Active and passive double-source combined shock wave CT inversion method and rock burst early warning method

Abstract

The invention discloses a shock wave CT inversion method and a rock burst early warning method based on active and passive double-source combination. The method comprises the following steps: 1, constructing a probability non-uniform initial velocity distribution model and a working face initial grid model of shock wave longitudinal waves and / or transverse waves; 2, travel time tomography forward modeling is carried out, and theoretical travel time and residual errors of theoretical longitudinal waves and / or transverse waves are calculated; 3, solving the gradient of the target function of the travel time residual; 4, carrying out seismic wave travel time tomography inversion, enabling the residual error and the RMS residual error to reach a stable state through the iterative adjustment of the seismic source and the velocity parameters of the longitudinal wave and / or transverse wave of the seismic wave, and outputting the final seismic source parameter and wave velocity; and 5, verifying the feasibility and accuracy of the inversion model through active CT numerical simulation, passive CT numerical simulation and active and passive double-source combined CT numerical simulation experiments. Working face wave velocity distribution obtained through inversion is more accurate, and the efficiency and accuracy of the shock wave CT technology are improved.

Description

Technical Field

[0001] The invention relates to an active-passive dual-source combined shock wave CT inversion method and a rock burst early warning method. Background Art

[0002] Vibration wave CT technology is a key technology in the field of mine safety monitoring. By analyzing the changes in the propagation speed of vibration waves in coal and rock masses and inverting the distribution of underground stress fields, the technology can more accurately reflect the regional stress field, thereby predicting the occurrence of dynamic disasters such as rock bursts, providing a scientific basis for the prediction of microseismic events in space and future periods, and is of great significance for guiding mine safety production. Although vibration wave CT technology has shown certain advantages in detecting the risk of rock bursts in coal mines, its application also faces several challenges:

[0003] First of all, with the continuous deepening of coal resource exploitation, deep mining has become an important trend in the coal industry. However, with the increase in mining depth, the ground stress on the coal mine rock mass also increases significantly. The working conditions of the coal mine underground are more complicated and are greatly affected by the working environment. In addition, the coal seam contains many factors that affect the propagation of seismic waves. Therefore, when performing CT scanning on the coal rock layer, it is often impossible to scan all the rock layers, and different inversion models often need to be established during inversion.

[0004] Secondly, the large amount of coal and rock CT data and slow processing speed are also important factors restricting the application of vibration wave CT technology in coal mine rock burst risk detection.

[0005] In summary, although the shock wave CT technology has a good detection effect, it also has certain limitations. In particular, different inversion models need to be established during inversion. In addition, the large amount of data and slow processing speed have seriously restricted the application of shock wave CT technology in rock burst warning. Summary of the invention

[0006] In view of the above problems, the present invention provides an inversion method based on active and passive dual-source combined shock wave CT and an impact ground pressure early warning method, develops an inversion model and algorithm suitable for active and passive dual-source combined CT technology, realizes the correction of single shock wave CT imaging results, makes the inverted working face wave velocity distribution more accurate, improves the efficiency and accuracy of shock wave CT technology, and provides scientific guidance for pressure relief measures such as large-diameter drilling and coal rock blasting.

[0007] In order to achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions:

[0008] A method for inversion of active and passive dual-source combined shock wave CT includes the following steps:

[0009] Step 1: construct a probabilistic non-uniform initial velocity distribution model of longitudinal and / or transverse waves of the shock wave according to the structural characteristics of the working face, establish an initial grid model of the working face, and set the positions of the active and passive seismic sources and the positions of the seismic sensors for detecting the active and passive shock waves;

[0010] Step 2, using each initial model obtained in step 1 to perform travel time tomography forward modeling, and calculating the theoretical travel time and residual of the theoretical longitudinal wave and / or shear wave;

[0011] Step 3: According to the theoretical travel time and residual value obtained in step 2, the gradient of the objective function of the residual of the shock wave travel time is solved;

