ω takes a higher value, and vice versa.

[0049] The data in this embodiment satisfies (f) 实min ~f 实max )∩(f 计min ~f 计max )≥0.75(f 计min ~f 计max This method is applicable if the intersection frequency band of the theoretical frequency band and the effective frequency band of the seismic trough wave data is not less than 0.75 times the theoretical frequency band.

[0050] Taking d as the average thickness of the exposed coal seam, using the simplified seismic trough wave dispersion formula U = F(f), and setting U' = F'(f) = 0, we obtain the seismic trough wave Airy phase frequency f'. Substituting f' into U = F(f), we obtain the fixed seismic trough wave velocity U0 used to pick up the seismic trough wave frequency.

[0051] Using a fixed seismic trough wave velocity U0 as the lateral velocity baseline, the frequency corresponding to the point of strongest trough wave energy at velocity U0 is picked on the "frequency-velocity" energy spectrum of time-frequency analysis, thereby obtaining the seismic trough wave frequency data volume between different shot points and receiver points [f].

[0052] CT tomography was performed on the seismic channel wave frequency data volume [f] between different shot points and receiver points. The working face was divided into a 10m×10m grid. Based on the channel wave propagation path, a ray model of the shot point-receiver pair was established. The frequency values ​​of each grid node were inverted using SIRT (Simultaneous Iterative Reconstruction Technique) or LSQR algorithm. Then, Kriging interpolation was performed on the inversion results to generate a continuous working face frequency distribution map A. f like Figure 3 As shown, a pseudo-color plot is used to display the frequency distribution, with blue representing high frequency (thin coal seam) and red representing low frequency (thick coal seam).

[0053] exist Figure 3 Frequency distribution diagram A of the working surface is shown. f The coordinates of key locations such as the haulage roadway, return airway, and cut-off point are located, and the frequency value f corresponding to each key location coordinate point is read. 巷 , will f 巷 Compared with the measured coal thickness d 巷 Pairing is performed to construct a "frequency-coal thickness" dataset. Then, a mathematical function is fitted to the "frequency-coal thickness" dataset using linear, polynomial, exponential, or logarithmic models to obtain the mathematical function relationship between "frequency" and "coal thickness".

[0054] WillFigure 3 Working face frequency distribution diagram A f The frequency value of each grid node is substituted into the "frequency-coal thickness" mathematical function to calculate the coal thickness d, generating the initial coal thickness distribution map A. d0 In the initial coal thickness distribution map A d0 The measured coal thickness of the transport roadway, return air roadway, and cut-off section is forcibly assigned to the corresponding grid node values. Then, Gaussian filtering is applied to the corrected coal thickness map to eliminate local outliers, generating a result as shown below. Figure 4 The final coal seam thickness distribution map A shown below d The resolution reaches 10m×10m.

Claims

1. A method for predicting coal thickness based on seismic channel wave frequency, characterized in that, Includes the following steps: Step S1: Collect and organize the exposed coal thickness data, seismic channel wave data and existing coal and rock geophysical parameters of the longwall mining face; Step S2: Determine the actual effective frequency band range using seismic trough wave data, calculate the theoretical effective frequency band range based on the dispersion formula, and evaluate the matching degree between the actual effective frequency band range and the theoretical effective frequency band range to determine the applicability of the method. Step S3: If the data determined in step S2 meets the applicable conditions of the method, the fixed seismic trough wave velocity is calculated using the seismic trough wave group velocity formula; otherwise, the process terminates. Step S4: Extract the trough wave frequency data volume based on the fixed seismic trough wave velocity obtained in step S3. Step S5: Perform CT tomography on the slot wave frequency data volume obtained in step S4 to obtain the frequency distribution map of the working surface. Step S6: Pick the frequency values ​​of key locations from the frequency distribution map of the working face obtained in step S5, combine them with the measured coal thickness data of the corresponding key locations, construct a "frequency-coal thickness" dataset, and then fit the mathematical function of "frequency-coal thickness" from the "frequency-coal thickness" dataset through mathematical statistical analysis. Step S7: Substitute the frequency value of each node in the working face frequency distribution map obtained in step S5 into the "frequency-coal thickness" mathematical function obtained in step S6 to calculate the coal thickness value and generate the initial working face coal thickness distribution map. Step S8: Use the exposed coal thickness data obtained in step S1 to constrain and correct the initial working face coal thickness distribution map obtained in step S7, and generate the final working face coal thickness distribution map.

2. The coal thickness prediction method based on seismic trough wave frequency according to claim 1, characterized in that, In step S1, data on coal seam thickness revealed by tunneling and drilling at the longwall face, seismic channel wave data, and existing coal and rock geophysical parameters are collected. Combined with empirical formulas, the coal seam thickness d and coal seam density ρ are obtained. c Coal seam shear wave velocity v c Density of surrounding rock ρ r and the surrounding rock shear wave velocity v r Geophysical parameters of coal and rock required for seismic trough wave dispersion analysis.

