Earthquake positioning method, system, equipment and medium

Abstract

The invention provides an earthquake positioning method, system and device and a medium, relates to the technical field of earthquake positioning, and aims to relieve the technical problem of inaccurate positioning in the prior art. The method comprises the following steps: acquiring a target seismic signal, and determining each target station receiving the target seismic signal; performing pairwise non-repeated combination on all the target stations to obtain each station pair, and determining the correlation intensity and observed time difference of each station pair relative to the target seismic signal based on the waveform amplitude of the target seismic signal and when the target seismic signal of each station pair is observed; determining an equal time difference curved surface probability distribution function of each station pair based on the correlation intensity of each station pair relative to the target seismic signal and the observed time difference; and determining the position of the target seismic signal based on the equal time difference curved surface probability distribution function of each station pair, so as to improve the accuracy and reliability of positioning the seismic position.

Description

Technical Field

[0001] The present invention relates to the technical field of earthquake positioning, and in particular to an earthquake positioning method, system, equipment and medium. Background Art

[0002] Earthquake location is a classic and fundamental issue in seismology. For large-scale destructive natural earthquakes, quickly and accurately locating the earthquake's location is crucial for earthquake early warning, earthquake disaster assessment, earthquake rescue and hazard assessment. For small-scale microearthquakes, microseismic source information can reflect the location of rock rupture and stress state, and has important application value in safe mining, shale gas fracturing effect evaluation and landslide early warning.

[0003] Currently, the existing earthquake positioning technologies mainly include two methods: one based on arrival time picking and the other based on station equal difference of time (EDT) surface. Among them, the method based on arrival time picking is simple and efficient, but it is sensitive to abnormal data and will lead to inaccurate positioning results; the positioning method based on EDT surface improves the noise resistance of positioning, but there may be multiple areas with the same maximum number of crossings, resulting in a decrease in positioning accuracy and an increase in the difficulty of positioning search. Summary of the invention

[0004] In view of this, an object of the present invention is to provide an earthquake locating method, system, device and medium to improve the accuracy and reliability of locating earthquake positions.

[0005] In a first aspect, the present invention provides an earthquake locating method, comprising: Acquire target seismic signals and determine each target station that receives the target seismic signals; All target stations are combined in pairs without duplication to obtain station pairs. Based on the waveform amplitude of the target seismic signal and the time when the target seismic signal of each station pair is observed, the correlation strength and observed time difference of each station pair relative to the target seismic signal are determined. Based on the correlation strength and observed time difference of each station pair relative to the target seismic signal, the probability distribution function of the equal time difference surface of each station pair is determined; The location of the target seismic signal is determined based on the probability distribution function of the equal time difference surface of each station pair.

[0006] Optionally, determining the correlation strength and observed time difference of each station pair relative to the target seismic signal based on the waveform amplitude of the target seismic signal and the observed time of the target seismic signal of each station pair includes: Based on the waveform amplitude of the target seismic signal and the time window length of the station pair, the relative cross-correlation coefficient of each station pair is obtained; Based on the relative mutual correlation coefficient of each station pair, determine the correlation strength of each station pair relative to the target seismic signal; Based on the observation time of the target seismic signal of each station pair, the observed time difference of each station pair is determined.

[0007] Optionally, based on the correlation strength of each station pair relative to the target seismic signal and the observed time difference, determining the probability distribution function of the equal time difference surface of each station pair includes: Based on the observed time difference of each station pair and the hypocenter position of the target seismic signal, the residual of the observed time difference of each station pair and the hypocenter position is determined; Based on the correlation strength and residual of each station pair, the probability distribution function of the equal time difference surface of each station pair is determined.

[0008] Optionally, determining the position of the target seismic signal based on the equal time difference surface probability distribution function of each station pair includes: The probability distribution functions of the equal time difference surfaces of all station pairs are grouped; The probability distribution function of the equal time difference surface in each group is processed to obtain the probability distribution of target positioning imaging; Based on the target positioning imaging probability distribution, the location of the target earthquake is determined.

[0009] Optionally, the probability distribution function of the equal time difference surface in each group is processed to obtain the target positioning imaging probability distribution, including: The probability distribution functions of the equal time difference surfaces in each group are added together to obtain the positioning imaging probability distribution of each group; The positioning and imaging probability distributions of each component are multiplied to obtain the target positioning and imaging probability distribution.

