Microseismic event positioning method and device, electronic equipment and storage medium

Abstract

The invention provides a microseismic event positioning method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the network division of a first target region based on a first interval, and obtaining a plurality of first grid points and first coherence values corresponding to the first grid points; determining a zero point and a reference grid point in the plurality of first grid points according to the first coherence value; determining a second target area based on the distance between the reference grid point and the zero point under the condition that the first interval is greater than or equal to an interval threshold value; determining a second spacing based on the reference calculation time and the second target area; and returning to execute the step of carrying out network division on the second target area based on the second interval and the second target area, repeating iteration until any interval is determined to be smaller than an interval threshold value, and determining zero points in all grid points corresponding to the interval as the position of the micro-seismic event. The range of the micro-seismic event can be quickly locked, and the real-time performance of micro-seismic event positioning is improved while the positioning precision is ensured.

Description

Technical Field

[0001] The present application relates to the technical field of microseismic monitoring, and particularly to a method, device, electronic device and storage medium for locating microseismic events. Background Art

[0002] Microseismic monitoring technology has been widely applied in fields such as shale gas extraction, mining, deep geothermal development, and geotechnical engineering. It can monitor the fracture and stability of underground rock formations by recording small-scale seismic events. Traditional positioning methods usually rely on phase picking, that is, identifying the arrival time information of P-waves and S-waves from the observed waveforms in a noisy environment, and combining ray tracing or travel time inversion for positioning.

[0003] However, for the cases where the distance from the seismic source to the receiver is very short (only a few hundred meters or a few kilometers), the signal-to-noise ratio of the event is low, or it is difficult to separate P-waves and S-waves, it is often very difficult to pick up reliable phases, resulting in low positioning accuracy or inability to position by traditional methods. Therefore, a microseismic event positioning method with higher accuracy and efficiency is needed. Summary of the Invention

[0004] The present application aims to solve at least one of the technical problems in the related art to some extent.

[0005] To this end, the first object of the present application is to propose a method for locating microseismic events, so as to reduce the calculation amount by introducing the calculation of probability density function and the strategy of phased collapsed grid during the grid search process, and be able to improve the detection and positioning accuracy of microseismic events under low signal-to-noise ratio conditions while ensuring the calculation time, and reduce the dependence on the arrival time picking of P-waves and S-waves during microseismic event positioning.

[0006] The second object of the present application is to propose a device for locating microseismic events.

[0007] The third object of the present application is to propose an electronic device.

[0008] The fourth object of the present application is to propose a computer-readable storage medium.

[0009] To achieve the above object, the first aspect embodiment of the present application proposes a method for locating microseismic events, including:

[0010] Based on the first spacing, perform network division on the first target area to obtain a plurality of first grid points, where the first target area contains microseismic events;

[0011] Determine the first coherence value corresponding to each of the first grid points;

[0012] Determine the zero points and reference grid points among the multiple first grid points according to the first coherence value;

[0013] When the first spacing is greater than or equal to the spacing threshold, determine a second target area based on the distance between the reference grid point and the zero point, where the second target area is smaller than the first target area;

[0014] Determine a second spacing based on the reference calculation time and the second target area;

[0015] Based on the second spacing and the second target area, return to execute the step of network partitioning for the second target area, and repeat the iteration until it is determined that any spacing is less than the spacing threshold, and determine the zero point among all grid points corresponding to the any spacing as the location of the microseismic event.

[0016] To achieve the above object, an embodiment of the second aspect of the present application provides a microseismic event positioning device, including:

[0017] A partitioning module, configured to perform network partitioning on a first target area based on a first spacing to obtain a plurality of first grid points, where the first target area contains a microseismic event;

[0018] A first determination module, configured to determine a first coherence value corresponding to each of the first grid points;

[0019] A second determination module, configured to determine the zero points and reference grid points among the multiple first grid points according to the first coherence value;

[0020] A third determination module, configured to determine a second target area based on the distance between the reference grid point and the zero point when the first spacing is greater than or equal to the spacing threshold, where the second target area is smaller than the first target area;

[0021] A fourth determination module, configured to determine a second spacing based on the reference calculation time and the second target area;

[0022] A processing module, configured to return to execute the step of network partitioning for the second target area based on the second spacing and the second target area, and repeat the iteration until it is determined that any spacing is less than the spacing threshold, and determine the zero point among all grid points corresponding to the any spacing as the location of the microseismic event.

[0023] To achieve the above object, an embodiment of the third aspect of the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0024] The memory stores computer execution instructions;

[0025] The processor executes the computer-executable instructions stored in the memory to implement the microseismic event location method provided in the embodiment of the first aspect of this application.

[0026] To achieve the above object, an embodiment of the fourth aspect of this application proposes a computer-readable storage medium storing computer-executable instructions, which are used to implement the microseismic event location method provided in the embodiment of the first aspect of this application when executed by a processor.

