Seismic source positioning method based on single three-component microseismic sensor

Abstract

According to the seismic source positioning method based on the single three-component micro-seismic sensor provided by the invention, seismic source positioning can be well completed under the condition that only the single three-component micro-seismic sensor receives the micro-seismic signal; therefore, the seismic source positioning requirement can be well met under the condition that a monitoring target with a wide monitoring range is faced or the number of sensors is limited, the problems of difficult positioning and even omission in the prior art are solved, and the timeliness and accuracy of early warning of geological disasters such as rockburst, mine earthquake or collapse are further improved.

Description

Technical Field

[0001] The present application relates to the field of microseismic monitoring, and particularly to a method for locating a seismic source based on a single three-component microseismic sensor. Background Art

[0002] At present, there are more and more deep rock engineering projects with increasing depths. As the depth increases, the geological environment in which the rock mass is located becomes more complex, the in-situ stress is higher, and major engineering disasters such as rock bursts, rock bumps, gas explosions, water inrusions, and high-temperature heat damage induced by excavation are more prominent and serious, and there are obvious corresponding safety risk problems.

[0003] The microseismic monitoring technology is one of the most effective and potential monitoring methods for rock mass dynamic disasters, especially for predicting and forecasting rock bursts, rock bumps, etc. Microseismic source location is a key issue in microseismic monitoring and disaster warning, which directly affects the analysis of subsequent issues such as energy calculation, microseismic activity, and rock burst warning.

[0004] At present, most of the seismic source location methods are optimization algorithms that construct objective functions based on arrival-time data, and multiple microseismic sensors are required to monitor the same rock fracture vibration signal to solve the objective function. However, in some monitoring scenarios such as oil storage tanks and rock slopes, due to the wide monitoring range and small sensor layout density, the rock fracture signal attenuates after long-distance propagation and is difficult to trigger multiple microseismic sensors, and even only a single sensor may be triggered, resulting in a large number of rock fracture signals being missed and it being difficult to give a timely and accurate warning of disasters.

[0005] That is to say, the existing seismic source location methods are difficult to perform effective seismic source location when facing monitoring targets with a wide monitoring range or limited number of sensors. Summary of the Invention

[0006] The present application provides a method for locating a seismic source based on a single three-component microseismic sensor. In the case where only a single three-component microseismic sensor receives a microseismic signal, the seismic source location can be well completed. Thus, the seismic source location requirements can be well met even when facing monitoring targets with a wide monitoring range or limited number of sensors, avoiding the difficult problem of location and even omission in the prior art, and further improving the timeliness and accuracy of early warning for geological disasters such as rock bursts, mine tremors, or collapses.

[0007] The present application provides a method for locating a seismic source based on a single three-component microseismic sensor, and the method includes: When a three-component microseismic sensor is installed in a monitoring area and a microseismic monitoring system is built, acquiring microseismic events collected by the microseismic monitoring system; Classifying the microseismic events through clustering processing to obtain one or more microseismic event classes; By coda wave interferometry analysis, determine the source spacing between every two microseismic events in the microseismic event class; Based on P-waves and S-waves, conduct polarization analysis and source distance calculation to determine the positioning locations of three target microseismic events; Combining the source spacing between every two microseismic events in the microseismic event class and the positioning locations of the three target microseismic events, determine the positioning locations of all microseismic events in the microseismic event class.

[0008] Preferably, during the clustering process, the following processing contents are included: When sorting the microseismic events with a total count of N, for each microseismic event within the selected time period, pair it with other microseismic events with a later order, obtaining 0.5×(N 2 -N) event pairs; Align the P-wave arrival times of all signals to the same position in the time-domain waveform; Taking the time window starting from the P-wave arrival time and ending at the waveform end as the calculation range, calculate the average value of the three correlation calculation values corresponding to the three components for each event pair as the correlation calculation result; Sort the correlation calculation results for each event pair, and retain the event pairs with values not less than the threshold N min ; Cluster the microseismic events according to the retained event pairs. Among them, during the processing, if event a in one event pair is related to event b, and event b in another event pair is also related to event c, then event a, event b, and event c are also considered related, and event a, event b, and event c are classified as the same class of events.

