A method and system for dynamic fracture source parameter quantitative inversion and rupture cross-scale characterization

Abstract

The application discloses a dynamic fracture source parameter quantitative inversion and rupture cross-scale characterization method and system, and the characterization method comprises the following steps: collecting waveform signals of the whole process of rock mass rupture; calculating the ratio of a short-time window and a long-time window of a characteristic function to identify real signal characteristics, determining dynamic fracture source coordinates according to a positioning algorithm, and screening to obtain a set of reliable source coordinate points; establishing a displacement discontinuity tensor dynamic fracture source model, constructing an objective function and calculating dynamic fracture source moment tensor components; solving dynamic fracture source head parameters according to the moment tensor components, realizing the description of the scale, orientation and mechanical characteristics of a single dynamic fracture event; and inductively counting all dynamic fracture source head core parameters, respectively counting all dynamic fracture source types, forming a dynamic fracture group data set of spatial orientation dominant orientation, dissipated energy spatial distribution, damage tensor principal axis direction and magnitude statistical distribution b value, and realizing the cross-scale process description of rock mass dynamic fracture evolution from single to cluster and from microcosmic to macroscopic.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rock mass fracture propagation monitoring, and particularly relates to a dynamic fracture source parameter quantitative inversion and fracture cross-scale characterization method and system. BACKGROUND

[0002] With the continuous increase of coal mining depth, it makes the coal mining operation face the challenge of complex and harsh conditions such as high stress, high temperature, high water pressure and strong mining disturbance, which leads to frequent disasters such as rock burst, coal and gas outburst, roof and floor water inrush, etc., and poses a threat to the safety of coal mine workers. The combination of microseismic monitoring technology and moment tensor theory can accurately obtain key information such as the spatial orientation, mechanical properties, area change, magnitude and damage degree of rock mass fracture, providing a quantitative evaluation means for in-depth analysis of the whole process of rock mass fracture from initiation to breakthrough to instability. Through the inversion of rock microcracks and the characterization of macro-micro cross-scale fractures, it is helpful to more accurately understand the mechanical behavior and failure mechanism of rock mass materials, thereby providing a solid theoretical basis and technical support for practical application.

[0003] In the process of rock micro-mechanism fracture analysis, many researchers have devoted to the inversion of fracture source parameters and their generation mechanism in order to obtain a more accurate and in-depth understanding. For example, Chinese patent CN114417612A discloses a stope microseismic source mechanism solving method based on moment tensor inversion, Chinese patent CN114994791A discloses a method for evaluating the monitoring capability of a well-ground integrated microseismic monitoring system, and Chinese patent CN103389489B discloses a microseismic monitoring and positioning method based on high-inclination wells. These all use microseismic sensors to pick up waveform signals, but do not consider the influence of sensor arrangement on the quality of picked-up waveforms. Chinese patent CN114113335A discloses a rock dissipated energy space-time distribution quantification method based on acoustic emission / microseismic monitoring, but does not deeply explore the relationship between fracture dissipated energy distribution and macroscopic fracture propagation path evolution. Chinese patent CN114137600B discloses a method for inverting rock fracture mechanism and instability prediction using microseismic monitoring data, and Chinese patent CN113050159A discloses a coal rock hydraulic fracturing crack microseismic positioning and extension mechanism monitoring method. The acoustic emission event coordinate points are calculated by positioning algorithm, but the inversion parameter data error is uncontrollable due to the screening of positioning coordinates with large errors. Chinese patent CN114063153B discloses a method and device for automatically inverting source mechanism solution, and Chinese patent CN107843924B discloses a source positioning and source mechanism joint inversion method using P-wave initial motion constraint. The first arrival time is picked up as the inversion input parameter, and the picking error precision is low due to interference signals, picking methods and other reasons. In addition, the inversion of the source parameters is not deep enough, and the evolution law between single fracture, fracture group and macroscopic main fracture is not deeply studied.

[0004] Therefore, the present patent discloses a dynamic fracture source parameter quantitative inversion and fracture cross-scale characterization method and system. Based on high-quality acoustic data acquisition and high-precision theoretical calculation, the rock fracture macro-micro cross-scale process is organically integrated through micro-fracture quantitative inversion and macro-fracture multi-dimensional characterization, which helps to better explain the rock fracture deformation, extension mode and disaster mechanism, which is of great significance to ensure the safe development of deep geological engineering. SUMMARY

[0005] The present scheme proposes a dynamic fracture source parameter quantitative inversion and fracture cross-scale characterization method and system to solve the problems and needs mentioned above. The above technical purposes can be achieved and other technical effects can be brought about due to the adoption of the following technical features.

[0006] One object of the present application is to propose a dynamic fracture source parameter quantitative inversion and fracture cross-scale characterization method, characterized in that the characterization method comprises the following steps:

[0007] S10: determining a potential area where a dynamic fracture event occurs, arranging N+1 acoustic wave sensors to form a monitoring network covering the potential area; wherein, by adjusting the position of the acoustic wave sensor to reduce the value of the covariance determinant, the optimization of the acoustic wave sensor network layout is realized;

[0008] S20: collecting waveform signals of the dynamic fracture event in the rock mass failure process by the acoustic wave sensor, filtering environmental noise and enhancing the real signal through a filter, and calculating the ratio of the short-time window to the long-time window by the characteristic function E(t) to identify the real signal characteristics, wherein when the ratio of the short-time window to the long-time window exceeds the set trigger threshold, the first wave arrival time t0 is picked up, and the take-off amplitude f0 is obtained;

[0009] S30: using the obtained waveform first wave arrival time, acoustic wave sensor coordinates and wave velocity information, determining the dynamic fracture source coordinates (x e ,y e ,z e ) according to the positioning algorithm, calculating the variance of the source coordinates in three-dimensional directions to obtain the actual confidence interval size of the source coordinates and quantify the reliability of the positioning results, and screening to obtain a set of reliable source coordinates;

[0010] S40: based on the generation of the dynamic fracture, the wave propagation, and the forward full process of the acoustic wave sensor response, a displacement discontinuity tensor microcrack source representation model of the dynamic fracture event is established, a target function is constructed under the constraint condition that the second eigenvalue of the displacement discontinuity tensor is zero, and the moment tensor component m b of the dynamic fracture event is calculated;

[0011] S50: according to the moment tensor component, the source core parameters of the dynamic fracture are solved, and the scale, orientation, and mechanical characteristics of a single dynamic fracture event are quantitatively and finely described; wherein, the source core parameters include the crack volume, the crack area, the crack opening displacement, the crack spatial orientation, the tensile-shear property, the instantaneous generation rate, the released energy, and the moment magnitude;

[0012] S60: the single dynamic fracture source core parameters obtained by inversion are summarized and statistically analyzed to form a crack cluster dataset including the spatial orientation dominant direction, the dissipated energy spatial distribution, the damage tensor principal axis direction, and the magnitude statistical distribution b value, and the macroscopic main crack propagation path is quantitatively characterized in multiple dimensions, so as to realize the cross-scale process description of the rock mass dynamic fracture evolution from single to cluster and from micro to macro.

[0013] In addition, the dynamic fracture source parameter quantitative inversion and fracture cross-scale representation method according to the present application can also have the following technical features:

[0014] In an example of the present application, in the step S10, the optimization of the acoustic wave sensor network layout by adjusting the position of the acoustic wave sensor to reduce the value of the covariance determinant specifically includes the following steps:

[0015] S11: Based on the error ellipsoid theory, the smaller the determinant of the variance-covariance matrix cov(X e ) is, the smaller the error ellipsoid volume is, and the optimal network layout scheme is determined by minimizing cov(X e ); wherein, the formula of the variance-covariance matrix cov(X e ) is as follows:

[0016] cov(X e ) = σ 2 (K T V -1 K) -1 = σ 2 Q

[0017] In the formula, indicates the comprehensive accuracy of each acoustic sensor to time measurement; the matrix Q depends on the geometric distribution of the acoustic sensor network and the location of the dynamic crack event source;

[0018] wherein, V is an N x N idempotent matrix, i.e.

[0019]

[0020] wherein, (I i ,m i ,n i ) is the direction cosine of the i-th acoustic sensor to the estimated location of the dynamic crack source;

[0021]

[0022] S12: Fine-tune the i-th acoustic sensor position, change the element values of (l i -l0), (m i -m0), (n i -n0) in the matrix K, until the determinant of the matrix K reaches the minimum value, at this time the minimum value position is determined as the optimal position of the acoustic sensor (x i , y i , z i ), repeat the step, fine-tune all the acoustic sensors to make the determinant of the variance-covariance matrix cov(X e ) reach the minimum value, and determine the optimal position of all acoustic sensors to optimize the acoustic sensor network;

[0023] wherein, (x e , y e , z e ) is the coordinate of the source location, l i , m i , n iThe calculation formula is as follows:

[0024]

[0025] In the formula, R ei is the straight-line distance between the moving crack source (x e , y e , z e ) and the i-th acoustic wave sensor (x i , y i , z i ).