[0027] The microseismic event location method, device, electronic device, and storage medium provided in this application determine the grid point most likely to be the source location in the area by calculating the coherence values of each grid point in the area. When the current grid accuracy does not meet the resolution requirement, the high-coherence value area in the current grid is determined as the target area for grid search in the next stage, and the grid interval for grid search in the next stage area is determined. The search volume is gradually reduced and the grid is refined, and multiple iterations are performed until the grid accuracy meets the resolution requirement to obtain the location result of the microseismic event. Therefore, by using a staged grid search, the initial coarse search can quickly lock the general range of the event, and the fine calculation is performed after multiple contractions. While maintaining the spatial resolution ability, the redundant calculation amount is greatly reduced, the efficiency of microseismic event location is improved, and real-time or near-real-time event location can be achieved.

[0028] The additional aspects and advantages of this application will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of this application. Description of the Drawings

[0029] The above and / or additional aspects and advantages of this application will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, where:

[0030] Figure 1 is a schematic flowchart of a microseismic event location method provided by an embodiment of this application;

[0031] Figure 2 is a schematic flowchart of another microseismic event location method provided by an embodiment of this application;

[0032] Figure 3 is a schematic flowchart of another microseismic event location method provided by an embodiment of this application;

[0033] Figure 4 is a schematic flowchart of another microseismic event location method provided by an embodiment of this application;

[0034] Figure 5 is a schematic structural diagram of a microseismic event location device provided by an embodiment of this application. Detailed Embodiments

[0035] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where like or similar reference numerals denote like or similar elements or elements having like or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application, but should not be construed as limiting the present application.

[0036] The microseismic event location method and device according to the embodiments of the present application will be described below with reference to the accompanying drawings.

[0037] Figure 1 It is a schematic flowchart of a microseismic event location method provided by an embodiment of the present application.

[0038] As Figure 1 shown, the microseismic event location method includes the following steps:

[0039] Step 101: Based on the first spacing, divide the first target area into a network to obtain a plurality of first grid points.

[0040] Among them, the first spacing is the distance between adjacent grid points when initially dividing a certain area into grids.

[0041] Among them, the first target area is a relatively large area containing microseismic events, that is, the initial area for locating microseismic events, which can be manually delineated.

[0042] In the present application, in order to quickly lock the position of the microseismic event, the first spacing should take a relatively large value, such as 1 kilometer, etc. The first spacing can also be a value determined according to the volume size of the first target area to be divided. The larger the area volume, the larger the first spacing, so as to ensure an appropriate number of grid points, avoid too long search time, and quickly lock the approximate range of the event.

[0043] In the embodiments of the present application, within the volume of the first target area, cubic grids can be divided with the first spacing, and each grid intersection obtained by the division is a first grid point.

[0044] Step 102: Determine the first coherence value corresponding to each first grid point.

[0045] Among them, the coherence value is a value that measures the similarity degree of two signals when they shift with time. It can be obtained by calculating the correlation coefficient, such as the cross-correlation coefficient, Pearson correlation coefficient, etc. The more similar the waveforms of the two signals are, the higher the coherence value. The coherence value corresponding to a grid point is the superposition result of the coherence values between every two signals among all signals at the position of this grid point.

[0046] In the embodiments of the present application, the Trace Coherency Stacking Method (TCSM) can be used to calculate the first coherence value corresponding to each first grid point. First, the geophones in the first target area can be paired up two by two, the coherence of the waveforms of each geophone pair (station pair) can be calculated, and then the coherence values of all geophone pairs can be stacked on the spatial network, so that the first coherence values corresponding to each first grid point on the network can be obtained. The stacking formula of the coherence values can be shown as formula (1) below.

[0047]

[0048] Among them, M is the number of seismic traces participating in the calculation. The number of seismic traces is the number of geophones. The waveform data recorded by one geophone is one seismic trace. For a specific time window (abbreviated as time window) after the start time of the microseismic event, f ij is the jth sampling point of the ith trace, N is the size of the time window, N can be determined according to the duration of the signal, etc., k is the center position of the time window, and S(k) is the size after the coherence values are stacked within the specific time window.

[0049] It should be noted that the occurrence of microseismic events often does not occur at an exact hour, and an accurate start time cannot be determined. Therefore, in order to find the optimal source spatio-temporal position, in the present application, searches or attempts can be made at multiple start times within a certain range. A coherence value will be obtained for each grid point and each possible start time, and then the coherence values of each grid point at different start times will be compared, and the maximum coherence value will be determined as the coherence value of the grid point. The start time corresponding to this coherence value is the optimal solution among all possible start times.

[0050] In the embodiments of the present application, if the coherence value of the first grid point is high, it can be explained that at the position of the first grid point, most geophone pairs can exhibit synchronous and similar waveform characteristics, and it is more likely to be a potential source position, which conforms to the actual wave field propagation situation. Therefore, in the present application, the location of microseismic events can be searched by calculating the coherence values at grid points. Compared with the traditional method that needs to pick up P-waves or S-waves one by one, TCSM can maintain high reliability for seismic records with relatively weak magnitudes or low SNR (signal-to-noise ratio).

[0051] In the embodiments of the present application, since the calculation time required by the TCSM algorithm has a linear growth relationship with the number of grid points, therefore, the larger the target area for research location and / or the smaller the spatial interval between grid points, the longer the time required to locate a microseismic event.

[0052] Step 103: Determine the zero points and reference grid points among the multiple first grid points according to the first coherence value.

[0053] Among them, the zero point is the point among all current first grid points that is closest to the microseismic event location, that is, the point with the largest first coherence value among all first grid points.