3. The coal thickness prediction method based on seismic trough wave frequency according to claim 2, characterized in that, In step S2, spectral analysis is performed on the seismic trough wave data to obtain a "frequency-energy" spectrum; time-frequency analysis is performed on the seismic trough wave data to obtain a "frequency-velocity" energy spectrum; combining the "frequency-energy" spectrum and the "frequency-velocity" energy spectrum, the frequency band where the trough wave energy is ≥ 10% of the maximum trough wave energy is determined as the effective frequency band, and the lowest and highest frequencies of the effective frequency band are denoted as f. 实min and f 实max Thus, the actual effective frequency band range of the seismic trough wave data is determined to be f. 实min ~f 实max .

4. The coal thickness prediction method based on seismic trough wave frequency according to claim 3, characterized in that, In step S2, the seismic trough wave frequency f is used as a variable, along with the coal seam thickness d and coal seam density ρ obtained in step S1. c Coal seam shear wave velocity v c Density of surrounding rock ρ r and the surrounding rock shear wave velocity v r For quantitative purposes, the seismic trough wave group velocity formula U = F(d, ρ) is used. c , v c , ρ r ,v r The group velocity is simplified to U = F(f), that is, the group velocity is simplified to a function of the single variable of frequency; Select the minimum value d of the exposed coal thickness respectively min and maximum value d max To quantify this, the theoretical maximum value f of the frequency required for identifying coal seam thickness using seismic channel waves was calculated using either the first-order or second-order derivative of U = F(f). 计max and theoretical minimum value f 计min Therefore, the theoretical effective frequency band range f required for seismic channel wave identification of coal seam thickness is determined. 计min ~f 计max The specific method for finding the first or second derivative of U = F(f) is as follows: Calculation Method 1: The first-order derivative method can be used to obtain the Airy phase frequency corresponding to the Airy phase extremum point of the dispersion curve, for d=d min and d=d max The seismic channel wave Airy phase frequency when the first derivative of the channel wave group velocity formula is 0 is calculated, that is, the frequency f' corresponding to U' = F'(f) = 0; Calculation Method 2: The second-order derivative method can be used to obtain the frequency corresponding to the steep drop point of the dispersion curve, for d=d min and d=d max The frequency at which the seismic trough wave velocity changes the fastest when the second derivative of the trough wave group velocity formula is 0 is calculated, that is, the frequency f'' corresponding to U'' = F''(f) = 0.

5. The coal thickness prediction method based on seismic trough wave frequency according to claim 4, characterized in that, In step S2, the actual effective frequency band range f of the seismic trough wave data is compared. 实min ~f 实max and theoretical effective frequency band range f 计min ~f 计max If the theoretical effective frequency band is within the actual effective frequency band, that is (f 计min ~f 计max )∈(f 实min ~f 实max If the condition is met, the method is deemed applicable; otherwise, the process terminates.

6. The coal thickness prediction method based on seismic trough wave frequency according to claim 4, characterized in that, In step S2, the intersection frequency band of the theoretical effective frequency band and the actual effective frequency band is calculated, i.e., (f 实min ~f 实max )∩(f 计min ~f 计max Let ω be a weighting factor, taking a value from 0.6 to 0.

8. If (f 实min ~f 实max )∩(f 计min ~f 计max )≥ω(f 计min ~f 计max If the condition is not met, the process will terminate.

7. The coal thickness prediction method based on seismic trough wave frequency according to claim 5 or claim 6, characterized in that, In step S3, d is taken as the average thickness of the exposed coal seam. Calculation method 1 or calculation method 2 described in step S2 is used, i.e., by U' = F'(f) = 0 or U'' = F''(f) = 0, the Airy phase frequency f' or the frequency f'' with the fastest change in trough wave velocity is obtained. Substituting f' or f'' into the seismic trough wave group velocity formula U = F(f) in step S2, a fixed seismic trough wave velocity U0 is obtained for picking up the seismic trough wave frequency.

8. The coal thickness prediction method based on seismic trough wave frequency according to claim 7, characterized in that, In step S4, the fixed seismic trough wave velocity U0 obtained in step 3 is used as the velocity lateral baseline. On the "frequency-velocity" energy spectrum obtained in step S2, the frequency corresponding to the point with the strongest trough wave energy at velocity U0 is picked out, thereby obtaining the seismic trough wave frequency data volume between different shot points and receiver points.

9. The coal thickness prediction method based on seismic trough wave frequency according to claim 8, characterized in that, In step S5, CT tomography is performed on the seismic trough wave frequency data volumes between different shot points and receiver points obtained in step S4. Based on the trough wave propagation path, a ray model of the shot point-receiver point pair is established. The frequency values ​​of each node are inverted using SIRT synchronous iterative reconstruction technology or LSQR algorithm. Then, Kriging interpolation is performed on the inversion results to generate a continuous frequency distribution map, i.e., the working face frequency distribution map A. f。 10. The coal thickness prediction method based on seismic trough wave frequency according to claim 9, characterized in that, In step S6, the working surface frequency distribution map A obtained in step S5 is described. f Frequency values ​​at key points such as transport roadways, return airways, and cut-off statistical points are picked up. Combined with the exposed coal thickness values ​​at the above key points, the picked frequency values ​​and exposed coal thickness values ​​are paired to construct a "frequency-coal thickness" dataset. Then, the "frequency-coal thickness" dataset is fitted with a mathematical function through linear, polynomial, exponential, or logarithmic models to obtain the mathematical function between "frequency" and "coal thickness".

Images