[0010] Optionally, determining the position of the target seismic signal based on the target positioning imaging probability distribution includes: The target positioning imaging probability distribution is searched to determine the maximum value position of the target positioning imaging probability distribution; wherein the maximum value position of the target positioning imaging probability distribution is the position of the target earthquake.

[0011] Optionally, the method further comprises: Based on the reliability function, the accuracy of the location of the target seismic signal is determined.

[0012] In a second aspect, the present invention provides a seismic positioning system, comprising: An acquisition module, used to acquire a target seismic signal and determine each target station that receives the target seismic signal; A calculation module is used to combine all target stations in pairs without duplication to obtain each station pair, and determine the correlation strength and observed time difference of each station pair relative to the target seismic signal based on the waveform amplitude of the target seismic signal and the time when the target seismic signal of each station pair is observed; A construction module is used to determine the probability distribution function of the equal time difference surface for each station pair based on the correlation strength and observed time difference of each station pair relative to the target seismic signal; The positioning module is used to determine the location of the target seismic signal based on the probability distribution function of the equal time difference surface of each station pair.

[0013] In a third aspect, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the above-mentioned earthquake locating method is implemented when the processor executes the computer program.

[0014] In a fourth aspect, the present invention further provides a computer-readable storage medium storing machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions prompt the processor to execute the above-mentioned earthquake positioning method.

[0015] An earthquake positioning method, system, device and medium provided by an embodiment of the present invention obtain a target earthquake signal and determine each target station that receives the target earthquake signal; all target stations are combined in pairs without duplication to obtain each station pair, and based on the waveform amplitude of the target earthquake signal and the target earthquake signal of each station pair, the correlation strength and observed time difference of each station pair relative to the target earthquake signal are determined; based on the correlation strength and observed time difference of each station pair relative to the target earthquake signal, the probability distribution function of the equal time difference surface of each station pair is determined; based on the probability distribution function of the equal time difference surface of each station pair, the position of the target earthquake signal is determined to improve the accuracy and reliability of the earthquake positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A flow chart of an earthquake locating method provided by an embodiment of the present invention is shown; Figure 2 A schematic diagram of the structure of a three-dimensional monitoring network provided by an embodiment of the present invention is shown; Figure 3 A schematic diagram of the locations of two seismic sources S1 and S2 provided in an embodiment of the present invention is shown; Figure 4 A schematic diagram of a synthetic waveform of a microseismic event at a source S1 in a model provided by an embodiment of the present invention is shown; Figure 5 A schematic diagram of a synthetic microseismic waveform of a seismic signal R1 containing high-intensity noise at a source S1 provided by an embodiment of the present invention is shown; Figure 6 A schematic diagram showing the first arrival time picked up according to the maximum position of the automatic picking curve of the de-noised seismic signal R1 at the earthquake source S1 provided by an embodiment of the present invention; Figure 7 A schematic diagram of an automatic picking curve of a denoised seismic signal R1 at a seismic source S1 provided by an embodiment of the present invention is shown; Figure 8 A schematic diagram showing a probability imaging positioning result of a seismic signal R1 at a seismic source S1 provided by an embodiment of the present invention in an additive form is shown; Fig. 9 A schematic diagram showing a probability imaging positioning result of a seismic signal R1 at a seismic source S1 in a multiplied form provided by an embodiment of the present invention is shown; Fig.10 A schematic diagram showing the probability imaging positioning result of the seismic signal R1 at the source S1 provided by an embodiment of the present invention in the form of group addition and multiplication is shown; Fig.11 A schematic diagram showing the distribution of geophones for microseismic monitoring in a mine and the relative positions of seven blasting events provided by an embodiment of the present invention; Fig.12 A schematic diagram showing the waveform and first arrival time of No. 3 blasting event provided by an embodiment of the present invention is shown; Fig.13 A schematic diagram showing a comparison of blasting event location errors obtained by using addition, multiplication, and group superposition and multiplication provided by an embodiment of the present invention; Fig.14 A schematic diagram showing the probability imaging positioning result of the No. 3 blasting event in the addition form provided by an embodiment of the present invention; Fig.15 A schematic diagram showing the probability imaging positioning result of the No. 3 blasting event in a multiplication form provided by an embodiment of the present invention; Fig.16 A schematic diagram showing the probability imaging positioning result of the No. 3 blasting event in the form of group addition and multiplication provided by an embodiment of the present invention; Fig.17 A schematic diagram showing the actual mine microseismic event location distribution in the addition form provided by an embodiment of the present invention; Fig.18 A schematic diagram showing the actual mine microseismic event location distribution in a multiplication form provided by an embodiment of the present invention; Fig.19 A schematic diagram showing the actual distribution of microseismic event locations in a mine in the form of group addition and multiplication provided by an embodiment of the present invention; Fig. 20 A schematic diagram showing the comparison between the time residual obtained by using the addition and multiplication and the grouping superposition and multiplication forms and the reliability of the positioning result provided by the embodiment of the present invention; Fig.21 It shows a schematic diagram of the relocation result of data when the picking error is too large provided by an embodiment of the present invention; Fig. 22 A schematic structural diagram of an electronic device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0019] In order to facilitate those skilled in the art to better understand the present application, the technical terms involved in the present application are briefly introduced below.