[0026] In an example of the present application, the step S30 specifically comprises the following steps:

[0027] S31: using the first arrival time data received by all acoustic wave sensors, in combination with the information of acoustic wave sensor coordinates and material wave speed, the source is positioned in three dimensions through a simplex positioning algorithm, wherein the waveform of the moving crack source is transmitted to the i-th acoustic wave sensor position coordinate theoretical travel time T i The calculation formula is as follows:

[0028]

[0029] In the formula, (x e , y e , z e ) is the moving crack source coordinate; (x i , y i , z i ) is the coordinate of the i-th acoustic wave sensor; c p is the P-wave speed of the material; T0 is the time when the crack source occurs;

[0030] S32: the objective function is constructed by accumulating and summing the absolute values of the differences between the arrival times collected at all acoustic wave sensors and the theoretical arrival times, wherein the expression of the objective function is as follows:

[0031]

[0032] In the formula, N+1 is the number of acoustic wave sensors arranged; is the first arrival time picked up by the i-th acoustic wave sensor;

[0033] S33: the variance of the source coordinate point (x e , y e , z e ) in three dimensions is calculated through the major diagonal elements of the error ellipsoid variance-covariance matrix, and the confidence level t α / 2The confidence interval of the source positioning point coordinates in x, y and z directions is obtained under 95%; wherein, the narrower the confidence interval of the source positioning point in three-dimensional direction, the smaller the error ellipsoid volume, and the more accurate the acoustic emission positioning result; the confidence interval threshold x t , y t , z t is set in three directions, when the three-dimensional confidence interval length of the positioning point meets x l ≤x t , y l ≤y t , z l ≤z t , the source coordinate point positioning result is considered reliable.

[0034] wherein, under the confidence level t α / 2 , the confidence interval length of the dynamic fracture source coordinate point (x e , y e , z e ) in x, y and z directions is calculated by the following formula:

[0035]

[0036] wherein, q 11 , q 22 , q 33 are the main diagonal elements of the matrix Q in turn; and σ 2 represents the comprehensive accuracy of each acoustic wave sensor to time measurement.

[0037] S34: repeat the above steps until all source positioning coordinates meeting the condition of S33 are screened out, and a source coordinate data set with accurate positioning and small error is obtained.

[0038] In an example of the present application, in the step S40, based on the whole process of the generation of dynamic fracture, the propagation of wave and the acoustic wave sensor response, a displacement discontinuity tensor source characterization model of dynamic fracture event is established, which specifically includes the following steps:

[0039] S41: in the process of acoustic wave sensor response, the transformation coefficient S A is defined to realize the transformation between the output voltage value of acoustic wave sensor and the different physical quantities of input normal displacement and to quantify the coupling quality of acoustic wave sensor, so as to improve the inversion precision of source parameters, wherein, the calculation formula of the transformation coefficient S A is as follows:

[0040]

[0041] In the formula, υ is the medium Poisson's ratio; P is the applied load value; d is the propagation distance; f0 is the P-wave take-off amplitude value; G1 is the function value at the first peak value inflection point of the time-varying theory normal displacement;

[0042] S42: in the process of dynamic fracture source wave propagation, only considering the far-field displacement generated by P wave, under the assumption of synchronous source, the function relationship between the displacement disturbance at the dynamic fracture source and the displacement response generated at the acoustic wave sensor is established through the Green function and the elastic wave equation, and the specific expression is as follows:

[0043]

[0044] In the formula, r is the distance from the fracture source to the acoustic wave sensor position; γ is the directional cosine between the fracture source and the acoustic wave sensor; c p is the P-wave velocity; M jk is the moment tensor component value; T s is the dynamic fracture time of the dynamic fracture;

[0045] S43: the displacement discontinuity tensor ψ ij is used to represent the generated dynamic fracture source, wherein the displacement discontinuity tensor ψ ij The calculation formula is as follows:

[0046]

[0047] In the formula, C ijkl is the material elastic stiffness tensor; ΔA is the new area of the dynamic fracture; b is the dynamic fracture movement vector; n is the dynamic fracture surface normal vector.

[0048] In one example of the present application, in the step S40, the objective function is constructed under the constraint condition that the second eigenvalue of the displacement discontinuity tensor is zero, and the moment tensor component m b Specifically includes the following steps:

[0049] Firstly, the relationship between the displacement discontinuity tensor ψ and the moment tensor M is established, and in the isotropic medium, the relationship between the displacement discontinuity tensor and the moment tensor satisfies the following formula:

[0050] M kl = ψ ij C ijkl = λδ kL (ψ1+ψ2+ψ3)+2μψ kl

[0051] Wherein, C ijkl is the medium stiffness matrix; λ and μ are the Lame constants;

[0052] Secondly, the constraint condition of the second eigenvalue of the displacement discontinuity tensor ψ, ψ2=0, is a condition to be satisfied in any coordinate system, and according to the relationship between the displacement discontinuity tensor and the moment tensor, the constraint condition of ψ2=0 is rewritten into the form of moment tensor invariants, and the expression is as follows:

[0053]

[0054] Wherein, J1, J2 and J3 are the first, second and third invariants of the moment tensor M;

[0055] Then, according to the theoretical normal displacement of P wave at different acoustic wave sensor positions and the measured normal displacement data, the Lagrange indefinite multiplier γ is introduced under the constraint condition of ψ2=0 to determine the objective function E and then to solve the moment tensor components, and the specific formula of the objective function E is as follows:

[0056]

[0057] In the formula, (S A f0) i is the measured normal displacement at the i th acoustic wave sensor; u i (x, M jk ) is the normal displacement calculated by the dynamic crack moment tensor source theory at the i th acoustic wave sensor;

[0058] Finally, the six components of the moment tensor are obtained by iterative solving of the objective function E by using the damped Newton method.

[0059] In an example of the present application, in the step S50, the source core parameters of the dynamic crack are solved according to the moment tensor components, and the quantitative and fine description of the scale, orientation and mechanical properties of a single dynamic crack event is realized, which specifically includes the following steps:

[0060] S51: The eigenvalues and eigenvectors of the moment tensor M are solved by matrix operation, and then the eigenvalues and eigenvectors of the displacement discontinuity tensor ψ are calculated, wherein the eigenvectors of the displacement discontinuity tensor coincide with the eigenvectors of the moment tensor, and the calculation formula of the eigenvalues of the discontinuity tensor calculated from the eigenvalues of the moment tensor is as follows:

[0061]

[0062] Wherein, λ and μ are the Lame constants; tr(M) is the trace of the moment tensor; M i and ψ i (i=1, 2, 3) are three eigenvalues of the moment tensor and the displacement discontinuity tensor, respectively;

[0063] S52: Establishing the quantitative function relationship between the eigenvalue and eigenvector of the displacement discontinuity tensor and the source parameters of the dynamic crack, and calculating the source parameters of the dynamic crack according to the solved eigenvalue and eigenvector of the displacement discontinuity tensor.

[0064] In one example of the present application, the source parameters include: crack volume Vol, crack area ΔA, crack opening displacement |b|, mode angle α, dynamic crack orientation, dynamic crack instantaneous generation rate V d , absolute energy E c and moment magnitude m n .

[0065] The crack volume Vol, crack area ΔA and crack opening displacement |b| are calculated according to the following specific formula:

[0066]

[0067] Wherein, ζ is a proportional coefficient, and is taken as 10 -3 .

[0068] The mode angle α is calculated according to the eigenvalue of the displacement discontinuity tensor, and the expression is:

[0069]

[0070] The dynamic crack orientation includes crack surface space orientation, crack surface normal n and crack movement vector b, and the calculation formula of n and b in the three-dimensional coordinate system formed by the three eigenvectors of the displacement discontinuity tensor as the base is:

[0071]

[0072] The dynamic crack instantaneous generation rate V d is defined as the ratio of the dynamic crack size to the dynamic rupture time T s , that is:

[0073]

[0074] The absolute energy E c and the moment magnitude m n , wherein the expressions of the absolute energy E c and the moment magnitude m n are as follows:

[0075]

[0076] Wherein, σ t , σ s are the tensile and shear strengths of the sample respectively; M i (i=1,2,3) are three eigenvalues of the moment tensor.

[0077] In one example of the present application, in the step S60, the fracture group data set of the spatial orientation dominant orientation, the dissipated energy spatial distribution, the damage tensor principal axis direction, and the magnitude statistical distribution b value is formed, and specifically includes the following steps:

[0078] S61: Determine the macroscopic main fracture propagation plane, and set the direction perpendicular to the main fracture direction as the X axis and the parallel macroscopic main fracture direction as the Y axis in the propagation plane to construct a fracture propagation plane rectangular coordinate system XOY with the fracture initiation position as the origin; wherein, a plurality of rectangular analysis regions are formed by sequentially intercepting in the Y axis direction with a width of L mm and intercepting in the X axis direction with a length covering the fracture group boundary.

[0079] S62: Calculate the angle θ between all single fractures and the macroscopic main fracture according to the dynamic fracture normal, that is, the complementary angle of the angle between the dynamic fracture normal n and the Y axis direction, calculate and count the range of the angle θ between each dynamic fracture and the main fracture, regard the angle θ between the single fracture and the macroscopic main fracture less than a preset value θ0 as a dynamic fracture event with a dominant orientation, obtain the dynamic fracture event with a dominant orientation and calculate its occurrence frequency, and form a fracture group data set of the fracture spatial orientation dominant orientation.

[0080] The calculation formula of the angle θ is:

[0081]

[0082] In the formula, Y is the Y axis direction vector; is the dynamic fracture normal vector;

[0083] S63: In combination with the dynamic fracture positioning and the dissipated energy calculation results, the dissipated energy values E c are respectively accumulated along the X axis and Y axis directions of the fracture propagation plane with a specified size as the resolution interval, the dissipated energy distribution histograms along the directions parallel and perpendicular to the main fracture propagation direction are drawn, and the dissipated energy spatial distribution morphology of the dynamic fracture group is obtained.

[0084] S64: Jointly consider the size and orientation of the dynamic fracture, define the fracture group damage tensor D, and solve the eigenvalue and eigenvector of the fracture damage tensor D in each rectangular analysis region through matrix operation; wherein, the calculation formula of the fracture group damage tensor D is:

[0085]

[0086] In the formula, D kl is the fracture group damage tensor; N c is the total number of dynamic fractures in the volume V; A i is the area of the i-th fracture; n i is the normal vector of the i-th fracture; ​

[0087] S65: Calculate the moment magnitude m of all cracks n And determine the distribution range, record the maximum and minimum values of the moment magnitude as m a , m b , divide the interval [m a , m b ] into S moment magnitude subintervals, count the frequency of dynamic crack events in each subinterval and the frequency P(m) of events greater than the magnitude m of the interval, draw the P(m)-m curve in the semilog coordinate system, linearly fit the log P(m)-m curve, then the fitting slope is the b value of the G-R relationship, obtain the crack group data set of the magnitude statistical distribution b value, and the magnitude statistical distribution b value is used to quantify the proportion of crack size in the dynamic crack group.

