Deep rock mass fracture seismic source mechanism and damage evolution four-dimensional imaging analysis method

Abstract

The invention discloses a deep rock mass fracture seismic source mechanism and damage evolution four-dimensional imaging analysis method. The method comprises the steps that 1, deep rock mass in-situ sampling is carried out; step 2, loading test and parameter acquisition; step 3, establishing an acoustic emission monitoring system; step 4, data analysis and visualization processing; according to the invention, based on a double-difference seismic positioning algorithm, a seismic source position of a microearthquake generated in a crack development process is positioned and the crack development process is monitored; through combination of data about rock mass components and basic mechanics in basic physical and mechanical parameter tests, stress and strain data collected in a uniaxial loading test and acoustic emission data collected by acoustic monitoring equipment, analysis and data combination are carried out on a monitored deep rock mass from various scales; the crack convergence criterion and the acoustic emission criterion are generated, the data source comprehensiveness of the method is improved, and the problem of unsatisfactory uniformity hypothesis occurring in the deep rock mass research process is solved.

Description

Technical Field

[0001] The invention relates to the technical field of deep rock mass development, and in particular to an analysis method for four-dimensional imaging of deep rock mass rupture source mechanism and damage evolution. Background Art

[0002] Deep rock masses often have characteristics such as high stress environment, complex stress field distribution, large deformation, strong rheology, high geothermal temperature, and high osmotic pressure. The complex and changeable environment of deep rock masses puts forward higher requirements on the stability of deep mining sites and their safety monitoring; deep rock masses are both the objects of human mining and the objects of protection and support for safe mining. Their internal bearing state directly determines the stability of deep engineering. With the continuous advancement of science and technology and the continuous development of support technology, the application prospects of deep rock engineering are still very broad. In the future, with the application of new technologies such as double-difference seismic imaging algorithms, the stability and safety of deep rock engineering will be further improved.

[0003] There are many challenges in the current deep rock mass development process, such as the rock mass does not meet the uniformity hypothesis, the failure and instability usually comes from the gradual collapse caused by the local failure of stress concentration, which is not conducive to the hazard warning of deep rock mass engineering.

[0004] Therefore, it is of great significance to the stability of deep rock engineering to consider the heterogeneity of rock mass, understand the source mechanism of deep rock mass rupture under mining disturbance and four-dimensional imaging of damage evolution, and take timely emergency measures. Summary of the invention

[0005] In order to overcome the problems existing in the background technology, an embodiment of the present invention provides an analysis method for four-dimensional imaging of deep rock mass fracture focal mechanism and damage evolution.

[0006] The purpose of the present invention can be achieved by the following technical scheme: an analysis method for four-dimensional imaging of deep rock mass fracture focal mechanism and damage evolution, comprising step one, in-situ sampling of deep rock mass; step two, loading test and parameter acquisition; step three, establishing an acoustic emission monitoring system; step four, data analysis and visualization processing, specifically:

[0007] Step 1: In-situ sampling of deep rock mass;

[0008] Several sampling points are evenly arranged on the surface of the studied rock mass, and drilling equipment is used to drill and sample at each sampling point to take out deep core samples. The taken out core samples are cut, polished and cleaned to prepare several standard cubic specimens of the rock mass.

[0009] Step 2: Loading test and parameter acquisition;

[0010] S201, basic physical and mechanical parameter test;

[0011] Take a standard cubic rock sample and prepare it into rock powder. Scan the rock powder based on the XRD test (X-ray diffraction test) to determine its mineral composition and content. The mineral components include quartz, feldspar, mica, non-metallic element single minerals, metal element single minerals, sulfide minerals, halide minerals, etc. Each mineral component category corresponds to a preset mineral component parameter Ai, and the content Bi of each mineral component is obtained, where i is the total number of mineral types detected. The mineral composition index E1 is obtained by the formula E1=∑Ai×Bi×ki, where ki is the influencing factor corresponding to each type of mineral component. Take several standard cubic rock samples and determine their cohesion e1, internal friction angle e2, compressive strength e3, shear strength e3, tensile strength e4, dynamic compressive strength e5, dynamic shear strength e6 and dynamic tensile strength e7 based on triaxial loading tests. By the formula

[0012] E2=λ1×e1+λ2×e2+λ3×e3+λ4×e4+λ5×e5+λ6×e6+λ7×e7Calculate the mechanical evaluation index E2, where λ1, λ2, λ3, λ4, λ5, λ6 and λ7 are preset weight coefficients. Obtain the safety factor K.