[0054] Among them, the reference grid points are the points among all first grid points whose first coherence values meet the screening conditions, and the reference grid points are used to further narrow down the positioning range of the microseismic event.

[0055] In the embodiments of the present application, the screening condition for the reference grid points can be that the grid points with corresponding coherence values greater than the quantile threshold are reference grid points. For example, according to the need of the grid search rate, the quantile threshold can be set to 0.99. Then, all first grid points can be sorted in ascending order according to the corresponding first coherence values, and the first coherence value at the 0.99th quantile in this sorting is determined and denoted as A. Thus, all first grid points corresponding to first coherence values greater than A can be determined as a reference grid point.

[0056] In the embodiments of the present application, the first coherence values of all first grid points can be compared, and the first grid point corresponding to the largest first coherence value is determined as the zero point. The largest first coherence value indicates that the zero point is the grid point with the smallest difference between the observed travel time and the calculated travel time among all first grid points, and the source location of the microseismic event is most likely at the zero point. Since the current spacing between grid points is relatively large, the source location of the currently to-be-located microseismic event may be between grid points. Using the first grid point as the positioning result has poor accuracy. Therefore, it is necessary to further narrow down the search volume and grid spacing to improve the positioning accuracy of the microseismic event. Grid points among all first grid points whose first coherence values meet the screening conditions can be selected as reference grid points to determine the high-coherence region adjacent to the zero point as the region for the next-stage grid search.

[0057] Step 104, when the first spacing is greater than or equal to the spacing threshold, determine the second target region based on the distance between the reference grid point and the zero point.

[0058] Among them, the spacing threshold can be determined according to the accuracy of the maximum spatial error of the grid cell centroid.

[0059] In the embodiments of the present application, for a cubic grid, the maximum spatial error of the grid cell centroid is shown in the following formula (2), where D is the maximum spatial error and Δx is the grid spacing.

[0060]

[0061] Then, using formula (2), when the maximum spatial error D needs to be controlled at the order of 1m, the maximum value of the grid spacing can be calculated to obtain the spacing threshold.

[0062] In the embodiments of the present application, when the first spacing is greater than or equal to the spacing threshold, it can be determined that the position result error determined by the grid points divided based on the first spacing is relatively large at this time. It is necessary to adopt a multi-stage contraction strategy to further narrow the search space for positioning and improve the accuracy of network search.

[0063] Among them, the second target area is the area for grid search in the next stage. The second target area is included in the first target area, and the volume of the second target area is smaller than the volume of the first target area.

[0064] In the embodiments of the present application, the denser the reference grid points are, the greater the possibility that the source location of the microseismic event is near them. Therefore, the distance between each reference grid point and the zero point can be calculated to determine the peak distance that maximizes the density of the reference grid points. Then, taking the zero point as the center, the peak distance can be extended to three dimensions to obtain a new and smaller cubic search volume as the second target area for the next iteration of grid search, so that the high-resolution network only expands near the position where the source is most likely to appear, thereby saving the overall calculation time.

[0065] In the embodiments of the present application, the distance distributions of the reference grid points and the zero point in the north-south, east-west, and vertical directions can be statistically analyzed, and the probability density function (PDF) in each direction can be calculated respectively. Then, according to the distance corresponding to the peak of the probability density function in any direction, a three-dimensional cubic area is obtained by truncating with the zero point as the center and this distance in the first target area. After that, the cubic areas obtained in all directions can be fused to obtain the second target area, so that the second target area can cover the main possible ranges of the source location in each dimension.

[0066] Step 105: Determine the second spacing based on the reference calculation time and the second target area.

[0067] Among them, the second spacing is the distance between adjacent grid points when the second target area is divided into grids. The second spacing should be smaller than the first spacing.

[0068] In the embodiments of the present application, the reference calculation time refers to the maximum duration that the TCSM algorithm can calculate each time when performing grid search in order to control the calculation time. Since the calculation time required by the TCSM algorithm has a linear growth relationship with the number of grid points, the smaller the grid point spacing, the more grid points are determined in the same area, and the longer the time for the TCSM algorithm to calculate the coherence values at all grid points. And if the grid point spacing is too large, it will also lead to low efficiency of grid iterative search. Therefore, a suitable grid spacing, that is, the second spacing, needs to be determined for each iterative search to control the time required to locate a microseismic event.

[0069] In the embodiments of the present application, the number of grid points that can be calculated by the TCSM algorithm within the reference calculation time can be determined first, and then based on the number of grid points and the size of the second target area, when the number of grid points is evenly distributed in the second target area, the distance between adjacent grid points, that is, the second distance, can be determined.

[0070] Step 106: Based on the second distance and the second target area, return to perform the step of network partitioning on the second target area, and repeat the iteration until it is determined that any distance is less than the distance threshold, and determine the zero points among all the grid points corresponding to any distance as the positions of microseismic events.

[0071] Among them, any distance can be the first distance, the second distance, or the distance determined during any iteration. After determining a distance each time during the iteration, it is necessary to compare its size with the distance threshold. Once a certain distance is less than the distance threshold, the iteration can be stopped.