[0012] Step 4: Performing seismic wave travel time tomography inversion on the gradient of the objective function obtained in step 3, making the residual and RMS residual reach a stable state by iteratively adjusting the velocity parameters of the source and the longitudinal and / or shear waves of the seismic wave, and outputting the final source parameters and wave velocity;

[0013] Step 5: Verify the feasibility and accuracy of the inversion model through active CT numerical simulation, passive CT numerical simulation, and active and passive dual-source combined CT numerical simulation experiments: When the active CT numerical simulation, passive CT numerical simulation, and active and passive dual-source combined CT numerical simulation all meet the feasibility and accuracy, the inversion ends.

[0014] Preferably, in step 1, the step of constructing a probabilistic non-uniform initial velocity distribution model comprises:

[0015] Step 101, establishing an initial coal mine tunnel model that simulates the actual situation of the coal mine tunnel at the working face, and preliminarily calculating the observed wave velocity of each longitudinal wave and / or transverse wave of the shock wave by dividing the distance by the duration according to the distance between the active and passive seismic sources and the seismic pickup sensor and the initial arrival time of the shock wave;

[0016] Step 102, using a random number algorithm to select a value within the observed wave velocity range as a probabilistic non-uniform initial velocity and assigning it to an initial shock wave travel time tomography inversion model;

[0017] Step 103, performing inversion numerical simulation, and verifying the accuracy of the initial velocity distribution model through active CT numerical simulation, passive CT numerical simulation, and active and passive dual-source combined CT numerical simulation;

[0018] Step 104: When the active CT numerical simulation, the passive CT numerical simulation, and the active and passive dual-source combined CT numerical simulation all meet the accuracy requirements, the inversion ends, and the obtained initial velocity distribution model is the probabilistic non-uniform initial velocity distribution model of the shock wave longitudinal wave and / or shear wave.

[0019] Preferably, in step 3, the specific calculation steps include:

[0020] Step 301, define the shock wave travel time residual E as the objective function of the travel time difference:

[0021]

[0022] Where E(c, t0, s) is the residual of the travel time of the shock wave; c is the propagation speed of the longitudinal and / or transverse waves of the shock wave, t0 is the starting time of the earthquake source, and s is the propagation distance of the shock wave; T(c, g; t0, s x ,s y ,s z ) is the earthquake source location (s x ,s y ,s z ) is the theoretical time it takes for the vibration wave to propagate to the vibration sensor g; T(c, g; t0, s x ,s y ,s z )=T(c,g;s x ,s y ,s z )+t0,(s x ,s y ,s z ) is the coordinate of the earthquake source location, T * (g) is the observed propagation time of the seismic pickup sensor g relative to the chosen zero time;

[0023] Step 302: If the velocity c of the longitudinal and / or transverse wave propagation and the source parameter (s x ,s y ,s z , t0) causes the calculated arrival time T of the transmitting signal source to change accordingly, so the change of the travel time residual is for:

[0024]

[0025] Step 303, the partial derivative of the residual E with respect to the position, origin time and speed change is:

[0026]

[0027] Among them, s i =s x ,s y or z , λ is the Lagrange multiplier;

[0028] Step 304: Passing at the border Initialize λ with the boundary value and set the remaining grid points to zero;

[0029] Step 305: Alternately scan the entire domain, using Update the λ value of non-boundary positions;

[0030] Step 306: For a given convergence criterion ε>0, check the criterion ||λ point by point n+1 -λ n || L1 ≤ε to check convergence;

[0031] Step 307: When convergence is satisfied, the corresponding The value is used as the gradient of the objective function;

[0032] in, is the normal vector perpendicular to the surface of the vibration sensor, is the gradient, T is the calculated arrival time of the transmitting signal source, λ is the Lagrange multiplier, T° refers to the propagation time of the longitudinal and / or shear waves of the vibration waves observed by the vibration pickup sensor, Ω is the vibration pickup sensor surface, x∈Ω refers to the position x on the vibration pickup sensor surface, ||λ n+1 -λ n || L1 is the Lagrange multiplier matrix L 1 norm, indicating that the algorithm converges when the rate of change of the Lagrange multiplier is negative, λ n+1 is the value of λ obtained at the n+1th iteration, λ n is the value of λ obtained at the nth iteration.

