Microseismic source location method, device and computer equipment based on Thiessen polygon

Abstract

The present application discloses a microseismic source location method, device and computer equipment based on Voronoi polygons, which relates to the field of microseismic monitoring and can solve the problem that there is currently a lack of a simple and effective global source location method, resulting in poor source location accuracy and the microseismic monitoring effect not meeting the requirements of the mining party. After a microseismic event occurs, a first waveform sorting is generated according to the reception time of the corresponding P-waves of each station; the first waveform sorting is verified according to the Voronoi polygons drawn based on the three-dimensional coordinates of each station to determine the effective waveform sorting and the effective waveform set, and the source constraint region is determined according to the effective waveform sorting; at least four sub-network combinations of stations are formed based on the effective waveform set, the source location results under different sub-network combinations are calculated to obtain possible source points; the possible source points within the source constraint region are determined as credible source points, the spatial concentration degree is calculated based on the credible source points, and the credible source point with the highest spatial concentration degree is determined as the optimal source point.

Description

Technical Field

[0001] The present application relates to the field of microseismic monitoring, and in particular, to a microseismic source location method, device, and computer device based on Thiessen polygons. Background Art

[0002] During the coal mining process, the extraction of coal will cause the redistribution of surrounding rock stress and the caving and movement of overlying strata. In this process, vibrations will be generated and elastic waves will be released outward. The basic principle of the microseismic location method is to arrange a certain number of sensors in a specific rock mass area and use the arrival time difference of the same elastic wave signal received by different sensors to perform the inversion calculation of the source location. The accuracy of source location is an important indicator to measure the monitoring quality of the network, and to a large extent determines the quality of microseismic monitoring.

[0003] Underground in coal mines, there are errors in the location of microseismic event sources. The location errors are affected by various factors, such as station distribution, velocity model, phase reading error, travel time area anomaly, location algorithm, equipment operation status and environmental noise, location algorithm, etc. At present, there is a lack of a simple and effective global method for source location, resulting in poor source location accuracy and the microseismic monitoring effect not meeting the requirements of the mine. Summary of the Invention

[0004] In view of this, the present application provides a microseismic source location method, device, and computer device based on Thiessen polygons, mainly solving the problem that there is currently a lack of a simple and effective global source location method, resulting in poor source location accuracy and the microseismic monitoring effect not meeting the requirements of the mine.

[0005] According to one aspect of the present application, a microseismic source location method based on Thiessen polygons is provided. The method includes:

[0006] After a microseismic event occurs, generate a first waveform sorting according to the reception time of the longitudinal seismic waves corresponding to each station;

[0007] Verify the effectiveness of the first waveform sorting according to the Thiessen polygons drawn based on the three-dimensional coordinates of each station in the microseismic monitoring network, determine the effective waveform sorting and the effective waveform set, and determine the source restriction area according to the effective waveform sorting;

[0008] Perform sub-network combinations of at least four stations according to the effective waveform set, calculate the source location results under different sub-network combinations, and obtain possible source points;

[0009] Determine the possible source points within the source restriction area as credible source points, calculate the spatial concentration degree according to the credible source points, and determine the credible source point corresponding to the highest spatial concentration degree as the best source point.

[0010] According to another aspect of the present application, there is provided a microseismic source positioning device based on Thiessen polygons, the device comprising:

[0011] A generation module, configured to generate a first waveform sorting according to the reception time of the longitudinal seismic waves corresponding to each station after a microseismic event occurs;

[0012] A verification module, configured to perform validity verification on the first waveform sorting according to the Thiessen polygons drawn based on the three-dimensional coordinates of each station in the microseismic monitoring network, determine a valid waveform sorting and a valid waveform set, and determine a source restriction area according to the valid waveform sorting;

[0013] A first calculation module, configured to perform sub-network combinations of at least four stations based on the valid waveform set, calculate the source positioning results under different sub-network combinations, and obtain possible source points;

[0014] A second calculation module, configured to determine the possible source points within the source restriction area as credible source points, calculate the spatial concentration degree based on the credible source points, and determine the credible source point corresponding to the highest spatial concentration degree as the optimal source point.

[0015] According to still another aspect of the present application, there is provided a non-volatile readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned microseismic source positioning method based on Thiessen polygons is implemented.

[0016] According to yet another aspect of the present application, there is provided a computer device, comprising a non-volatile readable storage medium, a processor, and a computer program stored on the non-volatile readable storage medium and executable on the processor, and when the processor executes the program, the above-mentioned microseismic source positioning method based on Thiessen polygons is implemented.

[0017] With the above technical solution, the present application provides a microseismic source location method, device and computer equipment based on Thiessen polygons, which solves the problem that there is currently a lack of a simple and effective global seismic source location method, resulting in poor seismic source location accuracy and the microseismic monitoring effect not meeting the requirements of the mining party. After a microseismic event occurs in the present application, a first waveform sorting is generated according to the reception time of the corresponding P-waves of each station; the validity of the first waveform sorting is verified according to the Thiessen polygons drawn based on the three-dimensional coordinates of each station in the microseismic monitoring network, and the valid waveform sorting and the valid waveform set are determined, and the seismic source restricted area is determined according to the valid waveform sorting; at least four sub-networks of stations are combined based on the valid waveform set, and the seismic source location results under different combinations of the sub-networks are calculated to obtain possible seismic source points; the possible seismic source points within the seismic source restricted area are determined as credible seismic source points, the spatial concentration degree is calculated based on the credible seismic source points, and the credible seismic source point with the highest corresponding spatial concentration degree is determined as the optimal seismic source point. Through the technical solution in the present application, after a microseismic event occurs, through the combination of calculations in multiple dimensions, the optimal seismic source point can be screened layer by layer, effectively improving the seismic source location accuracy, reducing the seismic source location error, greatly improving the seismic source location speed and the stability of the location result, and ensuring that the microseismic monitoring effect meets the requirements of the mining party. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0019] Figure 1 The flowchart of a microseismic source location method based on Thiessen polygons provided by an embodiment of the present application is shown;

[0020] Figure 2 The flowchart of another microseismic source location method based on Thiessen polygons provided by an embodiment of the present application is shown;

[0021] Figure 3 The schematic diagram of the principle of a microseismic source location based on Thiessen polygons provided by an embodiment of the present application is shown;

[0022] Figure 4 The structural diagram of a microseismic source location device based on Thiessen polygons provided by an embodiment of the present application is shown;

[0023] Figure 5 The structural diagram of another microseismic source location device based on Thiessen polygons provided by an embodiment of the present application is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The present application will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other.