[0072] In the embodiments of the present application, after determining the second distance and the second target area, step 101 can be returned to. Using the second distance, network partitioning is performed on the second target area to obtain a plurality of second grid points, and then the coherence value is calculated for each second grid point, and the zero points and reference grid points among all the second grid points are determined. If the second distance is still greater than or equal to the distance threshold, continue to determine the target area and grid point distance in the next stage, and so on, for multiple iterations. If the second distance is less than the distance threshold, since the coherence value of the zero point is the largest, the zero point among the second grid points can be determined as the position of the microseismic event.

[0073] In the embodiments of the present application, in order to reduce the calculation time required for TCSM to calculate the source position at a specific spatial resolution, this process is divided into several iterations, starting from a large search space and a large spatial interval (i.e., the distance between adjacent grid points). Based on the results of each iteration, the search volume is further shrunk around the new optimal coherence region, the search space gradually shrinks, and at the same time, the spatial resolution is improved by reducing the spatial interval between grid points to improve the positioning error of TCSM until the expected spatial resolution (i.e., the grid spacing is less than the threshold) is reached, the iteration is stopped, and the zero points among the grid points divided in the last time are determined as the positions of microseismic events.

[0074] In this embodiment, by calculating the coherence values of each grid point in the area, the grid point most likely to be the source location in the area is determined. When the current grid accuracy does not meet the resolution requirement, the high-coherence value area in the current grid is determined as the target area for grid search in the next stage, and the grid interval for grid search in the next stage area is determined, gradually reducing the search volume and refining the grid, and performing multiple iterations until the grid accuracy meets the resolution requirement to obtain the positioning result of the microseismic event. Therefore, by using staged grid search, the initial rough search can quickly lock the general range of the event, and after multiple contractions, fine calculations are performed. While maintaining the spatial resolution ability, a large amount of redundant calculations is greatly reduced, the efficiency of microseismic event positioning is improved, and real-time or near-real-time event positioning can be achieved.

[0075] The present application also provides another method for locating microseismic events. Figure 2 It is a schematic flowchart of another method for locating microseismic events provided by the embodiments of the present application.

[0076] As Figure 2 shown, the method for locating microseismic events may include the following steps:

[0077] Step 201: Based on the first spacing, divide the first target area into grids to obtain a plurality of first grid points.

[0078] For a detailed description of the above step 201, reference can be made to other embodiments of the present application, which will not be elaborated here.

[0079] Step 202: Traverse all the geophones in the first target area to determine a plurality of geophone pairs.

[0080] In the embodiments of the present application, the number of geophones may depend on the size of the first target area, geological complexity, resolution requirements, etc. The geophones can be arranged at a certain grid spacing in the first target area to cover the entire area. All the geophones in the first target area can be paired in pairs to determine a plurality of geophone pairs.

[0081] For example, when the number of geophones is N, the number of geophone pairs is approximately N(N - 1) / 2. Since the positive and negative symmetry often does not need to be calculated repeatedly, that is, the geophone pair (i, j) and (j, i) formed by the i-th geophone and the j-th geophone are the same when calculating the coherence value, and when the geophone spacing is too large, the signal arrival time difference is large, and the significance of calculating the coherence value is not high. Therefore, in the present application, the number of geophone pairs can be N - 1.

[0082] Step 203: Calculate the second coherence value of each geophone pair according to the waveform data received by each geophone.

[0083] In an embodiment of the present application, the cross-correlation coefficient between the waveform data received by the two detectors can be calculated for each detector pair as the second coherence value of the detector pair. The cross-correlation is used to measure the similarity of two signals when they are offset over time. The more similar the shapes are, the higher the cross-correlation coefficient will be, and the higher the second coherence value will be.

[0084] It should be noted that the second coherence value ranges from 0 to 1, and a larger value indicates more similar signals.

[0085] Step 204, based on the earthquake occurrence time and the coordinates of each first grid point, the second coherence value is superimposed to obtain the first coherence value corresponding to each first grid point.

[0086] Among them, the earthquake occurrence time is the time when the seismic wave begins to propagate, which can be used to correct the propagation time of the seismic wave and ensure that the signals received by different detectors are aligned in time.

[0087] In the embodiment of the present application, the coherence value calculation is performed within a specific time window, and the earthquake occurrence time can help determine the start and end time of the analysis time window, eliminate noise interference, and improve the signal-to-noise ratio and accuracy of the coherence value calculation. Therefore, when calculating the first coherence value corresponding to each first grid point, a unified earthquake occurrence time can also be determined to ensure that the second coherence value is time-aligned when superimposed, constrain the earthquake location process, and improve the location accuracy.

[0088] In the embodiment of the present application, the coherence values ​​of the detector pairs can be mapped and superimposed according to the spatial grid. For each first grid point, the second coherence values ​​of all detector pairs located at the coordinates of the first grid point are superimposed to obtain the first coherence value corresponding to the first grid point.

[0089] It should be noted that the occurrence of microseismic events is often not at the exact time, so it is impossible to determine an accurate starting time. In this application, we can first estimate multiple possible earthquake occurrence times based on actual conditions, and then calculate the coherence value of each point in the spatial network for each possible earthquake occurrence time. The larger the coherence value, the closer the earthquake occurrence time is to the time when the actual seismic wave begins to propagate. Therefore, the estimated value of the earthquake occurrence time can be corrected in turn according to the positioning result of the microseismic event, forming an iterative optimization process.

