CN114779331A - Mine earthquake risk area prediction method based on accumulated microseismic response - Google Patents
Mine earthquake risk area prediction method based on accumulated microseismic response Download PDFInfo
- Publication number
- CN114779331A CN114779331A CN202210450383.7A CN202210450383A CN114779331A CN 114779331 A CN114779331 A CN 114779331A CN 202210450383 A CN202210450383 A CN 202210450383A CN 114779331 A CN114779331 A CN 114779331A
- Authority
- CN
- China
- Prior art keywords
- roadway
- ppv
- microseismic
- cumulative
- risk area
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- 230000001186 cumulative effect Effects 0.000 claims abstract description 27
- 238000009826 distribution Methods 0.000 claims abstract description 19
- 238000012544 monitoring process Methods 0.000 claims description 14
- 239000002245 particle Substances 0.000 claims description 11
- 239000011435 rock Substances 0.000 claims description 5
- 230000001133 acceleration Effects 0.000 claims description 4
- 238000004803 parallel plate viscometry Methods 0.000 claims 16
- 229920000553 poly(phenylenevinylene) Polymers 0.000 claims 16
- 241000702619 Porcine parvovirus Species 0.000 claims 1
- 238000004364 calculation method Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 9
- 239000003245 coal Substances 0.000 description 7
- 238000005065 mining Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 230000035939 shock Effects 0.000 description 4
- 230000001902 propagating effect Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000009795 derivation Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012805 post-processing Methods 0.000 description 1
- 238000012502 risk assessment Methods 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/288—Event detection in seismic signals, e.g. microseismics
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/01—Measuring or predicting earthquakes
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Environmental & Geological Engineering (AREA)
- Acoustics & Sound (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
本发明公开了一种基于累积微震响应的矿震风险区域预测方法，包括：首先确定待预测区域并采集该区域微震监测数据，通过构建巷道简化模型并计算巷道的PPV分布，进一步统计巷道累积PPV分布并确定危险阈值，根据巷道累积PPV响应次数分布预测矿震风险区域。本发明提出的方法具有计算模型明确，普适性及可操作性强的优点，可有效预测冲击显现区域。
The invention discloses a method for predicting a mine earthquake risk area based on cumulative microseismic response. Distribute and determine the risk threshold, and predict the mine earthquake risk area according to the distribution of the cumulative PPV response times of the roadway. The method proposed by the invention has the advantages of clear calculation model, strong universality and operability, and can effectively predict the impact display area.
Description
技术领域technical field
本发明属于煤矿开采及煤矿安全技术领域，特别是涉及一种基于累积微震响应的矿震风险区域预测方法。The invention belongs to the technical field of coal mining and coal mine safety, and in particular relates to a mine earthquake risk area prediction method based on cumulative microseismic response.
背景技术Background technique
矿震是伴随煤矿生产活动而产生的，只能在有限的可能下尽量避免矿震造成的危害。由于煤矿井下工人以及机械作业的场所均位于巷道内，那么如何评估连续产生的矿震对巷道的影响进而对矿震的风险区域进行预测便首当其冲。Mine earthquakes are produced along with coal mine production activities, and the hazards caused by mine earthquakes can only be avoided as far as possible. Since the underground coal mine workers and machinery are located in the roadway, how to evaluate the impact of the continuous mine earthquake on the roadway and then predict the risk area of the mine earthquake is the first.
近年来微震系统广泛部署于冲击地压矿井中用于对矿震信号的捕捉，通过该系统可获得震动信号的清晰波形。微震波形中蕴藏着丰富矿震信息，如波形的振幅、持续时间以及震动频率等均可以从某些侧面反应矿震对巷道的影响。但是如何有效利用波形内蕴藏的信息，充分考虑连续产生的矿震对巷道的影响进而预测矿震风险区域仍未得到较好解决。此外，微震系统往往煤矿采掘空间周围布置一定数量的台站采集波形，因此从微震系统获得的波形信息仅为台站附近的煤岩体震动信息；而利用这些波形信息对巷道进行风险评估时需用到整条巷道的震动信息，因此如何根据有限的微震台站信息以科学的方法获得整条巷道的震动信息便变得尤为重要。In recent years, microseismic systems have been widely deployed in rockburst mines to capture mine seismic signals, through which clear waveforms of vibration signals can be obtained. The microseismic waveform contains rich information of mine earthquake, such as the amplitude, duration and vibration frequency of the waveform, which can reflect the impact of mine earthquake on the roadway from certain sides. However, how to effectively use the information contained in the waveform, fully consider the impact of the continuous mine shock on the roadway, and predict the risk area of the mine shock has not been well resolved. In addition, the microseismic system usually arranges a certain number of stations around the mining space of the coal mine 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 the use of these waveform information for risk assessment of roadways requires The vibration information of the whole roadway is used, so it is particularly important to obtain the vibration information of the whole roadway in a scientific way according to the limited information of microseismic stations.