[0020] A station is a station that receives seismic wave signals from the earth's interior through sensors and converts physical vibrations into electrical signals; a station pair is a non-repetitive combination of all stations receiving seismic signals, with two stations forming a station pair; the correlation strength is a measure of the similarity of the waveforms of two seismic signals; the observed time difference is the time delay between the seismic waveforms received by the two stations.

[0021] After introducing the technical terms involved in this application, the technical solutions provided by this application are described in detail.

[0022] Figure 1 A schematic diagram of a flow chart of an earthquake positioning method provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the method comprises at least the following steps: Step S110: Acquire the target seismic signal, and determine each target station that receives the target seismic signal.

[0023] In this application, synthetic data is used to test the application effect of the earthquake location method in this application. First, Figure 2 As shown in the figure, a 300m×300m×300m three-dimensional monitoring network is set up, with a detector arranged in each of the eight corners to receive seismic event signals (i.e., target earthquake signals) with an isotropic uniform P wave velocity of 5 km / s. This layout is more common in actual mine microseismic monitoring. Figure 3 As shown in the figure, two seismic sources are set up at the same time: source S1 is located inside the detector array with coordinates of (240, 240, 200) m; source S2 is located outside the detector array, and the monitoring azimuth is greater than 180°, with coordinates of (500, 60, 400) m. The purpose of setting the seismic sources is to test the impact of the observation system on the earthquake location probability results.

[0024] Figure 4 The synthetic waveform of the microseismic event of the model is obtained by convolution of the source wavelet and the transmission coefficient sequence. The source wavelet adopts an exponentially decaying sine wave with a main frequency of 150 Hz, and the received waveform amplitude decays with the source distance. Therefore, the maximum amplitude of the seismic signal received by each detector is inconsistent, and the maximum amplitude value is 1.

[0025] In order to simulate the situation where there are multiple outliers in the first arrival picking data, high-intensity noise with a mean of 0 and a variance ranging from 0 to 1 is added to the noise-free waveform record, such as Figure 5 The synthetic microseismic waveform with high-intensity noise is shown in Figure 1. In this case, the microseismic signals on most geophones are seriously contaminated by noise, making the signals difficult to identify. After preprocessing, the denoised microseismic signals gradually appear, as shown in Figure 1. Figure 6 As shown, the difficulty of automatic picking at the first arrival is effectively reduced. Figure 7 The maximum position of the automatic first arrival picking curve is shown, and the Figure 6 The first arrival time of the microseismic signal on each geophone. It can be seen that except for the No. 1 geophone of the earthquake event E1 and the No. 3, 4, and 5 geophones of S2, the first arrival automatic picking results of other geophones are close to the theoretical first arrival time. Among them, the picking errors of the earthquake events E1 and E2 on each geophone show that the picking errors of the No. 1 and No. 7 geophones of the microseismic event MS1 and the No. 3, 4, and 5 geophones of MS2 are 0.142 s, 0.013 s, 0.089 s, 0.187 s, and 0.387 s, respectively. These are all abnormal values ​​with large picking errors in the first arrival picking results.

[0026] It should be noted that, in the present application, the earthquake event occurring at source S1 is E1. According to the magnitude of the earthquake, the earthquake event E1 is determined to be a microseismic event MS1. The earthquake signal generated by the earthquake event occurring at source S1 is R1.

[0027] Step S120: All target stations are combined in pairs without duplication to obtain station pairs, and based on the waveform amplitude of the target seismic signal and the time when the target seismic signal of each station pair is observed, the correlation strength and observed time difference of each station pair relative to the target seismic signal are determined.