[0025] In view of the current lack of a simple and effective global seismic source location method, resulting in poor seismic source location accuracy and the microseismic monitoring effect not meeting the requirements of the mining party, the embodiments of the present application provide a microseismic source location method based on Thiessen polygons, as Figure 1 shown, the method includes:

[0026] 101. After a microseismic event occurs, generate a first waveform sorting according to the reception times of the corresponding P-waves of each station.

[0027] Among them, the P-wave is also called the pressure wave, the primary wave, and the P-wave. Among all seismic waves, the P-wave has the fastest propagation speed. Therefore, when a microseismic event occurs, the P-wave is the earliest seismic wave to reach the station. For this embodiment, the reception times of the P-waves received by each station can be determined by the short-term average over long-term average (STA / LTA) method. The principle of the short-term average over long-term average (STA / LTA) method is that when the ratio of the short-term average value to the long-term average value exceeds the user-defined trigger threshold, this point is determined as the arrival time of the P-wave. Sort the reception times of the P-waves received by each station in ascending order to obtain the first waveform sorting. For example, if the reception times of the P-waves received by Station 1, Station 2, and Station 3 are 0.00399899 s, 0.00387002 s, and 0.00446878 s respectively, the first waveform sorting obtained by sorting the reception times of the P-waves received by each station in ascending order is Station 2, Station 1, Station 3.

[0028] 102. Validate the effectiveness of the first waveform sorting according to the Thiessen polygons drawn based on the three-dimensional coordinates of each station in the microseismic monitoring network, determine the effective waveform sorting and the effective waveform set, and determine the seismic source restricted area according to the effective waveform sorting.

[0029] Among them, the Thiessen polygon, also known as the Voronoi diagram or V - diagram, named after Georgy Voronoi, is composed of a set of continuous polygons formed by the perpendicular bisectors of the lines connecting adjacent points. Due to the equal - division characteristics of the Thiessen polygon in spatial subdivision, it can be used to solve problems such as the nearest point, the smallest enclosing circle, and many spatial analysis problems, such as adjacency, proximity, and accessibility analysis. For this embodiment, Matlab can be used to plot the three - dimensional coordinates of each station as a Thiessen polygon, and verify whether the sorting of the first waveform is correct according to the Thiessen polygon. During the process of verifying and determining the effective waveform sorting, the invalid waveforms are deleted to obtain the set of effective waveforms.

[0030] The specific process of verification is as follows: The micro - seismic monitoring network includes n stations, which are (P1, P2... P n ). After a micro - seismic event occurs, m stations among the n stations receive the seismic longitudinal wave, and these m stations are (P1, P2... P m ). Assuming that the sorting of P1 is correct, in the Thiessen polygon of the micro - seismic monitoring network after removing the i - th station, the name of the polygon where P j is located is K ij , and P j is the center point of the polygon K ij . According to the time when each station receives the seismic longitudinal wave, sorted from early to late, the first waveform sorting is obtained as P1, P2... P n .

[0031] (1) Using the n stations to form a Thiessen polygon, the epicenter is within the polygon K 01 where P1 is located;

[0032] (2) Removing P1, using P2... P n to form a Thiessen polygon, check whether the polygon where P2 is located intersects with the polygon K 01 where P1 is located in (1), that is, If this formula is satisfied, the triggering order of P2 is correct, and go to (3); if not, the sorting is incorrect;

[0033] (3) Removing P1 and P2, using P3... P n to form a Thiessen polygon, check whether the polygon where P3 is located intersects with the intersection of the polygons of P1 and P2 in (2), that is, satisfy If satisfied, the triggering order of P3 is correct, and go to (4); if not, the sorting is incorrect;

[0034] (4) Removing P1, P2, and P3, using P4... P n to form a Thiessen polygon, check whether it satisfies If satisfied, the triggering order of P4 is correct, and go to (5); if not, the sorting is incorrect;

[0035] (5) Check whether the triggering order of m stations is correct in sequence according to steps (1), (2), (3), and (4). If the conditions are met in each step, the sorting is correct; otherwise, it is incorrect. Then, delete the invalid waveforms or adjust the sorting and re-execute the above process.

[0036] Through the method of verifying the sorting of the first waveform by the Thiessen polygon in this solution, the position where the sorting goes wrong can be obtained, which is convenient for quickly querying the reason, correcting the error, and then obtaining the correct sorting. For example, query the reason according to the position where the sorting goes wrong and find that the epicenter is in Sichuan Province, but the stations in Shanghai receive the P-wave of the earthquake earlier than the stations in Sichuan Province. At this time, delete the P-wave of the earthquake received by the stations in Shanghai as invalid waveforms and re-sort.

[0037] The determination of the sorting of the valid waveforms is to obtain the epicenter restricted area. The epicenter restricted area is the smallest range of the possible epicenter area. The epicenter restricted area is the intersection of the areas of the Thiessen polygons corresponding to all stations in the sorting of the valid waveforms. By screening the calculated epicenter location results through the epicenter restricted area, the range where the best epicenter point is located can be narrowed, and the positioning accuracy and reliability can be improved.