发明内容SUMMARY OF THE INVENTION
本发明的目的是提供一种基于累积微震响应的矿震风险区域预测方法，以解决上述现有技术存在的问题。The purpose of the present invention is to provide a mine earthquake risk area prediction method based on cumulative microseismic response, so as to solve the above problems existing in the prior art.
为实现上述目的，本发明提供了一种基于累积微震响应的矿震风险区域预测方法，包括：To achieve the above purpose, the present invention provides a method for predicting a mine earthquake risk area based on cumulative microseismic responses, including:
采集待预测区域的微震监测数据，构建巷道简化模型；Collect the microseismic monitoring data of the area to be predicted, and build a simplified model of the roadway;
基于所述微震监测数据与所述巷道简化模型预测矿震风险区域。The mine earthquake risk area is predicted based on the microseismic monitoring data and the roadway simplified model.
可选地，所述微震监测数据包括微震监测系统台站坐标、微震震源坐标以及不同微震台站拾取的PPV的峰值，所述PPV为巷道的质点峰值速度。Optionally, the microseismic monitoring data includes the station coordinates of the microseismic monitoring system, the coordinates of the microseismic source, and the peak value of PPV picked up by different microseismic stations, where the PPV is the peak particle velocity of the roadway.
可选地，所述巷道简化模型的构建方法为：将巷道简化为直线，将所述直线离散为散点。Optionally, the method for constructing the simplified roadway model is: simplifying the roadway into a straight line, and discretizing the straight line into scattered points.
可选地，基于所述微震监测数据与所述巷道简化模型预测矿震风险区域的过程包括：计算震源半径，基于所述巷道简化模型的散点与震源定位、震源半径的大小关系计算散点的PPV，基于所述巷道简化模型与散点的PPV预测矿震风险区域。Optionally, the process of predicting a mine earthquake risk area based on the microseismic monitoring data and the simplified roadway model includes: calculating the focal radius, and calculating the scatter based on the relationship between the scatter points of the simplified roadway model, the location of the focal point, and the focal radius. The PPV, based on the simplified model of the roadway and the PPV of scattered points to predict the mine earthquake risk area.
可选地，基于所述巷道简化模型与散点的PPV预测矿震风险区域的过程包括：Optionally, the process of predicting the mine earthquake risk area based on the simplified roadway model and the scattered PPV includes:
基于所述巷道简化模型计算巷道的PPV分布；Calculate the PPV distribution of the roadway based on the roadway simplified model;
统计所述巷道的累积PPV分布；Count the cumulative PPV distribution of the roadway;
计算巷道累积PPV响应次数分布并确定危险阈值；Calculate the distribution of cumulative PPV response times in the roadway and determine the risk threshold;
基于所述巷道累积PPV响应次数分布预测矿震风险区域。The mine earthquake risk area is predicted based on the distribution of cumulative PPV response times of the roadway.
可选地，所述震源半径采用下式计算：Optionally, the hypocenter radius is calculated by the following formula:
其中，r0为震源半径，VA为震源的视体积；G为煤岩体的剪切模量；M0为震源的地震矩；Es为震源能量。Among them, r 0 is the source radius, VA is the apparent volume of the source; G is the shear modulus of the coal-rock mass; M 0 is the seismic moment of the source; E s is the source energy.
可选地，基于所述散点与震源定位、所述震源半径的大小关系计算所述散点的PPV数值的过程中包括：所述散点距离震源的直线距离小于等于巷道半径时，采用下式计算散点的PPV数值：Optionally, the process of calculating the PPV value of the scatter point based on the relationship between the scatter point, the location of the epicenter, and the radius of the epicenter includes: when the linear distance between the scatter point and the epicenter is less than or equal to the radius of the roadway, the following method is used. The formula calculates the PPV value of the scatter:
ppv近场＝1.28(Cs/G)ρRppappv near field =1.28(C s /G)ρRppa
其中CS为剪切波波速，ρ为传播介质的密度，R为震源到台站的距离，ppa为台站的质点峰值加速度，由速度波形求导获得。where C S is the shear wave velocity, ρ is the density of the propagation medium, R is the distance from the source to the station, and ppa is the peak particle acceleration of the station, obtained from the velocity waveform.