[0028] Among them, determine whether the number of target stations is an even number. If not, perform elimination processing. The elimination processing can be judged based on the strength of the received target seismic signal, and the station with the weakest target seismic signal strength will be eliminated. It can also be based on the time when the target station receives the target seismic signal, and the station that takes the longest time to receive the target seismic signal will be eliminated.

[0029] Furthermore, all target stations are combined in pairs without duplication to obtain station pairs, and the target seismic signals received by all target stations are preprocessed by bandpass filtering.

[0030] In an optional embodiment, in step S120, based on the waveform amplitude of the target seismic signal and the observed time difference of the target seismic signal of each station pair, the correlation strength and the observed time difference of each station pair relative to the target seismic signal are determined, including: Based on the waveform amplitude of the target seismic signal and the time window length of the station pair, the relative cross-correlation coefficient of each station pair is obtained; Based on the relative mutual correlation coefficient of each station pair, determine the correlation strength of each station pair relative to the target seismic signal; Based on the observation time of the target seismic signal of each station pair, the observed time difference of each station pair is determined.

[0031] Furthermore, the relative correlation coefficient of each station pair can be obtained by the following formula:

[0032] In the formula, For station pairs and At the sampling point The mutual correlation coefficient at is the time window length for cross-correlation calculation, For earthquake At the sampling point The waveform amplitude at For earthquake At the sampling point The amplitude of the waveform at .

[0033] Furthermore, according to the absolute maximum value and position of the mutual correlation coefficient of the station pair, the correlation strength and observed time difference data of the corresponding station to the target seismic signal waveform are obtained, where The maximum value of The corresponding time is , then the correlation strength of the seismic signal waveform of the station pair is and the observed time difference It can be expressed as:

[0034]

[0035] In the formula, and Station pairs and When the earthquake signal is observed.

[0036] Step S130: Determine the probability distribution function of the equal time difference surface of each station pair based on the correlation strength of each station pair relative to the target seismic signal and the observed time difference.

[0037] In an optional embodiment, in step S130, based on the correlation strength of each station pair relative to the target seismic signal and the observed time difference, the probability distribution function of the equal time difference surface of each station pair is determined, including: Based on the observed time difference of each station pair and the hypocenter position of the target seismic signal, the residual of the observed time difference of each station pair and the hypocenter position is determined; Based on the correlation strength and residual of each station pair, the probability distribution function of the equal time difference surface of each station pair is determined; where the probability distribution function of the equal time difference surface is:

[0038] In the formula, The earthquake source location is The probability distribution function of the equal time difference surface, is the tolerance parameter, The time difference between the observed station pair and the earthquake source position is The residual at is the correlation strength of the seismic signal waveforms of the station pair.

[0039] Step S140: Determine the position of the target seismic signal based on the equitime surface probability distribution function of each station pair.

[0040] In an optional embodiment, in step S140, determining the position of the target seismic signal based on the equal time difference surface probability distribution function of each station pair includes: The probability distribution functions of the equal time difference surfaces of all station pairs are grouped; The probability distribution function of the equal time difference surface in each group is processed to obtain the probability distribution of target positioning imaging; Based on the target positioning imaging probability distribution, the location of the target earthquake is determined.

[0041] Among them, the probability distribution function of the equal time difference surface in each group is processed to obtain the target positioning imaging probability distribution, including: The probability distribution functions of the equal time difference surfaces in each group are added together to obtain the positioning imaging probability distribution of each group; The positioning and imaging probability distributions of each component are multiplied to obtain the target positioning and imaging probability distribution.

[0042] Wherein, based on the target positioning imaging probability distribution, determining the position of the target seismic signal includes: The target positioning imaging probability distribution is searched to determine the maximum value position of the target positioning imaging probability distribution; wherein the maximum value position of the target positioning imaging probability distribution is the position of the target seismic signal.