[0033] Preferably, in step 4, the step of outputting the final source parameters and wave velocity is:

[0034] When the shock wave travels, the residual E and the RMS residual If a stable state is reached, the inversion is judged to be converged, and the final source parameters and wave velocity are output, where N is the number of observed vibrations; otherwise, step 302 is entered for iteration.

[0035] Preferably, the probabilistic non-uniform initial velocity ranges from 1000 m / s to 6500 m / s.

[0036] Correspondingly, a rock burst warning method uses the inversion model obtained by the active and passive dual-source combined shock wave CT inversion method as described above to perform rock burst warning.

[0037] The beneficial effects of the present invention are:

[0038] First, the active and passive dual-source joint CT inversion method of the present invention improves the limitations of a single imaging method, and adopts an adjoint state algorithm based on rapid scanning to improve the convergence speed of the inversion model and the accuracy of the inversion results, providing a powerful reference for the prediction of coal mine rock burst hazards.

[0039] Second, the probabilistic non-uniform initial velocity distribution model of the present invention has high accuracy and strong practicality, and plays an excellent role in optimizing the coal mine vibration wave tomography technology. The velocity distribution obtained by inversion is closer to the actual situation, and can better predict the high-stress dangerous areas of the mining face, providing a basis for the prediction and prevention of rock burst risks.

[0040] Third, the present invention directly obtains the objective function gradient, adopts the gradient method and nonlinear optimization algorithm, avoids the traditional direct solution of the Fréchet equation, and avoids the shortcomings of its slow operation speed and unsuitability for large-scale model data processing.

[0041] Fourth, the present invention integrates the two major advantages of active CT in detection accuracy and passive CT in detection timeliness, and eliminates to the maximum extent the deficiencies and shortcomings of active CT inversion technology in detection timeliness and its detection process in production, as well as the deficiencies and shortcomings of passive CT inversion technology in inversion accuracy, thereby realizing real-time detection inversion of fast short-interval continuous wave velocity. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is an overall flow chart of the present invention based on the active and passive dual-source combined shock wave CT inversion method;

[0043] Figure 2 This is a rendering of the coal mine tunnel model of the present invention;

[0044] Figure 3 1. It is a schematic diagram comparing the effects of the uniform initial velocity distribution and the probabilistic non-uniform initial velocity distribution model of the present invention;

[0045] Figure 4 is a schematic diagram for comparing the effects of the shock wave tomography simulation of the present invention;

[0046] Figure 5 : is a layout diagram of artificial blasting points and vibration pickup sensors on a working face according to an embodiment of the present invention;

[0047] Figure 6 is a distribution diagram of the probabilistic non-uniform initial velocity values ​​of the working face according to an embodiment of the present invention;

[0048] Figure 7 is a wave velocity contour map of the working face vibration wave tomography of an embodiment of the present invention;

[0049] Figure 8 It is the model and effect diagram of the active CT inversion numerical simulation of the present invention;

[0050] Fig. 9 It is the model and effect diagram of the passive CT inversion numerical simulation of the present invention;

[0051] Fig.10It is the model and effect diagram of the active and passive dual-source combined CT inversion numerical simulation of the present invention. DETAILED DESCRIPTION

[0052] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0053] like Figure 1 As shown, a method for inversion of active and passive dual-source combined shock wave CT includes the following steps:

[0054] Step 1: construct a probabilistic non-uniform initial velocity distribution model of longitudinal and / or transverse vibration waves according to the structural characteristics of the working face, establish an initial grid model of the working face, and set the positions of active and passive seismic sources and the positions of seismic sensors for detecting active and passive vibration waves, where the artificial seismic source corresponds to the active seismic source and the natural seismic source corresponds to the passive seismic source.