可选地，基于所述散点与震源定位、所述震源半径的大小关系计算所述散点的PPV数值的过程中还包括：当所述散点距离震源的直线距离大于巷道半径时，统计震源到所有台站的距离与对应的PPV，获得PPV与距离的衰减关系，基于所述衰减关系获得所述散点的PPV数值。Optionally, the process of calculating the PPV value of the scatter point based on the relationship between the scatter point, the location of the epicenter, and the radius of the epicenter also includes: when the linear distance between the scatter point and the epicenter is greater than the radius of the roadway, statistical The distance from the source to all stations and the corresponding PPV, the attenuation relationship between the PPV and the distance is obtained, and the PPV value of the scatter point is obtained based on the attenuation relationship.
可选地，确定所述危险阈值的方法为：选取所述PPV分布的80％作为阈值。Optionally, the method for determining the risk threshold is: selecting 80% of the PPV distribution as the threshold.
可选地，确定所述危险阈值时考虑震源尺寸与所述巷道的空间关系。Optionally, the spatial relationship between the source size and the roadway is considered when determining the risk threshold.
本发明的技术效果为：The technical effect of the present invention is:
本发明通过采集微震监测数据、构建巷道简化模型并基于微震监测数据与巷道简化模型预测矿震风险区域。本发明提出的方法具有计算模型明确，普适性及可操作性强的优点，可有效预测冲击显现区域。The invention collects microseismic monitoring data, constructs a simplified roadway model, and predicts a mine earthquake risk area based on the microseismic monitoring data and the roadway simplified model. The method proposed by the invention has the advantages of clear calculation model, strong universality and operability, and can effectively predict the impact display area.
附图说明Description of drawings
构成本申请的一部分的附图用来提供对本申请的进一步理解，本申请的示意性实施例及其说明用于解释本申请，并不构成对本申请的不当限定。在附图中：The accompanying drawings constituting a part of the present application are used to provide further understanding of the present application, and the schematic embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation of the present application. In the attached image:
图1为本发明实施例中的矿震风险区域预测方法流程图；1 is a flowchart of a method for predicting a mine earthquake risk area in an embodiment of the present invention;
图2为本发明实施例中LW250106-1工作面回采时冲击显现位置示意图；Fig. 2 is a schematic diagram showing the position of the impact during the mining of the LW250106-1 working face according to the embodiment of the present invention;
图3为本发明实施例中的研究区域以及微震台站布置示意图；3 is a schematic diagram of the research area and the arrangement of microseismic stations in an embodiment of the present invention;
图4为本发明实施例中研究区域内某一次微震事件的典型震动波形图；4 is a typical vibration waveform diagram of a microseismic event in the research area in the embodiment of the present invention;
图5为本发明实施例中研究区域某一通道(探头)的质点峰值速度拾取示意图；5 is a schematic diagram of picking up the peak particle velocity of a certain channel (probe) in the research area in the embodiment of the present invention;
图6为本发明实施例中震源半径范围内外矿震震动波传播质点峰值速度及能量衰减示意图；FIG. 6 is a schematic diagram of the peak velocity and energy attenuation of the propagating particle peak velocity of the shock wave of the mine shock inside and outside the radius of the epicenter in the embodiment of the present invention;
图7为本发明实施例中研究区域内震源半径外某次微震事件质点峰值速度衰减系数拟合示意图；FIG. 7 is a schematic diagram of the fitting diagram of the peak velocity attenuation coefficient of a particle of a microseismic event outside the hypocenter radius in the study area in the embodiment of the present invention;
图8为本发明实施例中统计巷道累积PPV分布并确定危险阈值的示意图；8 is a schematic diagram of calculating the cumulative PPV distribution of a roadway and determining a danger threshold in an embodiment of the present invention;
图9为本发明实施例中实际冲击显现区域与预测的矿震风险区域对比示意图。FIG. 9 is a schematic diagram showing the comparison between the actual impact manifestation area and the predicted mine earthquake risk area in the embodiment of the present invention.