[0043] Specifically, firstly, the probability distribution functions of the equal time difference surfaces of all station pairs are reasonably grouped, for example, they can be grouped according to the relative positions between the station pairs, or according to the characteristics of the target seismic signals recorded by each station pair, or they can be grouped automatically using a machine learning algorithm; Secondly, the probability distribution functions of the equal time difference surfaces in each group are added together to obtain the positioning imaging probability part of each group, and the positioning imaging probability distribution of each component is multiplied to obtain the target positioning imaging probability distribution, where the target positioning imaging probability distribution expression is:

[0044]

[0045] in, For location The probability distribution of target positioning imaging at For all station pairs divided into Groups, For the Groups at location The probability distribution of positioning imaging at For the There are a total of The probability distribution function of the equal time difference surface of the station pairs is: For the In the group Station pairs at locations The probability distribution function of the equal time difference surface corresponding to the location; Then, the maximum position of the target positioning imaging probability distribution is searched to obtain the position of the target seismic signal, wherein randomized search methods such as simulated annealing, genetic algorithm, particle swarm optimization and ant colony algorithm can be used to find the maximum position in the target positioning imaging probability distribution.

[0046] further, Figure 8 The location probability imaging results are added, multiplied and grouped and superimposed in the multiplied form. The distribution of the added location probability imaging results and the true source position can be seen, among which, Figure 8 The "cross" in the figure is the calculated source position in the YX plane, YZ plane and ZX plane, and the intersection of the dotted lines is the real source position in the YX plane, YZ plane and ZX plane. Due to the influence of multiple outliers, obvious and serious stripe artifacts appear in the stacked imaging results. Fig. 9 is the probability imaging positioning result in the multiplication form, where Fig. 9 The "cross" in the figure is the calculated location of the earthquake source in the YX plane, YZ plane and ZX plane, and the intersection of the dotted lines is the location of the real earthquake source in the YX plane, YZ plane and ZX plane. Fig. 9 It can be seen that the multiplication of the positioning probability imaging results in a large positioning error. Although the multiplication form successfully eliminates the superimposed fringe artifacts and improves the resolution of the probability imaging, the probability maximum value fails to concentrate on the true source position, which still leads to a large positioning error. Fig.10 is the probability imaging positioning result in the form of group addition and multiplication, where Fig.10 The "cross" in the figure is the calculated location of the earthquake source in the YX plane, YZ plane and ZX plane, and the intersection of the dotted lines is the location of the real earthquake source in the YX plane, YZ plane and ZX plane. Fig.10 It can be clearly seen that the group stacking and multiplication form not only successfully eliminates the stacking fringe artifacts and improves the imaging resolution, but also makes the maximum value of the positioning probability concentrated near the theoretical source position, and the positioning error is minimized. This is because the variable Gaussian probability distribution function has a slow attenuation effect on the first arrival time data with large picking errors, which can make the potential true source position obtain a relatively high probability value, so that the group stacking and multiplication form can obtain a stable positioning result with excellent imaging resolution and positioning accuracy.

[0047] It should be noted that Figure 8 , Fig. 9 and Fig.10 The hypocenter location calculated in is the hypocenter location under Normalized probability.

[0048] In an optional embodiment, the method further comprises the following steps: Based on the reliability function, the accuracy of the location of the target seismic signal is determined.

[0049] The reliability function is:

[0050] In the formula, To ensure the accuracy of the positioning results, To meet the station and The residual difference between the observed time difference and the arrival time difference is less than the tolerance The number of station pairs, is a function, is the number of all station pairs.

[0051] further, is a symbolic function representing 1 if it is, 0 otherwise.

[0052] In order to ensure the accuracy of the location of the target seismic signal, the accuracy of the location of the target seismic signal is verified by a reliability function, where: The accuracy value varies between 0 and 1. The larger the value, the more accurate the positioning result.

[0053] like Fig.11 As shown, the microseismic monitoring network of a metal mine provided in the embodiment of the present application includes 41 single-component geophones arranged in tunnels at altitudes of 75 m, 35 m, and -5 m. According to the data recorded by the BSN system, 7 mining blasts were carried out in the mine area between March 26 and March 31, 2021. The relative positions of the blasting events and geophones are as follows: Fig.11 The inverted triangle in the figure is the detector, and the hexagon is the explosion event. Fig.12 The original waveform of the No. 3 blasting event and the automatically picked first arrival time show that the waveform consistency between the detectors is low. The velocity model of the mining area was determined by the exploration geologist to be a uniform P-wave velocity of 4908 m / s.