[0055] As an important geophysical method, shock wave tomography technology analyzes the difference in the propagation speed of shock waves in different media, measures the propagation time of shock waves in coal and rock mass, and inverts the velocity structure inside the coal and rock mass. It has good applicability and accuracy for assessing the risk of rock burst. This method can reveal the stress concentration areas and high-risk areas inside the coal and rock mass, and provide a scientific basis for the prediction and prevention of rock burst. Studies have shown that the speed of shock waves is closely related to the stress state of coal and rock mass, and high wave velocity areas often correspond to high stress areas and potential areas for rock burst.

[0056] In the prior art, there are relatively few studies on the optimization of the initial velocity model of shock wave tomography. Most inversion studies use the mean velocity model, which assumes that the initial velocity remains unchanged. However, the velocity of shock waves is different when passing through different rock masses, and the simple mean velocity model cannot simulate the real geological environment of the coal mine working face. Therefore, in order to improve the accuracy of shock wave tomography technology, it is necessary to further optimize the initial velocity model to reflect the velocity changes of shock waves passing through different coal and rock masses, so as to adapt to the complex geological and production environment of coal mines and improve the accuracy of rock burst risk prediction.

[0057] The principle of CT inversion is to invert and reconstruct the velocity model through the distance and the first arrival time received. The initial velocity model is unknown, and the setting of the initial velocity model is particularly important for the inversion accuracy. The closer the initial velocity model is to the velocity model in the actual situation, the more accurate the accuracy after inversion will be. In this regard, the present invention proposes a probabilistic non-uniform initial velocity distribution model of longitudinal and / or transverse waves of vibration waves constructed according to the structural characteristics of the strata of the working face, and the construction steps are as follows:

[0058] Step 101, establish an initial coal mine tunnel model that simulates the actual situation of the coal mine tunnel at the working face, and preliminarily calculate the observed wave velocity of each vibration wave longitudinal wave (P wave) and / or transverse wave (S wave) by dividing the distance by the duration according to the distance between the active and passive seismic sources and the seismic pickup sensor and the initial arrival time of the vibration wave.

[0059] The purpose of using coal mine tunnel models is to better reflect the actual situation of the mine working face, such as Figure 2 As shown in the figure, a low-velocity area of ​​an elliptical cylinder in the XZ direction is set in the middle of the deployment range of the seismic sensor. The radius of the short semi-axis of the ellipse is 20m, the radius of the long semi-axis is 30m, and the height of the elliptical cylinder is 100m. The velocity inside the elliptical cylinder is set to 4500m / s as a low-velocity area to simulate the velocity anomaly, while the velocity of the remaining part is set to 5500m / s as a high-velocity area. This is used as the initial velocity model to simulate the internal conditions of the tunnel, and then a control experiment is carried out. According to the distance between the artificial or natural seismic source and the seismic sensor and the initial arrival time of the seismic wave, the observed velocity of each seismic wave is preliminarily calculated by dividing the distance by the duration.

[0060] Step 102: using a random number algorithm to select a value within the observed wave velocity range as a probabilistic non-uniform initial velocity and assign it to an initial shock wave travel time tomography inversion model.

[0061] It is known that the acoustic wave velocity of coal seams is between 1990 and 3000 m / s, and the acoustic wave velocity of surrounding rocks is between 2300 and 5100 m / s. In order to better reduce the error caused by the vibration wave received by the station, the range of randomly extracted wave velocities is set to 1000 m / s-6500 m / s. After screening, the wave velocities that are too high or too low due to some reasons can be removed. Under real geological conditions, the extracted wave velocities are generally in line with the normal distribution. The generated mean velocity model (i.e., equivalued uniform distribution model) and probabilistic non-uniform velocity model are as follows: Figure 3 shown.