[0038] 103. Combine at least four stations into sub-network combinations based on the set of valid waveforms, calculate the epicenter location results under different sub-network combinations, and obtain the possible epicenter points.

[0039] Among them, the microseismic monitoring network includes all stations. The sub-network is a subset of the microseismic monitoring network, and the sub-network includes at least four stations. For example, sub-network 1 can include stations 1, 2, 3, and 4, sub-network 2 can include stations 1, 2, 3, and 5, and sub-network 3 can include stations 1, 2, 3, 4, and 5, etc.

[0040] For this embodiment, the method for calculating the epicenter location results under all sub-network combinations is specifically as follows:

[0041]

[0042] is the P-wave velocity, (x i , y i , z i ) is the three-dimensional coordinate of the i-th station, i = 1, 2,..., n, t i is the reception time of the valid waveform corresponding to the i-th station, i = 1, 2,..., m, m is the number of valid waveforms, and (x0, y0, z0) is the predicted epicenter coordinate.

[0043] The specific derivation process of formula (1) is as follows:

[0044]

[0045]

[0046]

[0047] Substituting formulas (3) and (4) into formula (2) gives formula (5).

[0048]

[0049] Formula (1) is obtained from formula (5).

[0050] where d i is the actual distance between the seismic source and the i-th station, T i is the calculated travel time for the waveform to propagate from the seismic source to the i-th station, and t0 is the origin time of the earthquake.

[0051] Based on formula (1) and the information of four stations, four equations containing four unknowns (x0, y0, z0), r i can be listed. Solving these four equations can calculate a predicted seismic source coordinate. m is the number of effective waveforms. Then the combination methods of the sub-station networks include types. Each sub-station network corresponds to a predicted seismic source coordinate, that is, the seismic source location result. Therefore, the seismic source location results under all sub-station network combinations include ones. This seismic source location result is only a possible seismic source point. It is necessary to further determine the optimal seismic source point in step 104. For any microseismic monitoring sub-station network in this scheme, an optimal solution can be obtained, and there will be no situation of non-convergence or multiple solutions of the equations. Moreover, the robustness of the present invention is good. Especially for sub-station networks with poor spatial distribution, the superiority of this scheme can be more prominently shown.

[0052] 104. Determine the possible seismic source points within the seismic source restricted area as credible seismic source points, calculate the spatial concentration degree based on the credible seismic source points, and determine the credible seismic source point with the highest corresponding spatial concentration degree as the optimal seismic source point.

[0053] For this embodiment, the possible seismic source points within the seismic source restriction area are selected as credible seismic source points, and the possible seismic source points outside the seismic source restriction area are excluded as non-credible seismic source points. The specific implementation method for calculating the spatial concentration degree based on the credible seismic source points is as follows: The seismic source restriction area is subjected to a first grid division, and the number of credible seismic source points within the first grid is determined as the value of the center point of the first grid. Based on the value of the center point of the first grid and the Kriging interpolation algorithm, a first three-dimensional concentration degree cloud map of the first grid is drawn; the first grid with the highest concentration degree is determined according to the first three-dimensional concentration degree cloud map; the first grid with the highest concentration degree is subjected to a second grid division, and a second three-dimensional concentration degree cloud map of the second grid is drawn based on the Kriging interpolation algorithm, where the grid area of the first grid is larger than that of the second grid; the second grid with the highest concentration degree is determined according to the second three-dimensional concentration degree cloud map, and the center point of the second grid is determined as the optimal seismic source point.

[0054] When performing grid division, at a certain fixed distance interval, the number of grids divided in each dimension is determined. When performing grid division, more times of grid division can be carried out according to the range size of the seismic source restriction area. This solution does not limit the number of grid division times. For example, the first grid can be set to 10m×10m×10m, the second grid to 1m×1m×1m, and two divisions are carried out, and the precise positioning effect can be achieved at the accuracy of 1m×1m×1m. Or the first grid can be set to 10m×10m×10m, the second grid to 5m×5m×5m, and the third grid to 1m×1m×1m, and three divisions are carried out, and the precise positioning effect can be achieved at the accuracy of 1m×1m×1m.

[0055] For this embodiment, the surfer three-dimensional modeling software can be used to draw the three-dimensional concentration degree cloud map. Among them, the three-dimensional concentration degree cloud map can be drawn through the Kriging algorithm in the surfer three-dimensional modeling software. The three-dimensional concentration degree cloud map contains contour lines representing the concentration degree. The value of the grid center point is set as the number of credible seismic source points falling within the grid. The more the number of credible seismic source points, the larger the value of the center point of the grid, the smaller the value of the corresponding contour line, and the higher the seismic source concentration degree, corresponding to the optimal seismic source point. After the first grid division, the first grid with the highest concentration degree is selected, and then the first grid with the highest concentration degree is subjected to a second grid division, and the maximum value of the concentration degree in the second grid is selected again as the optimal seismic source point. Using the surfer three-dimensional modeling software can clearly and intuitively find the position corresponding to the minimum value of the contour line, which is convenient for analysis.

[0056] Through the microseismic source location method based on Voronoi polygons in this embodiment, after a microseismic event occurs, a first waveform sorting can be generated according to the receiving times of the corresponding seismic longitudinal waves at each station; according to the Voronoi polygons drawn based on the three-dimensional coordinates of each station in the microseismic monitoring network, the effectiveness of the first waveform sorting is verified to determine the effective waveform sorting and the effective waveform set, and the source constraint region is determined according to the effective waveform sorting; at least four sub-networks of stations are combined based on the effective waveform set, the source location results under different sub-network combinations are calculated to obtain possible source points; the possible source points within the source constraint region are determined as credible source points, the spatial concentration degree is calculated based on the credible source points, and the credible source point with the highest corresponding spatial concentration degree is determined as the optimal source point. Through the technical solution in this application, after a microseismic event occurs, through a combination of calculations in multiple dimensions, the optimal source point can be screened layer by layer, effectively improving the source location accuracy, reducing the source location error, greatly improving the source location speed and the stability of the location result, and ensuring that the microseismic monitoring effect meets the requirements of the mining party.

