A method for predicting mining earthquake risk areas based on cumulative microseismic response

Abstract

The present invention discloses a method for predicting a mine earthquake risk area based on cumulative microseismic response, comprising: first determining a region to be predicted and collecting microseismic monitoring data in the region, constructing a simplified model of a tunnel and calculating the PPV distribution of the tunnel, further statistically analyzing the cumulative PPV distribution of the tunnel and determining the danger threshold, and predicting the mine earthquake risk area according to the cumulative PPV response number distribution of the tunnel. The method proposed by the present invention has the advantages of clear calculation model, universality and strong operability, and can effectively predict the impact manifestation area.

Description

Technical Field

[0001] The invention belongs to the technical field of coal mining and coal mine safety, and in particular relates to a method for predicting a mine earthquake risk area based on cumulative microseismic responses. Background Art

[0002] Mine tremors are generated along with coal mine production activities, and the hazards caused by mine tremors can only be avoided as much as possible under limited possibilities. Since the underground workers and mechanical operations of coal mines are all located in the tunnels, how to evaluate the impact of continuous mine tremors on the tunnels and then predict the risk areas of mine tremors is the first priority.

[0003] In recent years, microseismic systems have been widely deployed in rock burst mines to capture mine earthquake signals. Through this system, a clear waveform of the vibration signal can be obtained. The microseismic waveform contains rich mine earthquake information, such as the amplitude, duration, and vibration frequency of the waveform, which can reflect the impact of mine earthquakes on the roadway from certain aspects. However, how to effectively use the information contained in the waveform, fully consider the impact of continuous mine earthquakes on the roadway, and then predict the mine earthquake risk area has not been well solved. In addition, the microseismic system often arranges a certain number of stations around the coal mining space to collect waveforms, so the waveform information obtained from the microseismic system is only the vibration information of the coal and rock mass near the station; and when using these waveform information to conduct risk assessment of the roadway, the vibration information of the entire roadway is required. Therefore, it becomes particularly important to obtain the vibration information of the entire roadway in a scientific way based on the limited microseismic station information. Summary of the invention

[0004] The purpose of the present invention is to provide a method for predicting mining earthquake risk areas based on cumulative microseismic responses to solve the problems existing in the above-mentioned prior art.

[0005] To achieve the above object, the present invention provides a method for predicting mining earthquake risk areas based on cumulative microseismic responses, comprising:

[0006] Collect microseismic monitoring data of the area to be predicted and construct a simplified model of the tunnel;

[0007] The mine earthquake risk area is predicted based on the microseismic monitoring data and the simplified tunnel model.

[0008] Optionally, the microseismic monitoring data includes the coordinates of the microseismic monitoring system station, the coordinates of the microseismic source, and the peak values ​​of PPV picked up by different microseismic stations, where the PPV is the peak particle velocity of the tunnel.

[0009] Optionally, the simplified lane model is constructed by simplifying the lane into a straight line and discretizing the straight line into scattered points.

[0010] Optionally, the process of predicting the mine earthquake risk area based on the microseismic monitoring data and the simplified tunnel model includes: calculating the focal radius, calculating the PPV of the scattered points based on the relationship between the scattered points of the simplified tunnel model and the focal location and the size of the focal radius, and predicting the mine earthquake risk area based on the simplified tunnel model and the PPV of the scattered points.

[0011] Optionally, the process of predicting the mine earthquake risk area based on the simplified tunnel model and the PPV of the scattered points includes:

[0012] Calculating the PPV distribution of the lane based on the simplified lane model;

[0013] Counting the cumulative PPV distribution of the lane;

[0014] Calculate the cumulative PPV response times distribution of the laneway and determine the danger threshold;

[0015] The mine earthquake risk area is predicted based on the distribution of the cumulative PPV response times of the tunnel.

[0016] Optionally, the earthquake source radius is calculated using the following formula:

[0017]

[0018] Among them, r0 is the focal radius, V A is the apparent volume of the earthquake source; G is the shear modulus of the coal rock mass; M0 is the seismic moment of the earthquake source; E s is the source energy.

