CN115327617A - Micro-seismic source rapid convergence and high-precision positioning method - Google Patents
Micro-seismic source rapid convergence and high-precision positioning method Download PDFInfo
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Abstract
The invention provides a method for quickly converging and positioning a microseismic source, and belongs to the technical field of mine microseismic monitoring. The method for quickly converging and positioning the micro seismic source comprises the steps of (1) arranging a micro seismic monitoring sensor in a mine monitoring area, and measuring coordinates of the micro seismic monitoring sensor; (2) Carrying out two times of blasting tests in the monitoring area range to determine the average wave velocity of the rock mass in the monitoring area range; (3) A micro seismic source positioning target function is established by combining a time window energy ratio method and an AIC method to pick up the arrival time of a P wave; (4) And calculating the coordinate position of the microseismic source by using a self-adaptive artificial bee colony algorithm. The method has high positioning precision on the micro seismic source, and can promote the application of the micro seismic monitoring technology in engineering practice.
Description
Technical Field
The invention relates to the technical field of mine micro-seismic monitoring, in particular to a method for quickly converging and positioning a micro-seismic source at high precision.
Background
With the rapid development of economic society, the demand of China on mineral resources is continuously increased, and the current domestic shallow mineral resources are gradually exhausted, the mining depth is increased, so that the problem of mine ground pressure is gradually highlighted, the rock body dynamic disasters such as roof caving, pillar caving and the like occur in mining, meanwhile, the border-crossing mining activity of surrounding mines exists, and the stability of a rock structure system is not influenced by mining operation. The microseismic monitoring technology is an important means for ensuring the safe production in the mining process of a mine. The microseismic monitoring technology is one of the effective methods which are acknowledged in the industry and can monitor the stability of the ore rock in the process of mine exploitation and tunneling, and the method utilizes a sensor to receive elastic waves generated by the fracture of the mine rock mass, analyzes and obtains the time, space, intensity, seismic source mechanism and other related information of a microseismic event, and monitors and warns the deep mine disasters. Compared with the traditional rock mass monitoring technology, the micro-seismic monitoring technology can realize remote, full-area, real-time and dynamic monitoring, and has the advantages of analyzing the rock mass destruction trend, the unstable body position, early warning and the like.
Currently, the primary method of microseismic source localization is the inversion method. The method is characterized in that the seismic source detection detector receives the seismic source first arrival time to invert the position of the seismic source, and the inversion method comprises 2 types of non-heuristic methods and heuristic methods. Non-heuristic methods mainly include newton methods, quasi-newton methods, gradient descent methods, and the like. Although the non-heuristic method can improve the positioning accuracy of the seismic source through certain improvement, the problems of complex derivative solution, local search, low convergence speed and the like exist, the error position is easily positioned, and the positioning accuracy is poor. Therefore, the heuristic method is the mainstream method of the current research, and mainly comprises a simulated annealing method, a simplex method, a genetic algorithm, a particle swarm optimization algorithm and the like. However, the simulated annealing method, the simplex method, the genetic algorithm and the particle swarm optimization algorithm have the disadvantages that the search capability is gradually reduced when iterative computation is carried out, the convergence speed is low, the computation accuracy is low, and local optimization is easily caused. Therefore, a method for fast convergence and high-precision positioning of the micro seismic sources is needed.
Disclosure of Invention
The invention aims to provide a method for quickly converging and positioning a micro seismic source, which can simply, quickly and effectively identify the micro seismic time and accurately pick up the arrival of P waves, has high positioning accuracy on the micro seismic source, meets the requirements of the existing engineering, and promotes the micro seismic monitoring technology to better play the roles of prediction and early warning in engineering practice.
In order to realize the purpose of the invention, the invention adopts the following technical scheme:
according to one aspect of the invention, a method for fast convergence and high-precision positioning of a micro seismic source is provided. The method for rapidly converging and positioning the micro seismic source with high precision comprises the following steps:
(1) Installing a microseismic monitoring sensor:
installing m micro-seismic monitoring sensors in the rock mass area to be monitored, and measuring the space seats of all the micro-seismic monitoring sensorsSubject to the standard that
The coordinate of each microseismic monitoring sensor is
Wherein m is more than or equal to 4,m microseismic monitoring sensors which are distributed in a space net structure;
(2) Acquiring arrival time of a P wave;
(3) Establishing a micro seismic source positioning objective function:
assuming that the rock mass is homogeneous and homogeneous, the wave velocity of the P wave is kept unchanged, and establishing a travel time equation:
in the formula:
suppose thatkThe theoretical moment of P wave picked up by each microseismic monitoring sensor is as follows:
first, thekIs first and seconduThe theoretical arrival time difference of each microseismic monitoring sensor is as follows:
the microseismic location objective function can be expressed as:
in the formula:
the minimum value calculated by the formula (4) is the coordinate value of the micro seismic source;
(4) Initialization of honey sources
Initializing honey source according to formula (5), and calculating fitness value according to formula (6)
Wherein, in the step (A),
in the formula:
dis the dimension of the honey source, wherein,d=1，2，3，4；
(5) And (3) updating and searching new honey sources:
employing bees to search for new honey sources in the vicinity of the honey sources using equation (8) with an adaptive search strategy;
in the formula:
maxcycleis the maximum cycle number;
formula (7) the conventional honey source search formula is known from formula (9): at the beginning of the cycle, the cycle is started,
at the moment, the formula (8) is mainly based on the traditional honey source searching formula (7), so that the strong exploration capacity can be kept, as the searching is carried out, each honey source gradually approaches, and the neighborhood range gradually decreases; finally, the greedy algorithm is utilized to compare the adaptive values of the new and old honey sources, and the one with the smallest adaptive value is selected as the superior one;
(6) Probability of hiring bees to choose to observe bees:
in the formula:
NPnumber of honey sources；
Randomly generating a random number between 0 and 1, comparing the random number with the probability calculated by the formula (10), and when the generated random number is less than the probability
Selecting the corresponding hiring bee as an observation bee, and performing neighborhood search by using a formula (8);
(7) Bee detection stage
The honey source has a parameter trim, when the new honey source is better than the current honey source, the honey source update is preserved, and trail =0; otherwise, if the current honey source is reserved, trail = trail +1 so as to count the times that the current honey source is not updated;
when the trail value of a honey source exceeds the preset threshold limit, the honey source needs to be abandoned, the scout bee stage is started, and in the scout bee stage, the scout bee randomly searches a new honey source by using a formula (5) to replace the abandoned honey source.
According to one embodiment of the invention, the picking of the arrival time of the P wave of the micro-seismic event is carried out based on a time window energy ratio method and an AIC method;
and constructing a micro seismic source positioning target function based on an adaptive artificial bee colony algorithm.
According to an embodiment of the invention, the microseismic source coordinate calculation is carried out by utilizing an adaptive artificial bee colony algorithm in combination with the acquired P wave arrival time and microseismic monitoring sensor coordinate positions so as to search the microseismic source coordinate with the minimum travel time residual error in a three-dimensional space.
According to an embodiment of the present invention, in the scout bee stage, the fitness value is further calculated by formula (6), and the minimum fitness value is saved.
One embodiment of the present invention has the following advantages or benefits:
the method for quickly converging and positioning the micro seismic source quickly can simply, quickly and effectively identify the micro seismic time and accurately pick up the P wave arrival, has high positioning precision on the micro seismic source, meets the requirements of the existing engineering, and promotes the micro seismic monitoring technology to better play the roles of prediction and early warning in engineering practice.
Drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
FIG. 1 is a flow chart illustrating a method for micro-seismic source fast convergence and high-precision localization according to an exemplary embodiment.
Fig. 2 is a diagram illustrating the results of P-wave arrival times picked up based on the time window energy ratio method and the AIC method according to an exemplary embodiment.
FIG. 3 is a schematic diagram illustrating a sensor mounting location according to an exemplary embodiment.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus a detailed description thereof will be omitted.
The terms "a", "an", "the", "said" are used to indicate the presence of one or more elements/components/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. other than the listed elements/components/etc.
As shown in fig. 1 to fig. 3, fig. 1 is a flowchart illustrating a method for fast convergence and high-precision positioning of a micro seismic source according to the present invention. Fig. 2 shows a result diagram of P-wave arrival times picked up based on the time window energy ratio method and the AIC method provided by the invention. Fig. 3 shows a schematic diagram of the installation position of the sensor provided by the invention.
The method for rapidly converging and positioning the micro seismic source with high precision comprises the following steps:
(1) Installing a microseismic monitoring sensor:
m microseismic monitoring sensors are arranged in the area to be monitored, and the area to be monitored is measuredSpatial coordinates of the microseismic monitoring sensor will beiThe coordinate of each microseismic monitoring sensor is
Wherein m is more than or equal to 4,m microseismic monitoring sensors which are distributed in a space net structure;
(2) Acquiring arrival time of a P wave;
(3) Establishing a micro seismic source positioning objective function:
assuming that the rock mass is homogeneous and homogeneous, the wave velocity of the P wave is kept unchanged, and establishing a travel time equation:
in the formula:
suppose thatkThe theoretical moment of P wave picked up by each microseismic monitoring sensor is as follows:
first, thekIs first and seconduThe theoretical arrival time difference of each microseismic monitoring sensor is as follows:
the microseismic location objective function can be expressed as:
in the formula:
the minimum value calculated by the formula (4) is the coordinate value of the micro seismic source;
(4) Initialization of honey sources
Initializing honey source according to formula (5), and calculating fitness value according to formula (6)
Wherein, in the step (A),
in the formula:
dis the dimension of the honey source, wherein,d=1，2，3，4；
(5) Updating and searching new honey sources:
employing bees to search for new honey sources in the vicinity of the honey sources using equation (8) with an adaptive search strategy;
in the formula:
maxcycleis the maximum cycle number;
equation (7) the conventional honey source search equation consisting ofAs can be seen from equation (9): at the beginning of the cycle, the cycle is started,
at the moment, the formula (8) is mainly based on the traditional honey source searching formula (7), so that the strong exploration capability can be kept, as the searching is carried out, each honey source gradually approaches, and the neighborhood range gradually decreases; finally, the greedy algorithm is utilized to compare the adaptive values of the new and old honey sources, and the minimum adaptive value is selected as the optimal value;
(6) Probability of hiring bees to choose to observe bees:
in the formula:
NPthe number of honey sources;
randomly generating a random number between 0 and 1, comparing the random number with the probability calculated by the formula (10), and when the generated random number is less than the probability
Selecting the corresponding hiring bee as an observation bee, and performing neighborhood search by using a formula (8);
(7) Bee detection stage
The honey source has a parameter trim, when the new honey source is better than the current honey source, the honey source update is preserved, and trail =0; on the contrary, if the current honey source is reserved, trail = trail +1 so as to count the times that the current honey source is not updated;
when the trail value of a honey source exceeds the preset threshold limit, the honey source needs to be abandoned, the scout bee stage is started, and in the scout bee stage, the scout bee randomly searches a new honey source by using a formula (5) to replace the abandoned honey source.
In a preferred embodiment of the invention, the picking of the arrival time of the P wave of the microseism event is carried out based on a time window energy ratio method and an AIC method; and constructing a micro seismic source positioning target function based on the self-adaptive artificial bee colony algorithm.
And calculating the micro seismic source coordinate by using a self-adaptive artificial bee colony algorithm by combining the acquired P wave arrival time and the sensor coordinate position so as to search the micro seismic source coordinate with the minimum travel time residual error in the three-dimensional space.
In the bee investigation stage, the fitness value is also calculated through the formula (6), and the obtained minimum fitness value is stored.
The time window energy ratio method has the advantages of simplicity, directness, effectiveness and the like in the aspect of identifying the microseism event, but the selection of the size of the time window has larger influence on the wave arrival time pickup; the AIC method is an Akaike information criterion rule, can accurately pick up the arrival time of the micro-seismic event, but cannot identify the micro-seismic event. The method has the advantages that the time window energy ratio method and the AIC method are combined to pick up the arrival time of the P wave of the microseism event, the advantages of the two methods can be combined, the arrival time can be rapidly identified, and the method has the advantages of being simple, direct, rapid, accurate and effective.
In addition, the artificial bee colony algorithm simulates the actual bee honey collection mechanism to solve the engineering problem. Artificial bee colonies are generally divided into three categories: hiring bees, observing bees, and reconnaissance bees. The bees are hired and observed for exploiting the honey sources, and the bees are detected to avoid the shortage of the honey source types. The solution of the optimization problem and the corresponding function value are abstracted into the position of the honey source and the number of nectar. The process of finding the optimal honey source is as follows: employing bees to find and memorize honey sources, searching new honey sources nearby each honey source, selecting and marking superior honey sources according to the number of nectar in the honey sources before and after; the hiring bees release information which is in direct proportion to the quality of the marked honey sources and are used for recruiting the observation bees, the observation bees select the proper marked honey sources under a certain mechanism and search new honey sources nearby the proper marked honey sources, the marked honey sources are compared with the new honey sources, the excellent honey sources are selected as the final marked honey sources of the current cycle, and the optimal honey sources are searched in a repeated cycle. However, if the honey source is unchanged after a plurality of searches in the honey collecting process, the corresponding employed bee becomes a scout bee, and a new honey source is randomly searched.
The artificial bee colony algorithm is introduced into the field of microseismic positioning, which is equivalent to searching the honey source with the minimum travel residual error in a three-dimensional space. The method has the advantages that the convergence speed of the artificial bee colony algorithm is low, the artificial bee colony algorithm is easy to fall into the local optimal solution and the like, the traditional honey source search formula (7) is further improved, the fast-convergence self-adaptive honey source search formula (8) is obtained, and the self-adaptive artificial bee colony algorithm is constructed and is used for improving the positioning precision and speed of the micro seismic source.
In this example, the search space is the extent of the monitoring region, such as the monitoring region is a 200 x 200 region,
can be set to (0), 0, 0, 0），
Can be arranged as (200), 200, 200,v p ）。
The wave velocity of the P-wave is obtained by the sonic wave test, and the typical search stage adds 5% and 10% error to the P-wave. The upper and lower bounds are the coordinate ranges of locations where the microseismic source may occur.
、
Calculating the fitness value with equation (6)
Has the same meaning as that of the compound, wherein,
is a 4-dimensional vector of the vector,
is represented by
To middledOne value of the dimension.
In order to make the objects and advantages of the invention more apparent, the invention will be further explained with reference to the following embodiments and drawings:
in the embodiment, the area rock mass is positioned in a uniform single medium model, and the size of the area rock mass area of the micro seismic source to be detected is 200m
200m
200m, the concrete micro seismic source positioning steps are as follows:
(1) 8 micro-seismic monitoring sensors are arranged in the rock mass monitoring area, the serial numbers of the 8 micro-seismic monitoring sensors are respectively S-1, S-2, S-3, S-4, S-5, S-6, S-7 and S-8, and the 8 micro-seismic monitoring sensors are distributed in a spatial network structure. The coordinates and the positions of the seismic source points of each microseismic monitoring sensor are shown in table 1.
TABLE 1 spatial coordinates of the sensors
Marking micro-seismic source coordinates by blasting, drilling two blasting holes in the monitoring area, wherein the coordinates are respectively M1 (80), 91, 122），M2(75, 84, 102). The specific operation process is as follows: mounting 200g of emulsion explosive at the bottom of the blast hole, and connecting the emulsion explosive with an explosion wire and a high-voltage electrostatic detonator to realize blasting; the opening of the blast hole is suitably plugged with in-situ soil to reduce energy dissipation. And taking M1 as a known explosion point to acquire the P wave velocity of the region, and taking M2 as an unknown seismic source to simulate a micro seismic source.
(2) The collected blasting signals are processed, and the time of arrival of the P waves is picked up by combining the time window energy ratio method and the AIC method, and the picking is shown in figure 2. The arrival-time picking results of the signal P waves of the 8 channels are shown in the table 2, and the picked arrival-time of the P waves is stored in a database for the next calculation.
TABLE 2 arrival times of P-waves of the microseismic monitoring sensors
(3) And calculating the micro seismic source coordinates by using a self-adaptive artificial bee colony algorithm in combination with the picked P wave arrival time and the known sensor coordinate position. Initialization of the honey source is performed according to equation (5) where the boundary vectors are respectively
、
And respectively calculating an objective function value and a honey source adaptability value through a formula (4) and a formula (6).
(4) And (3) performing honey source search in the neighborhood by using a self-adaptive honey source search formula (8), storing the updated honey source in a database, calculating the fitness value of the new honey source, and judging the advantages and disadvantages of the updated new honey source and the current honey source. When the updated honey source is superior to the current honey source, updating the position of the honey source, wherein Trail =0; when the new honey source is inferior to the current honey source, trail = Trail +1, and whether the Trail value exceeds a preset threshold limit is judged, if so, the corresponding employed bee is selected as a detected bee; and if the fitness value of the new honey source is equal to that of the current honey source, the new honey source cannot be selected as the scout bee, and the new honey source is selected as the observation bee according to the fifth step.
(5) Calculating the probability of adopting bees to select as observation bees according to the formula (10), randomly generating a random number between 0 and 1, and comparing the generated random number with the probability calculated by the formula (10), when the generated random number is less than the probability
Selecting a corresponding hiring bee as an observation bee, performing neighborhood search by using a formula (8), and updating a honey source; and storing the updated honey source in a database, calculating the fitness value of the new honey source, and judging the advantages and disadvantages of the updated new honey source and the current honey source according to the fitness value of the new honey source and the current honey source. When the updated new honey source is superior to the current honey source, updating the position of the honey source, wherein Trail =0; when the new honey source is inferior to the current honey source, trail = Trail +1, and whether the Trail value exceeds a preset threshold limit is judged, and if the Trail value exceeds the preset threshold limit, the new honey source is converted into the detection bees.
(6) The honey sources which are not updated for a plurality of times, namely the honey sources with trail values exceeding the preset threshold limit, are updated by using the formula (5), and the fitness value is calculated.
(7) After the stages of bee hiring, bee observation and bee reconnaissance, the minimum fitness value, namely the obtained global optimum value (the obtained microseismic source coordinates are obtained through calculation) is calculated and stored.
Finally, the multiple averages of the calculation results are (75.159, 84.159, 101.964), and the coordinate distance between the theoretical micro seismic source coordinate and the actual micro seismic source coordinate located in this embodiment is:
in addition, the embodiment also adopts a nonlinear positioning method particle swarm algorithm and an artificial bee colony algorithm to calculate the micro seismic source positioning, wherein Max iscycle=100, since both algorithms are prior art, thisThe invention is not described in detail herein, and the micro seismic source coordinates calculated by the two algorithms are respectively as follows according to the acquired P wave arrival time and the known sensor coordinate position:
the theoretical micro seismic source coordinates calculated by the particle swarm algorithm are as follows: (57.391, 72.516, 109.336) that is a coordinate distance from the actual microseismic source coordinates of:
the theoretical micro seismic source coordinates calculated by the artificial bee colony algorithm are as follows: (68.476, 81.395, 103.454) that is a coordinate distance from the actual microseismic source coordinates of:
with the increase of the iteration times, the coordinate distances between the theoretical micro seismic source coordinates and the actual micro seismic source coordinates, which are respectively calculated by the self-adaptive artificial bee colony algorithm, the nonlinear positioning particle swarm algorithm and the artificial bee colony algorithm, are as follows (see the following table 3):
TABLE 3 coordinate distances for different algorithms as the number of iterations increases
Comparing the theoretical micro seismic source calculated by the adaptive artificial bee colony algorithm, the nonlinear positioning particle swarm algorithm and the artificial bee colony algorithm with the actual micro seismic source, the position of the theoretical micro seismic source positioned by the adaptive artificial bee colony algorithm is closer to the real position of the micro seismic source, which also shows that the positioning method has higher precision.
In embodiments of the present invention, the term "plurality" means two or more unless explicitly defined otherwise. The terms "mounted," "connected," "fixed," and the like are to be construed broadly and include, for example, fixed connections, removable connections, or integral connections. Specific meanings of the above terms in the embodiments of the present invention may be understood by those of ordinary skill in the art according to specific situations.
In the description of the embodiments of the present invention, it should be understood that the terms "upper", "lower", and the like indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings, which are merely for convenience in describing the embodiments of the present invention and simplifying the description, but do not indicate or imply that the referred devices or units must have a specific direction, be configured and operated in a specific orientation, and thus, should not be construed as limiting the embodiments of the present invention.
In the description herein, the appearances of the phrase "one embodiment," "a preferred embodiment," or the like, are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the embodiments of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the present embodiment by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the embodiments of the present invention should be included in the protection scope of the embodiments of the present invention.
Claims (4)
1. A method for fast convergence and high-precision positioning of a micro seismic source is characterized by comprising the following steps:
(1) Installing a microseismic monitoring sensor:
installing m micro-seismic monitoring sensors in a rock mass area to be monitored, measuring the space coordinates of all the micro-seismic monitoring sensors, and measuring the space coordinates of the micro-seismic monitoring sensors
The coordinate of each microseismic monitoring sensor is
Wherein m is more than or equal to 4,m microseismic monitoring sensors are distributed in a spatial mesh structure;
(2) Acquiring arrival time of a P wave;
(3) Establishing a micro seismic source positioning objective function:
assuming that the rock mass is homogeneous and homogeneous, the wave speed of the P wave is kept unchanged, and establishing a travel time equation:
in the formula:
suppose thatkThe theoretical moment of P wave picked up by each microseismic monitoring sensor is as follows:
first, thekIs first and seconduThe theoretical arrival time difference of each microseismic monitoring sensor is as follows:
the microseismic location objective function can be expressed as:
in the formula:
the minimum value calculated by the formula (4) is the coordinate value of the micro seismic source;
(4) Initialization of honey sources
Initializing honey source according to formula (5), and calculating fitness value according to formula (6)
Wherein, in the step (A),
in the formula:
dis the dimension of the honey source, wherein,d=1，2，3，4；
(5) And (3) updating and searching new honey sources:
employing bees to search for new honey sources in the vicinity of the honey sources using equation (8) with an adaptive search strategy;
in the formula:
maxcycleis the maximum cycle number;
formula (7) the conventional honey source search formula is known from formula (9): at the beginning of the cycle,
at the moment, the formula (8) is mainly based on the traditional honey source searching formula (7), so that the strong exploration capability can be kept, as the searching is carried out, each honey source gradually approaches, and the neighborhood range gradually decreases; finally, the greedy algorithm is utilized to compare the adaptive values of the new and old honey sources, and the minimum adaptive value is selected as the optimal value;
(6) Probability of hiring bees to choose to observe bees:
in the formula:
NPthe number of honey sources;
randomly generating a random number between 0 and 1, comparing the random number with the probability calculated by the formula (10), and when the generated random number is less than the probability
Selecting the corresponding hiring bee as an observation bee, and performing neighborhood search by using a formula (8);
(7) Bee detection stage
The honey source has a parameter trim, when the new honey source is better than the current honey source, the honey source update is preserved, and trail =0; on the contrary, if the current honey source is reserved, trail = trail +1 so as to count the times that the current honey source is not updated;
when the trail value of a honey source exceeds the preset threshold limit, the honey source needs to be abandoned, the scout bee stage is started, and in the scout bee stage, the scout bee randomly searches a new honey source by using a formula (5) to replace the abandoned honey source.
2. The method for micro seismic source fast convergence and high precision positioning according to claim 1, characterized in that the picking of the arrival time of the P-wave of the micro seismic event is performed based on a time window energy ratio method and an AIC method;
and constructing a micro seismic source positioning target function based on the self-adaptive artificial bee colony algorithm.
3. The method for micro seismic source fast convergence and high precision positioning according to claim 2, characterized in that the micro seismic source coordinate calculation is performed by using an adaptive artificial bee colony algorithm in combination with the picked P-wave arrival time and the micro seismic monitoring sensor coordinate position to find the micro seismic source coordinate with the minimum travel time residual in the three-dimensional space.
4. The method for micro seismic source fast convergence and high precision positioning according to claim 1, characterized in that in the scout bee stage, the fitness value is further calculated by formula (6), and the obtained minimum fitness value is saved.
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