[0054] According to the suggestions of the on-site microseismic monitoring technicians and the actual location of the blasting event, the target area range of the positioning imaging is set to: -100 m to 700 m in the X direction, -100 m to 700 m in the Y direction, -200 m to 200 m in the Z direction, and the spatial step length is 10 m. According to the research area of ​​the mine, during the positioning process, the parameters in the probability distribution function Set to 0.005 s. By comparison Fig.13The positioning errors of the seven blasting events in different combinations are shown. It can be seen that the overall positioning error of the group superposition and multiplication form is the smallest, with an average positioning error of 24.53m and a minimum positioning error of only 8.3m. Specifically, although the No. 2 blasting event with the largest positioning error is 50.8m, this error is still much smaller than the positioning error of the addition and multiplication forms.

[0055] In order to compare the positioning probability imaging results of different probability distribution functions, the blasting events No. 6, No. 2, and No. 7 were selected in the order of blasting locations. Fig.14 The positioning probability imaging results in the additive form are shown. Due to the large number of detectors triggered by the blasting event, the positioning imaging probability distribution in the superposition form did not show obvious local probability maximum artifacts and topological structures, but there was a significant tailing phenomenon. From the positioning results of the No. 2 blasting event, it can be seen that since the azimuth angle of the detector in the XY plane is greater than 180° and the number of triggered detectors is relatively small, the positioning results have a large deviation in the XY plane. Although the multiplication form improves the convergence and resolution of positioning imaging, the positioning accuracy is still not significantly improved. Fig.15 However, the variable probability distribution function can obtain a higher probability value for the real blasting position by using the group superposition and multiplication form, and the error of the positioning result is the smallest, as shown in Fig.16 As shown, Fig.14 , Fig.15 and Fig.16 In the figure, the “cross” is the position of the calculated positioning result in the YX plane, YZ plane and ZX plane, and the intersection of the dotted lines is the position of the true source position in the YX plane, YZ plane and ZX plane.

[0056] These three probability distribution functions were used to locate 432 microseismic events measured in the mining area from March 30 to March 31, 2021. In order to ensure the quality of seismic event data, all events in the data set triggered more than 8 detectors. Through the above data preprocessing process, observation data such as the first arrival time and the corresponding signal-to-noise ratio of all microseismic events triggering the geophone were obtained. Due to the influence of the azimuth angle of some microseismic events relative to the triggered geophone greater than 180° and the arrival time data with large picking errors, the positioning results may be offset to the boundary of the target area. Therefore, the positioning results after excluding the microseismic events located at the boundary of the target area are defined as valid seismic events. Fig.17 The positioning results of adding fixed Gaussian distribution functions are shown; Fig.18 The positioning results of the addition and multiplication forms of fixed Gaussian distribution functions are shown, among which there are 338 and 279 effective earthquake events respectively. The source locations are relatively matched with the locations of blasting events and are distributed near the blasting locations, but the degree of aggregation is not high. Fig.19The variable Gaussian probability distribution function is displayed using the group superposition and multiplication form to obtain the positioning results, among which the number of effective earthquake events accounts for the highest proportion, 361 and 358 respectively; the matching degree between the source location and the blasting location is high, and the degree of aggregation is significantly higher than the positioning results of the addition and multiplication form. These results are helpful to further delineate the microseismic event aggregation area, evaluate the intensity of mine seismic activity, and provide certain guidance for on-site mining and safe production.

[0057] The reliability provided by this application is used to quantitatively calculate the positioning reliability of addition, multiplication, and group superposition and multiplication, and compared and analyzed with the positioning result travel time residual, such as Fig. 20 As shown. It can be seen that when the travel time residuals of most microseismic events are small, the reliability of the positioning results is high. The mean reliability of the positioning results of the variable Gaussian probability distribution function in the form of group superposition and multiplication is 0.7652, which is significantly higher than the addition and multiplication forms, indicating that more high-quality arrival time data are involved in the positioning of microseismic events. According to the positioning results of the method of the present invention, after removing the discrete data with large errors in the arrival time data, repositioning is performed, as shown in Fig.21 As shown in the figure, the relocated hypocenter locations are more concentrated, which is conducive to determining the intensity of seismic activity.

[0058] The earthquake location method provided by the present application has the following beneficial effects: 1. Through the correlation degree of waveform cross-correlation and the arrival time difference information corresponding to the maximum value of the cross-correlation coefficient of the station, when the waveform signal-to-noise ratio is high, the corresponding waveform correlation degree and arrival time difference accuracy are also high, and the width of the equal time difference surface is narrowed, showing a non-heavy-tailed distribution feature; when the signal-to-noise ratio is low, the corresponding waveform correlation degree and arrival time difference accuracy are also low, and the width of the equal time difference surface becomes wider, showing a heavy-tailed distribution feature, realizing the adaptive adjustment of the probability distribution function of the equal time difference surface, and automatically reducing the weight of low signal-to-noise ratio data in the objective function; 2. The target positioning imaging probability distribution is obtained in the form of grouping, that is, addition within the group and multiplication between groups. This can not only effectively suppress the local maximum of the positioning probability generated by superposition, but also improve the probability imaging resolution and positioning accuracy.