[0062] Step 103, performing inversion numerical simulation on the inversion model obtained in step 102, and verifying the accuracy of the initial velocity distribution model through active CT numerical simulation, passive CT numerical simulation, and active and passive dual-source combined CT numerical simulation.

[0063] Step 104: When the active CT numerical simulation, the passive CT numerical simulation, and the active and passive dual-source combined CT numerical simulation all meet the accuracy requirements, the inversion ends, and the obtained initial velocity distribution model is the probabilistic non-uniform initial velocity distribution model of the shock wave longitudinal wave and / or shear wave.

[0064] By comparing the simulation results of the uniform velocity distribution model in the three tomography methods in step 103, the superiority of the probabilistic non-uniform velocity model in terms of restoration degree is verified, such as Figure 4 As shown, where:

[0065] In the active CT numerical simulation results, the residual of the uniform velocity distribution model decreased from 213.104 to 0.322, and the RMS decreased from 0.703 to 0.027; while the residual of the non-uniform initial velocity model decreased from 195.716 to 0.239, and the RMS decreased from 0.670 to 0.023. Under the same number of iterations, whether from the initial value of the residual or the convergence effect of the final iteration, the value of the non-uniform initial velocity model is smaller than the mean initial velocity model, and the effect is better.

[0066] In the passive CT numerical simulation results, the residual of the uniform velocity distribution model decreased from 253.445 to 6.667, and the RMS decreased from 0.3190 to 0.0517; while the residual of the non-uniform initial velocity model decreased from 190.631 to 1.831, and the RMS decreased from 0.2766 to 0.0271. Under the same number of iterations, whether from the initial value of the residual or the convergence effect of the final iteration, the value of the non-uniform initial velocity model is smaller than that of the mean initial velocity model, and the effect is better.

[0067] In the numerical simulation results of active and passive dual-source CT, the residual of the uniform velocity distribution model decreased from 167.995 to 3.297, and the RMS decreased from 0.2597 to 0.0364; while the residual of the non-uniform initial velocity model decreased from 119.736 to 2.3551, and the RMS decreased from 0.2023 to 0.0283. The residual iteration effect of the non-uniform initial velocity model is better than that of the mean initial velocity model.

[0068] Example application A coal mine working face is selected as the research object, such as Figure 5 The following figure shows the layout of the tunnels at the working face. Figure 5 The positions of artificial shot points and seismic sensors (i.e., geophones) are shown in the figure. Shot points are arranged on the lower wall of the upper lane of the working face, with a spacing of 18m between the shot points, and a total of 33 shot points are arranged. Geophones are arranged on the upper wall of the lower lane, with a spacing of 9m (15 times the bolt spacing), and a total of 66 receiving points are arranged. The initial velocity model of the studied working face is established through the initial velocity distribution optimization model of the shock wave tomography of the present invention, and the velocity abnormal area of ​​the working face is analyzed by inversion through active CT, passive CT, and active and passive dual-source CT. Finally, the accuracy of the inversion result is verified by the distribution of microseismic sources of mining.

[0069] The initial wave velocity model used in the inversion is based on the probability non-uniform initial velocity distribution. Most of the shock waves generated by the shot point pass through the single medium of the coal seam and are received by the sensor. The non-uniform initial wave velocity range is set to 1000m / s-6500m / s. The wave velocity distribution is as follows: Figure 6 shown.

[0070] like Figure 7 As shown in FIG. 1 , according to the initial velocity model, the adjoint state method based on FSM (fast scanning method) is used to perform active, passive, and active-passive dual-source joint CT inversion on the model of the embodiment, and the high wave velocity area above 3800 m / s has been Figure 7 It is pointed out that the earthquake sources induced in the mining process are basically distributed in the high wave velocity area and the wave velocity change area, and the active and passive dual-source joint CT inversion can correct the passive CT inversion wave velocity image, which is more consistent with the distribution of mining earthquake sources.