[0088] In one example of the present application, in step S60, the multi-dimensional quantitative characterization of the macroscopic main crack propagation path realizes the cross-scale process description of the rock mass dynamic crack evolution from single to cluster and from micro to macro, and specifically includes the following steps:

[0089] In the spatial orientation dimension: determine the direction in which the crack group occupies the largest proportion in the rectangular analysis region, which is the optimal direction of crack group propagation, and connect the optimal direction in each rectangular analysis region to obtain the macroscopic main crack propagation path determined by the spatial orientation

[0090] In the damage tensor dimension: determine the principal axis direction of the damage tensor of the crack group in the rectangular analysis region, and connect the principal axis direction in each rectangular analysis region, which is the macroscopic main crack propagation path determined by the damage tensor

[0091] In the energy dissipation dimension: set the energy dissipation cumulative threshold E f , calculate the cumulative value E r of the dissipated energy of all crack events in the rectangular analysis region; when E r is greater than or equal to E f , it is considered that the opening size of the regional crack group is large, and the main fracture occurs; determine the region R r whose dissipated energy cumulative value E f exceeds E k , and connect the distribution position of the region R k , which is the macroscopic main crack propagation path determined by the energy dissipation dimension

[0092] In the magnitude distribution dimension: set the magnitude threshold m t , when the magnitude of the dynamic crack event is greater than the set threshold, it is considered that the event has a large-scale fracture, and the main fracture occurs; select all dynamic crack events with magnitude m nMore than m t Data set E m The macroscopic main fracture propagation path is described by the coordinates of the set E m

[0093] From The two paths with the highest coincidence degree are selected from the four propagation paths, and the average of the directions of the two paths is the macroscopic main fracture propagation path determined by multi-dimension, and then the cross-scale process description of the rock mass dynamic fracture evolution from single to cluster and from micro to macro is realized.

[0094] Another object of the application is to provide a dynamic fracture source parameter quantitative inversion and fracture cross-scale characterization system, characterized by comprising:

[0095] The signal acquisition device is configured to determine the potential area of the dynamic fracture event, and N+1 acoustic sensors are arranged to form a monitoring network covering the potential area; wherein the acoustic sensor network layout optimization is realized by adjusting the acoustic sensor position to reduce the numerical value of the covariance determinant;

[0096] The signal processing device is configured to collect the waveform signal of the dynamic fracture event in the rock mass fracture process by the acoustic sensor, filter the environmental noise by the filter and enhance the real signal, and calculate the ratio of the short-time window to the long-time window by the characteristic function E(t) to identify the real signal characteristics, wherein when the ratio of the short-time window to the long-time window exceeds the set trigger threshold, the first wave arrival time t0 is picked up, and the take-off amplitude f0 is obtained;

[0097] The source coordinate obtaining device is configured to utilize the obtained waveform first wave arrival time, acoustic sensor coordinates and wave velocity information to determine the dynamic fracture source coordinates (x e ,y e ,z e ) according to the positioning algorithm, calculate the variance of the source coordinates in three directions, obtain the actual confidence interval size of the source coordinates and quantify the positioning result reliability, and screen to obtain a set of reliable source coordinate points;

[0098] The inversion model establishing device is configured to establish a displacement discontinuity tensor microcrack source characterization model of the dynamic fracture event based on the whole process of the generation of the dynamic fracture, the propagation of the wave and the response of the acoustic sensor, construct an objective function under the constraint condition that the second eigenvalue of the displacement discontinuity tensor is zero, and calculate the moment tensor component m b of the dynamic fracture event;

[0099] ​The source parameter solving device is configured to solve source core parameters of a dynamic crack according to moment tensor components, and realize quantitative and fine description of scale, orientation and mechanical characteristics of a single dynamic crack event; wherein the source core parameters include crack volume, crack area, crack opening displacement, crack spatial orientation, shear property, instantaneous generation rate, released energy and moment magnitude.

[0100] The dynamic crack group depicting device is configured to statistically summarize all single dynamic crack source core parameters obtained through inversion, form a crack group data set of spatial orientation dominant orientation, dissipated energy spatial distribution, damage tensor principal axis direction and magnitude statistical distribution b value, quantitatively represent a macroscopic main crack propagation path in multiple dimensions, and realize cross-scale process depiction of rock mass dynamic crack evolution from single to group and from micro to macro.

[0101] Compared with the prior art, the present application has the following beneficial effects:

[0102] 1、The present application picks up the first wave arrival time and the take-off amplitude, and identifies the real signal characteristics by calculating the ratio of short time window to long time window based on waveform characteristics, to pick up the first wave arrival time t0 and the take-off amplitude f0; compared with the traditional method, the present application is beneficial to avoid the picking error caused by the similar noise waveform and microseismic waveform, so that the first wave arrival time is determined more quickly and accurately.

[0103] 2、The present application optimizes the sensor network layout, screens the coordinate points with large positioning errors, comprehensively considers the whole process of source generation, wave propagation and sensor response dynamics, and realizes inversion of the rupture source parameters under certain constraints by constructing an objective function, so that the data calculation is more accurate and the theoretical model is more perfect, thereby ensuring the high precision of the crack source parameter inversion result and providing reliable input data for subsequent single crack and crack group event depiction and analysis.

[0104] 3、The present application provides a quantitative inversion and fine description method of single micro crack source parameters such as orientation, scale and mechanics, which can more accurately understand the crack propagation and damage in the structure of rock under stress, and is helpful to improve the accuracy of monitoring rock structure instability, which has important significance for timely discovering potential safety hazards and preventing catastrophic accidents.

[0105] 4、On the basis of single crack inversion, the present application forms a macroscopic main crack propagation multi-dimensional representation method based on crack group spatial orientation dominant orientation, dissipated energy spatial distribution, damage tensor principal axis direction and magnitude statistical distribution b value, which extends the traditional inversion-based source parameters to represent macroscopic propagation path by using crack group parameters, realizes organic integration of rock rupture macro-micro cross-scale process, and is helpful to intuitively reveal the rock rupture evolution process and source catastrophe mechanism.

[0106] The most preferred embodiments of implementing the present application will be described in more detail hereinafter with reference to the drawings, so as to make the features and advantages of the present application easily understood. BRIEF DESCRIPTION OF DRAWINGS

[0107] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings of the embodiments of the present application will be briefly introduced hereinafter. The drawings are merely used to show some embodiments of the present application, and the present application is not limited to the drawings.

[0108] Figure 1 Flow chart of a dynamic fracture source parameter quantitative inversion and fracture cross-scale characterization method according to an embodiment of the present application;

[0109] Figure 2 Flow chart of dynamic fracture event original waveform signal processing according to an embodiment of the present application;

[0110] Figure 3 Flow chart of a simplex positioning algorithm according to an embodiment of the present application;

[0111] Figure 4 Length diagram of a dynamic fracture coordinate error ellipsoid three-dimensional confidence interval according to an embodiment of the present application;

[0112] Figure 5 Schematic diagram of a dynamic fracture generation-wave propagation-sensor response forward theoretical model according to an embodiment of the present application;

[0113] Figure 6 Schematic diagram of a fracture spatial orientation determination method in a displacement discontinuity tensor coordinate system according to an embodiment of the present application;

[0114] Figure 7 Schematic diagram of a dynamic fracture event typical waveform and calculation parameter according to an embodiment of the present application;

[0115] Figure 8 Schematic diagram of a dynamic fracture group rectangular analysis region according to an embodiment of the present application;

[0116] Figure 9 Schematic diagram of a dynamic fracture group magnitude statistical distribution b value calculation according to an embodiment of the present application. DETAILED DESCRIPTION

[0117] In order to make the purpose, technical scheme and advantages of the technical scheme of the present application more clear, the technical scheme of the embodiments of the present application will be described clearly and completely below in combination with the drawings of the embodiments of the present application. The same reference signs in the drawings represent the same parts. It should be noted that the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the described embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0118] Unless otherwise defined, technical terms or scientific terms used herein should be understood as having the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terms "first", "second", and similar terms used in the description and the claims of the present patent application do not necessarily mean any order, number, or importance, but are only used to distinguish different components. Similarly, the terms "one" or "a" and the like do not necessarily mean a quantity limitation. The terms "comprise" or "include" and the like mean that the elements or objects before the terms encompass the elements or objects listed after the terms and their equivalents, without excluding other elements or objects. The terms "connected" or "connected" and the like do not necessarily mean physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "up", "down", "left", "right", and the like are only used to represent relative positional relationships, and when the absolute positions of the described objects change, the relative positional relationships may also change accordingly.