[0090] Optionally, the second coherence values ​​may be superimposed based on each earthquake occurrence time and the coordinates of a first grid point to obtain a third coherence value of the first grid point at each earthquake occurrence time, and then the maximum value of the third coherence values ​​is determined as the first coherence value corresponding to the first grid point.

[0091] In the embodiments of the present application, since the signal characteristics of the seismic wave are the most obvious when it first reaches the geophone and the coherence value is the largest at this time, for each first grid point, the third coherence values at different earthquake occurrence times can be determined respectively, and then the magnitudes of all the third coherence values are compared. The largest third coherence value is determined as the first coherence value corresponding to the first grid point, and the earthquake occurrence time corresponding to the largest third coherence value is the optimal solution of the earthquake start time when the first grid point is the origin position of the microseismic event.

[0092] Step 205: Determine the zero point and the reference grid points among the multiple first grid points according to the first coherence value.

[0093] Optionally, the first grid point corresponding to the largest first coherence value can be determined as the zero point, and the first grid points corresponding to the first coherence values greater than the preset quantile threshold can be determined as the reference grid points.

[0094] For example, there are 1000 first grid points, which are respectively marked as the first grid point 1, the first grid point 2, ……, the first grid point 999, and the first grid point 1000. After being arranged in ascending order of the first coherence values they respectively correspond to, they are the first grid point 1000, the first grid point 999, ……, the first grid point 2, and the first grid point 1. Then the zero point is the first grid point 1. When the preset quantile threshold is 0.99, the reference grid points are all the first grid points greater than the 990th position (i.e., the first grid point 11) in the sorting, including the first grid point 1, the first grid point, ……, the first grid point 10.

[0095] Step 206: When the first distance is greater than or equal to the distance threshold, determine the second target area based on the distance between the reference grid point and the zero point.

[0096] Step 207: Determine the second distance based on the reference calculation time and the second target area.

[0097] Step 208: Based on the second distance and the second target area, return to execute the step of partitioning the network for the second target area, and repeat the iteration until it is determined that any distance is less than the distance threshold. Then, determine the zero point among all the grid points corresponding to any distance as the position of the microseismic event.

[0098] For the detailed description of the above steps 205 to 208, reference can be made to other embodiments of the present application, which will not be elaborated here.

[0099] In this embodiment, by calculating the coherence of the waveforms of all the geophone pairs participating in the calculation in the target area of the location of the microseismic event to be studied, and then performing coherence value superposition according to the estimated earthquake occurrence time and the coordinates of each grid point in the area, the first coherence value at each grid point can be obtained, thereby improving the signal-to-noise ratio and accuracy of the coherence value calculation, and further ensuring the reliability of the microseismic event location result.

[0100] The present application also provides another microseismic event location method. Figure 3 It is a schematic flowchart of another microseismic event location method provided by the embodiment of the present application.

[0101] As Figure 3 shown, the microseismic event location method may include the following steps:

[0102] Step 301, based on the first spacing, divide the first target area into a network to obtain a plurality of first grid points.

[0103] Step 302, determine the first coherence value corresponding to each first grid point.

[0104] Step 303, according to the first coherence value, determine the zero points and reference grid points among the plurality of first grid points.

[0105] For the detailed description of the above steps 301 to 303, reference may be made to other embodiments of the present application, which will not be elaborated here.

[0106] Step 304, when the first spacing is greater than or equal to the spacing threshold, determine the distances of the reference grid point in each target direction of the zero point.

[0107] Among them, there are three target directions, which can be the north-south direction, the east-west direction, and the vertical direction respectively, and any two of the three target directions are perpendicular to each other.

[0108] In the embodiment of the present application, when the first spacing is greater than or equal to the spacing threshold, it can be determined that the position result error determined by the grid points divided based on the first spacing is relatively large at this time, and it is necessary to further narrow the search space for location. Therefore, the distance distribution of the reference grid points with high coherence values among the first grid points relative to the zero point can be determined to determine the high coherence area adjacent to the zero point as the target area for the next stage of search.

[0109] In the embodiment of the present application, in order to determine the distance distribution of the reference grid points with high coherence values among the first grid points relative to the zero point, the distances of the reference grid point in each target direction of the zero point can be determined first. In the case where the reference grid point is not in any target direction of the zero point, the reference grid point can be mapped to the target direction of the zero point to obtain the distance of the reference grid point in the target direction of the zero point.

[0110] For example, a coordinate system can be established with the three target directions of the zero point as the coordinate axes, where the north-south direction is the x-axis, the east-west direction is the y-axis, and the vertical direction is the z-axis. The coordinates of each reference grid point can be expressed as (x, y, z), and the coordinates of the zero point are (0, 0, 0). When the coordinates of a reference grid point are (2, 1, 3), it can be known that the distance between this reference grid point and the zero point in the north-south direction is 2, the distance in the east-west direction is 1, and the distance in the vertical direction is 3.

[0111] In the embodiments of the present application, by determining the spacing between the reference grid point and the zero point in different directions, it is convenient to determine the key direction when the search volume is further shrunk, and to estimate the positional relationship between the microseismic event location and the zero point determined in the current stage, which helps to improve the positioning efficiency.

[0112] Step 305: Calculate the probability density function of any target direction according to the distance distribution in any target direction.