具体实施方式Detailed ways
需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。下面将参考附图并结合实施例来详细说明本申请。It should be noted that the embodiments in the present application and the features of the embodiments may be combined with each other in the case of no conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
需要说明的是，在附图的流程图示出的步骤可以在诸如一组计算机可执行指令的计算机系统中执行，并且，虽然在流程图中示出了逻辑顺序，但是在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤。It should be noted that the steps shown in the flowcharts of the accompanying drawings may be executed in a computer system, such as a set of computer-executable instructions, and, although a logical sequence is shown in the flowcharts, in some cases, Steps shown or described may be performed in an order different from that herein.
实施例一Example 1
如图1所示，本实施例提供了一种基于累积微震响应的矿震风险区域预测方法，包括：As shown in Figure 1, this embodiment provides a method for predicting a mine earthquake risk area based on cumulative microseismic responses, including:
首先确定待预测区域并采集该区域微震监测数据，通过构建巷道简化模型并计算巷道的PPV(质点峰值速度)分布，进一步统计巷道累积PPV分布并确定危险阈值，根据巷道累积PPV响应次数分布预测矿震风险区域；其中具体包括：采集的微震数据主要包括微震监测系统台站坐标、微震震源坐标以及不同微震台站拾取的PPV峰值；构建巷道简化模型时将巷道简化为直线；统计巷道微震损伤的PPV阈值时考虑震源尺寸与巷道的空间关系。First, determine the area to be predicted and collect the microseismic monitoring data in this area. By constructing a simplified model of the roadway and calculating the PPV (Particle Peak Velocity) distribution of the roadway, the cumulative PPV distribution of the roadway is further calculated and the danger threshold is determined. The seismic risk area includes: the collected microseismic data mainly includes the station coordinates of the microseismic monitoring system, the coordinates of the microseismic source, and the peak value of PPV picked up by different microseismic stations; the roadway is simplified as a straight line when the roadway simplified model is constructed; the statistics of the roadway microseismic damage The spatial relationship between the source size and the roadway is considered in the PPV threshold.
作为本发明的一种优选技术方案：所述的通过构建巷道简化模型并计算巷道的PPV(质点峰值速度)分布时，首先将巷道简化为直线，然后进一步离散为散点，并计算震源半径，根据离散后的散点与震源定位、震源半径的大小关系计算散点的PPV。As a preferred technical solution of the present invention: when the PPV (Particle Peak Velocity) distribution of the roadway is calculated by constructing a simplified model of the roadway, the roadway is first simplified into a straight line, then further dispersed into scattered points, and the hypocenter radius is calculated, The PPV of the scattered points is calculated according to the relationship between the discrete scattered points, the location of the hypocenter, and the radius of the hypocenter.
作为本发明的一种优选技术方案：所述的震源半径r0采用下式计算：As a preferred technical solution of the present invention: the hypocenter radius r 0 is calculated by the following formula:
式中，VA为震源的视体积；G为煤岩体的剪切模量；M0为震源的地震矩；Es为震源能量。where VA is the apparent volume of the source; G is the shear modulus of the coal-rock mass; M 0 is the seismic moment of the source; E s is the energy of the source.
作为本发明的一种优选技术方案：所述的散点距离震源的直线距离不大于巷道半径时采用下式计算散点的PPV数值：As a preferred technical solution of the present invention: the following formula is used to calculate the PPV value of the scatter points when the linear distance between the scatter points and the epicenter is not greater than the radius of the roadway:
ppv近场＝1.28(Cs/G)ρRppappv near field =1.28(C s /G)ρRppa
其中CS为剪切波波速，ρ为传播介质的密度，R为震源到台站的距离，ppa为台站的质点峰值加速度，可由速度波形求导获得。where C S is the shear wave velocity, ρ is the density of the propagating medium, R is the distance from the source to the station, and ppa is the peak particle acceleration of the station, which can be obtained by derivation of the velocity waveform.
作为本发明的一种优选技术方案：所述的散点距离震源的直线距离大于巷道半径时需统计震源到所有台站的距离与对应的PPV获得PPV与距离的衰减关系，根据衰减关系获得散点的PPV数值。As a preferred technical solution of the present invention: when the linear distance between the scatter point and the source is greater than the radius of the roadway, it is necessary to count the distance from the source to all stations and the corresponding PPV to obtain the attenuation relationship between the PPV and the distance, and obtain the scatter according to the attenuation relationship. Point's PPV value.