[0119] According to the dynamic fracture source parameter quantitative inversion and fracture cross-scale characterization method of the first aspect of the present application, as shown in Figure 1 The characterization method comprises the following steps:

[0120] S10: Determine the potential area where the dynamic fracture event occurs, and arrange N+1 (numbered according to 0, 1, 2, …, N, N≥6) acoustic sensors to form a monitoring network covering the potential area; wherein the acoustic sensor network layout optimization is achieved by adjusting the acoustic sensor position to reduce the numerical value of the covariance determinant;

[0121] S20: As shown in Figure 2 The waveform signal of the dynamic fracture event in the rock mass fracture process is collected by the acoustic sensor, the environmental noise is filtered by the filter and the real signal is enhanced, and the ratio of the short-time window to the long-time window is calculated by the characteristic function E(t) to identify the real signal characteristics, wherein when the ratio of the short-time window to the long-time window exceeds the set trigger threshold, the first wave arrival time t0 is picked up, and the take-off amplitude f0 is obtained;

[0122] S30: Using the obtained waveform first wave arrival time, acoustic sensor coordinates and wave velocity information, the dynamic fracture source coordinates (xe y e z e ), by calculating the variance of the source coordinates in three-dimensional directions, the actual confidence interval size of the source coordinates is obtained, and the positioning result reliability is quantified, and a set of reliable source coordinates is screened out;

[0123] S40: based on the generation of dynamic crack, wave propagation, forward full process of acoustic sensor response, a displacement discontinuity tensor microcrack source characterization model of dynamic crack event is established, a target function is constructed under the constraint condition that the second eigenvalue of the displacement discontinuity tensor is zero, and the moment tensor component m b of the dynamic crack event is calculated;

[0124] S50: according to the moment tensor component, the source core parameters of the dynamic crack are solved, and the scale, orientation and mechanical properties of a single dynamic crack event are quantitatively and finely described; wherein the source core parameters include crack volume, crack area, crack opening displacement, crack spatial orientation, tension-shear property, instantaneous generation rate, released energy and moment magnitude;

[0125] S60: all the single dynamic crack source core parameters obtained by inversion are summarized and statistically analyzed to form a crack group dataset including spatial orientation dominant direction, dissipated energy spatial distribution, damage tensor principal axis direction and magnitude statistical distribution b value, which quantitatively characterizes the macroscopic main crack propagation path in multiple dimensions, and realizes the cross-scale process description of the dynamic crack evolution of rock mass from single to cluster and from micro to macro.

[0126] The characterization method is based on waveform characteristics when picking up the first arrival time and the take-off amplitude, and the ratio of short-time window to long-time window is calculated by the characteristic function E(t) to identify the real signal characteristics, and the first arrival time t0 and the take-off amplitude f0 are picked up. Compared with the traditional method, this method is helpful to avoid the picking error caused by the similarity between noise waveform and microseismic waveform, so it is more rapid and accurate to determine the first arrival time.

[0127] The characterization method optimizes the sensor network layout and screens out the coordinate points with large positioning error, comprehensively considers the dynamic full process of source generation, wave propagation and sensor response, and realizes the inversion of the rupture source parameters under certain constraint conditions, so that the data calculation is more accurate and the theoretical model is more perfect, thereby ensuring the high precision of the crack source parameter inversion result, and providing reliable input data for subsequent single crack and crack group event description and analysis.

[0128] The characterization method provides a quantitative inversion and fine description method for the orientation, size and mechanical source parameters of a single microcrack, can more accurately understand the crack propagation and damage condition of the structure inside the rock under the action of stress, and is helpful to improve the accuracy of monitoring the instability of rock structure, which has important significance for timely discovering potential safety hazards and preventing catastrophic accidents.

[0129] On the basis of the inversion of a single crack, the characterization method forms a multi-dimensional macroscopic main crack propagation characterization method based on the spatial orientation dominant orientation of crack group, the spatial distribution of dissipated energy, the main axis direction of damage tensor and the statistical distribution b value of magnitude, and extends the traditional inversion-based source parameters to the macroscopic propagation path using the parameters of crack group, realizes the organic integration of the macro-microscopic cross-scale process of rock failure, and helps to intuitively reveal the rock failure evolution process and source disaster mechanism.

[0130] In one example of the present application, in the step S10, the numerical value of the covariance determinant is reduced by adjusting the position of the acoustic wave sensor, and the optimization of the acoustic wave sensor network layout specifically includes the following steps:

[0131] S11: Based on the error ellipsoid theory, it is known that the smaller the determinant of the variance-covariance matrix cov(X e ), the smaller the volume of the error ellipsoid, and the network layout scheme that satisfies the minimum cov(X e ) is the optimal network layout scheme; wherein the formula of the variance-covariance matrix cov(X e ) is as follows:

[0132] cov(X e ) = sigma 2 (K T V -1 K) -1 = sigma 2 Q

[0133] In the formula, indicates the comprehensive accuracy of each acoustic wave sensor to time measurement; the matrix Q depends on the geometric distribution of the acoustic wave sensor network and the position of the dynamic crack event source;

[0134] Wherein, V is an N*N order idempotent matrix, that is

[0135]

[0136] Wherein, (I i ,m i ,n i ) is the direction cosine of the i-th acoustic wave sensor to the estimated position of the dynamic crack source;

[0137]

[0138] S12: fine-tuning the i-th acoustic wave sensor position, changing the element value of (l i -l0), (m i -m0), (n i -n0) in the matrix K until the determinant of the matrix K reaches the minimum value, at this time the minimum value position is determined as the optimal position of the acoustic wave sensor (x i , y i , z i ), repeating the step, fine-tuning all acoustic wave sensors in turn until the determinant of the variance-covariance matrix cov(X e ) reaches the minimum value, determining the optimal position of all acoustic wave sensors to achieve the optimization of the acoustic wave sensor network;

[0139] wherein (x e , y e , z e ) is the coordinate of the source positioning point, l i , m i , n i The calculation formula is as follows:

[0140]

[0141] In the formula, R ei is the straight-line distance between the moving crack source (x e , y e , z e ) and the i-th acoustic wave sensor (x i , y i , z i ).

[0142] In an example of the present application, in the step S20, the expression of the characteristic function E(t) is as follows:

[0143]

[0144] In the formula, X i is the waveform amplitude corresponding to the time series; is the first-order difference thereof; C i is a weight constant, and its C i expression is as follows:

[0145] In an example of the present application, the step S30 specifically comprises the following steps:

[0146] S31: using the first arrival time data received by all acoustic wave sensors, combining the acoustic wave sensor coordinates, material wave speed information, and through the simplex positioning algorithm, the seismic source is three-dimensionally positioned. It is through constructing a simplex and comparing the function values of each vertex of the simplex in space, through mapping, expanding outward, shrinking inward, and shrinking four basic changes to constantly replace the vertex with a large function value, until the point with the smallest function value in space is found, which is the optimal solution of the spatial coordinates of the seismic source. The specific process of the simplex positioning algorithm is shown in Figure 3 . Among them, the waveform of the moving fracture source is transmitted to the i-th acoustic wave sensor position coordinate theoretical travel time T i The calculation formula is:

[0147]

[0148] In the formula, (x e , y e , z e ) is the coordinate of the moving fracture source; (x i , y i , z i ) is the coordinate of the i-th acoustic wave sensor; c p is the P-wave speed of the material; T0 is the time when the fracture source occurs;

[0149] S32: the target function is constructed by accumulating and summing the absolute value of the difference between the actual time and the theoretical time of all acoustic wave sensors, and the expression of the target function is as follows:

[0150]

[0151] In the formula, N+1 is the number of acoustic wave sensors arranged; is the first arrival time picked up by the i-th acoustic wave sensor;

[0152] S33: as shown in Figure 4 , the variance of the source coordinate point (x e , y e , z e ) in three-dimensional direction is calculated through the major diagonal elements of the error ellipsoid variance-covariance matrix, and the confidence interval of the source positioning point coordinate in x, y, z three directions is obtained under the confidence level t α / 2 is 95%; wherein the narrower the confidence interval of the source positioning point in three-dimensional direction, the smaller the volume of the error ellipsoid, which indicates that the acoustic emission positioning result is more accurate; the confidence interval threshold x t , y t , z t is set in three directions, when the three-dimensional confidence interval length of the positioning point satisfies x l ≤x t , y l ≤y t , zl ≤z t If the result is reliable, the source coordinate point is considered to be positioned reliably.

[0153] If the confidence level is t α / 2 , the confidence interval length of the dynamic fracture source coordinate point (x e , y e , z e ) in the x, y, and z directions is calculated according to the following formula:

[0154]

[0155] In the formula, q 11 , q 22 , and q 33 are the main diagonal elements of the matrix Q, respectively; and σ 2 represents the comprehensive accuracy of the time measurement of each acoustic sensor.

[0156] S34: Repeat the above steps until all source positioning coordinates meeting the condition of S33 are screened out, and a set of source coordinate data with accurate positioning and small error is obtained.

[0157] In one example of the present application, in the step S40, a displacement discontinuity tensor source characterization model of the dynamic fracture event is established based on the whole process of the generation of the dynamic fracture, the propagation of the wave, and the forward acoustic sensor response, as shown in the following formula: Figure 5

[0158] S41: In the process of the acoustic sensor response, the sensitivity conversion coefficient S A is defined to realize the conversion between the output voltage value of the acoustic sensor and the different physical quantities of the input normal displacement and to quantify the coupling quality of the acoustic sensor, thereby improving the inversion accuracy of the source parameters, wherein the sensitivity conversion coefficient S A is calculated according to the following formula:

[0159]

[0160] In the formula, υ is the medium Poisson's ratio; P is the applied load value; d is the propagation distance; f0 is the picked P-wave take-off amplitude; and G1 is the function value at the first peak value inflection point of the time-varying theoretical normal displacement.

