Advanced detection method for unfavorable geologic body based on blasting information

Abstract

The invention discloses an unfavorable geologic body advanced detection method based on blasting information. The method comprises the following steps: firstly, establishing an observation system by adopting a non-uniform long-short time window blasting construction scheme and a three-dimensional sensor array so as to realize effective extraction of a single-section blasting signal; secondly, a three-dimensional ray tracing method for diffraction of an excavated tunnel goaf is considered, accurate calculation of the earthquake generating moment t0 is achieved based on a eikonal equation, and a blasting signal after t0 correction is obtained based on the blasting signal and the earthquake generating moment obtained in the early stage; and finally, providing a least square inversion algorithm based on an AIC reflected wave observation time extraction and reflected wave layer display theory, inverting the inclination angle and position information of the two-dimensional unfavorable geologic body under the current mileage in combination with the reflected wave observation time, and dynamically updating the inclination angle and position information of the unfavorable geologic body according to the latest monitored blasting information. According to the method, damage to side wall surrounding rock and supporting bodies caused by blast holes in a traditional geophysical prospecting method can be avoided, the normal construction order is guaranteed, and meanwhile the detection distance is increased and the detection repeatability is achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of microseismic monitoring and geophysical exploration, and relates to an advanced detection method for poor geological bodies based on blasting information. Technical Background

[0002] Unfavorable geological bodies and structural surfaces are one of the main controlling factors for the occurrence of deep engineering disasters, and their cognitive effects seriously affect the effectiveness of disaster warning and prevention and control.

[0003] There are many problems with the existing geophysical exploration methods:

[0004] 1. The test cost is high and the construction time is long

[0005] 2. The small explosive blasting commonly used in the original geophysical exploration method destroyed the integrity and effectiveness of the side wall rock mass and support body to a certain extent during the geophysical exploration process, increasing the cost of subsequent maintenance.

[0006] 3. The original geophysical exploration method is intermittent and the scope of geophysical exploration is limited; while excavation disturbance is real-time, the credibility of a single forecast result is not high

[0007] The elastic wave TSP geophysical exploration method has gradually become an essential geophysical exploration method for tunnel and mine construction. Its large-scale application has also brought some difficulties and challenges. For example, before TSP operation, more than 20 construction holes need to be arranged in a fixed interval at a distance of about 15m from the single side wall of the tunnel face. The drilling preparation stage and geophysical exploration process take up a lot of time. In order to obtain blasting data with a high signal-to-noise ratio, the method of stopping work or working alone also affects the construction progress of the tunnel to a certain extent. Secondly, the multiple triggered small explosive blastings have destroyed the integrity and effectiveness of the side wall rock mass and support body to a certain extent during the geophysical exploration process, which undoubtedly increases the cost of later maintenance. Secondly, affected by the amount of explosives, the geophysical exploration range of the original TSP method is also limited. The effective range is often within 100m. Finally, since TSP geophysical exploration is intermittent and excavation disturbance is real-time, as the tunnel face advances, the state of the bad geological body changes in real time, and the credibility of the previous measurement results decreases accordingly. Therefore, a real-time and non-destructive method for advanced detection of bad geological bodies is urgently needed.

[0008] Microseismic monitoring technology is an effective rock mass damage monitoring and early warning technology. It is widely considered to be an important means to obtain precursor information of rock fracture and predict rock burst risks. It has been widely used in deep rock engineering. Existing studies have shown that the presence of unfavorable geological bodies and broken zones near the face is often associated with the high-level occurrence of immediate rock bursts. In this case, the damage zone usually forms a larger "V"-shaped explosion pit, showing a more complex damage mechanism. The spatial evolution law of microseismic events further reveals that the cracks first extend along the structural surface of the unfavorable geological body and finally slide along the structural surface. This finding emphasizes the dominant role of the structural surface in inducing such disasters. Real-time and dynamic grasp of the original and development conditions of unfavorable geological bodies not only provides important guarantees for the stability evaluation of rock mass engineering and early warning of major disasters on site, but also buys valuable time for the formulation of emergency plans on site. Follow-up microseismic monitoring can effectively monitor various signals in real time during the construction process. Among them, the evolution law of the spatial and temporal distribution of rock fracture signals, the energy size, and the moment tensor characteristics can dynamically predict the rock burst risk level and damage type of the potential damage zone. However, the role of the tunnel face blasting signal in the original microseismic monitoring system is not significant. Considering that the tunnel face blasting signal has stronger energy and longer detection distance, it can avoid the damage of the traditional small cannon source to the side wall rock mass and support body without occupying the normal construction process. In theory, it is more qualified as a geophysical source, but it still needs to solve the problem of the difficulty in measuring the time of the tunnel face blasting signal and the overlapping of multiple blasting signals of millisecond delay blasting.