作为本发明的一种优选技术方案：所述的统计巷道累积PPV分布并确定危险阈值时将所有PPV分布的80％作为阈值。As a preferred technical solution of the present invention: 80% of all PPV distributions are used as the threshold when the statistical roadway cumulative PPV distribution and the risk threshold are determined.
实施例二
如图2-9所示，本实施例中提供一种基于累积微震响应的矿震风险区域预测方法的预测实例，包括：As shown in Figure 2-9, this embodiment provides a prediction example of a method for predicting a mine earthquake risk area based on cumulative microseismic responses, including:
如图2所示，2017年5月14日，甘肃华亭某矿LW250106-1工作面回采时发生一起冲击显现事件，造成工作面运输顺槽前方197～257m范围发生底鼓破坏，底鼓高度达0.2～0.3m，并造成内巷道内设备损坏，无人员伤亡。如图3所示，该矿为了监测工作面采掘期间的矿震事件，已在全矿井范围尤其是LW250106-1工作面附近安装了微震台站，微震台站可有效监测矿震事件产生的震动波形并记录(图4)，通过微震后处理程度可计算震源的发震时间及空间坐标。As shown in Figure 2, on May 14, 2017, an impact event occurred during the mining of the LW250106-1 working face of a mine in Huating, Gansu Province, which caused damage to the floor drum within 197-257m in front of the working face transportation along the groove, and the height of the floor drum reached 0.2 ~ 0.3m, and cause damage to the equipment in the inner roadway, no casualties. As shown in Figure 3, in order to monitor the mine earthquake events during the mining of the working face, a microseismic station has been installed in the whole mine, especially near the LW250106-1 working face. The microseismic station can effectively monitor the vibration generated by the mine earthquake event. The waveform is recorded and recorded (Fig. 4), and the earthquake occurrence time and spatial coordinates of the source can be calculated by the degree of post-processing of the microseismic earthquake.
为检验本发明提出矿震风险区域预测方法的有效性，采用该次事故案例进行验证。首先确定LW250106-1工作面为本发明预测的目标区域，采集LW250106-1工作面回采时的微震数据建立微震数据库。具体微震数据包括LW250106-1工作面发生冲击前一个月内的微震数据，主要包括震源坐标、各个微震台站记录的微震波形、微震台站的坐标等。In order to test the validity of the mine earthquake risk area prediction method proposed by the present invention, this accident case is used for verification. Firstly, it is determined that the LW250106-1 working face is the target area predicted by the present invention, and the microseismic data of the LW250106-1 working face is collected to establish a microseismic database. The specific microseismic data includes the microseismic data within one month before the impact of the LW250106-1 working face, mainly including the coordinates of the source, the waveform of the microseismic recorded by each microseismic station, and the coordinates of the microseismic station.
由于煤矿井下巷道断面相对于整个矿井来说面积可忽略不计，因此在分析矿井尺度空间问题时可将巷道简化为具有空间直线；为后续预测计算处理方便，可进一步将直线离散为散点，例如一条巷道长度为1000m，将其简化为直线后进一步可简化为由1001个散点组成，间隔为1m的散点。实施本发明时，首先拾取每个微震事件中不同台站记录的波形并拾取PPV数值，例如图5为某次微震事件的拾取某个台站记录波形的PPV峰值的示意图。对微震数据库中所有数据拾取完PPV数值后，计算微震事件对巷道的累积效应。具体首先判断离散后的巷道散点与震源位置以及震源半径的相关性关系，例如图6所示，若离散后的散点(图中左侧深色区域)位于震源半径范围内，则采用式(1)计算散点的PPV数值。Since the area of the tunnel section under the coal mine is negligible relative to the entire mine, the tunnel can be simplified as a spatial straight line when analyzing the mine scale space problem; for the convenience of subsequent prediction and calculation, the straight line can be further discretized into scattered points, such as The length of a roadway is 1000m. After simplifying it into a straight line, it can be further simplified to be composed of 1001 scattered points with an interval of 1m. When implementing the present invention, firstly, the waveforms recorded by different stations in each microseismic event are picked up and the PPV value is picked up. After picking up PPV values for all the data in the microseismic database, the cumulative effect of microseismic events on the roadway is calculated. Specifically, first determine the correlation between the discrete roadway scatter points and the source position and the source radius. For example, as shown in Figure 6, if the discrete scatter points (the dark area on the left in the figure) are located within the source radius, the formula (1) Calculate the PPV value of the scattered points.