[0009] Preferably, by coda wave interferometry analysis, determining the source spacing between every two microseismic events in the microseismic event class includes: Divide the calculation window; Calculate the mean square angular frequency of the waveform through the following formula: , where, w r 2 is the mean square angular frequency, the waveform S2(t) is the derivative of the waveform S1(t) with respect to time, t1 is the start time of the calculation window, and t2 is the end time of the calculation window; Calculate the maximum correlation within each calculation window through the following formula: , where, is the maximum correlation within the calculation window, e is the time stretching factor, and u1 and u2 are the waveform data in the time series form of the currently required processed event pair; According to the mean square angular frequency and the maximum correlation, the source distance of the currently required event pair to be processed is calculated by the following formula: , where r is the source distance of the currently required event pair to be processed, and v is the P-wave velocity.

[0010] Preferably, based on the P-wave and S-wave, polarization analysis is carried out to determine the positioning positions of three target microseismic events, including: Obtain the covariance matrix Q of each microseismic event, where the following processing contents are included: For the microseismic event i containing only P-waves within a certain time interval, the components A xi , A yi , A zi in three directions are combined to form a matrix A. Perform covariance calculation on the matrix A to obtain the covariance matrix Q, and express it as: , where N is the number of samples, E(A ji ) is the average value of the sequence A, i is the sampling point, the covariance matrix Q is a positive semi-definite matrix, the eigenvalues in the positive semi-definite matrix are all non-negative real numbers, and the covariance matrix Q is the coefficient matrix of the quadratic form of the particle motion trajectory ellipsoid; For the covariance matrix Q, arrange the eigenvalues in descending order to obtain λ1, λ2, λ3, and the corresponding eigenvectors are u1, u2, u3; Based on the eigenvalues, calculate the polarization coefficients of each microseismic event in the microseismic event class, and find the three target microseismic events with the highest polarization coefficients; For the three target microseismic events respectively, calculate the source distance of the event by the following formula: , where R is the source distance, V p is the P-wave velocity, V s is the S-wave velocity, T p is the arrival time of the P-wave, and T s is the arrival time of the S-wave; For the three target microseismic events respectively, for the eigenvector u1 = [u 11 , u 12 , u 13 corresponding to the largest eigenvalue λ1 in the covariance matrix Q T , determine the azimuth angle of the corresponding source in the XOY plane by the following formula: , where θ xoy is the azimuth angle, and the incident angle of the corresponding seismic source in the XOY plane is determined by the following formula: , where α xoy is the incident angle; According to the azimuth angle, incident angle, and seismic source distance, the coordinates of the three target microseismic events in the sensor's own coordinate system are calculated respectively; Based on the coordinates of the three target microseismic events in the sensor's own coordinate system respectively, combined with the Euler angles of the three-component microseismic sensor transformed from the engineering actual coordinate system to the sensor's own coordinate system, the coordinates of the three target microseismic events in the engineering actual coordinate system and output as the positioning positions are calculated respectively.

[0011] Preferably, based on the eigenvalues, the polarization coefficient of each microseismic event in the microseismic event class is calculated, including: Based on the eigenvalues, the polarization coefficient of each microseismic event in the microseismic event class is calculated by the following formula: , where R is the polarization coefficient, , .

[0012] Preferably, according to the azimuth angle, incident angle, and seismic source distance, the coordinates of the three target microseismic events in the sensor's own coordinate system are calculated respectively, including: According to the azimuth angle, incident angle, and seismic source distance, the coordinates of the three target microseismic events in the sensor's own coordinate system are calculated respectively by the following formula: where (x0′, y0′, z0′) are the spatial coordinates of the target microseismic event in the sensor's own coordinate system.

[0013] Preferably, based on the coordinates of the three target microseismic events in the sensor's own coordinate system respectively, combined with the Euler angles of the three-component microseismic sensor transformed from the engineering actual coordinate system to the sensor's own coordinate system, the coordinates of the three target microseismic events in the engineering actual coordinate system and output as the positioning positions are calculated respectively, including: Based on the coordinates of the three target microseismic events in the sensor's own coordinate system respectively, combined with the Euler angles of the three-component microseismic sensor transformed from the engineering actual coordinate system to the sensor's own coordinate system, the coordinates of the three target microseismic events in the engineering actual coordinate system and output as the positioning positions are calculated respectively by the following formula: Among them, (x0, y0, z0) is the coordinate of the target microseismic event in the actual engineering coordinate system, which is output as the positioning position, M x 、M y 、M z are the rotation matrices corresponding to the three axes, (x S , y S , z S ) is the sensor coordinate, and (r, p, y) are the Euler angles.

[0014] Preferably, combining the source spacing between two microseismic events in the microseismic event class and the positioning positions of three target microseismic events, the positioning positions of all microseismic events in the microseismic event class are determined, including: Let the positioning positions of the three target microseismic events be (x1, y1, z1), (x2, y2, z2) and (x3, y3, z3) respectively. Combining the source spacing between two microseismic events in the microseismic event class, solve the following formula to obtain the positioning position of any source event i other than the three target microseismic events in the microseismic event class, so as to determine the positioning positions of all microseismic events in the microseismic event class: , , , where r i1 、r i2 and r i3 are the source spacings between microseismic event i and the three target microseismic events. From the above content, it can be concluded that the present application has the following beneficial effects: The present application provides a source location method based on a single three-component microseismic sensor. In the case where only a single three-component microseismic sensor receives microseismic signals, source location can be well completed. Thus, in the face of monitoring targets with a wide monitoring range or limited number of sensors, the source location requirements can also be well met, avoiding the difficult positioning or even omission problems in the prior art, and further improving the timeliness and accuracy of early warnings for geological disasters such as rock bursts, mine tremors or collapses. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for description in the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0016] Figure 1 is a schematic flowchart of a source location method based on a single three-component microseismic sensor of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Next, in combination with the accompanying drawings in the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0018] First, refer to Figure 1 , Figure 1 which shows a schematic flowchart of a method for source location based on a single three-component microseismic sensor in the present application. The method for source location based on a single three-component microseismic sensor provided by the present application specifically may include the following steps S101 to step S105: Step S101, when a three-component microseismic sensor is installed in a monitoring area and a microseismic monitoring system is built, obtain the microseismic events collected by the microseismic monitoring system; It can be understood that the solution of the present application is applied / deployed through a correspondingly configured microseismic monitoring system in specific applications. The solution of the present application mainly aims at rock engineering with a wide monitoring range and / or a limited number of deployable monitoring sensors. That is to say, the monitoring area mentioned here is the geological area where such rock engineering is located. Of course, in actual situations, it is not excluded that in other types of geological areas, the corresponding source location is carried out through the solution of the present application, which is also possible.

[0019] It should be noted that although the present application states that the corresponding source location can be carried out only based on a single three-component microseismic sensor, this does not mean that only one three-component microseismic sensor is deployed in the monitored geological area / microseismic monitoring system. Multiple sensors can be deployed, and the processing of the solution of the present application can be carried out for a single target microseismic sensor among them, forming a source location effect with a single microseismic sensor granularity or in units of a single microseismic sensor.

[0020] Step S102, through clustering processing, classify the microseismic events to obtain one or more microseismic event classes; Specifically, the present application also gives a further implementation supporting solution from the specific operation level.

[0021] It can be understood that, based on the corresponding waveform parameters of different microseismic events, through relevant clustering strategies / methods, the clustering goal can be achieved according to the commonalities of microseismic events in some aspects, and the corresponding microseismic event classes (that is, the clustering clusters obtained by clustering in the scenario of the present application) can be obtained.

[0022] As an example, specific clustering methods such as hierarchical clustering methods, density-based clustering methods, or grid-based clustering methods can be used.

[0023] In addition, it can be understood that the clustering method adopted can either use existing solutions, or be further optimized and improved based on existing solutions, or a novel self-developed solution can be adopted.

[0024] Correspondingly, the present application also configures an optimized clustering method. As a further exemplary embodiment, during the clustering process, the following processing contents may specifically be included: 1) When sorting the microseismic events with a total count of N, for each microseismic event within the selected time period, pair it with other microseismic events with a later order to obtain 0.5×(N 2 - N) event pairs; Among them, N is the number of microseismic events in the selected time period, rather than determined by manual or corresponding autonomous selection strategies / rules.

[0025] As an example, first pair event 1 with event 2, event 3,..., event N, and a total of N - 1 pairs can be obtained; then, pair event 2 with event 3, event 4,..., event N, and a total of N - 2 pairs can be obtained... and so on. Finally, 1 + 2 + 3 +... + N - 1 pairs can be obtained, that is, 0.5×(N 2 - N) event pairs.

[0026] When aligning the P-wave arrival times of all signals to the same position in the time-domain waveform; This processing step can also be referred to as signal alignment processing.

[0027] 3) Taking the time window from the P-wave arrival time to the end of the waveform as the calculation range, calculate the average value of the three correlation calculation values corresponding to the three components of each event pair as the correlation calculation result; Among them, it can be understood that the sensor parameters collected by the three-component microseismic sensor involve three components. Therefore, three correlation values can be obtained for the same event pair, and at this time, the average value of the three is taken as the final correlation value of the microseismic event pair.

[0028] 4) Sort the correlation calculation results of each event pair and retain the event pairs with values not less than the threshold N min ; Or rather, here, the event pairs with correlation calculation results having values less than the threshold N min are excluded, and the data of such event pairs are not allowed to participate in the subsequent clustering process.

[0029] 5) Cluster the microseismic events according to the remaining event pairs. During the processing, if event a and event b in an event pair are related (i.e., the correlation between event a and event b is greater than the threshold N min ), and event b and event c in another event pair are also related, then event a, event b, and event c are also considered related, and event a, event b, and event c are classified into the same type of event.

[0030] After completing the classification according to the above classification logic, the number of microseismic event classes and the number of microseismic events N in each microseismic event class can be determined. class 。

[0031] In the embodiment herein, starting from the actual operation level, the present application gives a specific implementation supporting scheme for clustering to obtain microseismic event classes, which has better practical significance.

[0032] Step S103, determine the source spacing between any two microseismic events in the microseismic event class through coda wave interferometry analysis; After obtaining the microseismic event classes previously, the source spacing between any two microseismic events in the microseismic event class can be specifically determined through coda wave interferometry analysis, so as to lay a foundation for the subsequent positioning of each microseismic event in the microseismic event class.

[0033] As an example, for the source spacing, the method of waveform matching and similarity measurement can be used to indirectly estimate the source spacing.

[0034] In addition, it can be understood that the source spacing calculation method adopted can either adopt the existing scheme, or be further optimized and improved on the basis of the existing scheme, or a novel self-developed scheme can also be adopted.

[0035] Correspondingly, the present application also configures an optimized source spacing calculation method. As a further exemplary embodiment, here, through coda wave interferometry analysis, the source spacing between pairwise microseismic events in the microseismic event class is determined, which specifically may include: 1) Divide the calculation window; Among them, the calculation window is used to limit and constrain the calculation range, laying a good foundation for more convenient and accurate data processing next.

[0036] As an example, the following configuration content may be specifically included in the process of dividing the calculation window: A window starting from 70 milliseconds after the arrival time of the P wave and with a length of 200 milliseconds, and the signal is evenly divided into four small calculation windows with a length of 50 milliseconds.

[0037] 2) Calculate the mean square angular frequency of the waveform through the following formula: , where, w r 2 is the mean square angular frequency, the waveform S2(t) is the derivative of the waveform S1(t) with respect to time, t1 is the start time of the calculation window, and t2 is the end time of the calculation window; 3) Calculate the maximum correlation within each calculation window through the following formula: , where, is the maximum correlation within the calculation window, e is the time stretching factor, and u1 and u2 are the waveform data in the time series form of the event pair to be processed currently (which can be arranged arbitrarily); It can be understood that the maximum correlation involved here is specifically the maximum correlation between two signal waveforms between two moments (t1 - t2).

[0038] 4) Calculate the source distance of the event pair to be processed currently according to the mean square angular frequency and the maximum correlation through the following formula: , where, r is the source distance of the event pair to be processed currently, and v is the P-wave velocity.

[0039] In the embodiment here, starting from the actual operation level, the present application gives a specific implementation supporting scheme for how to calculate the source distance in combination with the quantization formula, which has better practical significance.

[0040] Step S104: Based on the P-wave and S-wave, perform polarization analysis and source distance calculation to determine the positioning positions of three target microseismic events; It can be understood that the present application can also focus on the information carried by the P-wave and S-wave. Based on the P-wave and S-wave, through the data processing of deviation analysis and source distance calculation constructed by the present application, the positioning positions of three specific microseismic events or target microseismic events among all microseismic events in the microseismic event class are calculated, for subsequent cooperation with the source distances of any two microseismic events in the microseismic event class determined previously to finally determine the positions of other microseismic events in the overall microseismic event class.

[0041] In terms of details, the present application also configures an optimized method for calculating the positioning positions of target microseismic events. As a further exemplary embodiment, based on the P-wave and S-wave here, perform polarization analysis and source distance calculation to determine the positioning positions of three target microseismic events, which may specifically include: 1) Obtain the covariance matrix Q of each microseismic event, where the following processing contents are included: 1.1) For the microseismic event i that only contains P-wave within a certain time interval, the components A in three directions xi , Ayi and A zi form a matrix A. It should be noted that S-waves are not involved here, and the time interval taken can be denoted as t.

[0042] Extract the microseismic event data involving only P-waves and the corresponding three components to form a column vector A. xi and A yi and A zi , where x, y, and z correspond to the three directions of the three components, namely the x-axis, y-axis, and z-axis, and i is the sampling point or the number of each data portion. Then, arrange the column vectors A xi and A yi and A zi in order to form matrix A.

[0043] In addition, it should be understood that these vectors or the features in the vectors themselves have corresponding time points. Taking A xi as an example, it can be specifically marked as A xi (t).

[0044] 1.2) Calculate the covariance of matrix A to obtain the covariance matrix Q, Q = cov(A), and specifically express it as: , where N is the number of samplings, E(A ji ) is the average value of the sequence A, i is the sampling point, the covariance matrix Q is a positive semi-definite matrix, and the eigenvalues in the positive semi-definite matrix are all non-negative real numbers (some may be zero). The covariance matrix Q is the coefficient matrix of the quadratic form of the particle motion trajectory ellipsoid; In addition, it should be understood that for the application of three-component microseismic sensors, the following situations exist: Under the influence of the seismic source, the vibration waves generated by rock fractures are all linearly polarized, and the polarization directions (i.e., the polarization directions) are different. The particle vibration direction of the P-wave is consistent with the wave propagation direction. However, when two or more vibrations are superimposed, more complex vector vibrations can also be generated. The particles not only move along a straight line direction but also often describe a more complex motion trajectory, and such a trajectory is often represented by an elliptical space curve, which can be called the particle motion trajectory ellipsoid here.

[0045] The microseismic signals in three components collected by a three-component microseismic sensor can record the information of the underground wave field more accurately, obtain the wave field projections in all directions of the multi-component microseismic signals, and can more comprehensively reflect the propagation laws and characteristics of waves in the underground medium, providing for accurately reconstructing the motion trajectory of the particle. Among them, the polarization points of the microseismic signals can be represented by time, and these polarization points can be understood as the combination of points in space arranged in chronological order. Connecting each polarization point in chronological order can restore the motion trajectory of the medium particle.

[0046] 2) For the covariance matrix Q, arrange the eigenvalues in descending order to obtain λ1, λ2, λ3, and the corresponding eigenvectors are u1, u2, u3; Among them, the eigenvalues λ1, λ2, λ3 are the three main axes of the particle motion trajectory ellipsoid, and the corresponding eigenvectors u1, u2, u3 are the directions of the main axes. Determining the main axes of the ellipsoid determines the particle motion within the time interval t.

[0047] 3) Based on the eigenvalues, calculate the polarization coefficient of each microseismic event in the microseismic event class, and find the three target microseismic events with the highest polarization coefficients; Among them, it can be easily seen that the eigenvalue set involved in calculating the polarization coefficient here is λ1, λ2, λ3 involved above. The calculation of the polarization coefficient is to screen out target microseismic events with high specificity that can be used as a benchmark to infer the source location of other microseismic events.

[0048] As an example, specifically, based on the eigenvalues, the polarization coefficient of each microseismic event in the microseismic event class can be calculated by the following formula: , where R is the polarization coefficient, , .

[0049] 4) For each of the three target microseismic events, calculate the source distance of the event by the following formula: , where R is the source distance, V p is the P-wave velocity, V s is the S-wave velocity, T p is the arrival time of the P-wave, T s is the arrival time of the S-wave; In addition, at this time, the origin time can also be calculated by the following formula: , where t0 is the origin time.

[0050] 5) For each of the three target microseismic events, for the eigenvector u1 = [u 11 , u 12 , u 13 corresponding to the largest eigenvalue λ1 in the covariance matrix Q T , determine the azimuth angle of the corresponding seismic source in the XOY plane through the following formula: , where θ xoy is the azimuth angle, determine the incident angle of the corresponding seismic source in the XOY plane through the following formula: , where α xoy is the incident angle; 6) Calculate the coordinates of the three target microseismic events in the sensor's own coordinate system respectively according to the azimuth angle, incident angle, and source distance; It can be understood that the present application can specifically calculate the coordinates (x0′, y0′, z0′) of the seismic source involved in the target microseismic event in the sensor's own coordinate system based on the previous azimuth angle (θ xoy ), incident angle (α xoy ), and source distance (R) through a pre-configured coordinate calculation formula.

[0051] Specifically, the coordinates of the three target microseismic events in the sensor's own coordinate system can be calculated respectively according to the azimuth angle, incident angle, and source distance through the following formula; where (x0′, y0′, z0′) are the spatial coordinates of the target microseismic event in the sensor's own coordinate system.

[0052] 5) Based on the coordinates of the three target microseismic events in the sensor's own coordinate system respectively, and in combination with the Euler angles of the three-component microseismic sensor transformed from the engineering actual coordinate system to the sensor's own coordinate system, calculate the coordinates of the three target microseismic events in the engineering actual coordinate system for output as the positioning positions respectively.

[0053] Similar to the above, the present application has also pre-configured a quantization formula for calculating the positioning coordinates (actual coordinates), so as to combine the Euler angles (r, p, y) of the three-component microseismic sensor transformed from the engineering actual coordinate system to the sensor's own coordinate system (which can be understood as an inherent characteristic information of the three-component microseismic sensor itself), and convert the coordinates of the target microseismic event in the sensor's own coordinate system into the coordinates in the engineering actual coordinate system for output.

[0054] Specifically, based on the coordinates of three target microseismic events in the sensor's own coordinate system, combined with the Euler angles of the three-component microseismic sensor transformed from the engineering actual coordinate system to the sensor's own coordinate system, the coordinates of the three target microseismic events in the engineering actual coordinate system and output as the positioning positions can be calculated respectively through the following formula: Among them, (x0, y0, z0) are the coordinates (actual coordinates) of the target microseismic event in the engineering actual coordinate system and output as the positioning positions, M x 、M y 、M z are the rotation matrices corresponding to the three axes, (x S , y S , z S ) are the sensor coordinates, and (r, p, y) are the Euler angles.

[0055] For the Euler angles, r, p, and y are the roll angle, pitch angle, and yaw angle in the Euler angles respectively.

[0056] It can be understood that the positioning positions calculated here can also be understood in terms of actual coordinates.

[0057] In this way, through the embodiments here, starting from the actual operation level, the present application gives a specific implementation plan for calculating the positioning positions of target microseismic events in combination with the quantization formula, which has better practical significance.

[0058] Step S105: Determine the positioning positions of all microseismic events in the microseismic event class by combining the source spacings between pairwise microseismic events in the microseismic event class and the positioning positions of the three target microseismic events.

[0059] After obtaining the source spacings between any two microseismic events in the microseismic event class and the positioning positions of the target microseismic events through the above two aspects of processing, then based on the source spacings between any two microseismic events in the microseismic event class and referring to the positioning positions of the target microseismic events, the positions of all microseismic events in the entire microseismic event class (excluding the three target microseismic events) can be calculated, so as to achieve precise positioning of the entire microseismic event class in the case of a single three-component microseismic sensor, and further complete the precise positioning of different microseismic event classes, that is, all microseismic events.

[0060] Specifically, for this processing link, the present application also configures an optimized processing scheme. As a further exemplary embodiment, here, by combining the source spacings between pairwise microseismic events in the microseismic event class and the positioning positions of the three target microseismic events to determine the positioning positions of all microseismic events in the microseismic event class, it specifically may include: Let the positioning positions of three target microseismic events be (x1, y1, z1), (x2, y2, z2), and (x3, y3, z3) respectively (corresponding to the quantitative coordinates (x0, y0, z0) mentioned above). Combining the source spacings between pairwise microseismic events in the microseismic event class, solve the following formula to obtain the positioning position of any source event i other than the three target microseismic events in the microseismic event class, so as to determine the positioning positions of all microseismic events in the microseismic event class: , , , where r i1 , r i2 , and r i3 are the source spacings between microseismic event i and the three target microseismic events, obtained from the source spacings between any two microseismic events determined in the previous step S103 in the microseismic event class.

[0061] It can be understood that while the positioning positions of the three target microseismic events are determined previously, the positioning positions of different microseismic events i are determined here respectively, thus completing the source positioning of any microseismic event in the microseismic event class and achieving the source positioning goal of the solution of this application based on a single three-component microseismic sensor.

[0062] Therefore, under the settings of the embodiments here, starting from the actual operation level, this application gives a specific implementation supporting solution on how to secondarily optimize the positions of each event in the entire microseismic event class, which has better practical significance.

[0063] Finally, regarding the above solution content, generally speaking, this application provides a source positioning method based on a single three-component microseismic sensor. In the case where only a single three-component microseismic sensor receives microseismic signals, it can well complete source positioning. Thus, in the face of monitoring targets with a wide monitoring range or limited number of sensors, it can also well meet the source positioning requirements, avoiding the difficult positioning problem and even the problem of omission in the prior art, and then improving the timeliness and accuracy of early warnings for geological disasters such as rock bursts, mine tremors, or collapses.

[0064] The above has introduced in detail the source positioning method based on a single three-component microseismic sensor provided by this application. Specific examples are used in this article to elaborate on the principle and implementation manner of this application. The description of the above embodiments is only used to help understand the core idea of this application; at the same time, for those skilled in the art, according to the idea of this application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A method for locating a seismic source based on a single three-component microseismic sensor, characterized in that, The method includes: When a three-component microseismic sensor is installed in a monitoring area and a microseismic monitoring system is built, acquiring microseismic events collected by the microseismic monitoring system; Through clustering processing, classifying the microseismic events to obtain one or more microseismic event classes; Through coda wave interferometry analysis, determining the source spacing between every two microseismic events in the microseismic event class; Based on P-waves and S-waves, performing polarization analysis and source distance calculation to determine the positioning positions of three target microseismic events; Combining the source spacing between every two microseismic events in the microseismic event class and the positioning positions of the three target microseismic events, determining the positioning positions of all microseismic events in the microseismic event class.

2. The method according to claim 1, wherein During the clustering process, the following processing contents are included: When sorting the microseismic events with a total count of N, for each of the microseismic events within the selected time period, pair it with the other microseismic events with a later order, obtaining 0.5×(N 2 - N) event pairs; Aligning the arrival times of P-waves of all signals to the same position in the time-domain waveform; Taking the time window starting from the arrival time of the P-wave to the end of the waveform as the calculation range, calculating the average value of three correlation calculation values corresponding to three components for each event pair as the correlation calculation result; Sort the calculation results of the correlation for each of the event pairs, and retain the event pairs whose values are not less than the threshold N min of the event pairs; Clustering the microseismic events according to the remaining event pairs. During the processing, if event a and event b in one event pair are related, and event b and event c in another event pair are also related, then event a, event b, and event c are also considered related, and event a, event b, and event c are classified into the same class of events.

3. The method according to claim 1, characterized in that, The step of determining the source spacing between every two microseismic events in the microseismic event class through coda wave interferometry analysis includes: Dividing the calculation window; Calculating the mean square angular frequency of the waveform through the following formula: ， where w r 2 is the mean square angular frequency, the waveform S2(t) is the derivative of the waveform S1(t) with respect to time, t1 is the start time of the calculation window, and t2 is the end time of the calculation window; Calculating the maximum correlation within each calculation window through the following formula: ， Among them, is the maximum correlation within the said calculation window, e is the time stretching factor, and u1 and u2 are the waveform data in the time series form of the event pair to be processed currently; According to the mean square angular frequency and the maximum correlation, calculating the source spacing of the currently required event pair to be processed through the following formula: ， Where r is the source spacing of the currently required event pair to be processed, and v is the P-wave velocity.