[0009] Therefore, how to effectively design blasting plans, monitoring plans, inversion algorithms, and use the blasting signals monitored by the microseismic monitoring system to establish a method suitable for both rockburst monitoring and advance detection of unfavorable geological bodies under drilling and blasting construction conditions is a technical problem that urgently needs to be solved in this field. Summary of the invention

[0010] The technical difficulties to be solved by the present invention are: the overlapping of multiple blasting signals on the face is difficult to separate, the time of earthquake occurrence is difficult to accurately obtain, and there is a lack of microseismic sensor layout schemes and inversion methods suitable for the detection of poor geological bodies. In order to solve the above technical difficulties, the present invention proposes a method for advanced detection of poor geological bodies based on blasting information.

[0011] The method of the present invention firstly adopts a non-uniform long and short time window blasting construction scheme, and simultaneously takes into account the good sensor arrangement array of rock burst monitoring and poor geological body detection, establishes an observation system, and then realizes the effective extraction of single-segment blasting signals; secondly, a three-dimensional ray tracing method considering the diffraction of the empty area of ​​the excavated tunnel is proposed, and a three-dimensional slowness model corresponding to the site is established under finite element software, and the accurate calculation of the earthquake time t0 is realized based on the Eikonal equation, and based on the blasting signal and the earthquake time obtained in the early stage, the blasting signal after correction t0 is obtained; finally, a least square inversion algorithm based on the AIC (Akaike Information Criterion) reflection wave observation time extraction and display reflection wave layer theory is given, and the two-dimensional poor geological body inclination and position information at the current mileage are inverted in combination with the reflection wave observation time, and the inclination and position information of the poor geological body are updated according to the latest monitored blasting dynamics, and then different prevention and control measures are taken by comparing the average distance between the inverted poor geological body and the current excavation face and the ratio of the excavation footage, so as to ensure the safety of construction.

[0012] The technical solutions adopted by the present invention are as follows:

[0013] Step 1: Use non-uniform long and short time window blasting construction

[0014] The detonation interval of each section of blasting hole is adjusted by a digital detonator matched with the electronic detonator, specifically: the detonation interval of the first section of the core blasting hole and the second section of the groove blasting hole is controlled to be 500ms. If one section of the core blasting hole has more than two single detonators, the detonation interval of the two single detonators is 0ms, and the detonation interval after the second section of the blasting hole is 50ms;

[0015] Step 2: Use a good sensor array that takes into account both rock burst monitoring and poor geological body detection.

[0016] The sensor array can be arranged in the following manner: divided into three monitoring sections, with a section distribution of 3-2-3 sensors; the tunnel walls on both sides must adopt a section distribution of 2-2-2, and the tunnel vault can adopt a section distribution of 1-0-1;

[0017] Step 3: Record the spatial coordinates (x0, y0, z0) of the daily slotting blasting holes and the coordinates (x i ,y i ,z i ), record the current excavation blasting data M1(i) through the sensor, and pick up the observation time t1(i) of the current blasting P wave;

[0018] Step 4: Create a modeling .txt file of the field observation space through command flow, import it into Gmsh software for meshing, and generate the corresponding .msh finite element mesh file;

[0019] Step 5: Import the .msh file in Python, obtain the node number and coordinates of the three-dimensional space, define the three-dimensional space slowness array, and calculate the theoretical arrival time t2(i) of the current explosion P wave based on the three-dimensional ray tracing method;