[0019] Optionally, the process of calculating the PPV value of the scattered point based on the relationship between the scattered point and the earthquake source location and the earthquake source radius includes: when the straight-line distance between the scattered point and the earthquake source is less than or equal to the roadway radius, the PPV value of the scattered point is calculated using the following formula:

[0020] ppv 近场 =1.28(C s / G)ρRppa

[0021] Among them C S is the shear wave velocity, ρ is the density of the propagation medium, R is the distance from the earthquake source to the station, and ppa is the peak acceleration of the particle at the station, which is obtained by derivation of the velocity waveform.

[0022] Optionally, the process of calculating the PPV value of the scattered point based on the relationship between the scattered point and the source location and the size of the source radius also includes: when the straight-line distance between the scattered point and the source is greater than the tunnel radius, the distance from the source to all stations and the corresponding PPV are counted to obtain the attenuation relationship between PPV and distance, and the PPV value of the scattered point is obtained based on the attenuation relationship.

[0023] Optionally, the method for determining the danger threshold is: selecting 80% of the PPV distribution as the threshold.

[0024] Optionally, the spatial relationship between the earthquake source size and the tunnel is considered when determining the danger threshold.

[0025] The technical effects of the present invention are:

[0026] The present invention collects microseismic monitoring data, constructs a simplified tunnel model, and predicts the mine earthquake risk area based on the microseismic monitoring data and the simplified tunnel model. The method proposed in the present invention has the advantages of clear calculation model, universality and strong operability, and can effectively predict the impact manifestation area. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0028] Figure 1 is a flow chart of a method for predicting a mine earthquake risk area in an embodiment of the present invention;

[0029] Figure 2 This is a schematic diagram of the impact appearance position during mining of the LW250106-1 working face in an embodiment of the present invention;

[0030] Figure 3 A schematic diagram of the study area and microseismic station layout in an embodiment of the present invention;

[0031] Figure 4 A typical vibration waveform diagram of a microseismic event in the study area in the embodiment of the present invention;

[0032] Figure 5 It is a schematic diagram of picking up the peak velocity of a particle in a certain channel (probe) in the research area in an embodiment of the present invention;

[0033] Figure 6 Schematic diagram of peak velocity and energy attenuation of vibration wave propagation of mining earthquake within and outside the earthquake source radius in an embodiment of the present invention;

[0034] Figure 7 It is a schematic diagram of fitting the particle peak velocity attenuation coefficient of a microseismic event outside the focal radius in the study area in an embodiment of the present invention;

[0035] Figure 8 It is a schematic diagram of calculating the cumulative PPV distribution of the lane and determining the danger threshold in an embodiment of the present invention;

[0036] Fig. 9 It is a schematic diagram comparing the actual impact manifestation area and the predicted mine earthquake risk area in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0038] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0039] Embodiment 1

[0040] like Figure 1 As shown, this embodiment provides a method for predicting mining earthquake risk areas based on cumulative microseismic responses, including:

[0041] First, determine the area to be predicted and collect microseismic monitoring data in the area. By constructing a simplified tunnel model and calculating the PPV (particle peak velocity) distribution of the tunnel, further statistically analyze the cumulative PPV distribution of the tunnel and determine the danger threshold. The mine earthquake risk area is predicted based on the distribution of the cumulative PPV response times of the tunnel. Specifically, the collected microseismic data mainly include the coordinates of the microseismic monitoring system station, the coordinates of the microseismic source, and the PPV peak values ​​picked up by different microseismic stations. When constructing the simplified tunnel model, the tunnel is simplified into a straight line. When calculating the PPV threshold of the tunnel microseismic damage, the spatial relationship between the source size and the tunnel is considered.

[0042] As a preferred technical solution of the present invention: when constructing a simplified tunnel model and calculating the PPV (particle peak velocity) distribution of the tunnel, the tunnel is first simplified into a straight line, and then further discretized into scattered points, and the focal radius is calculated, and the PPV of the scattered points is calculated based on the relationship between the discrete scattered points and the focal location and the focal radius.

[0043] As a preferred technical solution of the present invention: the earthquake source radius r0 is calculated using the following formula:

[0044]

[0045] Where V A is the apparent volume of the earthquake source; G is the shear modulus of the coal rock mass; M0 is the seismic moment of the earthquake source; E s is the source energy.

[0046] As a preferred technical solution of the present invention: when the straight-line distance between the scattered points and the earthquake source is not greater than the radius of the roadway, the PPV value of the scattered points is calculated using the following formula:

[0047] ppv 近场 =1.28(Cs / G)ρRppa

[0048] Among them C S is the shear wave velocity, ρ is the density of the propagation medium, R is the distance from the earthquake source to the station, and ppa is the peak acceleration of the particle at the station, which can be obtained by derivation of the velocity waveform.

[0049] As a preferred technical solution of the present invention: when the straight-line distance of the scattered point from the earthquake source is greater than the radius of the tunnel, it is necessary to count the distances from the earthquake source to all stations and the corresponding PPVs to obtain the attenuation relationship between PPV and distance, and obtain the PPV value of the scattered point based on the attenuation relationship.

[0050] As a preferred technical solution of the present invention: when the statistical cumulative PPV distribution of the lane is used to determine the danger threshold, 80% of all PPV distributions are used as the threshold.

[0051] Embodiment 2

[0052] like Figure 2-9 As shown, this embodiment provides a prediction example of a method for predicting a mining earthquake risk area based on cumulative microseismic response, including:

[0053] like Figure 2 As shown in the figure, on May 14, 2017, an impact event occurred during the mining of the LW250106-1 working face in Huating, Gansu Province, causing floor damage in the range of 197 to 257 meters in front of the working face transport drift, with a floor height of 0.2 to 0.3 meters, and causing damage to equipment in the inner tunnel, but no casualties. Figure 3 As shown in the figure, in order to monitor the mine earthquake events during the mining process, the mine has installed microseismic stations throughout the mine, especially near the LW250106-1 working face. The microseismic stations can effectively monitor the vibration waveforms generated by mine earthquake events and record ( Figure 4 ), the time and spatial coordinates of the earthquake source can be calculated through the degree of microseismic post-processing.

[0054] In order to test the effectiveness of the mine earthquake risk area prediction method proposed in the present invention, this accident case was used for verification. First, the LW250106-1 working face was determined as the target area predicted by the present invention, and the microseismic data of the LW250106-1 working face during mining were collected to establish a microseismic database. The specific microseismic data include the microseismic data within one month before the impact of the LW250106-1 working face, mainly including the source coordinates, the microseismic waveforms recorded by each microseismic station, the coordinates of the microseismic station, etc.

[0055] Since the cross-section of the underground tunnel in a coal mine is negligible relative to the entire mine, the tunnel can be simplified to a spatial straight line when analyzing the scale space problem of the mine; for the convenience of subsequent prediction calculation and processing, the straight line can be further discretized into scattered points. For example, a tunnel length of 1000m can be further simplified to 1001 scattered points with an interval of 1m after being simplified to a straight line. When implementing the present invention, firstly pick up the waveforms recorded by different stations in each microseismic event and pick up the PPV value, for example Figure 5 The following is a schematic diagram of picking the PPV peak value of the waveform recorded by a certain station for a certain microseismic event. After picking the PPV values ​​of all data in the microseismic database, the cumulative effect of the microseismic event on the roadway is calculated. Specifically, the correlation between the discrete roadway scattered points and the source position and source radius is first determined, for example Figure 6 As shown in the figure, if the discretized scattered points (the dark area on the left side of the figure) are located within the focal radius, the PPV value of the scattered points is calculated using formula (1).

[0056] ppv 近场 =1.28(C s / G)ρRppa

[0057] Among them C S is the shear wave velocity, ρ is the density of the propagation medium, R is the distance from the earthquake source to the station, and ppa is the peak acceleration of the particle at the station, which can be obtained by derivation of the velocity waveform.

[0058] In addition, as a preferred technical solution of the present invention: the earthquake source radius r0 is calculated using the following formula:

[0059]

[0060] Where V A is the apparent volume of the earthquake source; G is the shear modulus of the coal rock mass; M0 is the seismic moment of the earthquake source; E s is the source energy.

[0061] If the scattered points are outside the focal radius, the attenuation relationship between the PPV and propagation distance of all received microseismic waveforms of the microseismic event is first calculated, and the attenuation relationship expression is obtained ( Figure 7 ), the PPV values ​​of all scattered points are calculated using the attenuation relationship expression according to the scattered points and their distance from the center of the earthquake source.

[0062] Furthermore, the PPV caused by all microseismic events in the database to the nearest point of the roadway is used to determine the danger threshold, which is obtained through a large number of experimental tests by the inventors, such as Figure 8As shown, the best prediction effect is obtained when 80% of all statistics is used as the critical threshold. Therefore, the PPV value corresponding to 80% of the cumulative frequency is used as the critical threshold. In this embodiment, the critical PPV threshold is 0.01m / s.