4. The method according to claim 1, characterized in that, The step of performing polarization analysis and source distance calculation based on P-waves and S-waves to determine the positioning positions of three target microseismic events includes: Acquiring the covariance matrix Q of each microseismic event, where the following processing contents are included: For a microseismic event i that only contains the P-wave within a certain time interval, the components A in three directions xi , A yi , A zi are combined to form a matrix A. Performing covariance calculation on the matrix A to obtain the covariance matrix Q, and expressing it as: ， where N is the number of samplings, E(A ji ) is the average value of the sequence A, i is the sampling point, the covariance matrix Q is a positive semi-definite matrix, the eigenvalues in the positive semi-definite matrix are all non-negative real numbers, and the covariance matrix Q is the coefficient matrix of the quadratic form of the ellipsoid of the particle motion trajectory; For the covariance matrix Q, arranging the eigenvalues in descending order to obtain λ1, λ2, λ3, and the corresponding eigenvectors are u1, u2, u3; Based on the eigenvalues, calculating the polarization coefficient of each microseismic event, and finding the three target microseismic events with the highest polarization coefficients; For each of the three target microseismic events, calculating the source distance of the event through the following formula: ， where R is the source distance, V p is the P-wave velocity, V s is the S-wave velocity, T p is the P-wave arrival time, T s is the S-wave arrival time; For each of the three target microseismic events, for the eigenvector u1 = [u 11 , u 12 , u 13 corresponding to the largest eigenvalue λ1 in the covariance matrix Q T , the azimuth angle of the corresponding seismic source in the XOY plane is determined by the following formula: ， where θ xoy is the azimuth angle, Determining the incident angle of the corresponding source in the XOY plane through the following formula: ， where α xoy is the angle of incidence; According to the azimuth angle, the incident angle, and the source distance, calculating the coordinates of the three target microseismic events in the sensor's own coordinate system respectively; Based on the coordinates of the three target microseismic events in the coordinate system of the sensor itself, combined with the Euler angles of the three-component microseismic sensor transformed from the engineering actual coordinate system to the coordinate system of the sensor itself, calculate the coordinates of the three target microseismic events in the engineering actual coordinate system and output them as the positioning positions respectively.

5. The method according to claim 4, wherein Calculating the polarization coefficient of each microseismic event based on the eigenvalue includes: Calculating the polarization coefficient of each microseismic event based on the eigenvalue by the following formula: ， wherein, R is the polarization coefficient, , .

6. The method according to claim 4, characterized in that Calculating the coordinates of the three target microseismic events in the coordinate system of the sensor itself according to the azimuth angle, the incident angle and the source distance respectively includes: Calculating the coordinates of the three target microseismic events in the coordinate system of the sensor itself according to the azimuth angle, the incident angle and the source distance by the following formula respectively: Where, (x0′, y0′, z0′) are the spatial coordinates of the target microseismic event in the coordinate system of the sensor itself.

7. The method according to claim 6, wherein Based on the coordinates of the three target microseismic events in the coordinate system of the sensor itself, combined with the Euler angles of the three-component microseismic sensor transformed from the engineering actual coordinate system to the coordinate system of the sensor itself, calculating the coordinates of the three target microseismic events in the engineering actual coordinate system and outputting them as the positioning positions respectively includes: Based on the coordinates of the three target microseismic events in the coordinate system of the sensor itself, combined with the Euler angles of the three-component microseismic sensor transformed from the engineering actual coordinate system to the coordinate system of the sensor itself, calculate the coordinates of the three target microseismic events in the engineering actual coordinate system and output them as the positioning positions respectively by the following formula: Among them, (x0, y0, z0) is the coordinate of the target microseismic event in the actual engineering coordinate system and is output as the positioning position, M x , M y , M z are the rotation matrices corresponding to the three axes, (x S , y S , z S ) is the sensor coordinate, and (r, p, y) are the Euler angles.

8. The method according to claim 4, wherein Combining the source spacing between two microseismic events in the microseismic event class and the positioning positions of the three target microseismic events to determine the positioning positions of all microseismic events in the microseismic event class includes: Assume that the positioning positions of the three target microseismic events are (x1, y1, z1), (x2, y2, z2) and (x3, y3, z3) respectively. Combining the source spacing between two microseismic events in the microseismic event class, solve the following formula to obtain the positioning position of any source event i other than the three target microseismic events in the microseismic event class, so as to determine the positioning positions of all microseismic events in the microseismic event class: ， ， ， where r i1 , r i2 and r i3 are the source distances between the microseismic event i and the three target microseismic events.

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