[0059] An embodiment of the present application provides a seismic positioning system, the system comprising: An acquisition module, used to acquire a target seismic signal and determine each target station that receives the target seismic signal; A calculation module is used to combine all target stations in pairs without duplication to obtain each station pair, and determine the correlation strength and observed time difference of each station pair relative to the target seismic signal based on the waveform amplitude of the target seismic signal and the time when the target seismic signal of each station pair is observed; A construction module is used to determine the probability distribution function of the equal time difference surface for each station pair based on the correlation strength and observed time difference of each station pair relative to the target seismic signal; The positioning module is used to determine the location of the target seismic signal based on the probability distribution function of the equal time difference surface of each station pair.

[0060] In an optional embodiment, the construction module is also used to: obtain the relative mutual correlation coefficient of each station pair based on the waveform amplitude of the target seismic signal and the time window length of the station pair; determine the correlation strength of each station pair relative to the target seismic signal based on the relative mutual correlation coefficient of each station pair; and determine the observed time difference of each station pair based on the time when the target seismic signal of each station pair is observed.

[0061] In an optional embodiment, the construction module is further used to: determine the residual of the observed time difference and the source position of each station pair based on the observed time difference of each station pair and the source position of the target seismic signal; determine the equal time difference surface probability distribution function of each station pair based on the correlation strength and residual of each station pair; wherein the equal time difference surface probability distribution function is:

[0062] In the formula, The earthquake source location is The probability distribution function of the equal time difference surface, is the tolerance parameter, The time difference between the observed station pair and the earthquake source position is The residual at is the correlation strength of the seismic signal waveforms of the station pair.

[0063] In an optional embodiment, the positioning module is also used to: group the equal time difference surface probability distribution functions of all station pairs; process the equal time difference surface probability distribution functions in each group to obtain the target positioning imaging probability distribution; and determine the location of the target earthquake based on the target positioning imaging probability distribution.

[0064] In an optional embodiment, the positioning module is also used to: add the equal time difference surface probability distribution functions in each group to obtain the positioning imaging probability distribution of each group; multiply the positioning imaging probability distribution of each component to obtain the target positioning imaging probability distribution.

[0065] In an optional embodiment, the positioning module is also used to: search for the target positioning imaging probability distribution, and determine the maximum value position of the target positioning imaging probability distribution; wherein the maximum value position of the target positioning imaging probability distribution is the position of the target earthquake.

[0066] In an optional embodiment, the positioning module is further used to determine the accuracy of the position of the target seismic signal based on the reliability function.

[0067] In an optional embodiment, the reliability function is:

[0068] In the formula, To ensure the accuracy of the positioning results, To meet the station and The residual difference between the observed time difference and the arrival time difference is less than the tolerance The number of station pairs, is a function, is the number of all station pairs.

[0069] The implementation principle and technical effects of the device provided in the embodiments of the present application are the same as those of the aforementioned method embodiments. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned method embodiments.

[0070] like Fig. 22 As shown, an electronic device 600 provided in an embodiment of the present application includes: a processor 601, a memory 602 and a bus, the memory 602 stores machine-readable instructions executable by the processor 601, when the electronic device is running, the processor 601 and the memory 602 communicate through the bus, and the processor 601 executes the machine-readable instructions to perform the steps of the above-mentioned earthquake positioning method.

[0071] Specifically, the memory 602 and the processor 601 can be general-purpose memories and processors, which are not specifically limited here. When the processor 601 runs the computer program stored in the memory 602, the earthquake locating method can be executed.

[0072] The processor 601 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 601 or the instructions in the form of software. The above processor 601 can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0073] Corresponding to the above-mentioned earthquake positioning method, an embodiment of the present application also provides a computer-readable storage medium, which stores machine-executable instructions. When the computer-executable instructions are called and executed by the processor, the computer-executable instructions prompt the processor to execute the steps of the above-mentioned earthquake positioning method.