[0013] S202, uniaxial loading test based on high-speed camera;

[0014] As a preferred embodiment of the present invention, several standard cube rock samples are taken, and speckles are drawn on the surface of the samples using a paint pen. An industrial-grade high-speed camera is used to capture images of the surface of the standard cube rock samples at preset intervals during the uniaxial loading test. The position of each speckle is extracted from the photographic image, and the speckles with a displacement less than a preset threshold value one are marked green, the speckles with a displacement less than a preset threshold value two and greater than or equal to the preset threshold value one are marked yellow, and the speckles with a displacement greater than or equal to the preset threshold value two are marked red. The image processing technology is used to combine the positions of each speckle and the marking color to generate a strain cloud map. The number of red speckles n1, the number of yellow speckles n2, and the total number of speckles N in the displacement cloud map are obtained, and the formula is used to calculate the strain cloud map. The proportion of red speckles α1 and the proportion of yellow speckles α2 are calculated, and all displacement cloud maps and their corresponding stresses that satisfy the condition β1×α1+β2×α2>ω are extracted. The median of the stress is recorded as the basic strength index E3, where β1 and β2 are preset influencing factors, and ω is a preset judgment factor.

[0015] S203, uniaxial loading test based on acoustic emission monitoring;

[0016] Micro-earthquakes are generated during the generation and occurrence of cracks in the rock mass. Acoustic emission monitoring can capture the transient elastic ultrasonic waves generated by micro-earthquakes, and analyze the stress distribution through the position and energy of the transient elastic ultrasonic waves.

[0017] As a preferred embodiment of the present invention, the stress σ during the loading process is recorded at preset intervals, and the number of acoustic emission events n and the energy of acoustic emission events are obtained through acoustic emission monitoring equipment based on AE technology (Acoustic Emission). The image of the cumulative number of acoustic emission events and energy changing with stress is plotted with stress as the independent variable and the acoustic emission event energy and the number of acoustic emission events as the dependent variables, which is recorded as the acoustic emission characteristic image. In the acoustic emission characteristic image, the image is divided into four stages by three preset straight lines: x1=A1xE3; x2=A2xE3 and x3=A3xE3, where E3 is the basic strength index, A1, A2 and A3 are a set of preset weight factors, 0<A1<A2<A3<1. The four stages are stage one, crack initiation stage; stage two, stable crack development stage; stage three, unstable crack development stage; stage four, crack penetration stage. Extract the energy and number of events corresponding to the beginning of the unstable crack development stage And recorded as the acoustic emission judgment vector.

[0018] Step 3: Establish an acoustic emission monitoring system;

[0019] As a preferred embodiment of the present invention, the schematic diagram of the principle of the double-difference positioning method is as follows: cracks and damages in the rock mass are accompanied by local stress concentrations in the rock mass. When the acoustic wave signal emitted by the acoustic emission probe passes through these local stress concentration areas, it will quickly release energy and generate transient elastic waves. The generation of each transient elastic wave is recorded as an acoustic emission event, hereinafter referred to as an event. By comparing the actual time difference of arrival observed at the same measuring station for the transient elastic waves generated by two adjacent events i and j with the theoretically calculated time difference of arrival, the coordinates (x1, x2, x3) of the crack location and fine velocity structure imaging can be inverted. Through the inversion model formula Calculate the location (x1, x2, x3), time and velocity structure of the crack, where and It is the difference between the predicted arrival time and the actual arrival time of event n at the station, recorded as the first arrival time residual; is the double difference between event m and event n; and represents the observed arrival time of events m and n at the station; is the position coordinate component where event m occurs, p = 1, 2, 3; is the position coordinate component where event n occurs, p = 1, 2, 3; and represents the correction amount of the source position disturbance of event m and n, p = 1, 2, 3; Δτm and Δτn are the starting time of time m and event n respectively; δμ1 and δμ2 are the slow disturbances of event m and event n respectively;