[0063] Furthermore, the statistical distribution of the number of times that the microseismic events in the microseismic database caused the PPV to be greater than 0.01 m / s at scattered points in the tunnel was calculated. Fig. 9 The figure shows the scattered distribution of tunnels with PPV greater than 0.01 m / s in this embodiment, which is used as the predicted mine earthquake risk area. Fig. 9 It can be found that the impact appearance area of ​​250106-1 working face ( Fig. 9 The dark-medium area) all fall into the predicted mine earthquake risk area and are obviously located in the strong vibration frequency (PPV greater than 0.01m / s), indicating that the prediction method proposed in the present invention completely predicts the impact manifestation area and has a good prediction effect.

[0064] The above is only a preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for predicting mining earthquake risk areas based on cumulative microseismic responses, characterized in that: Collect microseismic monitoring data of the area to be predicted and construct a simplified model of the tunnel; Predicting the mine earthquake risk area based on the microseismic monitoring data and the simplified tunnel model; The process of predicting the mine earthquake risk area based on the simplified tunnel model and the PPV of scattered points includes: Calculate the PPV distribution of the lane based on the simplified lane model, where the PPV is the peak velocity of particles in the lane; Counting the cumulative PPV distribution of the lane; Calculate the cumulative PPV response times distribution of the laneway and determine the danger threshold; The mine earthquake risk area is predicted based on the distribution of the cumulative PPV response times of the tunnel.

2. The method for predicting mining earthquake risk areas based on cumulative microseismic responses according to claim 1 is characterized in that: The microseismic monitoring data include the coordinates of the microseismic monitoring system stations, the coordinates of the microseismic source, and the peak values ​​of the PPV picked up by different microseismic stations.

3. The method for predicting mining earthquake risk areas based on cumulative microseismic responses according to claim 1 is characterized in that: The simplified lane model is constructed by simplifying the lane into a straight line and discretizing the straight line into scattered points.

4. The method for predicting mining earthquake risk areas based on cumulative microseismic responses according to claim 1 is characterized in that: The process of predicting the mine earthquake risk area based on the microseismic monitoring data and the simplified tunnel model includes: calculating the focal radius, calculating the PPV of the scattered points based on the relationship between the scattered points of the simplified tunnel model and the focal location and the size of the focal radius, and predicting the mine earthquake risk area based on the simplified tunnel model and the PPV of the scattered points.

5. The method for predicting mining earthquake risk areas based on cumulative microseismic responses according to claim 4 is characterized in that: The focal radius is calculated using the following formula: Among them, r0 is the focal radius, V A is the apparent volume of the earthquake source; G is the shear modulus of the coal rock mass; M0 is the seismic moment of the earthquake source; E s is the source energy.

6. The method for predicting mining earthquake risk areas based on cumulative microseismic responses according to claim 4 is characterized in that: The process of calculating the PPV value of the scattered point based on the relationship between the scattered point and the earthquake source location and the earthquake source radius includes: when the straight-line distance between the scattered point and the earthquake source is less than or equal to the earthquake source radius, the PPV value of the scattered point is calculated using the following formula: ppv 近场 =1.28(C s / G)ρRppa Among them C S is the shear wave velocity, ρ is the density of the propagation medium, R is the distance from the earthquake source to the station, and ppa is the peak acceleration of the particle at the station, which is obtained by derivation of the velocity waveform.

7. The method for predicting mining earthquake risk areas based on cumulative microseismic responses according to claim 4 is characterized in that: The process of calculating the PPV value of the scattered point based on the relationship between the scattered point and the source location and the source radius also includes: when the straight-line distance between the scattered point and the source is greater than the source radius, the distance from the source to all stations and the corresponding PPV are counted to obtain the attenuation relationship between PPV and distance, and the PPV value of the scattered point is obtained based on the attenuation relationship.

8. The method for predicting mining earthquake risk areas based on cumulative microseismic responses according to claim 1 is characterized in that: The method for determining the danger threshold is: determining the danger threshold based on the spatial relationship between the earthquake source size and the tunnel, and selecting 80% of the PPV distribution as the danger threshold.

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