[0071] The initial velocity distribution optimization model of shock wave tomography involved in the present invention improves the limitation that the initial velocity distribution selected for inversion is mostly the mean distribution model, so that the wave velocity distribution is more consistent with the actual mine geological environment, and the inversion result is accurately applied to various shock wave tomography schemes of coal mine tunnel models. That is, through this method, the wave velocity distribution of the working face obtained by inversion can be made more accurate and closer to the actual situation of the working face, which can provide scientific guidance for the implementation of pressure relief measures in rock burst mines, and has good practical significance.

[0072] Step 2, using each initial model obtained in step 1 to perform travel time tomography forward modeling, and calculating the theoretical travel time and residual of the theoretical longitudinal wave and / or shear wave;

[0073] Step 3: According to the theoretical travel time and residual value obtained in step 2, the gradient of the objective function of the residual of the shock wave travel time is solved;

[0074] Step 4: Performing seismic wave travel time tomography inversion on the gradient of the objective function obtained in step 3, making the residual and RMS residual reach a stable state by iteratively adjusting the velocity parameters of the source and the longitudinal and / or shear waves of the seismic wave, and outputting the final source parameters and wave velocity;

[0075] Step 5: Verify the feasibility and accuracy of the inversion model through active CT numerical simulation, passive CT numerical simulation, and active and passive dual-source combined CT numerical simulation experiments: When the active CT numerical simulation, passive CT numerical simulation, and active and passive dual-source combined CT numerical simulation all meet the feasibility and accuracy, the inversion ends.

[0076] In step 1: establish the initial grid model of the working face, and set the positions of the active and passive seismic sources and the positions of the seismic sensors for detecting the active and passive vibration waves: for example, establish a 3D rectangular model simulating underground rock conditions, with a size of 60m×10m×100m, in which 30 seismic sensors with good azimuth coverage are arranged.

[0077] Preferably, in step 3, the specific calculation steps include:

[0078] Step 301, define the shock wave travel time residual E as the objective function of the travel time difference:

[0079]

[0080] Where E(c, t0, s) is the residual of the travel time of the shock wave; c is the propagation speed of the longitudinal and / or transverse waves of the shock wave, t0 is the starting time of the earthquake source, and s is the propagation distance of the shock wave; T(c, g; t0, s x ,s y ,s z ) is the earthquake source location (s x ,s y ,s z ) is the theoretical time it takes for the vibration wave to propagate to the vibration sensor g; T(c, g; t0, s x ,s y ,s z )=T(c,g;s x ,s y ,s z )+t0,(s x ,s y ,s z ) is the coordinate of the earthquake source location, T * (g) is the observed propagation time of the seismic pickup sensor g relative to the chosen zero time;

[0081] Step 302: If the velocity c of the longitudinal and / or transverse wave propagation and the source parameter (s x ,s y ,s z , t0) causes a corresponding change in the calculated arrival time T of the transmitting signal source (if it does not cause a change, the residual value is 0), then the change in the travel time residual for:

[0082]

[0083] Step 303, the partial derivative of the residual E with respect to the position, origin time and speed change is:

[0084]

[0085] Among them, s i =s x ,s y or z , λ is the Lagrange multiplier;

[0086] Step 304: Passing at the border Initialize λ with the boundary value and set the remaining grid points to zero;

[0087] Step 305: Alternately scan the entire domain, using Update the λ value of non-boundary positions;

[0088] Step 306: For a given convergence criterion ε>0, check the criterion ||λ point by point n+1 -λ n || L1 ≤ε to check convergence;

[0089] Step 307: When convergence is satisfied, the corresponding The value is used as the gradient of the objective function;

[0090] in, is the normal vector perpendicular to the surface of the vibration sensor, is the gradient, T is the calculated arrival time of the transmitting signal source, λ is the Lagrange multiplier, T ° It refers to the propagation time of the longitudinal and / or transverse waves of the vibration waves observed by the vibration pickup sensor, Ω is the surface of the vibration pickup sensor, x∈Ω refers to the position x on the surface of the vibration pickup sensor, ‖λ nt1 -λ n ‖ L1 is the Lagrange multiplier matrix L 1 norm, indicating that the algorithm converges when the rate of change of the Lagrange multiplier is negative, λ n+1 is the value of λ obtained at the n+1th iteration, λ n is the value of λ obtained at the nth iteration.

[0091] Preferably, in step 4, considering that the residual E has different degrees of sensitivity to the changes of t0, s and c, at the end of the iteration, when the shock wave travels, the residual E and the RMS residual If a stable state is reached, that is, the percentage of reduction is less than the target threshold, the inversion is judged to be converged, and the final source parameters and wave velocity are output, where N is the number of observed vibrations; otherwise, step 302 is entered for iteration.

[0092] Through active CT (such as Figure 8 As shown), passive CT (as Fig. 9 As shown), active and passive dual-source combined CT (as shown Fig.10 The feasibility and accuracy of the inversion model are verified by numerical simulation experiments (shown in Figure 2), that is, the distribution of the wave velocity anomaly area is consistent with the actual source position, and the residual converges to the ideal value. In the active and passive dual-source joint CT inversion numerical simulation, the mode of mutual acceptance of rays by sensors in the active CT inversion is changed to a mode in which the station position is a known source, and a passive source with random disturbance is added, that is, random disturbances whose time and position obey the normal standard normal distribution are added to the source to simulate the randomness of microseismic events on site.

[0093] Examples show that the inversion method involved in the present invention has high feasibility, simple data collection, timely and clear analysis results, and strong practicality. It can well predict the high stress dangerous area of ​​the mining face and provide a reference for pressure relief measures. And it has been verified that: almost all earthquake sources are distributed in high wave velocity areas and wave velocity change areas. Based on this, the above inversion model can be applied to rock burst warning. Correspondingly, a rock burst warning method uses any of the above-mentioned inversion models obtained by the active and passive dual-source combined shock wave CT inversion method to carry out rock burst warning.

[0094] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for inversion of active and passive dual-source combined shock wave CT, characterized in that: The steps include: Step 1: construct a probabilistic non-uniform initial velocity distribution model of longitudinal and / or transverse waves of the shock wave according to the structural characteristics of the working face, establish an initial grid model of the working face, and set the positions of the active and passive seismic sources and the positions of the seismic sensors for detecting the active and passive shock waves; Step 2, using each initial model obtained in step 1 to perform travel time tomography forward modeling, and calculating the theoretical travel time and residual of the theoretical longitudinal wave and / or shear wave; Step 3: According to the theoretical travel time and residual value obtained in step 2, the gradient of the objective function of the residual of the shock wave travel time is solved; Step 4: Performing seismic wave travel time tomography inversion on the gradient of the objective function obtained in step 3, making the residual and RMS residual reach a stable state by iteratively adjusting the velocity parameters of the source and the longitudinal and / or shear waves of the seismic wave, and outputting the final source parameters and wave velocity; Step 5: Verify the feasibility and accuracy of the inversion model through active CT numerical simulation, passive CT numerical simulation, and active and passive dual-source combined CT numerical simulation experiments: When the active CT numerical simulation, passive CT numerical simulation, and active and passive dual-source combined CT numerical simulation all meet the feasibility and accuracy, the inversion ends.

2. The method for inversion based on active and passive dual-source combined shock wave CT according to claim 1, characterized in that: In step 1, the steps of constructing the probabilistic non-uniform initial velocity distribution model include: Step 101, establishing an initial coal mine tunnel model that simulates the actual situation of the coal mine tunnel at the working face, and preliminarily calculating the observed wave velocity of each longitudinal wave and / or transverse wave of the shock wave by dividing the distance by the duration according to the distance between the active and passive seismic sources and the seismic pickup sensor and the initial arrival time of the shock wave; Step 102, using a random number algorithm to select a value within the observed wave velocity range as a probabilistic non-uniform initial velocity and assigning it to an initial shock wave travel time tomography inversion model; Step 103, performing inversion numerical simulation, and verifying the accuracy of the initial velocity distribution model through active CT numerical simulation, passive CT numerical simulation, and active and passive dual-source combined CT numerical simulation; Step 104: When the active CT numerical simulation, the passive CT numerical simulation, and the active and passive dual-source combined CT numerical simulation all meet the accuracy requirements, the inversion ends, and the obtained initial velocity distribution model is the probabilistic non-uniform initial velocity distribution model of the shock wave longitudinal wave and / or shear wave.

3. The method for inversion based on active and passive dual-source combined shock wave CT according to claim 2 is characterized in that: In step 3, the specific calculation steps include: Step 301, define the shock wave travel time residual E as the objective function of the travel time difference: Where E(c, t0, s) is the residual of the travel time of the shock wave; c is the propagation speed of the longitudinal and / or transverse waves of the shock wave, t0 is the starting time of the earthquake source, and s is the propagation distance of the shock wave; T(c, g; t0, s x ,s y ,s z ) is the earthquake source location (s x ,s y ,s z ) is the theoretical time it takes for the vibration wave to propagate to the vibration sensor g; T(c, g; t0, s x ,s y ,s z )=T(c,g;s x ,s y ,s z )+t0,(s x ,s y ,s z ) is the coordinate of the earthquake source location, T * (g) is the observed propagation time of the seismic pickup sensor g relative to the chosen zero time; Step 302: If the velocity c of the longitudinal and / or transverse wave propagation and the source parameter (s x ,s y ,s z , t0) causes the calculated arrival time T of the transmitting signal source to change accordingly, so the change of the travel time residual is for: Step 303, the partial derivative of the residual E with respect to the position, origin time and speed change is: Among them, s i =s x ,s y or z , λ is the Lagrange multiplier; Step 304: Passing at the border (x∈Ω), initialize λ with the boundary value and set the remaining grid points to zero; Step 305: Alternately scan the entire domain, using (x∈Ω), update the λ value of non-boundary positions; Step 306: For a given convergence criterion ε>0, check the criterion ‖λ point by point n+1 -λ n ‖ L1 ≤ε to check convergence; Step 307: When convergence is satisfied, the corresponding The value is used as the gradient of the objective function; in, is the normal vector perpendicular to the surface of the vibration sensor, is the gradient, T is the calculated arrival time of the transmitting signal source, λ is the Lagrange multiplier, T° refers to the propagation time of the longitudinal and / or shear waves of the vibration waves observed by the vibration pickup sensor, Ω is the vibration pickup sensor surface, x∈Ω refers to the position x on the vibration pickup sensor surface, ‖λ n+1 -λ n ‖ L1 is the Lagrange multiplier matrix L 1 norm, indicating that the algorithm converges when the rate of change of the Lagrange multiplier is negative, λ n+1 is the value of λ obtained in the n+1th iteration, λ n is the value of λ obtained at the nth iteration.

4. The method of inversion based on active and passive dual-source combined shock wave CT according to claim 3 is characterized in that: In step 4, the steps to output the final source parameters and wave velocity are: When the shock wave travels, the residual E and the RMS residual If a stable state is reached, the inversion is judged to be converged, and the final source parameters and wave velocity are output, where N is the number of observed vibrations; otherwise, step 302 is entered for iteration.

5. The method for inversion based on active and passive dual-source combined shock wave CT according to claim 2 is characterized in that: The probabilistic non-uniform initial velocity ranges from 1000m / s to 6500m / s.

6. A rock burst warning method, characterized in that: The inversion model obtained by the active and passive dual-source combined shock wave CT inversion method as described in any one of claims 1 to 5 is used for rock burst warning.

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