[0020] The number of events n and event energy E obtained by the emission monitoring equipment are extracted at preset intervals, and (n, E) is called the acoustic emission criterion. The formation stage of the crack is matched in the acoustic emission characteristic image according to the value of (n, E).

[0021] Step 4: Data analysis and visualization;

[0022] As a preferred embodiment of the present invention, all event position points (x1, x2, x3) of crack occurrence are calculated by the inversion model formula every preset time t, four-dimensional imaging of damage evolution is generated based on the time-lapse tomography algorithm, all generated event position points are recorded and all adjacent event position points are connected to generate a crack body inversion model, and the current time t is taken as the moment O, and cracks generated before the preset time T1 are rendered in green, cracks generated after the preset time T1 and before the preset time T2 are rendered in yellow, and cracks generated after the preset time T2 are rendered in red. The preset time T1 is greater than the preset time T2.

[0023] The total volume V of the fracture inversion model is extracted at preset time intervals. The image of V varying with t is generated with time t as the independent variable and the volume V of the fracture inversion model as the dependent variable. The convergence of the function in the image is analyzed based on mathematical analysis software. When the image does not converge, the fracture convergence criterion is generated. The value of the fracture convergence criterion is Where V is the total volume of the fracture body inversion model, and K is the safety factor.

[0024] When the value of the crack convergence criterion is greater than a preset threshold, an instability alarm signal is generated.

[0025] When the acoustic emission number n in the acoustic emission criterion is greater than the acoustic emission judgment vector And the event energy E is greater than the acoustic emission judgment vector When , an instability alarm signal is generated.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. The present invention accurately locates the microseismic source position generated during the development of cracks based on the double-difference seismic location algorithm, thereby monitoring the development of cracks and improving the location accuracy of deep rock damage. Compared with other damage location methods, the double-difference location method has higher accuracy, lower requirements on the layout density and location of stations, and better applicability;

[0028] 2. The present invention combines the data on rock mass composition and basic mechanics in basic physical and mechanical parameter tests, the stress and strain data collected in uniaxial loading tests, and the acoustic emission data collected by acoustic monitoring equipment, analyzes the monitored deep rock mass from various scales and combines the data to generate crack convergence criteria and acoustic emission criteria, thereby improving the comprehensiveness of the data source of the present invention, improving the reliability and accuracy of data processing, and providing data support for the deep rock mass fracture mechanism and subsequent damage development monitoring;

[0029] 3. The present invention combines the waveform data and source location data obtained by the acoustic emission monitoring equipment with the time-lapse tomography technology to perform four-dimensional imaging of damage evolution, visualizes the damage development process of the deep rock mass, improves the interpretability of the data, and proposes an instability monitoring method for the deep rock mass based on the fracture inversion model. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0031] Figure 1 is a flow chart of the method of the present invention;

[0032] Figure 2 It is a schematic diagram of the uniaxial loading test based on high-speed photography and its speckle arrangement of the present invention;

[0033] Figure 3 It is a schematic diagram of the acoustic emission characteristic image of the present invention;

[0034] Figure 4 It is a schematic diagram of the principle of the double difference positioning method of the present invention;

[0035] Figure 5 It is a schematic diagram of the fracture body inversion model of the present invention. DETAILED DESCRIPTION

[0036] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. 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.

[0037] See also Figure 1 As shown in the figure, the analysis method of four-dimensional imaging of deep rock mass fracture focal mechanism and damage evolution includes:

[0038] Step 1: In-situ sampling of deep rock mass;

[0039] Several sampling points are evenly arranged on the surface of the studied rock mass, and drilling equipment is used to drill and sample at each sampling point to take out deep core samples. The taken out core samples are cut, polished and cleaned to prepare several standard cubic specimens of the rock mass.

[0040] Step 2: Loading test and parameter acquisition;

[0041] S201, basic physical and mechanical parameter test;

[0042] Take a standard cubic rock sample and prepare it into rock powder. Scan the rock powder based on the XRD test (X-ray diffraction test) to determine its mineral composition and content. The mineral components include quartz, feldspar, mica, non-metallic element single minerals, metal element single minerals, sulfide minerals, halide minerals, etc. Each mineral component category corresponds to a preset mineral component parameter Ai, and the content Bi of each mineral component is obtained, where i is the total number of mineral types detected. The mineral composition index E1 is obtained by the formula E1=ΣAi×Bi×ki, where ki is the influencing factor corresponding to each type of mineral component. Take several standard cubic rock samples and determine their cohesion e1, internal friction angle e2, compressive strength e3, shear strength e3, tensile strength e4, dynamic compressive strength e5, dynamic shear strength e6 and dynamic tensile strength e7 based on triaxial loading tests. By the formula

[0043] E2=λ1×e1+λ2×e2+λ3×e3+λ4×e4+λ5×e5+λ6×e6+λ7×e7Calculate the mechanical evaluation index E2, where λ1, λ2, λ3, λ4, λ5, λ6 and λ7 are preset weight coefficients. Get the safety factor K.

[0044] S202, uniaxial loading test based on high-speed camera;

[0045] See also Figure 2 As shown, several standard rock cube specimens are taken, and speckles are drawn on the surface of the specimens using a paint pen. An industrial-grade high-speed camera is used to capture images of the surface of the standard rock cube specimens at preset intervals during the uniaxial loading test. The position of each speckle is extracted from the photographic image, and the speckles with a displacement less than the preset threshold value one are marked green, the speckles with a displacement less than the preset threshold value two and greater than or equal to the preset threshold value one are marked yellow, and the speckles with a displacement greater than or equal to the preset threshold value two are marked red. The image processing technology is used to combine the positions of each speckle and the marking color to generate a strain cloud map. The number of red speckles n1, the number of yellow speckles n2, and the total number of speckles N in the displacement cloud map are obtained, and the formula is used to calculate the strain cloud map. The proportion of red speckles α1 and the proportion of yellow speckles α2 are calculated, and all displacement cloud maps and their corresponding stresses that satisfy the condition β1×α1+β2×α2>ω are extracted, and the minimum stress value is recorded as the basic strength index E3, where β1 and β2 are preset influencing factors, and ω is a preset judgment factor.

[0046] S203, uniaxial loading test based on acoustic emission monitoring;

[0047] Micro-earthquakes are generated during the generation and occurrence of cracks in the rock mass. Acoustic emission monitoring can capture the transient elastic ultrasonic waves generated by micro-earthquakes, and analyze the stress distribution through the position and energy of the transient elastic ultrasonic waves.

[0048] See also Figure 3 As shown, the stress σ during the loading process is recorded at preset intervals, and the number of acoustic emission events n and the energy of acoustic emission events are obtained through acoustic emission monitoring equipment based on AE technology (Acoustic Emission). The image of the cumulative number of acoustic emission events and energy changing with stress is plotted with stress as the independent variable and the acoustic emission event energy and the number of acoustic emission events as the dependent variables, which is recorded as the acoustic emission characteristic image. In the acoustic emission characteristic image, the image is divided into four stages by three preset straight lines: x1=A1xE3; x2=A2xE3 and x3=A3xE3, where E3 is the basic strength index, A1, A2 and A3 are a set of preset weight factors, 0<A1<A2<A3<1. The four stages are stage one, crack initiation stage; stage two, stable crack development stage; stage three, unstable crack development stage; stage four, crack penetration stage. Extract the energy and number of events corresponding to the beginning of the unstable crack development stage And recorded as the acoustic emission judgment vector.

[0049] Step 3: Establish an acoustic emission monitoring system;

[0050] See also Figure 4 As shown in the figure, the schematic diagram of the principle of the double-difference positioning method is shown. The cracks and damages in the rock mass are accompanied by local stress concentration in the rock mass. When the acoustic wave signal emitted by the acoustic emission probe passes through these local stress concentration areas, it will quickly release energy and generate transient elastic waves. The generation of each transient elastic wave is recorded as an acoustic emission event, hereinafter referred to as an event. By comparing the actual time difference of arrival observed at the same measuring station for the transient elastic waves generated by two adjacent events i and j with the theoretically calculated time difference of arrival, the coordinates (x1, x2, x3) of the crack location and the fine velocity structure imaging can be inverted. Through the inversion model formula Calculate the location (x1, x2, x3), time and velocity structure of the crack, where and It is the difference between the predicted arrival time and the actual arrival time of event n at the station, recorded as the first arrival time residual; is the double difference between event m and event n; and represents the observed arrival time of events m and n at the station; is the position coordinate component where event m occurs, p = 1, 2, 3; is the position coordinate component where event n occurs, p = 1, 2, 3; and represents the correction amount of the source position disturbance of event m and n, p = 1, 2, 3; Δτm and Δτn are the starting time of time m and event n respectively; δμ1 and δμ2 are the slow disturbances of event m and event n respectively;

[0051] The number of events n and event energy E obtained by the emission monitoring equipment are extracted at preset intervals, and (n, E) is called the acoustic emission criterion. The formation stage of the crack is matched in the acoustic emission characteristic image according to the value of (n, E).

[0052] Step 4: Data analysis and visualization;

[0053] See also Figure 5 As shown, all event position points (x1, x2, x3) of crack occurrence are calculated by the inversion model formula at every preset time t, and four-dimensional imaging of damage evolution is generated based on the time-lapse tomography algorithm. All generated event position points are recorded and all adjacent event position points are connected to generate a crack body inversion model. With the current time t as the O moment, green is used to render cracks generated before the preset time T1, yellow is used to render cracks generated after the preset time T1 and before the preset time T2, and red is used to render cracks generated after the preset time T2. The preset time T1 is greater than the preset time T2.

[0054] The total volume V of the fracture inversion model is extracted at preset time intervals. The image of V varying with t is generated with time t as the independent variable and the volume V of the fracture inversion model as the dependent variable. The convergence of the function in the image is analyzed based on mathematical analysis software. When the image does not converge, the fracture convergence criterion is generated. The value of the fracture convergence criterion is Where V is the total volume of the fracture body inversion model, and K is the safety factor.

[0055] When the value of the crack convergence criterion is greater than a preset threshold, an instability alarm signal is generated.

[0056] When the acoustic emission number n in the acoustic emission criterion is greater than the acoustic emission judgment vector And the event energy E is greater than the acoustic emission judgment vector When , an instability alarm signal is generated.

[0057] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0058] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and the claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and the claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations;

[0059] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The analysis method of the focal mechanism of deep rock mass rupture and four-dimensional imaging of damage evolution is characterized by: include: Step 1: In-situ sampling of deep rock mass; Step 2: Loading test and parameter acquisition; S201, basic physical and mechanical parameter test; S202, uniaxial loading test based on high-speed photography; generating a strain cloud map on the surface of the sample by high-speed photography; obtaining a basic strength index by image processing and calculation of the strain cloud map; S203, uniaxial loading test based on acoustic emission monitoring; Step 3: Establish an acoustic emission monitoring system; Step 4: Data analysis and visualization.

2. The method for analyzing the focal mechanism of deep rock mass rupture and four-dimensional imaging of damage evolution according to claim 1, characterized in that: The specific process of in-situ sampling of deep rock mass in step 1 is: evenly arrange a number of sampling points on the surface of the studied rock mass, perform drilling sampling at each sampling point by means of drilling equipment, and take out deep rock core samples; cut, grind and clean the taken out rock core samples, and prepare a number of standard cubic specimens of the rock mass.