[0074] The earthquake positioning system provided in the embodiment of the present application can be specific hardware on the device or software or firmware installed on the device. The device provided in the embodiment of the present application, its implementation principle and the technical effect produced are the same as those in the aforementioned method embodiment. For the sake of brief description, the parts not mentioned in the device embodiment can refer to the corresponding contents in the aforementioned method embodiment. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above can all refer to the corresponding processes in the aforementioned method embodiment, and will not be repeated here.

[0075] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0076] For another example, the flowchart and block diagram in the accompanying drawings show the possible architecture, functions and operations of the device, method and computer program product according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and a part of the module, program segment or code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0077] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0078] In addition, each functional unit in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0079] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable an electronic device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0080] Finally, it should be noted that the above embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the aforementioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the aforementioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application. They should all be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for earthquake location, characterized in that: include: Acquire a target seismic signal, and determine each target station that receives the target seismic signal; All the target stations are combined in pairs without duplication to obtain station pairs, and based on the waveform amplitude of the target seismic signal and the observed time of the target seismic signal of each station pair, the correlation strength and observed time difference of each station pair relative to the target seismic signal are determined; Determine the probability distribution function of the equal time difference surface of each station pair based on the correlation strength and observed time difference of each station pair relative to the target seismic signal; The position of the target seismic signal is determined based on the equal time difference surface probability distribution function of each station pair.

2. The earthquake locating method according to claim 1, characterized in that: Determining the correlation strength and observed time difference of each station pair relative to the target seismic signal based on the waveform amplitude of the target seismic signal and the observed time of the target seismic signal of each station pair, comprising: Based on the waveform amplitude of the target seismic signal and the time window length of the station pair, obtaining the relative mutual correlation coefficient of each of the station pairs; Determining the correlation strength of each station pair relative to the target seismic signal based on the relative mutual correlation coefficient of each station pair; Based on the observation times of the target seismic signals of each of the station pairs, the observed time difference of each of the station pairs is determined.

3. The earthquake locating method according to claim 2, characterized in that: Based on the correlation strength and observed time difference of each station pair relative to the target seismic signal, determining the equal time difference surface probability distribution function of each station pair, including: Based on the observed time difference of each of the station pairs and the hypocenter position of the target seismic signal, determining the residual of the observed time difference of each of the station pairs and the hypocenter position; Based on the correlation strength and the residual of each station pair, a probability distribution function of an equal time difference surface of each station pair is determined.

4. The earthquake locating method according to claim 3, characterized in that: Determining the position of the target seismic signal based on the equal time difference surface probability distribution function of each station pair includes: Grouping the equal time difference surface probability distribution functions of all the station pairs; Processing the probability distribution function of the equal time difference surface in each group to obtain the probability distribution of target positioning imaging; Based on the target positioning imaging probability distribution, the position of the target earthquake is determined.

5. The earthquake locating method according to claim 4, characterized in that: The probability distribution function of the equal time difference surface in each group is processed to obtain the target positioning imaging probability distribution, including: Adding the equal time difference surface probability distribution functions in each group to obtain the positioning imaging probability distribution of each group; The positioning imaging probability distribution of each component is multiplied to obtain the target positioning imaging probability distribution.

6. The earthquake locating method according to claim 5, characterized in that: Determining the position of the target seismic signal based on the target positioning imaging probability distribution includes: The target positioning imaging probability distribution is searched to determine the maximum value position of the target positioning imaging probability distribution; wherein the maximum value position of the target positioning imaging probability distribution is the position of the target earthquake.

7. The earthquake locating method according to claim 1, characterized in that: Also includes: Based on the reliability function, the accuracy of the location of the target seismic signal is determined.

8. An earthquake positioning system, characterized in that: include: An acquisition module, used to acquire a target seismic signal and determine each target station that has received the target seismic signal; A calculation module, used for combining all the target stations in pairs without duplication to obtain each station pair, and determining the correlation strength and observed time difference of each station pair relative to the target seismic signal based on the waveform amplitude of the target seismic signal and the observed time of the target seismic signal of each station pair; A construction module, for determining a probability distribution function of an equal time difference surface of each station pair based on the correlation strength and observed time difference of each station pair relative to the target seismic signal; A positioning module is used to determine the position of the target seismic signal based on the equal time difference surface probability distribution function of each station pair.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions prompt the processor to execute the method according to any one of claims 1 to 7.

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