[0113] In the embodiments of the present application, the probability density function in each target direction can be shown as the following formula (3).

[0114]

[0115] Where x is the distance variable in this target direction, μ is the average value of the distances from all reference grid points to the zero point in this target direction, and σ is the standard deviation of the distances from all reference grid points to the zero point in this target direction.

[0116] Step 306: Determine the search distance in any target direction according to the peak range of the probability density function.

[0117] In the embodiments of the present application, it can be determined from the above formula (3) that the range of the distance variable for which the function value is greater than a certain value in any target direction is the peak range of the probability density function. Then, the maximum value of the distance variable corresponding to this peak range can be determined as the search distance in this any target direction.

[0118] Step 307: Obtain the search area in this target direction based on the zero point and the search distance.

[0119] In the embodiments of the present application, after determining the search distance in any target direction, a three-dimensional cube region can be truncated at the positions of the search distance on the positive and negative semi-axes of each target direction with the zero point as the center, as the search area in this target direction.

[0120] Step 308: Determine the second target area from the search areas corresponding to all target directions.

[0121] In the embodiments of the present application, after obtaining the search regions corresponding to all target directions, the search regions can be fused to determine a second target region for grid search in the next stage, so that the search volume can better cover the main possible ranges of microseismic event positioning in each dimension, which is beneficial to improving the accuracy and reliability of microseismic event positioning.

[0122] Step 309: Determine a second spacing based on the reference calculation time and the second target region.

[0123] Step 310: Based on the second spacing and the second target region, return to execute the step of dividing the second target region into grids, and repeat the iteration until it is determined that any spacing is less than the spacing threshold, and then determine the zero point among all grid points corresponding to any spacing as the position of the microseismic event.

[0124] For the detailed descriptions of the above Step 309 and Step 310, reference can be made to other embodiments of the present application, which will not be elaborated here.

[0125] The present application also provides another method for microseismic event positioning. Figure 4 It is a schematic flowchart of another method for microseismic event positioning provided by the embodiments of the present application.

[0126] As Figure 4 shown, this method for microseismic event positioning may include the following steps:

[0127] Step 401: Divide a first target region into grids based on a first spacing to obtain a plurality of first grid points.

[0128] Step 402: Determine a first coherence value corresponding to each first grid point.

[0129] Step 403: Determine the zero point and the reference grid point among the plurality of first grid points according to the first coherence value.

[0130] Step 404: In the case where the first spacing is greater than or equal to the spacing threshold, determine a second target region based on the distance between the reference grid point and the zero point.

[0131] For the detailed descriptions of the above Step 401 to Step 404, reference can be made to other embodiments of the present application, which will not be elaborated here.

[0132] Step 405: Determine the number of grid points for dividing the second target region based on the reference calculation time.

[0133] In the embodiments of the present application, the reference calculation time refers to the maximum duration that the TCSM algorithm can calculate each time when performing grid search in order to control the calculation time. Since the more grid points there are, the longer the calculation time required. Therefore, the number of grid points that can be divided when dividing the second target area can be determined according to the specified reference calculation time.

[0134] It should be noted that in addition to being affected by the number of grid points, the influencing factors of the calculation time can also include the number of processor cores, the number of starting times related to the number of sampling points and the full length of the waveform within the selected time window, the number of geophones participating in the recording, and the coefficient related to the computer architecture, etc. The linear relationship between these influencing factors and the calculation time can be shown as the following formula (4):

[0135]

[0136] Among them, t is the calculation time. k is a coefficient related to the computer architecture, which is an empirical coefficient used to describe the differences between software implementation, cache mechanism, and other computer hardware.

[0137] Among them, N is the number of geophones participating in the recording. The number of geophone pairs is approximately N(N - 1) / 2. Since when calculating the cross-correlation for each geophone pair (i, j), the results of (i, j) and (j, i) are the same and do not need to be calculated repeatedly. s is the number of grid points. t is the number of starting times related to the number of sampling points and the full length of the waveform within the selected time window.

[0138] In the embodiments of the present application, in the case where the length of the digital signal is fixed for the cross-correlation operation, it is t proportional to the number of sampling points N. s If a complete waveform cross-correlation superposition is performed at each grid point, the total amount of operations increases with the product of N

[0139] and N(N - 1) / 2. c is the number of cores of the parallelized processor. The more cores there are, the shorter the calculation time required. Therefore, assuming that each core can evenly share the calculation task completely, the calculation time t should be c inversely proportional to N c and proportional to 1 / N.

[0140] In the embodiments of the present application, assuming that the same processor is used each time when calculating the coherence value, then c N and k can be regarded as constants. For a fixed waveform length, t N can also be a constant, and for the same observation system, the number of geophones remains unchanged. At this time, the calculation time only depends on the number of imaging points in the grid, that is, the number of grid points N sIt is proportional. Therefore, this application proposes to use the collapsed grid method to dynamically reduce the number of grids during the offset positioning process, which can reduce the calculation time of the TCSM algorithm without affecting the resolution performance of the seismic source positioning.

[0141] Step 406: Determine a second spacing based on the volume of the second target area and the number of grid points.

[0142] In the embodiment of this application, after determining the number of grid points for dividing the second target area, the volume of the second target area can be used to calculate the second spacing between adjacent grid points when performing a finer grid division on the reduced search area (i.e., the second target area). The calculation formula for the second spacing can be shown as the following formula (5).

[0143]

[0144] Among them, Δx1 is the second spacing, V1 is the volume of the second target area, and N s is the number of grid points that can be processed within the limited reference calculation time.

[0145] In the embodiment of this application, by dynamically judging the upper limit of the available number of grid points according to formula (4) before iteration and using formula (5) to calculate the network spacing for each iteration of network division, the calculation time can be controlled, the positioning error of the microseismic event can be gradually improved, and the accuracy and reliability of the final positioning result can be improved.

[0146] Step 407: Based on the second spacing and the second target area, return to execute the step of performing network division on the second target area, and repeat the iteration until it is determined that any spacing is less than the spacing threshold, and then determine the zero point among all the grid points corresponding to any spacing as the position of the microseismic event.

[0147] For the detailed description of the above step 407, reference can be made to other embodiments of this application, which will not be elaborated here.

[0148] To implement the above embodiments, this application also proposes a microseismic event positioning device.

[0149] Figure 5 It is a schematic structural diagram of a microseismic event positioning device provided by an embodiment of this application.

[0150] As Figure 5 shown, the microseismic event positioning device 50 may include:

[0151] A division module 501, configured to perform network division on a first target area based on a first spacing to obtain a plurality of first grid points, where the first target area contains a microseismic event;

[0152] The first determination module 502 is configured to determine a first coherence value corresponding to each first grid point;

[0153] The second determination module 503 is configured to determine a zero point and a reference grid point among a plurality of first grid points according to the first coherence value;

[0154] The third determination module 504 is configured to determine a second target area based on the distance between the reference grid point and the zero point when the first spacing is greater than or equal to the spacing threshold, wherein the second target area is smaller than the first target area;

[0155] The fourth determination module 505 is configured to determine a second spacing based on the reference calculation time and the second target area;

[0156] The processing module 506 is configured to return to perform the step of network partitioning on the second target area based on the second spacing and the second target area, and iterate repeatedly until it is determined that any spacing is less than the spacing threshold, and determine the zero point among all grid points corresponding to any spacing as the location of the microseismic event.

[0157] Further, in a possible implementation manner of the embodiment of the present application, the first determination module 502 may specifically be configured to:

[0158] Traverse all geophones in the first target area to determine a plurality of geophone pairs;

[0159] Calculate a second coherence value for each geophone pair according to the waveform data received by each geophone;

[0160] Based on the earthquake occurrence time and the coordinates of each first grid point, superimpose the second coherence values to obtain a first coherence value corresponding to each first grid point.

[0161] Further, in a possible implementation manner of the embodiment of the present application, the first determination module 502 may specifically be configured to:

[0162] Based on each earthquake occurrence time and the coordinates of a first grid point, respectively superimpose the second coherence values to obtain a third coherence value of the first grid point at each earthquake occurrence time;

[0163] Determine the maximum value among the third coherence values as the first coherence value corresponding to the first grid point.

[0164] Further, in a possible implementation manner of the embodiment of the present application, the third determination module 504 may further be configured to:

[0165] Determine the first grid point corresponding to the maximum first coherence value as the zero point;

[0166] Determine the first grid point corresponding to the first coherence value greater than the preset quantile threshold as the reference grid point.

[0167] Further, in a possible implementation manner of the embodiment of the present application, the third determination module 504 may specifically be configured to:

[0168] Determine the distances of the reference grid points in each target direction at the zero point, where there are three target directions and they are perpendicular to each other.

[0169] Further, in a possible implementation manner of the embodiment of the present application, the third determination module 504 may specifically be configured to:

[0170] Calculate the probability density function of any target direction according to the distance distribution in any target direction;

[0171] Determine the search distance in any target direction according to the peak range of the probability density function;

[0172] Based on the zero point and the search distance, obtain the search area corresponding to any target direction;

[0173] Determine the second target area from the search areas corresponding to all target directions.

[0174] Further, in a possible implementation manner of the embodiment of the present application, the fourth determination module 505 may specifically be configured to:

[0175] Determine the number of grid points for dividing the second target area based on the reference calculation time;

[0176] Determine the second pitch based on the volume of the second target area and the number of grid points.

[0177] It should be noted that the foregoing explanation of the embodiment of the microseismic event positioning method is also applicable to the microseismic event positioning device of this embodiment, and will not be elaborated here.

[0178] In the embodiment of the present application, by calculating the coherence value of each grid point in the area, the grid point most likely to be the source location in the area is determined. When the current grid accuracy does not meet the resolution requirement, the high-coherence value area in the current grid is determined as the target area for grid search in the next stage, and the network interval for grid search in the next stage area is determined. The search volume is gradually reduced and the grid is refined, and multiple iterations are performed until the grid accuracy meets the resolution requirement to obtain the positioning result of the microseismic event. Therefore, by using phased grid search, the initial rough search can quickly lock the general range of the event, and after multiple contractions, fine calculations are performed. While maintaining the spatial resolution ability, a large amount of redundant calculations are greatly reduced, the efficiency of microseismic event positioning is improved, and real-time or near-real-time event positioning can be achieved.

[0179] To implement the above embodiments, the present application also provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the microseismic event location method provided in the foregoing embodiments.