ppv近场＝1.28(Cs/G)ρRppappv near field =1.28(C s /G)ρRppa
其中CS为剪切波波速，ρ为传播介质的密度，R为震源到台站的距离，ppa为台站的质点峰值加速度，可由速度波形求导获得。where C S is the shear wave velocity, ρ is the density of the propagating medium, R is the distance from the source to the station, and ppa is the peak particle acceleration of the station, which can be obtained by derivation of the velocity waveform.
此外，作为本发明的一种优选技术方案：所述的震源半径r0采用下式计算：In addition, as a preferred technical solution of the present invention: the hypocenter radius r 0 is calculated by the following formula:
式中，VA为震源的视体积；G为煤岩体的剪切模量；M0为震源的地震矩；Es为震源能量。where VA is the apparent volume of the source; G is the shear modulus of the coal-rock mass; M 0 is the seismic moment of the source; E s is the energy of the source.
若散点位于震源半径之外，则首先统计该次微震事件所有接收到微震波形的PPV与传播距离的衰减关系，在获得衰减关系表达式(图7)后，根据散点与距震源中心的距离，采用该衰减关系表达式计算所有散点的PPV数值。If the scatter point is outside the hypocenter radius, firstly calculate the attenuation relationship between the PPV of all received microseismic waveforms and the propagation distance of this microseismic event, and after obtaining the attenuation relationship expression (Fig. distance, and the PPV value of all scattered points is calculated using this attenuation relationship expression.
进一步地，数据库中所有微震事件对巷道最近点造成的PPV获得确定危险阈值，其中经过发明人大量的实验测试，如图8所示，将所有统计的80％作为临界阈值时获得的预测效果最佳，因此此处将累积频率中对应80％占比时PPV数值作为临界阈值，在本实施例中临界PPV阈值为0.01m/s。Further, the PPV caused by all the microseismic events in the database to the nearest point of the roadway is obtained to determine the risk threshold. After a large number of experimental tests by the inventor, as shown in Figure 8, the prediction effect obtained when 80% of all statistics is taken as the critical threshold is the best. Therefore, the PPV value corresponding to 80% of the cumulative frequency is used as the critical threshold here. In this embodiment, the critical PPV threshold is 0.01 m/s.
进一步地，统计微震数据库中微震事件对巷道散点造成PPV大于0.01m/s的次数的统计分布。如图9所示为本实施例中统计的PPV大于0.01m/s的巷道散点分布，将其作为预测的矿震风险区域。从图9可发现，250106-1工作面冲击显现区域(图9中深色区域)全部落入了预测的矿震风险区域中，并且明显位于强震动频次(PPV大于0.01m/s),说明本发明提出的预测方法完整的预测了冲击显现区域，预测效果好。Further, the statistical distribution of the number of times that the microseismic events caused the PPV to be greater than 0.01m/s on the roadway scattered points in the statistical microseismic database. As shown in FIG. 9 , the scatter distribution of roadways with PPV greater than 0.01 m/s calculated in this embodiment is taken as the predicted mine earthquake risk area. From Figure 9, it can be found that the impact manifestation area of the 250106-1 working face (the dark area in Figure 9) all falls into the predicted mine earthquake risk area, and is obviously located in the strong vibration frequency (PPV is greater than 0.01m/s), indicating that The prediction method proposed by the present invention completely predicts the impact appearance area, and the prediction effect is good.
以上所述，仅为本申请较佳的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到的变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应该以权利要求的保护范围为准。The above are only the preferred specific embodiments of the present application, but the protection scope of the present application is not limited to this. Substitutions should be covered within the protection scope of this application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.