[0161] S42: In the process of the wave propagation of the dynamic fracture source, only the far-field displacement generated by the P wave is considered, and the function relationship between the displacement disturbance at the dynamic fracture source and the displacement response generated at the acoustic sensor is established by the Green function and the elastic wave equation under the assumption of the synchronous source, and the specific expression is as follows:

[0162]

[0163] ​wherein r is the distance from the crack source to the acoustic sensor position; γ is the directional cosine between the crack source and the acoustic sensor; c p is the P-wave velocity; M jk is the moment tensor component value; T s is the dynamic fracture (rise) time of the dynamic crack;

[0164] S43: the displacement discontinuity tensor ψ ij is used to represent the generated dynamic crack source, wherein the displacement discontinuity tensor ψ ij The calculation formula is as follows:

[0165]

[0166] wherein C ijkl is the material elastic stiffness tensor; ΔA is the new area of the dynamic crack; b is the motion vector of the dynamic crack; n is the normal vector of the dynamic crack surface;

[0167] The displacement discontinuity tensor ψ is solved by matrix operation to obtain three eigenvalues thereof:

[0168]

[0169] wherein ψ1, ψ2 and ψ3 are respectively the first, second and third eigenvalues of the displacement discontinuity tensor; |b| is the L2 norm of the motion vector b, that is,

[0170] In the dynamic crack source representation model, the second eigenvalue ψ2 of the displacement discontinuity tensor must be zero.

[0171] In one example of the present application, in the step S40, the objective function is constructed under the constraint condition that the second eigenvalue of the displacement discontinuity tensor is zero, and the moment tensor component m b Specifically, the method comprises the following steps:

[0172] Firstly, the relationship between the displacement discontinuity tensor ψ and the moment tensor M is established, and in the isotropic medium, the relationship between the displacement discontinuity tensor and the moment tensor satisfies the following relationship:

[0173] M kl = ψ ij C ijkl = λδ kL (ψ1+ψ2+ψ3)+2μψ kl

[0174] wherein C ijkl is the medium stiffness matrix; λ and μ are the Lame constants;

[0175] Secondly, the constraint condition of the second eigenvalue of the displacement discontinuity tensor ψ, ψ2=0, is a condition to be satisfied in any coordinate system, according to the relationship between the displacement discontinuity tensor and the moment tensor, the constraint condition of ψ2=0 is rewritten into the form of moment tensor invariants, and the expression is as follows:

[0176]

[0177] In the formula, J1, J2 and J3 are the first, second and third invariants of the moment tensor M;

[0178] Then, according to the theoretical normal displacement of P wave at different acoustic wave sensor positions and the measured normal displacement data, the Lagrange indefinite multiplier γ is introduced under the constraint condition of ψ2=0 to determine the objective function E and then to solve the moment tensor components, wherein the specific formula of the objective function E is as follows:

[0179]

[0180] In the formula, (S A f0) i is the measured normal displacement at the i-th acoustic wave sensor; u i (x, M jk ) is the normal displacement calculated by the dynamic crack moment tensor source theory at the i-th acoustic wave sensor;

[0181] Finally, the six components of the moment tensor are obtained by iteratively solving the objective function E by using the damped Newton method, that is, in the solving process, the initial trial value M 0 (m1, m2, m3, m4, m5, m6, γ) is given first, and M is updated according to the iteration formula constantly until the L2 norm of the moment tensor in this step and the last step is less than the preset iteration convergence precision, at which time m1 to m6 are the six components of the moment tensor, and according to the symmetry of the moment tensor, the moment tensor M can be written as:

[0182]

[0183] In an example of the present application, in the S50 step, the source core parameters of the dynamic crack are solved according to the moment tensor components, and the quantitative and fine description of the scale, orientation and mechanical properties of a single dynamic crack event is realized, which specifically includes the following steps:

[0184] S51: The eigenvalues and eigenvectors of the moment tensor M are solved by matrix operation, and then the eigenvalues and eigenvectors of the displacement discontinuity tensor ψ are calculated, wherein the eigenvectors of the displacement discontinuity tensor coincide with the eigenvectors of the moment tensor, and the calculation formula of the eigenvalues of the discontinuity tensor calculated from the eigenvalues of the moment tensor is as follows:

[0185]

[0186] where λ and μ are the Lame constants; tr(M) is the trace of the moment tensor; M i and ψ i (i = 1, 2, 3) are three eigenvalues of the moment tensor and the displacement discontinuity tensor respectively;

[0187] S52: Establish a quantitative function relationship between the eigenvalues and eigenvectors of the displacement discontinuity tensor and the source parameters of the dynamic crack, and calculate the source parameters of the dynamic crack according to the solved eigenvalues and eigenvectors of the displacement discontinuity tensor.

[0188] In an example of the present application, the source parameters include: crack volume Vol, crack area ΔA, crack opening displacement |b|, mode angle α, dynamic crack orientation, dynamic crack instantaneous generation rate V d , absolute energy E c , and moment magnitude m n :

[0189] The crack volume Vol, crack area ΔA and crack opening displacement |b| are specifically calculated according to the following formulas:

[0190]

[0191] where ζ is a proportional coefficient, and is taken as 10 -3 ;

[0192] The mode angle α is used to determine the tensile-shear property of the dynamic crack, and the formula for calculating the mode angle α according to the eigenvalues of the displacement discontinuity tensor is:

[0193]

[0194] That is, for the tensile-shear property of the dynamic crack, the mode angle α is used for determination, and the value range is [0°, 90°], and the method for determining the tensile-shear property of the dynamic crack according to the value of the mode angle α is: when α = 0° or 90°, the dynamic crack is a pure opening or closing property; when α = 45°, the dynamic crack is a shear property; when 0° < α ≤ 15° or 75° ≤ α < 90°, the dynamic crack is dominated by the I-type mechanism of opening or closing; when 15° < α < 30° or 60° < α < 75°, the dynamic crack is dominated by the complex mechanism of opening-shear or closing-shear; when 30° ≤ α < 45° and 45° < α ≤ 60°, the dynamic crack is a II-type mechanism dominated by shear;

[0195] The dynamic crack orientation is determined, and the dynamic crack orientation includes the crack surface space orientation, the crack surface normal n and the crack motion vector b, wherein in a three-dimensional coordinate system formed by the three eigenvectors of the displacement discontinuity tensor as the base, the calculation formulas of the crack surface normal n and the crack motion vector b are:

[0196]

[0197] n and b lie in the plane formed by the first and third eigenvectors of the displacement discontinuity tensor, and n and b are located on either side of the first eigenvector of the displacement discontinuity tensor, with the included angle being the mode angle α. For example... Figure 6 As shown, based on the calculated first and third eigenvectors of the displacement discontinuity tensor and the mode angle α, the moving fracture normal n and the moving fracture motion vector b can be determined. Then, the moving fracture and its orientation can be plotted, i.e., using the moving fracture coordinates (x... e y e , z e Centered on, with The plane with side length n and perpendicular to the normal n is the orientation of the dynamic fracture structure plane;

[0198] Quantitative dynamic fracture instantaneous generation rate V d It is defined as the dynamic crack size. With dynamic rupture time T s The ratio, that is:

[0199]

[0200] For example, such as Figure 7 As shown, a typical waveform of a dynamic fracture event acquired from rock fracturing is presented. A local magnification reveals that the arrival time t0 of the first wave, determined by the ratio of the characteristic function's long and short time windows, is the starting amplitude f0, which ranges from the lowest wave trough to zero. The time interval from the arrival time t0 of the first wave to the starting amplitude f0 is the dynamic fracture time T. s .

[0201] Calculate the absolute energy E dissipated during the formation of a dynamic fracture. c and moment magnitude m n Among them, absolute energy E c and moment magnitude m n The expression is as follows:

[0202]

[0203] Where, σ t σ s These are the tensile and shear strengths of the specimen, respectively; M i (i = 1, 2, 3) are the three eigenvalues ​​of the moment tensor.

[0204] In one example of the present invention, step S60, which involves forming a fracture cluster dataset with spatial orientation dominance, spatial distribution of dissipated energy, principal axis direction of damage tensor, and magnitude statistical distribution b-values, specifically includes the following steps:

[0205] S61: Determine the macroscopic main crack propagation plane, define the direction perpendicular to the main crack as the X axis and the direction parallel to the macroscopic main crack as the Y axis in the propagation plane, and construct a crack propagation plane rectangular coordinate system XOY with the crack initiation position as the origin; wherein, a number of rectangular analysis regions are formed by sequentially intercepting a width of L mm in the Y axis direction and intercepting a length covering the crack group boundary in the X axis direction; as shown in FIG. 6, the vertical long rectangular frame close to 0 on the X axis is a pre-prepared notch of the sample, and the circular dots are spatial coordinate points of the dynamic crack obtained by positioning algorithm, a number of rectangular analysis regions are formed by sequentially intercepting a width of L mm in the Y axis direction and intercepting a length covering the crack group boundary in the X axis direction, that is, in the X axis direction, the dynamic crack coordinates can be completely contained, and the propagation path is analyzed by the circular dot distribution in the rectangular frame. Figure 8

[0206] S62: Calculate the angle θ between all single cracks and the macroscopic main crack according to the normal direction of the dynamic crack, that is, the complementary angle of the angle between the normal direction n of the dynamic crack and the Y axis direction, and the calculation formula of the angle θ is:

[0207]

[0208] wherein, is the Y axis direction vector; is the dynamic crack normal vector;

[0209] Calculate and count the range of the angle θ between each dynamic crack and the main crack, regard the single crack with an angle θ less than a preset value θ0 as a dynamic crack event with a dominant orientation, obtain the dynamic crack event with a dominant orientation and calculate its occurrence frequency, and form a crack group data set with a dominant orientation of crack space orientation;

[0210] S63: Combine the positioning of the dynamic crack and the calculation result of the dissipated energy, and accumulate the dissipated energy values E c respectively along the X axis and Y axis directions of the crack propagation plane with a specified size (for example, 1 mm) as the resolution interval, draw the dissipated energy distribution histogram along the direction parallel and perpendicular to the main crack propagation direction, and obtain the spatial distribution form of the dissipated energy of the dynamic crack group;

[0211] S64: Jointly consider the size and orientation of the dynamic crack, define a crack group damage tensor D, which represents the overall damage degree of the dynamic crack in a unit volume, and the calculation formula of the crack group damage tensor D is:

[0212]

[0213] wherein, D kl is the crack group damage tensor; N c is the total number of dynamic cracks in the volume V; A i is the area of the i-th crack; n i is the normal vector of the i-th crack.​

[0214] The eigenvalues ​​and eigenvectors of the crack damage tensor D within each rectangular analysis region are solved using matrix operations, i.e.:

[0215] (D0δ kl -D kl )U i =0

[0216] Where D0 is the eigenvalue of the crack swarm damage tensor; U i is the eigenvector of the crack group damage tensor.

[0217] The largest eigenvalue of the fracture swarm damage tensor represents the fracture density in the analysis area, and the principal axis direction of the fracture swarm damage tensor represents the spatial weighted orientation of the fracture swarm. The damage tensor eigenvalues ​​and principal axis directions in all regions are obtained to form a fracture swarm damage tensor dataset.

[0218] S65: Calculate the moment magnitude m of all fractures. n The distribution range is determined, and the maximum and minimum moment magnitudes are denoted as m. a m b , the interval [m a ,m b The region is divided into S equal-order moment magnitude sub-intervals. The frequency of dynamic fracture events and the frequency P(m) of events greater than magnitude m in each sub-interval are statistically analyzed. A P(m)-m curve is plotted in a semi-logarithmic coordinate system. A linear fit is then performed on the log P(m)-m curve; the slope of the fit is the b-value of the GR relationship. For example, ... Figure 9 As shown, the left side is a bar chart of magnitude and corresponding frequency statistics, and the right side is a distribution chart of magnitude and frequency of occurrence of earthquakes greater than magnitude m. It can be seen from the figure that the b value of the fitted slope of the GR relationship is 2.02. The fracture group dataset with the magnitude statistical distribution b value is obtained by segmented calculation. By comparing the magnitude statistical distribution b value in different stages, the proportion of fracture scale in the dynamic fracture group can be quantified. The smaller the magnitude statistical distribution b value, the higher the proportion of large-scale fracture events in the dynamic fracture group in that stage.

[0219] In one example of the present invention, step S60 involves multi-dimensional quantitative characterization of the macroscopic main fracture propagation path, realizing a cross-scale process characterization of the dynamic fracture evolution of the rock mass from single to clustered, and from micro to macroscopic. Specifically, this includes the following steps:

[0220] In terms of spatial orientation: the orientation with the largest proportion of the fracture group within the rectangular analysis area in step S61 is determined, which is the optimal orientation for fracture group expansion. Connecting the optimal orientations within each rectangular analysis area yields the macroscopic main fracture expansion path determined by spatial orientation.

[0221] Regarding the damage tensor dimension: the principal axis directions of the damage tensor within the rectangular analysis regions of the fracture swarm in step S61 are determined, and the principal axis directions within each rectangular analysis region are connected, which are the macroscopic main fracture propagation paths determined by the damage tensor.

[0222] Regarding energy dissipation: Set an energy dissipation cumulative threshold E. f Calculate the cumulative energy dissipation E of all fracture events within the rectangular analysis region in step S61. r . When E r Greater than or equal to E f At that time, it was considered that the regional fracture swarm had a large opening scale, and the main fracture had occurred; the cumulative value of all dissipated energy E was determined. r More than E f Region R K Connecting region R k The distribution location is the macroscopic main fracture propagation path determined by the energy dissipation dimension.

[0223] Regarding the magnitude distribution dimension: set a magnitude threshold m. t When the magnitude of a dynamic fracture event exceeds a set threshold, it is considered that a large-scale rupture has occurred, and the main rupture has occurred. All dynamic fracture events with magnitudes m are then selected. n More than m t Dataset E m Through set E m Coordinates characterize the macroscopic main fracture propagation path

[0224] from The two paths with the highest overlap among the four expansion paths are selected. The average value of the orientation of these two paths is the macroscopic main fracture expansion path determined by multi-dimensional comprehensive analysis, thereby realizing the cross-scale process characterization of rock mass dynamic fracture evolution from single to cluster and from micro to macro.

[0225] A quantitative inversion system for dynamic fracture source parameters and a cross-scale characterization system for fracture, according to a second aspect of the present invention, comprises:

[0226] The signal acquisition device is configured to determine the potential area where dynamic fracture events occur, and N+1 acoustic wave sensors (numbered according to the sequence 0, 1, 2, ..., N, N≥6) are arranged to form a monitoring network covering the potential area; wherein, the acoustic wave sensor network layout is optimized by adjusting the position of the acoustic wave sensors to reduce the value of the covariance determinant.

[0227] The signal processing device is configured to collect waveform signals of dynamic fracture events in the rock mass fracture process by the acoustic sensor, filter environmental noise by a filter, enhance the real signal, and calculate the ratio of a short time window to a long time window by a characteristic function E(t) to identify the real signal characteristics, wherein when the ratio of the short time window to the long time window exceeds a set trigger threshold, the first arrival time t0 is picked up, and the take-off amplitude f0 is obtained.

[0228] The source coordinate obtaining device is configured to determine the dynamic fracture source coordinate (x e ,y e ,z e ) according to a positioning algorithm by using the waveform first arrival time, the acoustic sensor coordinate and the wave velocity information, calculate the variance of the source coordinate in three directions to obtain the actual confidence interval size of the source coordinate and quantify the positioning result reliability, and screen to obtain a set of reliable source coordinate points.

[0229] The inversion model establishing device is configured to establish a displacement discontinuity tensor micro-crack source representation model of the dynamic fracture event based on the generation of the dynamic fracture, the wave propagation and the forward whole process of the acoustic sensor response, construct an objective function under the constraint condition that the second eigenvalue of the displacement discontinuity tensor is zero, and calculate the moment tensor component m b .

[0230] The source parameter solving device is configured to solve the source core parameters of the dynamic fracture according to the moment tensor component, and realize quantitative and fine description of the size, orientation and mechanical properties of a single dynamic fracture event; wherein the source core parameters include the crack volume, the crack area, the crack opening displacement, the crack spatial orientation, the tensile-shear property, the instantaneous generation rate, the released energy and the moment magnitude.

[0231] The dynamic fracture group depicting device is configured to induce and statistically analyze all the single dynamic fracture source core parameters obtained by inversion to form a crack group data set of the spatial orientation dominant orientation, the dissipated energy spatial distribution, the damage tensor principal axis direction and the magnitude statistical distribution b value, quantitatively represent the macroscopic main crack propagation path in multiple dimensions, and realize the cross-scale process depiction of the rock mass dynamic fracture evolution from single to group and from micro to macro.

[0232] When picking up the first arrival time and the take-off amplitude, the representation system is based on waveform characteristics, calculates the ratio of a short time window to a long time window by a characteristic function E(t) to identify the real signal characteristics, picks up the first arrival time t0 and the take-off amplitude f0; compared with the traditional method, this method is helpful to avoid the picking error caused by the similarity between the noise waveform and the microseismic waveform, and thus the first arrival time is determined more quickly and accurately.

[0233] The characterization system optimizes the sensor network layout, screens coordinate points with large positioning errors, comprehensively considers the whole process of source generation, wave propagation and sensor response dynamics forward, and realizes the inversion of the source parameters of the fracture source under certain constraints to obtain more accurate data and more perfect theoretical models, thereby ensuring the high precision of the inversion results of the fracture source parameters and providing reliable input data for subsequent single fracture and fracture group event characterization and analysis.

[0234] The characterization system provides a quantitative inversion and fine description method for the orientation, size and mechanical source parameters of a single micro-fracture, which can more accurately understand the fracture expansion and damage of the structure inside the rock under stress, and help improve the accuracy of monitoring the instability of the rock structure, which is of great significance for timely discovering potential safety hazards and preventing catastrophic accidents.

[0235] Based on the inversion of a single fracture, the characterization system forms a multi-dimensional characterization method for the macroscopic main fracture expansion based on the spatial orientation advantage direction of the fracture group, the spatial distribution of dissipated energy, the main axis direction of the damage tensor and the statistical distribution b value of the magnitude, which extends the traditional inversion-based source parameters to the macroscopic expansion path using the parameters of the fracture group, realizes the organic integration of the macro-microscopic cross-scale process of rock failure, and helps intuitively reveal the rock failure evolution process and source catastrophe mechanism.

[0236] The above describes an exemplary embodiment of the dynamic fracture source parameter quantitative inversion and fracture cross-scale characterization method and system in detail with reference to the preferred embodiments, however, those skilled in the art can understand that various modifications and improvements can be made to the above specific embodiments without departing from the concept of the present application, and various technical features and structures of the present application can be combined without exceeding the scope of the present application, and the protection scope of the present application is determined by the appended claims.

Claims

1. A method for dynamic crack source parameter quantitative inversion and rupture cross-scale characterization, characterized in that, The characterization method comprises the following steps: S10: determine the potential area where the dynamic fracture event occurs, arrange N +1 acoustic wave sensor forms a monitoring network covering the potential area; wherein the optimization of the acoustic wave sensor network layout is achieved by adjusting the acoustic wave sensor position to reduce the numerical value of the covariance determinant; S20: Collecting the waveform signal of the dynamic fracture event in the rock mass fracture process by the acoustic wave sensor, filtering the environmental noise by the filter and enhancing the real signal, and identifying the real signal feature by the characteristic function The ratio of the short-time window to the long-time window is calculated to identify the real signal feature, wherein when the ratio of the short-time window to the long-time window exceeds the set trigger threshold, the first arrival time is picked up , and the take-off amplitude is obtained ; S30: Using the obtained waveform first arrival time, acoustic sensor coordinates and wave velocity information, the dynamic fracture source coordinates are determined according to a positioning algorithm (S30) , , ), the actual confidence interval size of the source coordinates is obtained by calculating the variance of the source coordinates in three-dimensional directions, and the positioning result reliability is quantified, and a set of reliable source coordinates is screened. S40: based on the generation of dynamic crack, wave propagation, forward process of acoustic sensor response, displacement discontinuity tensor micro crack source characterization model of dynamic crack event is established, the objective function is constructed under the constraint condition that the second eigenvalue of displacement discontinuity tensor is zero, and the moment tensor component of dynamic crack event is calculated ; S50: solving the source core parameters of the dynamic crack according to the moment tensor components, realizing quantitative and fine description of the scale, orientation and mechanical properties of a single dynamic crack event; wherein the source core parameters include crack volume, crack area, crack opening displacement, crack spatial orientation, shear attribute, instantaneous generation rate, released energy and moment magnitude; S60: inducing and statistically analyzing all the single dynamic crack source core parameters obtained by inversion, forming a crack cluster dataset of spatial orientation dominant direction, dissipated energy spatial distribution, damage tensor principal axis direction and magnitude statistical distribution b value, quantitatively representing the macroscopic main crack propagation path in multiple dimensions, and realizing the cross-scale process description of the dynamic crack evolution of the rock mass from single to cluster and from micro to macro; Specifically, the macroscopic main fracture propagation plane is determined. Within this plane, the direction perpendicular to the main fracture is defined as the X-axis, and the direction parallel to the macroscopic main fracture is defined as the Y-axis. A rectangular coordinate system XOY for the fracture propagation plane is constructed with the fracture initiation position as the origin. Furthermore, along the Y-axis, sections with widths of... L mm, the length covering the boundary of the fracture group is intercepted in the X-axis direction to form several rectangular analysis areas; The quantitative representation of the macroscopic main crack propagation path in multiple dimensions and the realization of the cross-scale process description of the dynamic crack evolution of the rock mass from single to cluster and from micro to macro specifically comprise the following steps: In the spatial orientation dimension: the orientation in which the fracture group occupies the largest proportion in the rectangular analysis area is determined, which is the optimal orientation of the fracture group expansion, and the optimal orientations in each rectangular analysis area are connected, i.e. the macroscopic main fracture expansion path determined by the spatial orientation is obtained ; In the damage tensor dimension: determine the principal axis direction of the damage tensor of the fracture group in the rectangular analysis area, and connect the principal axis direction in each rectangular analysis area, which is the macroscopic main fracture propagation path determined by the damage tensor ; Regarding energy dissipation: Set an energy dissipation cumulative threshold. Calculate the cumulative energy dissipation of all fracture events within the rectangular analysis region. ;when Greater than or equal to At that time, it was believed that the regional fracture swarm had a large opening scale, and the main fracture had occurred; the cumulative value of all dissipated energy was determined. Exceed area Connecting regions The distribution location is the macroscopic main fracture propagation path determined by the energy dissipation dimension. ; Regarding the magnitude distribution dimension: setting a magnitude threshold. When the magnitude of a dynamic fracture event exceeds a set threshold, it is considered that a large-scale rupture has occurred, and the main rupture has occurred. All dynamic fracture event magnitudes are then selected. Exceed dataset Through sets Coordinates characterize the macroscopic main fracture propagation path ; From , , , The two paths with the highest coincidence degree are selected from the four extended paths, and the average of the orientations of the two paths is the macroscopic main crack propagation path determined by multi-dimensional synthesis, thereby realizing the cross-scale process description of rock mass dynamic crack evolution from single to cluster and from micro to macro.

2. The dynamic crack source parameter quantitative inversion and rupture cross-scale characterization method according to claim 1, characterized in that, In the step S10, the numerical value of the covariance determinant is reduced by adjusting the position of the acoustic wave sensor, and the optimal layout of the acoustic wave sensor network is realized, which specifically comprises the following steps: S11: Based on the error ellipsoid theory, the variance-covariance matrix can be determined. The smaller the determinant, the smaller the volume of the error ellipsoid, indicating that the condition is satisfied. The minimum network deployment scheme is the optimal network deployment scheme; where the variance-covariance matrix is... The formula is as follows: wherein represents the overall accuracy of each acoustic sensor to time measurement; matrix depends on the geometrical distribution of the acoustic sensor network and the location of the moving fracture event source; wherein is an idempotent matrix of order N x N, i.e. wherein, , , ) is the direction cosine of the first i th acoustic wave sensor to the estimated location of the moving fracture source. K= S12: fine-tune the position of the first acoustic wave sensor, change the element value of the matrix i inside K , , , until the determinant of the matrix K reaches a minimum value, at which time the minimum value position is determined as the optimal position of the acoustic wave sensor , , . Repeat the step to fine-tune all the acoustic wave sensors in turn so that the determinant of the variance-covariance matrix reaches a minimum value, and determine the optimal positions of all the acoustic wave sensors to achieve the optimization of the acoustic wave sensor network. wherein (a) is the coordinate of the source location point, , , ) is the coordinate of the source location point, , , The calculation formula is as follows: wherein is the straight-line distance between the moving fracture source , , and the first i acoustic wave sensor , , .

3. The dynamic crack source parameter quantitative inversion and rupture cross-scale characterization method according to claim 1, characterized in that, The step S30 specifically comprises the following steps: S31: Using the first arrival time data received by all acoustic wave sensors, combined with the information of acoustic wave sensor coordinates and material wave speed, the three-dimensional location of the seismic source is determined by the simplex positioning algorithm, wherein the waveform of the dynamic fracture source is transmitted to the position coordinates of the first i Theoretical travel time of the acoustic wave sensor T i The calculation formula is: In the formula, ( x e , y e , z e () represents the coordinates of the dynamic fracture source; x i , y i , z i ) is the first i The coordinates of each acoustic sensor; The P-wave velocity of the material; T0 is the moment when the fracture origin occurs; S32: a target function is constructed by accumulating and summing the absolute values of the differences between the collected time and the theoretical time at all acoustic wave sensors, wherein the expression of the target function is as follows: wherein N +1 is the number of acoustic wave sensors arranged; T0i is the first arrival time picked up by the i-th acoustic wave sensor. S33: The source coordinates (x) are calculated using the main diagonal elements of the error ellipsoid variance-covariance matrix. e y e , z e The variance in three dimensions, and at confidence level At a 95% confidence level, the confidence intervals for the source location coordinates in the x, y, and z directions were obtained. The narrower the confidence interval in each of the three dimensions and the smaller the error ellipsoid volume, the more accurate the acoustic emission localization result. Confidence interval thresholds were set in the three directions. , , When the lengths of the three-dimensional confidence intervals of the positioning points all satisfy , , If so, the location result of the earthquake source coordinate point is considered reliable; Wherein, in the confidence level is cases, the dynamic fracture source coordinate point (x e , y e , z e ) in x, y, z three direction confidence interval length calculation formula is: wherein , , are, in order, the main diagonal elements of the matrix Q , is indicative of the overall accuracy of each acoustic wave sensor to time measurement; S34: repeat the above steps until all the source positioning coordinates meeting the condition of S33 are screened out, and a set of source coordinate data with accurate positioning and small error is obtained.

4. The dynamic crack source parameter quantitative inversion and rupture cross-scale characterization method according to claim 1, characterized in that, In the step S40, based on the whole process of forward modeling of the generation of dynamic cracks, wave propagation and acoustic wave sensor response, a displacement discontinuity tensor source characterization model of dynamic crack events is established, which specifically comprises the following steps: S41: converting the sensitivity conversion coefficient during the response of the acoustic wave sensor The conversion between the output voltage value of the acoustic wave sensor and the different physical quantities of the input normal displacement is realized, and the coupling mass of the acoustic wave sensor is quantified, wherein the sensitivity conversion coefficient The calculation formula is as follows: In the formula, is the medium Poisson's ratio; P is the applied load value; d is the propagation distance; is the picked-up P-wave take-off amplitude; G1 is the function value at the first peak inflection point of the time-varying theory normal displacement; S42: in the process of dynamic crack source wave propagation, only the far-field displacement generated by P wave is considered and the synchronous source assumption is made, a function relationship between the displacement disturbance at the dynamic crack source and the displacement response generated at the acoustic wave sensor is established by using the Green function and the elastic wave equation, and the specific expression is as follows: wherein is the distance from the fracture source to the acoustic sensor location; is the directional cosine between the fracture source and the acoustic sensor; is the P-wave velocity; is the moment tensor component value; T s is the dynamic break time for dynamic fracture formation; S43: Adopting displacement discontinuity tensor representing the generated dynamic fracture source, wherein the displacement discontinuity tensor The calculation formula is as follows: wherein C ijkl is the material elastic stiffness tensor; ΔA is the new area of the dynamic fracture; b is the dynamic fracture motion vector; and n is the normal vector to the dynamic fracture surface.

5. The dynamic crack source parameter quantitative inversion and rupture cross-scale characterization method according to claim 1, characterized in that, In the step S40, the objective function is constructed under the constraint condition that the second eigenvalue of the displacement discontinuity tensor is zero, and the moment tensor component of the dynamic fracture event is calculated Specifically includes the following steps: First, the displacement discontinuity tensor The relationship between the displacement discontinuity tensor and the moment tensor M in an isotropic medium is given by wherein is the medium stiffness matrix; λ and μ is the Lamé constant; Secondly, the displacement discontinuity tensor Second eigenvalue The constraint conditions are the conditions that must be satisfied in any coordinate system. Based on the relationship between the displacement discontinuity tensor and the moment tensor, The constraints can be rewritten in the form of moment tensor invariants, and their expression is as follows: wherein J 1, J 2 and J 3 are the 1st, 2nd and 3rd invariant of the metric tensor M; Then, according to the theoretical normal displacement of P-wave at different acoustic sensor positions and the measured normal displacement data, the Lagrange indeterminate multiplier is introduced under the constraint condition of , the objective function is determined, and the components of the matrix tensor are solved, wherein the specific formula of the objective function is as follows: wherein is the normal displacement measured at the jth acoustic wave sensor; i is the normal displacement measured at the jth acoustic wave sensor; is the normal displacement calculated from the dynamic crack tensor source theory at the jth acoustic wave sensor; i is the normal displacement calculated from the dynamic crack tensor source theory at the jth acoustic wave sensor; Finally, the 6 components of the stiffness tensor are obtained by solving the objective function E using the damped Newton method.

6. The dynamic crack source parameter quantitative inversion and rupture cross-scale characterization method according to claim 1, characterized in that, In the step S50, the source core parameters of the dynamic crack are solved according to the moment tensor components, and quantitative and fine description of the scale, orientation and mechanical properties of a single dynamic crack event is realized, which specifically comprises the following steps: S51: Solve the eigenvalues and eigenvectors of the moment tensor M by matrix operation, and then calculate the displacement discontinuity tensor The eigenvalues and eigenvectors of the displacement discontinuity tensor coincide with the eigenvalues and eigenvectors of the moment tensor, and the calculation formula of the eigenvalues of the discontinuity tensor calculated from the eigenvalues of the moment tensor is as follows: in, λ and μ tr( is Lamé constant); M ) is the trace of the moment tensor; M i and ( i =1, 2, 3) are the three eigenvalues ​​of the moment tensor and the displacement discontinuity tensor, respectively; S52: a quantitative function relationship between the displacement discontinuity tensor eigenvalue, eigenvector and the source core parameters of the dynamic crack is established, and the source core parameters of the dynamic crack are calculated according to the solved displacement discontinuity tensor eigenvalue and eigenvector.

7. The method according to claim 6, wherein, The source parameters include: fracture volume Vol、 fracture area fracture opening displacement mode angle dynamic fracture orientation, dynamic fracture transient creation rate absolute energy and moment magnitude : Fracture volume Vol Fracture area and fracture opening displacement and are calculated as follows: wherein is a proportionality factor, taken as 10 -3 ; Mode angle The formula according to the eigenvalue of the displacement discontinuity tensor is calculated, and its expression is: ； The dynamic fracture orientation includes a fracture plane spatial orientation, a fracture plane normal n and a fracture motion vector b, wherein, in a three-dimensional coordinate system with three eigenvectors of the displacement discontinuity tensor as a basis, the fracture plane normal n and the fracture motion vector b are calculated according to the following formulas: ； The rate of dynamic fracture transient generation defined as the dynamic fracture size to the dynamic fracture time i.e. absolute energy and the moment magnitude is given by the expression wherein , are the tensile and shear strength of the sample, respectively; M i i = 1, 2, 3 are the three eigenvalues of the moment tensor.​ 8. The method according to claim 1, wherein, In the step S60, the fracture group dataset of the spatial orientation dominant direction, the dissipated energy spatial distribution, the damage tensor principal axis direction and the magnitude statistical distribution b value is formed, and the specific steps include the following steps: S62: Calculate the angle between each single fracture and the macroscopic main fracture according to the dynamic fracture normal direction , which is the complementary angle of the angle between the dynamic fracture normal direction n and the Y-axis direction, calculate and count the range of the angle between each single fracture and the macroscopic main fracture, and regard the angle between the single fracture and the macroscopic main fracture less than the preset value as a dynamic fracture event with a dominant orientation, obtain the dynamic fracture event with the dominant orientation and calculate its occurrence frequency, and form a fracture group data set of the dominant orientation of the fracture spatial orientation ​​ Wherein, the included angle The calculation formula is: wherein is the Y-axis directional vector; is the dynamic crack normal vector; S63: combined with the dynamic fracture location and dissipation energy calculation results, the dissipation energy value is divided into intervals with a specified size along the X-axis and Y-axis directions of the fracture propagation plane E c respectively, the dissipation energy distribution histogram along the parallel and perpendicular to the main crack propagation direction is drawn, and the dissipation energy spatial distribution pattern of the dynamic crack group is obtained; S64: The size and orientation direction of the dynamic fracture are jointly considered, the fracture group damage tensor D is defined, and the eigenvalue and eigenvector of the fracture damage tensor D in each rectangular analysis area are solved by matrix operation; wherein, the fracture group damage tensor D is calculated according to the following formula: wherein, is the fracture group damage tensor; N c is the total number of dynamic fractures within the volume V; A i is the area of the i th fracture; is the normal vector of the i th fracture; S65: Calculate the moment magnitude of all cracks And determine the distribution range, record the maximum and minimum of the moment magnitude 、 , the interval [ , ] is divided into S moment magnitude subintervals, the frequency of dynamic crack events in each subinterval and the frequency P(m) of events greater than the interval magnitude m are counted, and the P(m)-m curve is drawn in semilogarithmic coordinates. Linear fitting is performed on the log P(m)-m curve, and the fitting slope is the b value of the G-R relationship, obtaining the crack group data set of the magnitude statistical distribution b value, which is used to quantify the proportion of crack size in the dynamic crack group.

9. A dynamic fracture source parameter quantitative inversion and rupture cross-scale characterization system, characterized in that, including: Signal acquisition device, configured for determining potential areas of dynamic fracture event occurrence, arrangement N +1 acoustic wave sensor forms a monitoring network covering the potential area; wherein the acoustic wave sensor network layout optimization is achieved by adjusting the acoustic wave sensor position to reduce the numerical value of the covariance determinant; Signal processing device, configured to collect waveform signals of dynamic fracture events in rock mass fracture process by acoustic wave sensor, filter environmental noise and enhance real signals by filter, and obtain first arrival time by characteristic function The ratio of short time window to long time window is calculated to identify real signal characteristics, wherein when the ratio of short time window to long time window exceeds a set trigger threshold, the first wave arrival time is picked up , and the take-off amplitude is obtained ; The source coordinate obtaining device is configured to determine the dynamic fracture source coordinates according to a positioning algorithm by using the obtained waveform first arrival time, the acoustic wave sensor coordinates and the wave velocity information , , ), the actual confidence interval size of the source coordinates is obtained by calculating the variance of the source coordinates in three-dimensional directions, and the positioning result reliability is quantified, and a set of reliable source coordinate points are screened. The inversion model establishment device is configured to establish a displacement discontinuity tensor micro-crack source representation model of a dynamic fracture event based on generation of a dynamic fracture, wave propagation, and a forward process of an acoustic wave sensor response, construct an objective function under a constraint condition that a second eigenvalue of the displacement discontinuity tensor is zero, and calculate a moment tensor component of the dynamic fracture event ​ The source parameter solving device is configured to solve the source core parameters of the dynamic fracture according to the moment tensor components, so as to quantitatively and finely describe the scale, orientation and mechanical properties of a single dynamic fracture event; wherein, the source core parameters include a fracture volume, a fracture area, a fracture opening displacement, a fracture spatial orientation, a tensile-shear property, an instantaneous generation rate, a released energy and a moment magnitude; The dynamic fracture group description device is configured to statistically summarize all the single dynamic fracture source core parameters obtained by inversion, form a fracture group dataset of the spatial orientation dominant direction, the dissipated energy spatial distribution, the damage tensor principal axis direction and the magnitude statistical distribution b value, quantitatively represent a macroscopic main fracture propagation path in multiple dimensions, and realize the cross-scale process description of the dynamic fracture evolution of the rock mass from single to group and from micro to macro; Specifically, the macroscopic main fracture propagation plane is determined. Within this plane, the direction perpendicular to the main fracture is defined as the X-axis, and the direction parallel to the macroscopic main fracture is defined as the Y-axis. A rectangular coordinate system XOY for the fracture propagation plane is constructed with the fracture initiation position as the origin. Furthermore, along the Y-axis, sections with widths of... L mm, the length covering the boundary of the fracture group is intercepted in the X-axis direction to form several rectangular analysis areas; wherein, the multiple-dimensional quantitative representation of the macroscopic main fracture propagation path realizes the cross-scale process description of the dynamic fracture evolution of the rock mass from single to group and from micro to macro, and the specific steps include the following steps: In the spatial orientation dimension: the orientation in which the fracture group occupies the largest proportion in the rectangular analysis area is determined, which is the optimal orientation of the fracture group expansion, and the optimal orientations in each rectangular analysis area are connected, i.e. the macroscopic main fracture expansion path determined by the spatial orientation is obtained ; In the damage tensor dimension: determine the principal axis direction of the damage tensor of the fracture group in the rectangular analysis area, and connect the principal axis direction in each rectangular analysis area, which is the macroscopic main fracture propagation path determined by the damage tensor ; Regarding energy dissipation: Set an energy dissipation cumulative threshold. Calculate the cumulative energy dissipation of all fracture events within the rectangular analysis region. ;when Greater than or equal to At that time, it was believed that the regional fracture swarm had a large opening scale, and the main fracture had occurred; the cumulative value of all dissipated energy was determined. Exceed area Connecting regions The distribution location is the macroscopic main fracture propagation path determined by the energy dissipation dimension. ; Regarding the magnitude distribution dimension: setting a magnitude threshold. When the magnitude of a dynamic fracture event exceeds a set threshold, it is considered that a large-scale rupture has occurred, and the main rupture has occurred. All dynamic fracture event magnitudes are then selected. Exceed dataset Through sets Coordinates characterize the macroscopic main fracture propagation path ; From 、 、 、 The two paths with the highest coincidence degree are selected from the four extended paths, and the average of the orientations of the two paths is the macroscopic main crack propagation path determined by multi-dimensional synthesis, thereby realizing the cross-scale process description of rock mass dynamic crack evolution from single to cluster and from micro to macro.

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