3. The method for analyzing the focal mechanism of deep rock mass rupture and four-dimensional imaging of damage evolution according to claim 1, characterized in that: The specific process of basic physical and mechanical parameter testing is as follows: take a standard cubic rock sample and prepare it into rock powder, scan the rock powder based on the XRD test to determine its mineral composition and content, each mineral composition category corresponds to a preset mineral composition parameter, obtain the content of each mineral composition, and obtain the mineral composition index through calculation; take several standard cubic rock samples and determine their basic mechanical parameters based on triaxial loading tests, and obtain the mechanical evaluation index through calculation; obtain the safety factor through calculation of the mineral composition index and the mechanical evaluation index; the basic mechanical parameters include cohesion, internal friction angle, compressive strength, shear strength, tensile strength, dynamic compressive strength, dynamic shear strength and dynamic tensile strength; The specific process of the uniaxial loading test based on acoustic emission monitoring is as follows: the stress during the loading process is recorded at preset time intervals, the number of acoustic emission events and the energy generated by acoustic emission events are obtained through acoustic emission monitoring equipment based on AE technology, and the image of the cumulative number of acoustic emission events and energy changing with stress is plotted with stress as the independent variable and the acoustic emission event energy and the number of acoustic emission events as the dependent variables. The image is divided into several stages based on the value of the basic strength index, including the crack initiation stage, the stable crack development stage, the unstable crack development stage and the crack penetration stage. The energy and number of events corresponding to the beginning of the unstable crack development stage are extracted and recorded as the acoustic emission judgment vector.

4. The method for analyzing the focal mechanism of deep rock mass rupture and four-dimensional imaging of damage evolution according to claim 1, characterized in that: The specific process of generating strain cloud diagram is as follows: Several standard cube rock samples were taken, speckles were drawn on the surface of the samples with a paint pen, and images of the surface of the standard cube rock samples were taken at preset intervals using an industrial-grade high-speed camera during the uniaxial loading test. The position of each speckle was extracted, and each speckle was marked with different colors according to the size of the displacement. The strain cloud map was generated by combining the position of each speckle and the marked color through image processing technology.

5. The method for analyzing the focal mechanism of deep rock mass rupture and four-dimensional imaging of damage evolution according to claim 4, characterized in that: The specific process of obtaining the basic strength index through image processing and calculation of the strain cloud map is as follows: The number of speckles marked with each color and the total number of all speckles in the displacement cloud map are obtained, and the proportion of the number of speckles of each color is obtained through calculation. All displacement cloud maps and their corresponding stresses whose proportion of the number of speckles of each color meets certain conditions are extracted, and the representative stress value is extracted as the basic strength index.

6. The method for analyzing the focal mechanism of deep rock mass rupture and four-dimensional imaging of damage evolution according to claim 1, characterized in that: The specific process of establishing the acoustic emission monitoring system in step three is: by comparing the actual arrival time difference observed at the same measuring station for the transient elastic waves generated by two adjacent events i and j with the arrival time difference obtained by theoretical calculation, the coordinates of the crack occurrence location and the fine velocity structure imaging are inverted; the location, time and velocity structure of the crack occurrence are calculated through the inversion model, and the number of events and event energy obtained by the emission monitoring equipment are extracted at preset time intervals, which is called the acoustic emission criterion.

7. The method for analyzing the focal mechanism of deep rock mass rupture and four-dimensional imaging of damage evolution according to claim 1, characterized in that: The specific process of data analysis and visualization in step 4 is as follows: calculate all event location points of crack occurrence by inversion model formula at preset time intervals, generate four-dimensional imaging of damage evolution based on tomography algorithm, record all event location points generated and connect all adjacent event location points to generate a crack body inversion model, and render in different colors according to the order of crack generation time; extract the total volume of the crack body inversion model, analyze whether the volume converges over time based on mathematical analysis software, and generate a crack convergence criterion by combining the total crack volume and safety factor; Whether to generate an instability alarm signal is determined based on the values ​​of the crack convergence criterion and the acoustic emission criterion.

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