[0180] To implement the above embodiments, the present application also provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the microseismic event location method provided in the foregoing embodiments when executed by a processor.

[0181] To implement the above embodiments, the present application also provides a computer program product including a computer program, which implements the microseismic event location method provided in the foregoing embodiments when executed by a processor.

[0182] The collection, storage, use, processing, transmission, provision, and disclosure of the user's personal information involved in the present application all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0183] It should be noted that personal information from users should be collected for legal and reasonable purposes and not shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after obtaining the informed consent of the user, including but not limited to notifying the user to read the user agreement / user notice and signing an agreement / authorization including authorizing relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others with access to the personal information data comply with their privacy policies and procedures.

[0184] The present application anticipates providing embodiments for users to selectively block the use or access of personal information data. That is, the present disclosure anticipates providing hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, the risk can be minimized by restricting data collection and deleting the data. In addition, when applicable, personal identifiers are removed from such personal information to protect the privacy of users.

[0185] In the descriptions of the foregoing embodiments, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0186] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0187] Any process or method description in a flowchart or described in other ways herein may be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a customized logic function or process, and the scope of the preferred embodiments of the present application includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0188] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or used in combination with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection portion having one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then storing it in a computer memory.

[0189] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0190] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of implementing the above embodiments can be completed by a program instructing relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0191] In addition, each functional unit in various embodiments of the present application may be integrated into a processing module, may exist separately physically for each unit, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0192] The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A microseismic event location method, characterized in that Including: Based on a first spacing, performing network partitioning on a first target area to obtain a plurality of first grid points, where the first target area contains microseismic events; Determining a first coherence value corresponding to each of the first grid points; Based on the first coherence value, determining zero points and reference grid points among the plurality of first grid points; When the first spacing is greater than or equal to a spacing threshold, determining a second target area based on the distance between the reference grid point and the zero point, where the second target area is smaller than the first target area; Based on a reference calculation time and the second target area, determining a second spacing; Based on the second spacing and the second target area, returning to execute the step of performing network partitioning on the second target area, repeating the iteration until it is determined that any spacing is less than the spacing threshold, and determining the zero point among all grid points corresponding to the any spacing as the location of the microseismic event.

2. The method according to claim 1, characterized in that The determining a first coherence value corresponding to each first grid point includes: Traversing all geophones in the first target area to determine a plurality of geophone pairs; According to the waveform data received by each geophone, calculating a second coherence value for each geophone pair; Based on the earthquake occurrence time and the coordinates of each first grid point, superimposing the second coherence value to obtain a first coherence value corresponding to each first grid point.

3. The method according to claim 2, characterized in that, There are multiple earthquake occurrence times, and the superimposing the second coherence value based on the earthquake occurrence time and the coordinates of each first grid point to obtain a first coherence value corresponding to each first grid point includes: Based on each earthquake occurrence time and the coordinates of a first grid point, respectively superimposing the second coherence value to obtain a third coherence value of the first grid point at each earthquake occurrence time; Determining the maximum value among the third coherence values as the first coherence value corresponding to the first grid point.

4. The method according to claim 1, wherein The determining zero points and reference grid points among the plurality of first grid points based on the first coherence value includes: Determining the first grid point corresponding to the maximum first coherence value as the zero point; Determining the first grid points corresponding to the first coherence values greater than a preset quantile threshold as reference grid points.

5. The method according to claim 1, characterized in that, Before determining the second target area based on the distance between the reference grid point and the zero point, it further includes: Determining the distances of the reference grid point in each target direction of the zero point, where there are three target directions and they are perpendicular to each other.

6. The method according to claim 5, wherein The determining the second target area based on the distance between the reference grid point and the zero point includes: According to the distance distribution in any target direction, calculating the probability density function of the any target direction; According to the peak range of the probability density function, determining the search distance in the any target direction; Based on the zero point and the search distance, obtaining the search area corresponding to the any target direction; Determining the second target area from the search areas corresponding to all target directions.

7. The method according to claim 1, wherein The determining the second spacing based on the reference calculation time and the second target area includes: Based on the reference calculation time, determining the number of grid points for partitioning the second target area; Determine a second spacing based on the volume of the second target area and the number of grid points.

8. A microseismic event positioning device, characterized in that, Comprising: A partitioning module, configured to perform network partitioning on a first target area based on a first spacing to obtain a plurality of first grid points, wherein microseismic events are included in the first target area; A first determination module, configured to determine a first coherence value corresponding to each of the first grid points; A second determination module, configured to determine a zero point and a reference grid point among the plurality of first grid points according to the first coherence value; A third determination module, configured to determine a second target area based on the distance between the reference grid point and the zero point when the first spacing is greater than or equal to a spacing threshold, wherein the second target area is smaller than the first target area; A fourth determination module, configured to determine a second spacing based on a reference calculation time and the second target area; A processing module, configured to return and execute the step of performing network partitioning on the second target area based on the second spacing and the second target area, and repeat the iteration until it is determined that any spacing is less than the spacing threshold, and determine the zero point among all grid points corresponding to the any spacing as the position of the microseismic event.

9. An electronic device, characterized in that, Comprising: A processor and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the microseismic event location method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement the microseismic event location method according to any one of claims 1-7.

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