Claims (9)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210450383.7A CN114779331B (en) | 2022-04-26 | 2022-04-26 | A method for predicting mining earthquake risk areas based on cumulative microseismic response |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210450383.7A CN114779331B (en) | 2022-04-26 | 2022-04-26 | A method for predicting mining earthquake risk areas based on cumulative microseismic response |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114779331A true CN114779331A (en) | 2022-07-22 |
| CN114779331B CN114779331B (en) | 2025-02-14 |
Family
ID=82433886
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210450383.7A Active CN114779331B (en) | 2022-04-26 | 2022-04-26 | A method for predicting mining earthquake risk areas based on cumulative microseismic response |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114779331B (en) |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102495425A (en) * | 2011-11-14 | 2012-06-13 | 北京科技大学 | Energy-based method for automatically locating earthquake focus of microearthquake |
| KR20150035633A (en) * | 2013-09-27 | 2015-04-07 | 한국전력공사 | Apparatus for measuring earthquake intensity and method for the same |
| US20190094397A1 (en) * | 2017-09-25 | 2019-03-28 | Real Time Geomechanics, Llc | Surface detection and location of microseismic events and earthquakes without the use of a velocity model |
| US20190302291A1 (en) * | 2018-03-29 | 2019-10-03 | Sri Venkata Tapovan Lolla | Enhanced Surveillance of Subsurface Operation Integrity Using Microseismic Data |
| WO2020019998A1 (en) * | 2018-07-25 | 2020-01-30 | 中国矿业大学 | Method for predicting mine strata pressure behavior data of stoping tunnel |
| CN111963243A (en) * | 2020-07-22 | 2020-11-20 | 中国矿业大学 | A monitoring and early warning method for rock burst danger based on dynamic and static combined stress analysis |
| CN112379425A (en) * | 2020-10-21 | 2021-02-19 | 中国矿业大学 | Regional impact hazard level and/30043territory identification method based on seismic source parameter inversion |
| CN112630826A (en) * | 2020-12-04 | 2021-04-09 | 中国矿业大学 | Method for determining mining tendency influence range of working face based on microseismic monitoring |
| CN113279813A (en) * | 2021-05-31 | 2021-08-20 | 北京科技大学 | Roadway supporting method based on dynamic load |
| CN113958366A (en) * | 2020-07-21 | 2022-01-21 | 东北大学 | Dynamic quantitative early warning method for impact risk based on vibration-stress double-field monitoring |
| CN114037212A (en) * | 2021-10-15 | 2022-02-11 | 深圳市中金岭南有色金属股份有限公司凡口铅锌矿 | Method and device for determining mine earthquake risk level and terminal equipment |
| CN114280663A (en) * | 2021-11-26 | 2022-04-05 | 中煤科工开采研究院有限公司 | Earthquake intensity monitoring system |
| CN114329974A (en) * | 2021-12-29 | 2022-04-12 | 武汉大学 | Monte Carlo simulation-based urban water supply pipe network earthquake damage assessment method |
-
2022
- 2022-04-26 CN CN202210450383.7A patent/CN114779331B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102495425A (en) * | 2011-11-14 | 2012-06-13 | 北京科技大学 | Energy-based method for automatically locating earthquake focus of microearthquake |
| KR20150035633A (en) * | 2013-09-27 | 2015-04-07 | 한국전력공사 | Apparatus for measuring earthquake intensity and method for the same |
| US20190094397A1 (en) * | 2017-09-25 | 2019-03-28 | Real Time Geomechanics, Llc | Surface detection and location of microseismic events and earthquakes without the use of a velocity model |
| US20190302291A1 (en) * | 2018-03-29 | 2019-10-03 | Sri Venkata Tapovan Lolla | Enhanced Surveillance of Subsurface Operation Integrity Using Microseismic Data |
| WO2020019998A1 (en) * | 2018-07-25 | 2020-01-30 | 中国矿业大学 | Method for predicting mine strata pressure behavior data of stoping tunnel |
| CN113958366A (en) * | 2020-07-21 | 2022-01-21 | 东北大学 | Dynamic quantitative early warning method for impact risk based on vibration-stress double-field monitoring |
| CN111963243A (en) * | 2020-07-22 | 2020-11-20 | 中国矿业大学 | A monitoring and early warning method for rock burst danger based on dynamic and static combined stress analysis |
| CN112379425A (en) * | 2020-10-21 | 2021-02-19 | 中国矿业大学 | Regional impact hazard level and/30043territory identification method based on seismic source parameter inversion |
| CN112630826A (en) * | 2020-12-04 | 2021-04-09 | 中国矿业大学 | Method for determining mining tendency influence range of working face based on microseismic monitoring |