[0057] Further, as a refinement and extension of the specific implementation manner of the above embodiment, in order to completely illustrate the specific implementation process in this embodiment, another microseismic source location method based on Voronoi polygons is provided, as Figure 2 shown, this method includes:

[0058] 201. After a microseismic event occurs, determine the receiving times of the corresponding seismic longitudinal waves at each station, and generate a first waveform sorting for each station in ascending order of the receiving times.

[0059] The specific implementation process can refer to the relevant description in step 101 of the embodiment and will not be elaborated here. In a specific application scenario, before generating the first waveform sorting, in order to improve the efficiency of microseismic source location, as a preferred method, obvious error seismic longitudinal waves can also be pre-eliminated, and the first waveform sorting is further generated using the eliminated seismic longitudinal waves, and then by executing steps 202 to 207 of the embodiment, the extraction of the optimal source point is realized.

[0060] 202. Draw Voronoi polygons according to the three-dimensional coordinates of each station in the microseismic monitoring network, and determine whether there is an intersection between the Voronoi polygons corresponding to any two adjacent stations in the first waveform sorting.

[0061] Among them, Thiessen polygons are also called Voronoi diagrams, named after Georgy Voronoi. They are composed of a set of continuous polygons composed of perpendicular bisectors connecting two adjacent points. Due to the equal division characteristics of Thiessen polygons in space subdivision, they can be used to solve problems such as the nearest point and the minimum closed circle, as well as many spatial analysis problems, such as adjacency, proximity and reachability analysis. For this embodiment, matlab can be used to draw the three-dimensional coordinates of each station into Thiessen polygons.

[0062] For example, a microseismic monitoring network includes n stations, namely (P1, P2…P n ), after a microseismic event occurs, m stations among n stations receive seismic longitudinal waves, and these m stations are (P1, P2…P m ), assuming that P1 is sorted correctly, the P in the Thiessen polygon of the microseismic monitoring network after removing the i-th station j The name of the polygon is K ij , P j For polygon K ij The first waveform is sorted from early to late according to the time when each station receives the seismic longitudinal wave, which is P1, P2…P m .

[0063] (1) Using n stations to draw Thiessen polygons, the epicenter is in the polygon K where P1 is located. 01 Inside;

[0064] (2) Remove P1 and replace P2…P n Draw Thiessen polygons and check whether the polygon where P2 is located is the same as the polygon K where P1 is located in (1). 01 There is an intersection, that is

[0065] (3) Remove P1 and P2, and take P3…P n Draw Thiessen polygons and check whether the polygon where P3 is located intersects with the intersection of the polygons P1 and P2 in (2), that is, it satisfies

[0066] (4) Remove P1, P2 and P3, and take P4…P n Draw Thiessen polygons and check whether

[0067] (5) Follow steps (1), (2), (3), and (4) to check whether

[0068] Judging whether there is an intersection in the Thiessen polygons corresponding to any adjacent stations in the first waveform sorting is to obtain an effective waveform set and an effective waveform sorting, and further determine the source restriction area.

[0069] 203. If it is judged that there is an intersection in the Thiessen polygons corresponding to any adjacent stations in the first waveform sorting, then the first waveform sorting is determined as the effective waveform sorting, the station waveforms in the first waveform sorting are determined as the effective waveforms, and an effective waveform set is generated.

[0070] The effective waveform sorting is the first waveform sorting that satisfies the condition that there is an intersection in the Thiessen polygons corresponding to all adjacent stations. If it is satisfied then it means that the first waveform sorting is the effective waveform sorting, and the station waveforms in the first waveform sorting are the effective waveforms.

[0071] 204. If it is judged that there is no intersection in the Thiessen polygons corresponding to any adjacent stations in the first waveform sorting, then adjust the arrangement order of the station waveforms in the first waveform sorting, or eliminate the invalid waveforms, so as to obtain the effective waveform sorting and the effective waveform set, and there is an intersection in the Thiessen polygons corresponding to any adjacent stations in the effective waveform sorting.

[0072] For this embodiment, continuing with the example in step 202, if it is judged that there is no intersection in the Thiessen polygons corresponding to any adjacent stations in the first waveform sorting, then adjusting the arrangement order of the station waveforms in the first waveform sorting, or eliminating the invalid waveforms specifically includes:

[0073] (1) Taking n stations to form Thiessen polygons, then the epicenter is within the polygon K where P1 is located 01 inside;

[0074] (2) Remove P1, and use P2…P n to form Thiessen polygons, and check whether the polygon where P2 is located intersects with the polygon K where P1 is located in (1), that is 01 if this formula is satisfied, then the triggering order of P2 is correct, and go to (3); if not, the sorting is incorrect; Satisfying this formula means that the triggering order of P2 is correct, proceed to (3), and if not satisfied, the sorting is incorrect;

[0075] (3) Remove P1 and P2, and use P3…P n to form Thiessen polygons, and check whether the polygon where P3 is located intersects with the intersection of the polygons of P1 and P2 in (2), that is, satisfying if satisfied, then the triggering order of P3 is correct, go to (4), if not satisfied, the sorting is incorrect;

[0076] (4) Remove P1, P2 and P3, and use P4…P n to form Thiessen polygons, and check whether it satisfies if satisfied, then the triggering order of P4 is correct, go to (5), if not satisfied, the sorting is incorrect;

[0077] (5) Check whether the triggering order of m stations is correct in sequence according to steps (1), (2), (3), and (4). If the conditions are met in each step, the sorting is correct; otherwise, it is incorrect. Then, delete the invalid waveforms or adjust the sorting and re - execute the above process.

[0078] The effective waveform sorting and the set of effective waveforms can be obtained by this method.

[0079] 205. Determine the regional intersection of the Thiessen polygons corresponding to all stations in the effective waveform sorting, and determine the regional intersection as the source restriction area.

[0080] Continuing from step 202 of the embodiment, the source restriction area is the minimum range of the possible source area, denoted as K 12 ∩K 23 ∩K 34 ∩…∩K (m-2)(m-1) ∩K (m-1)m . By screening the calculated source location results through the source restriction area, credible source points can be obtained, and the best source point is determined based on the credible source points, which can improve the positioning accuracy and reliability.

[0081] 206. Randomly select at least four stations from the set of effective waveforms and construct a sub - network combination based on the at least four stations; based on the source information and the information of each station in the sub - network combination, and according to a pre - designed calculation formula, calculate the predicted source coordinates under the sub - network combination, and determine the predicted source coordinates as the possible source points.

[0082] For this embodiment, the source information includes the P - wave velocity of the earthquake, and the station information includes the three - dimensional coordinates of the station and the reception time of the effective waveform corresponding to the station. The specific implementation process can refer to the relevant description in step 103 of the embodiment and will not be elaborated here.

[0083] 207. Determine the possible source points within the source restriction area as the credible source points, calculate the spatial concentration degree based on the credible source points, and determine the credible source point with the highest corresponding spatial concentration degree as the best source point.

[0084] For this embodiment, when calculating the spatial concentration degree based on the credible seismic source points and determining the optimal seismic source point among the credible seismic source points according to the spatial concentration degree, step 207 of the embodiment may specifically include: performing a first grid division on the seismic source restricted area, determining the number of credible seismic source points within the first grid as the value of the center point of the first grid, and based on the value of the center point of the first grid and the Kriging interpolation algorithm, drawing a first three-dimensional concentration degree cloud map of the first grid; determining the first grid with the maximum concentration degree according to the first three-dimensional concentration degree cloud map; performing a second grid division on the first grid with the maximum concentration degree and drawing a second three-dimensional concentration degree cloud map of the second grid based on the Kriging interpolation algorithm, where the grid area of the first grid is larger than that of the second grid; determining the second grid with the maximum concentration degree according to the second three-dimensional concentration degree cloud map, and determining the center point of the second grid as the optimal seismic source point.

[0085] For the specific implementation process, reference may be made to the relevant description in step 104 of the embodiment, which will not be elaborated here.

[0086] To fully illustrate the technical solution in this application, here in combination with the Figure 3 schematic diagram of the principle of microseismic source location based on Thiessen polygons in the attached drawings of the specification, the implementation process of this application will be fully described:

[0087] Step 1: After a microseismic event occurs, perform preprocessing on the original microseismic event data collected by each station to screen the waveforms, and delete the waveforms with obvious errors. This step can improve the speed of validating the effectiveness of the first waveform sorting according to the Thiessen polygon, that is, the V diagram, in step 3.

[0088] Step 2: After the waveform screening in step 1, generate a first waveform sorting according to the arrival times of the first P-waves received by each station from early to late.

[0089] Step 3: Validate the effectiveness of the first waveform sorting in step 2 according to the Thiessen polygon, that is, the V diagram. If it is incorrect, then delete the invalid waveforms or adjust the sorting and re-execute step 3. If it is correct, proceed to step 4. The validation is to obtain the valid waveforms and the valid waveform sorting.

[0090] Step 4: Determine the seismic source restricted area according to the valid waveform sorting in step 3.

[0091] Step 5: Perform sub-network combinations of at least four stations according to the valid waveform set in step 3, calculate the seismic source location results under different sub-network combinations, and obtain a set of seismic source points, where the set of seismic source points contains possible seismic source points.

[0092] Step 6: Determine the set of credible seismic source points according to the seismic source restricted area determined in step 4 and the set of seismic source points obtained in step 5. The set of credible seismic source points is the set of seismic source points contained within the seismic source restricted area.

[0093] Step 7: Perform concentration analysis based on the set of credible seismic source points determined in Step 6 to obtain the optimal seismic source point. The method for performing concentration analysis is to draw a three-dimensional concentration cloud map, and the maximum value of concentration is the optimal seismic source point.

[0094] With the above technical solution, a microseismic source location method, device, and computer device based on Thiessen polygons provided by the present application solve the problem that there is currently a lack of a simple and effective global seismic source location method, resulting in poor seismic source location accuracy and the microseismic monitoring effect not meeting the requirements of the mining party. After a microseismic event occurs in the present application, a first waveform sorting is generated according to the reception time of the corresponding seismic longitudinal waves at each station; based on the Thiessen polygons drawn according to the three-dimensional coordinates of each station in the microseismic monitoring network, the validity of the first waveform sorting is verified to determine the valid waveform sorting and the set of valid waveforms, and the seismic source restriction area is determined according to the valid waveform sorting; at least four stations are combined into a subnet based on the set of valid waveforms, the seismic source location results under different subnet combinations are calculated to obtain possible seismic source points; the possible seismic source points within the seismic source restriction area are determined as credible seismic source points, the spatial concentration is calculated based on the credible seismic source points, and the credible seismic source point corresponding to the highest spatial concentration is determined as the optimal seismic source point. Through the technical solution in the present application, after a microseismic event occurs, through a combination of calculations in multiple dimensions, the optimal seismic source point can be screened layer by layer, effectively improving the seismic source location accuracy, reducing the seismic source location error, greatly improving the seismic source location speed and the stability of the location result, and ensuring that the microseismic monitoring effect meets the requirements of the mining party. In addition, for the seismic longitudinal waves received by each station, there is no need to perform waveform screening in advance, and the invalid waveforms can be directly removed based on the Thiessen polygons to obtain the seismic source restriction area. At the same time, for any microseismic monitoring subnet, an optimal solution can be obtained, and there will be no situation of equation non-convergence or multiple solutions. The present invention has good robustness, especially for subnets with poor spatial distribution, and the superiority of the present solution can be more prominently shown.

[0095] Further, as Figure 1 and Figure 2 shown in the specific implementation of the method, the embodiment of the present application provides an abnormal point detection device for an automatic generation control program, as Figure 4 shown, the device includes: a generation module 31, a verification module 32, a first calculation module 33, and a second calculation module 34;

[0096] The generation module 31 can be used to generate a first waveform sorting according to the reception time of the corresponding seismic longitudinal waves at each station after a microseismic event occurs;

[0097] The verification module 32 can be used to verify the validity of the first waveform sorting based on the Thiessen polygons drawn according to the three-dimensional coordinates of each station in the microseismic monitoring network, determine the valid waveform sorting and the set of valid waveforms, and determine the seismic source restriction area according to the valid waveform sorting;

[0098] The first calculation module 33 can be used to perform subnet combinations of at least four stations based on the set of valid waveforms, calculate the source location results under different subnet combinations, and obtain possible source points.

[0099] The second calculation module 34 can be used to determine the possible source points within the source restriction area as credible source points, calculate the spatial concentration based on the credible source points, and determine the credible source point with the highest corresponding spatial concentration as the optimal source point.

[0100] In a specific application scenario, when generating the first waveform sorting according to the reception times of the seismic longitudinal waves corresponding to each station, the generation module 31 can specifically be used to determine the reception times of the seismic longitudinal waves corresponding to each station, and generate the first waveform sorting for each station in ascending order of the reception times.

[0101] In a specific application scenario, when validating the effectiveness of the first waveform sorting according to the Thiessen polygons drawn based on the three-dimensional coordinates of each station in the microseismic monitoring network, determining the valid waveform sorting and the set of valid waveforms, and determining the source restriction area according to the valid waveform sorting, as Figure 5 shown, the verification module 32 can specifically include: a judgment unit 321, a first determination unit 322, an adjustment unit 323, and a second determination unit 324;

[0102] The judgment unit 321 can be used to draw Thiessen polygons according to the three-dimensional coordinates of each station in the microseismic monitoring network, and judge whether there is an intersection between the Thiessen polygons corresponding to any two adjacent stations in the first waveform sorting.

[0103] The first determination unit 322 can be used to, if it is judged that there is an intersection between the Thiessen polygons corresponding to any two adjacent stations in the first waveform sorting, determine the first waveform sorting as the valid waveform sorting, determine the station waveforms in the first waveform sorting as the valid waveforms, and generate a set of valid waveforms.

[0104] The adjustment unit 323 can be used to, if it is judged that there is no intersection between the Thiessen polygons corresponding to any two adjacent stations in the first waveform sorting, adjust the arrangement order of the station waveforms in the first waveform sorting, or eliminate the invalid waveforms, so as to obtain the valid waveform sorting and the set of valid waveforms, and there is an intersection between the Thiessen polygons corresponding to any two adjacent stations in the valid waveform sorting.

[0105] The second determination unit 324 can be used to determine the regional intersection of the Thiessen polygons corresponding to all stations in the valid waveform sorting, and determine the regional intersection as the source restriction area.

[0106] In a specific application scenario, perform subnet combinations of at least four stations based on the set of valid waveforms, calculate the source location results under different subnet combinations, and obtain possible source points, as Figure 5As shown, the first calculation module 33 includes: a construction unit 331 and a first calculation unit 332;

[0107] The construction unit 331 can be used to randomly select at least four stations from the set of effective waveforms and construct a sub-station network combination based on the at least four stations;

[0108] The first calculation unit 332 can be used to calculate the predicted source coordinates under the sub-station network combination based on the source information and the information of each station in the sub-station network combination, and according to a pre-designed calculation formula, and determine the predicted source coordinates as the possible source points. The source information includes the P-wave velocity of the earthquake, and the station information includes the three-dimensional coordinates of the station and the reception time of the effective waveform corresponding to the station.

[0109] Among them, the formula characteristics of the pre-designed calculation formula are described as:

[0110]

[0111] Among them, R is the total residual of each station in the sub-station network combination, r i is the residual of the i-th station, V is the P-wave velocity of the earthquake, (x i , y i , z i ) is the three-dimensional coordinates of the i-th station, i = 1, 2,..., n, t i is the reception time of the effective waveform corresponding to the i-th station, i = 1, 2,..., m, m is the number of effective waveforms, and (x0, y0, z0) are the predicted source coordinates.

[0112] In a specific application scenario, when calculating the spatial concentration based on the credible source points and determining the credible source point with the highest corresponding spatial concentration as the best source point, as Figure 5 shown, the second calculation module 34 includes: a drawing unit 341, a third determination unit 342, a second drawing unit 343, and a fourth determination unit 344;

[0113] The drawing unit 341 can be used to perform a first grid division on the source restricted area, determine the number of credible source points in the first grid as the value of the center point of the first grid, and draw the first three-dimensional concentration cloud map of the first grid based on the value of the center point of the first grid and the Kriging interpolation algorithm;

[0114] The third determination unit 342 can be used to determine the first grid with the maximum concentration according to the first three-dimensional concentration cloud map;

[0115] The second drawing unit 343 can be used to perform a second grid division on the first grid with the maximum concentration and draw the second three-dimensional concentration cloud map of the second grid based on the Kriging interpolation algorithm, where the grid area of the first grid is larger than that of the second grid;

[0116] A fourth determination unit 344, which can be used to determine the second grid with the highest concentration according to the second three-dimensional concentration cloud map, and determine the center point of the second grid as the optimal seismic source point.

[0117] It should be noted that for other corresponding descriptions of each functional unit involved in the microseismic source positioning device based on the Thiessen polygon provided in this embodiment, reference can be made to Figures 1 to 2 the corresponding description, which will not be elaborated here.

[0118] Based on the above method as Figures 1 to 2 shown, correspondingly, this embodiment also provides a storage medium, which can be specifically a volatile or non-volatile storage medium, on which computer-readable instructions are stored. When the readable instructions are executed by a processor, the above-mentioned method based on the Thiessen polygon as Figures 1 to 2 shown is implemented.

[0119] Based on such an understanding, the technical solution of this application can be embodied in the form of a software product. The software product can be stored in a storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods in various implementation scenarios of this application.

[0120] Based on the above method as Figures 1 to 2 shown and Figure 4 、 Figure 5 the virtual device embodiment shown, in order to achieve the above object, this embodiment also provides a computer device, which includes a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to implement the above-mentioned method based on the Thiessen polygon as Figures 1 to 2 shown.

[0121] Optionally, the computer device may further include a user interface, a network interface, a camera, a radio frequency (RF) circuit, sensors, an audio circuit, a WI-FI module, etc. The user interface may include a display screen (Display), an input unit such as a keyboard (Keyboard), etc. Optionally, the user interface may further include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (such as a WI-FI interface), etc.

[0122] Those skilled in the art can understand that the structure of the computer device provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine some components, or have different component arrangements.

[0123] The storage medium may further include an operating system and a network communication module. The operating system is a program for managing the hardware and software resources of the above computer device, and supports the operation of the information processing program and other software and / or programs. The network communication module is used to implement communication between components inside the storage medium, as well as communication with other hardware and software in the information processing entity device.

[0124] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform, or can also be implemented by hardware.

[0125] By applying the technical solution of the present application, compared with the current existing technologies, the present application provides a microseismic source location method, device and computer device based on Thiessen polygons, which solves the problem that there is currently a lack of a simple and effective global seismic source location method, resulting in poor seismic source location accuracy and the microseismic monitoring effect not meeting the requirements of the mining party. After a microseismic event occurs in the present application, a first waveform sorting is generated according to the receiving time of the corresponding P-waves of each station; according to the Thiessen polygons drawn based on the three-dimensional coordinates of each station in the microseismic monitoring network, the validity of the first waveform sorting is verified to determine the valid waveform sorting and the valid waveform set, and the seismic source restricted area is determined according to the valid waveform sorting; at least four stations are combined into sub-networks based on the valid waveform set, the seismic source location results under different sub-network combinations are calculated to obtain possible seismic source points; the possible seismic source points within the seismic source restricted area are determined as credible seismic source points, the spatial concentration degree is calculated based on the credible seismic source points, and the credible seismic source point with the highest corresponding spatial concentration degree is determined as the optimal seismic source point. Through the technical solution in the present application, after a microseismic event occurs, through a combination of calculations in multiple dimensions, the optimal seismic source point can be screened layer by layer, effectively improving the seismic source location accuracy, reducing the seismic source location error, greatly improving the seismic source location speed and the stability of the location result, and ensuring that the microseismic monitoring effect meets the requirements of the mining party. In addition, for the P-waves received by each station, there is no need to pre-screen the waveforms, and the invalid waveforms can be directly removed based on the Thiessen polygons to obtain the seismic source restricted area. At the same time, for any microseismic monitoring sub-network, an optimal solution can be obtained, and there will be no situation of equation non-convergence or multiple solutions. The present invention has good robustness, especially for sub-networks with poor spatial distribution, and can better show the superiority of the present solution.

[0126] Those skilled in the art can understand that the drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the drawings are not necessarily essential for implementing the present application. Those skilled in the art can understand that the modules in the device in the implementation scenario can be distributed in the device in the implementation scenario according to the description of the implementation scenario, or can be correspondingly changed and located in one or more devices different from the present implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple sub-modules.

[0127] The above serial numbers of this application are only for description and do not represent the advantages or disadvantages of the implementation scenarios. The above disclosure is only several specific implementation scenarios of this application. However, this application is not limited thereto, and any changes that can be conceived by those skilled in the art should fall within the protection scope of this application.

Claims

1. A microseismic source location method based on Thiessen polygons, characterized in that include: After a microseismic event occurs, the first waveform sequence is generated according to the reception time of the corresponding seismic longitudinal wave at each station; According to the Thiessen polygons drawn by the three-dimensional coordinates of each station in the microseismic monitoring network, the validity of the first waveform sorting is verified, the valid waveform sorting and the valid waveform set are determined, and the source restriction area is determined according to the valid waveform sorting, including: drawing Thiessen polygons according to the three-dimensional coordinates of each station in the microseismic monitoring network, and judging whether the Thiessen polygons corresponding to any adjacent station in the first waveform sorting have an intersection; if it is judged that the Thiessen polygons corresponding to any adjacent station in the first waveform sorting have an intersection, the first waveform sorting is determined as a valid waveform sorting, the station waveform in the first waveform sorting is determined as a valid waveform, and a valid waveform set is generated; if it is judged that the Thiessen polygons corresponding to any adjacent station in the first waveform sorting do not have an intersection, the arrangement order of the waveforms of each station in the first waveform sorting is adjusted, or invalid waveforms are eliminated to obtain the valid waveform sorting and the valid waveform set, and the Thiessen polygons corresponding to any adjacent station in the valid waveform sorting have an intersection; determining the regional intersection of the Thiessen polygons corresponding to all the stations in the valid waveform sorting, and determining the regional intersection as the source restriction area; According to the effective waveform set, at least four stations are combined into a sub-network, and the earthquake source positioning results under different sub-network combinations are calculated to obtain possible earthquake source points, including: randomly selecting at least four stations from the effective waveform set, and building a sub-network combination according to the at least four stations; based on the earthquake source information and the information of each station in the sub-network combination, and according to a preset calculation formula, the predicted earthquake source coordinates under the sub-network combination are calculated, and the predicted earthquake source coordinates are determined as possible earthquake source points, the earthquake source information includes the earthquake longitudinal wave velocity, and the station information includes the three-dimensional coordinates of the station and the reception time of the corresponding effective waveform of the station; the formula feature of the preset calculation formula is described as: where R is the total residual of each station in the sub-network combination, is the residual of the i-th station, V is the P-wave velocity of the earthquake, ( is the three-dimensional coordinates of the i-th station is the reception time of the effective waveform corresponding to the i-th station, i = 1, 2, …, m, where m is the number of effective waveforms, ( and and ) are the predicted source coordinates; The possible seismic source points within the seismic source restriction area are determined as credible seismic source points, the spatial concentration is calculated based on the credible seismic source points, and the credible seismic source point with the highest spatial concentration is determined as the best seismic source point.

2. The method according to claim 1, characterized in that, The step of generating a first waveform sequence according to the reception time of the seismic longitudinal wave corresponding to each station includes: The receiving time of the seismic longitudinal wave corresponding to each station is determined, and a first waveform sequence for each station is generated in the order of the receiving time from small to large.

3. The method according to claim 1, characterized in that, The step of calculating the spatial concentration according to the credible seismic source points and determining the credible seismic source point with the highest spatial concentration as the best seismic source point comprises: Divide the seismic source restriction area into a first grid, determine the number of credible seismic source points in the first grid as the value of the center point of the first grid, and draw a first three-dimensional concentration cloud map of the first grid based on the value of the center point of the first grid and a Kriging difference algorithm; Determine a first grid with the largest concentration according to the first three-dimensional concentration cloud map; Divide the first grid with the largest concentration into a second grid, and draw a second three-dimensional concentration cloud map of the second grid based on the Kriging difference algorithm, wherein the grid area of ​​the first grid is larger than that of the second grid; A second grid with the largest concentration is determined according to the second three-dimensional concentration cloud map, and a center point of the second grid is determined as the optimal seismic source point.

4. A microseismic source positioning device based on Voronoi polygons, characterized in that include: A generation module, used for generating a first waveform sequence according to the reception time of the corresponding seismic longitudinal wave of each station after a microseismic event occurs; A verification module, used to verify the validity of the first waveform sorting according to the Thiessen polygons drawn by the three-dimensional coordinates of each station in the microseismic monitoring network, determine the valid waveform sorting and the valid waveform set, and determine the source restriction area according to the valid waveform sorting; A first calculation module is used to perform a sub-network combination of at least four stations according to the effective waveform set, calculate the earthquake source location results under different sub-network combinations, and obtain possible earthquake source points; A second calculation module is used to determine possible seismic source points within the seismic source restriction area as credible seismic source points, calculate spatial concentrations based on the credible seismic source points, and determine the credible seismic source point with the highest spatial concentration as the best seismic source point; The verification module comprises: A judgment unit, used for drawing Thiessen polygons according to the three-dimensional coordinates of each station in the microseismic monitoring network, and judging whether there is an intersection between Thiessen polygons corresponding to any adjacent stations in the first waveform sorting; A first determining unit is configured to determine the first waveform sorting as a valid waveform sorting, determine the station waveforms in the first waveform sorting as valid waveforms, and generate a valid waveform set if it is determined that the Thiessen polygons corresponding to any adjacent stations in the first waveform sorting have intersections; An adjusting unit, for adjusting the arrangement order of waveforms of each station in the first waveform sorting, or removing invalid waveforms, to obtain a valid waveform sorting and a valid waveform set, if it is determined that the Thiessen polygons corresponding to any adjacent stations in the first waveform sorting do not have an intersection, and the Thiessen polygons corresponding to any adjacent stations in the valid waveform sorting do have an intersection; The second determination unit can be used to determine the regional intersection of Thiessen polygons corresponding to all stations in the effective waveform sorting, and determine the regional intersection as the source restriction area; The first computing module comprises: A construction unit, used for randomly selecting at least four stations from the effective waveform set, and constructing a sub-station network combination according to the at least four stations; The first calculation unit is used to calculate the predicted earthquake source coordinates under the sub-station network combination based on the earthquake source information and the information of each station in the sub-station network combination and according to a preset calculation formula, and determine the predicted earthquake source coordinates as the possible earthquake source point, the earthquake source information includes the earthquake longitudinal wave velocity, and the station information includes the three-dimensional coordinates of the station and the reception time of the corresponding effective waveform of the station; The formula characteristics of the preset calculation formula are described as follows: Among them, R is the total residual of each station in the sub-network combination, is the residual of the i-th station, V is the P-wave velocity of the earthquake, ( is the three-dimensional coordinate of the i-th station is the reception time of the effective waveform corresponding to the i-th station, i = 1, 2, …, m, where m is the number of effective waveforms, ( 、 、 ) is the predicted earthquake source coordinate.

5. A storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, the microseismic source positioning method based on Thiessen polygons described in any one of claims 1 to 3 is implemented.

6. A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the program, the microseismic source positioning method based on Thiessen polygons described in any one of claims 1 to 3 is implemented.

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