[0020] Step 6, calculate the value of the corrected earthquake time as t1(i)-t2(i), and obtain the corrected blasting signal M2(i);

[0021] Step 7, based on the AIC method, calculate the arrival time T(i) of the reflected wave of the blasting signal M2(i) after the correction t0;

[0022] Step 8: Based on the displayed reflection wave tomography equation, the least squares fitting is performed between the observed arrival time T1(i) and the theoretical arrival time T2(i) of the reflection wave of M2(i) in step 7 to invert the inclination and position of the two-dimensional unfavorable geological body under the current excavation mileage and the average velocity field information of the monitoring area;

[0023] Step nine: determine the quantitative relationship between the average distance between the unfavorable geological body and the excavation face and the integer (at least 4 times) excavation footage under the current excavation mileage obtained by inversion, take different construction and prevention measures, and dynamically correct the inclination and position information of the unfavorable geological body and the average velocity field in the monitoring area according to the newly monitored blasting information, so as to continuously improve the accuracy and reliability of the unfavorable geological body prediction;

[0024] The present invention establishes a method suitable for both rockburst monitoring and detection of unfavorable geological bodies under drilling and blasting construction conditions, avoiding the damage of blasting holes in traditional geophysical exploration methods to the side wall surrounding rock and support bodies, ensuring normal construction order, and improving the efficiency and repeatability of detecting unfavorable geological bodies. At the same time, the blasting energy of the face is stronger and the detection range is theoretically wider. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is the construction drawing of blasting holes with non-uniform length and short time windows.

[0026] Figure 2 This is the effect diagram of non-uniform long and short time window blasting data.

[0027] Fig. 3 (Ⅰ-Ⅰ), Fig. 3 (Ⅱ-Ⅱ) and Fig. 3 (Ⅲ-Ⅲ) are cross-sectional views of the arrangement of three rows of microseismic sensors of the present invention.

[0028] Figure 4(a)-Figure 4(d) is a schematic diagram showing the reflected wave path.

[0029] Figure 5It is a flow chart for detection of adverse geological bodies. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] Figure 1 A blasting construction scheme with non-uniform long and short time windows is demonstrated, which aims to optimize the signal clarity and separation during the blasting process. The corresponding blasting parameters are detailed in Table 1. The blasting scheme uses a digital detonator matched with the electronic detonator to accurately adjust the detonation interval of each section of the blasting hole to achieve the best blasting effect. Specifically, the detonation interval between the 1st section of the heart-cut blasting hole and the 2nd section of the groove blasting hole is set to 300-500 milliseconds to ensure that there is enough time difference between the signals to reduce mutual interference. The detonation intervals of the blasting holes between sections 2 and 3, sections 3 and 4, and sections 5 and 6 are all uniformly set to 50 milliseconds and within the same section, the detonation interval of different single detonators is 0 milliseconds to ensure the tunneling effect of the blasting. The expected effect of the blasting data after adopting the blasting scheme proposed in the present invention is as follows. Figure 2 As shown in the figure, without affecting the overall blasting effect, one blasting section is separated from the other blasting sections, which significantly improves the analyzability of the data and provides a reliable data basis for the subsequent inversion of adverse geological bodies.

[0032] Table 1 Blasting parameters

[0033]

[0034]

[0035] Figure 3 (Ⅰ-Ⅰ), Figure 3 (Ⅱ-Ⅱ) and Figure 3 (Ⅲ-Ⅲ) are the plan view and cross-sectional view of the microseismic sensor layout designed by the present invention. It can be seen from the tunnel plan that a total of three rows of microseismic sensors are arranged, adopting a 3-2-3 layout scheme. Among them, the nearest row of sensors (Ⅲ-Ⅲ row) is 40-50 meters away from the face, and the distance between adjacent rows of sensors is set to 10 meters. In the Ⅰ-Ⅰ, Ⅱ-Ⅱ, and Ⅲ-Ⅲ cross-sectional views, it can be observed that the sensors on both sides of the tunnel are arranged linearly. This design ensures data collection at the same depth or level, and significantly reduces the data inconsistency caused by terrain changes. In addition, the linear layout can better capture the signal propagation characteristics, thereby improving the spatial resolution of poor geological body detection, simplifying the subsequent data processing process, and further improving the detection efficiency. Through the analysis of the Ⅰ-Ⅰ and Ⅲ-Ⅲ cross-sectional views, it can be seen that the sensors located at the arches of the two sections are distributed at symmetrical angles to each other, forming a good microseismic source array with the arrangement of sensors on both sides of the tunnel, which improves the detection capability of the observation system for microseismic events. In summary, the sensor array designed in the present invention can not only capture the changes of adverse geological bodies in a timely manner, but also ensure the early warning capability of the microseismic monitoring system for rock burst risks.

[0036] Figure 4(a)-Figure 4(d) The present invention proposes a schematic diagram of a reflection wave path, which assumes that the bad geological body in front of the face is a layered medium similar to the structure of the bad geological body, and constructs its shortest reflection path by the way of "pony crossing the bridge". The blue solid line in the figure represents the propagation path of the source reflection wave under different conditions, S is the distance from the source to the sensor, and h is the shortest vertical distance from the source to the interface of the bad geological body. As can be seen from the figure, if h, α, and v are given, the propagation path and travel time of the reflection wave can be solved in the triangle ABC based on the cosine theorem. Compared with the implicit reflection wave ray tracing method, this method is simple to operate and does not require solving a large number of Jacobian matrices. Their gradient update step size and boundaries are relatively easy to control, and the stability and universality of the inversion are higher. In addition, h, α, and v all have their own physical meanings. For example, v reflects the average velocity value of the observation space under the current excavation face, h is the shortest distance between the interface of the bad geological body and the first blasting point of the excavation face, and α reflects the vertical extension of the bad geological body.

[0037] Figure 5 This is a flow chart of the bad geological body detection based on the tunnel face blasting information proposed by the present invention, and its specific operations are as follows:

[0038] The first step is to arrange microseismic sensors and non-uniform long and short time window blasting construction plan. Before blasting, the location of the blasting source (x blast ,y blast ,z blast ), the coordinates of the sensor (xsensor (i),y sensor (i),z sensor (i)), after blasting, extract the blasting waveform data M1(i) of the current working surface, and pick up the observation time t1(i) of the current blasting P wave;

[0039] The second step is to establish the geometric model of the tunnel through the command stream, and to perform mesh division based on the Gmsh software, and further generate the .msh finite element mesh file, which mainly contains information such as node numbers and node coordinates after mesh division. Then, import the .msh file in python, generate a three-dimensional space array and define the slowness model, where the slowness value can refer to the empirical value or the inverse of the wave velocity test result of the indoor test. After defining the slowness model, the fast march method or the shortest path method is used to calculate the ray path of the source and the theoretical arrival time t2(i) of the current blasting P wave is calculated based on formula (1). Finally, the corrected value of each source M1(i) is calculated as t1(i)-t2(i), and the corrected blasting signal is further obtained as M2(i). In formula (1), S(l) is the slowness value of the one-dimensional space after flattening, and dl is the distance through each spatial grid in the shortest propagation path of the source M1(i);

[0040]

[0041] The third step is to calculate the observed reflected wave arrival time T1(i) of the corrected blasting signal M2(i) based on the AIC method through formula (2). In formula (2), q is the number of sampling points corresponding to the window function, and its value ranges from 1 to n, which is determined manually. Q is the total number of sampling points of the blasting signal M2(i);

[0042]

[0043] The fourth step is to construct the objective function of the observed reflection wave arrival time T1(i) and the theoretical reflection wave arrival time T2(i) of the blasting signal M2(i) with respect to the L2 norm, that is, formula (3), and fit the observed arrival time T1(i) and the theoretical reflection wave arrival time T2(i) by the least squares method, and further invert the corresponding unfavorable geological body information θ(v, h, α) under the current excavation mileage by constructing and updating the residual gradient equation, that is, formula (4), where the value of the theoretical reflection wave arrival time T2(i) under different conditions of sensor, source, and unfavorable geological body inclination is given by formula (5), where S and α' are given by formulas (6)-7 respectively;

[0044]

[0045] if y blast ≥y sensor (i) and

[0046]

[0047] if y blast ≥y sensor (i) and

[0048]

[0049] if y blast ≤y sensor (i) and

[0050]

[0051] if y blast ≤y sensor (i) and

[0052]

[0053] S(i) 2 =(y blast -x sensor (i)) 2 +(y blast -y sensor (i)) 2 (6)

[0054]

[0055] The fifth step is to calculate the average distance S between the bad geological body obtained by the previous i-time inversion and the i-th excavation face based on formula (8). When S>4Ri, the blasting plan can be maintained or fine-tuned according to the tunnel blasting situation of the face. Then, the inclination angle and position information of the bad geological body and the average velocity field in the monitoring area are dynamically corrected according to the newly monitored blasting information, so as to continuously improve the accuracy and reliability of the bad geological body prediction. When S≤4 times the excavation footage Ri, the construction should be stopped immediately, and the detected potential bad geological body should be verified by core drilling or borehole photography and preventive measures should be taken.

[0056]

Claims

1. A method for advanced detection of bad geological bodies based on blasting information, characterized in that: Firstly, a non-uniform long and short time window blasting construction scheme is adopted, and a good sensor arrangement array is arranged to take into account both rockburst monitoring and poor geological body detection, and an observation system is established to achieve effective extraction of single-segment blasting signals. Secondly, a three-dimensional ray tracing method considering the diffraction of the empty area of ​​the excavated tunnel is proposed. The corresponding three-dimensional slowness model of the site is established under the finite element software, and the accurate calculation of the earthquake time t0 is realized based on the Eikonal equation. Based on the blasting signal and the earthquake time obtained in the early stage, the blasting signal after the correction of t0 is obtained. Finally, a least squares inversion algorithm based on the theory of extracting and displaying reflection wave layers when AIC reflection waves are observed is proposed. The inclination and position information of the two-dimensional unfavorable geological body at the current mileage are inverted when the reflection waves are observed. The inclination and position information of the unfavorable geological body are updated according to the latest monitored blasting dynamics. By comparing the average distance between the inverted unfavorable geological body and the current excavation face and the ratio of excavation footage, different prevention and control measures are taken to ensure the safety of construction.

2. The method for advanced detection of bad geological bodies based on blasting information according to claim 1 is characterized in that: Step 1: Use non-uniform long and short time window blasting construction plan The detonation interval of each section of the blasting hole is adjusted by a digital detonator matched with the electronic detonator, specifically: the detonation interval of the first section of the core blasting hole and the second section of the groove blasting hole is controlled to be 500ms; Step 2: Use a good sensor array that takes into account both rock burst monitoring and poor geological body detection; The sensor array can be arranged in the following ways: divided into three monitoring sections, with a 3-2-3 sensor number section distribution method; Step 3: Record the spatial coordinates (x0, y0, z0) of the daily slotting blasting holes and the coordinates (x i ,y i ,z i ), record the current excavation blasting data M1(i) through the sensor, and pick up the observation time t1(i) of the current blasting P wave; Step 4: Create a modeling .txt file of the field observation space through command flow, import it into Gmsh software for meshing, and generate the corresponding .msh finite element mesh file; Step 5: Import the .msh file in Python, obtain the node number and coordinates of the three-dimensional space, define the three-dimensional space slowness array, and calculate the theoretical arrival time t2(i) of the current explosion P wave based on the three-dimensional ray tracing method; Step 6, calculate the value of the corrected earthquake time as t1(i)-t2(i), and obtain the corrected blasting signal M2(i); Step 7, based on the AIC method, calculate the arrival time T(i) of the reflected wave of the blasting signal M2(i) after the correction t0; Step 8: Based on the displayed reflection wave tomography equation, the least squares fitting is performed between the observed arrival time T1(i) and the theoretical arrival time T2(i) of the reflection wave of M2(i) in step 7 to invert the inclination and position of the two-dimensional unfavorable geological body under the current excavation mileage and the average velocity field information of the monitoring area; Step nine, determine the quantitative relationship between the average distance between the unfavorable geological body and the excavation face and the integer excavation footage under the current excavation mileage obtained by inversion, take different construction and prevention measures, and dynamically correct the inclination and position information of the unfavorable geological body and the average velocity field in the monitoring area based on the newly monitored blasting information, so as to continuously improve the accuracy and reliability of the unfavorable geological body prediction.

3. The method for advanced detection of bad geological bodies based on blasting information according to claim 1 is characterized in that: In the scheme of step one, if one section of the core hole has more than two single detonators, the detonation interval between the two single detonators is 0ms, and the detonation interval after the second section of the blasting hole is 50ms.

4. The method for advanced detection of bad geological bodies based on blasting information according to claim 1 is characterized in that: In the plan of step 2, the cross-section distribution of the walls on both sides of the tunnel must be 2-2-2.

5. The method for advanced detection of bad geological bodies based on blasting information according to claim 1 is characterized in that: In the solution of step 2, the tunnel vault adopts a 1-0-1 cross-section distribution method.

6. The method for advanced detection of bad geological bodies based on blasting information according to claim 1 is characterized in that: Step nine, determine the quantitative relationship between the average distance between the unfavorable geological body and the excavation face at the current excavation mileage obtained by inversion and at least 4 times the excavation footage.

7. The method for advanced detection of bad geological bodies based on blasting information according to claim 1 is characterized in that: The first step is to arrange microseismic sensors and non-uniform long and short time window blasting construction plan. Before blasting, the location of the blasting source (x blast ,y blast ,z blast ), the coordinates of the sensor (x sensor (i),y sensor (i),z sensor (i)), after blasting, extract the blasting waveform data M1(i) of the current working surface, and pick up the observation time t1(i) of the current blasting P wave; The second step is to establish the geometric model of the tunnel through the command stream, and to perform mesh division based on the Gmsh software, and further generate the .msh finite element mesh file, which mainly contains information such as node numbers and node coordinates after mesh division. Then, import the .msh file in Python, generate a three-dimensional space array and define the slowness model, where the slowness value can refer to the empirical value or the inverse of the wave velocity test result of the indoor test; after defining the slowness model, the fast marching method or the shortest path method is used to calculate the ray path of the source and the theoretical arrival time t2(i) of the current blasting P wave is calculated based on formula (1), and finally the corrected value of each source M1(i) is calculated as t1(i)-t2(i), and the corrected blasting signal is further obtained as M2(i); in formula (1), S(l) is the slowness value of the one-dimensional space after flattening, and dl is the distance through each spatial grid in the shortest propagation path of the source M1(i); The third step is to calculate the observed reflected wave arrival time T1(i) of the corrected blasting signal M2(i) based on the AIC method through formula (2). In formula (2), q is the number of sampling points corresponding to the window function, and its value ranges from 1 to n, which is determined manually. Q is the total number of sampling points of the blasting signal M2(i); The fourth step is to construct the objective function of the observed reflection wave arrival time T1(i) and the theoretical reflection wave arrival time T2(i) of the blasting signal M2(i) with respect to the L2 norm, that is, formula (3), and fit the observed arrival time T1(i) and the theoretical reflection wave arrival time T2(i) by the least squares method, and further invert the corresponding unfavorable geological body information θ(v, h, α) under the current excavation mileage by constructing and updating the residual gradient equation, that is, formula (4), where the value of the theoretical reflection wave arrival time T2(i) under different conditions of sensor, source, and unfavorable geological body inclination is given by formula (5), where S and α' are given by formulas (6)-7 respectively; S(i) 2 =(y blast -x sensor (i)) 2 +(y blast -y sensor (i)) 2 (6) The fifth step is to calculate the average distance S between the bad geological body obtained by the previous i-time inversion and the i-th excavation face based on formula (8). When S>4Ri, the blasting plan can be maintained or fine-tuned according to the tunnel blasting situation of the face. Then, the inclination angle and position information of the bad geological body and the average velocity field in the monitoring area are dynamically corrected according to the newly monitored blasting information, so as to continuously improve the accuracy and reliability of the bad geological body prediction. When S≤4 times the excavation footage Ri, the construction should be stopped immediately, and the detected potential bad geological body should be verified by core drilling or borehole photography and preventive measures should be taken.

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