| CN113279813A (en) * | 2021-05-31 | 2021-08-20 | 北京科技大学 | Roadway supporting method based on dynamic load |
| CN114037212A (en) * | 2021-10-15 | 2022-02-11 | 深圳市中金岭南有色金属股份有限公司凡口铅锌矿 | Method and device for determining mine earthquake risk level and terminal equipment |
| CN114280663A (en) * | 2021-11-26 | 2022-04-05 | 中煤科工开采研究院有限公司 | Earthquake intensity monitoring system |
| CN114329974A (en) * | 2021-12-29 | 2022-04-12 | 武汉大学 | Monte Carlo simulation-based urban water supply pipe network earthquake damage assessment method |
Non-Patent Citations (4)
| Title |
|---|
| YAOQI LIU等: "Attenuation characteristics analysis of seismic energy and its application to risk assessment in underground coal mines", GEOMATICS, NATURAL HAZARDS AND RISK, vol. 13, no. 01, 20 April 2022 (2022-04-20), pages 1021 - 1022 * |
| 刘耀琪等: "基于微震群震动波能量衰减特性的冲击地压危险预测方法", 煤炭学报, vol. 47, no. 04, 30 April 2022 (2022-04-30), pages 1523 - 1533 * |
| 牟宗龙;窦林名;巩思园;曹安业;: "矿井SOS微震监测网络优化设计及震源定位误差数值分析", 煤矿开采, no. 03, 15 June 2009 (2009-06-15), pages 8 - 12 * |
| 王桂峰;窦林名;李振雷;巩思园;何江;蔡武;: "支护防冲能力计算及微震反求支护参数可行性分析", 岩石力学与工程学报, no. 2, 15 September 2015 (2015-09-15), pages 4125 - 4131 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114779331B (en) | 2025-02-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20230168406A1 (en) | Rock burst hazard prediction method based on seismic wave energy attenuation characteristics of mine earthquake cluster | |
| Hu et al. | Effects of structural planes on rockburst position with respect to tunnel cross-sections: a case study involving a railway tunnel in China | |
| Zhou et al. | Predictive acoustical behavior of rockburst phenomena in Gaoligongshan tunnel, Dulong river highway, China | |
| Wang et al. | Location error based seismic cluster analysis and its application to burst damage assessment in underground coal mines | |
| CN111648826B (en) | Coal mine rock burst prediction early warning system and method | |
| WO2022051890A1 (en) | Vibration reduction method based on blast vibration prediction technology | |
| CN105607127A (en) | Microquake multi-parameter early warning method of rock burst in high-stress concentration area | |
| Feng et al. | Deterministic seismic hazard assessment of coal fractures in underground coal mine: A case study | |
| He et al. | Active velocity tomography for assessing rock burst hazards in a kilometer deep mine | |
| Chen et al. | Microseismic monitoring of columnar jointed basalt fracture activity: a trial at the Baihetan Hydropower Station, China | |
| CN112324506B (en) | Dynamic early warning method for preventing rock burst of coal mine based on microseism | |
| CN114412573B (en) | Mine wall breakage monitoring and early warning system and method | |
| Hu et al. | Characteristics of the microseismicity resulting from the construction of a deeply-buried shaft | |
| Jiang et al. | Combined early warning method for rockburst in a Deep Island, fully mechanized caving face | |
| Wang et al. | Study on deep mining-induced strata behavior based on the evolutional laws of multiple indices from microseismic monitoring | |
| CN115755185B (en) | Method for judging disaster causing performance of high-energy ore earthquake based on microseism monitoring | |
| Du et al. | Rockburst inoculation process at different structural planes and microseismic warning technology: a case study | |
| CN110261901A (en) | Deep rock mass rockburst intensity evaluation method based on induced vibration | |
| CN118625390A (en) | Microseismic monitoring inversion and intelligent anomaly recognition method for dynamic and static stress fields of coal and rock strata | |
| CN114779331A (en) | Mine earthquake risk area prediction method based on accumulated microseismic response | |
| CN113914932B (en) | A method for identifying dangerous areas of coal and gas outburst by using shock wave tomography | |
| CN117266842B (en) | Ground stress testing method based on microseismic monitoring | |
| CN118407807A (en) | Monitoring method and system for surrounding rock stress and deformation of coal mine tunnel | |
| CN117108354A (en) | A method for arranging rock burst microseismic sensors in asymmetric high ground stress tunnels | |
| CN105045969A (en) | Multi-information coupling prediction method for risk of geostress type rock burst |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |