Coal seam roof water inrush prediction method based on microseism and resistivity monitoring

Abstract

The invention discloses a coal seam roof water inrush prediction method based on microseism and resistivity monitoring, which comprises the following steps of: sequentially distributing underground geology including a coal seam, a roof rock stratum and a roof water body from bottom to top, and determining a distance H0 between the coal seam and the roof water body; arranging a micro-seismic monitoring system and a resistivity monitoring system in an underground roadway; a micro-seismic monitoring system is adopted to monitor whether a micro-seismic event possibly forming a through fracture exists in a roof rock stratum or not in real time, and the position of the micro-seismic event possibly forming the through fracture is accurately obtained; a resistivity monitoring system is adopted to monitor resistivity change data Di in the roof rock stratum in real time, so that the distance h'between the lowest point position O of the resistivity in the roof rock stratum and the roof water body is judged; and calculating the distance h (j) between the coal seam and the micro-seismic event possibly forming the through crack found in the search area, and calculating the coupling water inrush coefficient eta of the roof rock stratum through the distance h'and the distance, thereby solving the technical problem that the existing mine water disaster monitoring method cannot accurately judge the water inrush phenomenon in real time.

Description

Technical Field

[0001] The invention belongs to the field of coal mine roof water inrush monitoring, relates to monitoring roof rupture, and specifically is a coal seam roof water inrush prediction method based on microseismic and resistivity monitoring. Background Art

[0002] Mine water inrush is one of the important factors affecting safe production. The main causes of mine water inrush are: the source of water inrush and the formation of water inrush channels. The sources of water inrush mainly include atmospheric precipitation, water accumulation in goaf areas, and pressurized water in aquifers. The formation mechanism of water inrush channels is mainly the result of the macroscopic process of changes in water-conducting structures and the microscopic process of water inrush fissure formation. The dynamic changes of groundwater in coal mines are complex and are affected by factors such as rainfall, seasons, and geological structures. The outburst and infiltration of groundwater can cause deformation and damage to the mine roof, thereby causing water inrush accidents. However, the dynamic changes of groundwater are difficult to accurately predict, and the timing and measures to prevent water inrush often have certain uncertainties.

[0003] Although modern mine monitoring technology has been greatly developed, it still has certain limitations. The commonly used roof monitoring methods are mainly manual inspections and traditional ground point monitoring, which cannot monitor the changes of groundwater and roof in real time and comprehensively. Therefore, the lack of accurate monitoring and early warning technology is also one of the reasons why roof water inrush is difficult to prevent. Therefore, establishing a multi-parameter comprehensive early warning system based on the characteristics of different parameters can improve the accuracy of water hazard early warning.

[0004] In recent years, many scholars have conducted extensive research on mine water hazard monitoring methods. Jia Jing, Lu Gang and others invented "A mine water inrush warning system, method and terminal equipment" (CN113903149B). The warning system includes a data acquisition unit, a data recognition and statistics unit, an early warning unit, etc., which can perform real-time statistical analysis and calculation of the mine water level, water channel and water inflow, and judge the precursor information of mine water inrush by the changes in various parameters. However, the system cannot accurately locate the damaged position of the water channel and can only roughly judge the damaged area.

[0005] Invention patent CN103529488B of Wu Qiang, Liu Chunsheng and others: In the mine roof and floor water inrush monitoring and forecasting system and method, high-density electrical method is used to monitor the degree of damage to the roof and floor rocks, determine the degree of development of rock cracks, and predict the occurrence of water inrush. However, the electrical monitoring data has a certain lag relative to rock damage, so there are still some deficiencies in the comprehensiveness analysis of monitoring.

[0006] Water damage is often one of the precursors or inducements of mine disasters. Abnormal rise of the groundwater level, sudden increase in water pressure, etc. may all indicate the occurrence of water damage. Through water damage monitoring, hydrogeological information can be timely grasped and analyzed, the risk of mine water damage can be warned, and corresponding prevention and control measures can be taken to effectively avoid or reduce the occurrence of mine disasters. Currently, in actual on-site engineering, there is a lack of real-time monitoring of the whole process from the development, expansion to the breakthrough of water inrush through the cracks in the mine roof. Summary of the Invention

[0007] Aiming at the deficiencies existing in the prior art, the purpose of the present invention is to provide a method for predicting water inrush in coal seam roof based on microseismic and resistivity monitoring, so as to solve the technical problem that the existing mine water damage monitoring methods cannot judge the water inrush phenomenon in real time and accurately.

[0008] In order to solve the above technical problems, the present invention is realized by adopting the following technical solutions:

[0009] A method for predicting water inrush in coal seam roof based on microseismic and resistivity monitoring. The underground geological distribution from bottom to top is coal seam, roof rock layer and roof water body in sequence, and specifically includes the following steps:

[0010] Step 1, determine the water-bearing characteristics of the overlying rock layer of the working face, determine the distribution of water-rich abnormal areas, the development of geological structures and the water-conducting property of geological structures in the mining area, and determine the distance H0 between the coal seam and the roof water body;

[0011] Step 2, deploy a microseismic monitoring system and a resistivity monitoring system in the underground roadway;

[0012] Step 3, the microseismic monitoring system obtains and processes the energy waveform data in real time, filters the data, determines the microseismic event parameters, and judges whether there are microseismic events in the roof rock layer that may form through-cracks according to the microseismic event parameters. If so, obtain the microseismic events in the roof rock layer that may form through-cracks, otherwise there is no water inrush situation;

[0013] The microseismic event parameters include the number of microseismic events, the spatial positioning of each microseismic event, the source parameters of each microseismic event, and the time when each microseismic event occurs;

[0014] Step 4, the resistivity monitoring system obtains and processes the resistivity change data in real time, determines the initial resistance value of the roof rock layer according to the resistivity change data, and judges the resistivity change data D in the roof rock layer collected in real time according to the initial resistance value of the roof rock layer i Whether it satisfies D i < D1 or D1 < D i < D2. If so, the spatial coordinate C i corresponding to the resistivity change data D di (x di,y di ,z di ) as the lowest resistivity point O, calculate the distance h' between the lowest resistivity point O and the top water body, otherwise there is no water inrush;

[0015] The initial resistance value of the roof rock layer includes the resistivity D1 of the roof water body and the resistivity D2 of the roof rock layer;

[0016] Step 5: Find the microseismic events that may form through-fissures in the search area, and calculate the distance h between each microseismic event that may form through-fissures and the coal seam. (j) , select the distance h (j) The maximum value h max , where j represents the sequence number of the microseismic event that may form a through-fracture;

[0017] The search area is a cylinder formed vertically upward with O, the lowest resistivity point, as the center and R=10 as the search radius;

[0018] Taking the lowest resistivity point O as the starting point and R = 10 as the cylindrical search radius, a search area is formed, and microseismic events that may form through-fissures in the longitudinal area within the search area are found, and the distance h between all microseismic events that may form through-fissures and the coal seam is obtained. (j) , select the distance h (j) The maximum value h max , where j represents the sequence number of the microseismic event that may form a through-fracture;

[0019] Step 6: Calculate the coupling water inrush coefficient η according to the following formula. If the coupling water inrush coefficient η is less than 0.6, there is no water inrush. Otherwise, water inrush may occur.

[0020] η=(h max +h') / H0.

[0021] The method of screening and obtaining microseismic events that may form through-fissures in the roof rock layer according to microseismic event parameters specifically includes the following steps:

[0022] S1, screen out the microseismic events within 0-2 m above the top plate of the working face to form a spatial domain #1, and calculate the connectivity α of any two microseismic events in the spatial domain #1 according to formula (1). If α is greater than 1, the two microseismic events are considered to be microseismic events that may form through-fissures; if α is less than 1, the two microseismic events are considered to be microseismic events that cannot form through-fissures;

[0023]

[0024] Where:

[0025] Ri and R j are the source radii of two microseismic events respectively;

[0026] x i , y i and z i are the coordinates of the microseismic event;

[0027] xj, yj and zj are the coordinates of the microseismic event;

[0028] S2. Screen out the microseismic events within n to (n + 2) meters above the working face roof to form a spatial domain m. Calculate using formula (1) for all the microseismic events in the spatial domain (m - 1) and any microseismic event in the spatial domain m to obtain the connectivity α between any two microseismic events in the two spatial domains. If the connectivity α between any two microseismic events all satisfies α < 0.7, there is no water inrush situation; if there exists a connectivity α greater than 1, it is considered that the two microseismic events corresponding to this connectivity α are microseismic events that may form connected fissures; if there exists 0.7 ≤ α < 1, then take the two microseismic events corresponding to the maximum value of the connectivity α that satisfy this condition as the microseismic events that may form connected fissures;

[0029] wherein, the value range of n is 2, 4, 6...; the value range of m is 2, 3, 4...;

[0030] S3. Let n = n + 2, m = m + 1, return to S2 until n + 2 is equal to the thickness of the roof rock stratum, and enter step four.

[0031] The determination of the initial resistance value of the roof rock stratum based on the resistivity change data and the determination of the distance h' between the resistivity lowest point O and the roof water body specifically include the following steps:

[0032] Q1. Before the start of mining, the resistivity monitoring system obtains the initial resistance value of the roof rock stratum;

[0033] The initial resistance value of the roof rock stratum includes the resistivity D1 of the roof water body and the resistivity D2 of the roof rock stratum;

[0034] Q2. Judge whether the resistivity change data D i collected by the resistivity monitoring system in real time in the roof rock stratum i satisfies D i < D1. If it is satisfied, take the spatial coordinate C di (x di , y di , z di ) corresponding to this resistivity change data D as the resistivity lowest point O and enter Q4; if it is not satisfied, enter Q3.

[0035] Q3. Determine the resistivity change data D of the roof rock formation collected in real time by the resistivity monitoring system i Whether it satisfies D1 < D i < D2. If it is satisfied, then use the spatial coordinates C i corresponding to the resistivity change data D di (x di , y di , z di ) as the point O with the lowest resistivity, and enter Q4. If it is not satisfied, there is no water inrush situation;

[0036] Q4. Calculate the distance h' between the point O with the lowest resistivity and the roof water level.

[0037] Compared with the prior art, the beneficial technical effects of the present invention are as follows:

[0038] (Ⅰ) In the present invention, a microseismic monitoring system is used to monitor in real time whether there are microseismic events in the roof rock formation that may form through-going fractures, and the positions of the microseismic events that may form through-going fractures are accurately obtained; a resistivity monitoring system is used to monitor the resistivity change data D i in the roof rock formation in real time, so as to judge the distance h' between the point O with the lowest resistivity in the roof rock formation and the roof water body; then, by calculating the distance h (j) between the microseismic events that may form through-going fractures found in the search area and the coal seam, the coupling water inrush coefficient η of the roof rock formation is calculated by the distance h' and the distance, realizing the quantitative embodiment of the probability of water inrush events, more accurately locating the water-conducting channel, obtaining the early warning situation, and solving the technical problem that the existing mine water disaster monitoring methods cannot judge the water inrush phenomenon in real time and accurately.

[0039] (Ⅱ) The present invention couples the microseismic events and resistivity monitoring, realizing the effective identification of the whole process monitoring from the fracture development, expansion to the occurrence of water inrush through fracture penetration, which is of great significance for further improving the monitoring effect and for mine water disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the method of the present invention.

[0041] The following further explains the specific content of the present invention in detail with reference to the embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0042] It should be noted that all the components in the present invention, without special instructions, are components known in the art.

[0043] The following gives specific embodiments of the present invention. It should be noted that the present invention is not limited to the following specific embodiments, and all equivalent transformations made on the basis of the technical solution of the present application fall within the protection scope of the present invention.

[0044] The present invention provides a method for predicting water inrush from the roof of coal seams based on microseismic and resistivity monitoring. The underground geological distribution from bottom to top is successively coal seams, roof rock strata, and roof water bodies, and specifically includes the following steps:

[0045] Step 1: Determine the water-bearing characteristics of the overlying strata of the working face, determine the distribution of water-rich abnormal areas, the development of geological structures, and the water-conducting properties of geological structures in the mining area, and determine the distance H0 between the coal seam and the roof water body;

[0046] Step 2: Install a microseismic monitoring system and a resistivity monitoring system in the underground roadway;

[0047] Step 3: The microseismic monitoring system obtains and processes energy waveform data in real time, filters the data, determines microseismic event parameters, and determines whether there are microseismic events in the roof rock strata that may form through-going fractures based on the microseismic event parameters. If so, obtain the microseismic events in the roof rock strata that may form through-going fractures, otherwise there is no water inrush situation;

[0048] The microseismic event parameters include the number of microseismic events, the spatial location of each microseismic event, the source parameters of each microseismic event, and the time when each microseismic event occurs;

[0049] Step 4: The resistivity monitoring system obtains and processes resistivity change data in real time, determines the initial resistance value of the roof rock strata based on the resistivity change data, and determines whether the resistivity change data D i in the roof rock strata collected in real time satisfies D i < D1 or D1 < D i < D2. If so, take the spatial coordinates C i corresponding to the resistivity change data D di (x di ,y di ,z di ) as the point O with the lowest resistivity, and calculate the distance h' between the point O with the lowest resistivity and the roof water body, otherwise there is no water inrush situation;

[0050] The initial resistance value of the roof rock strata includes the resistivity D1 of the roof water body and the resistivity D2 of the roof rock strata;

[0051] Step 5: Search for microseismic events that may form through-going fractures in the search area, calculate the distance h (j) between each microseismic event that may form through-going fractures and the coal seam, and select the maximum value h (j) in h max , where j represents the serial number of the microseismic event that may form through-going fractures;

[0052] The search area is a cylinder formed vertically upward with O, the lowest resistivity point, as the center and R=10 as the search radius;

[0053] Taking the lowest resistivity point O as the starting point and R = 10 as the cylindrical search radius, a search area is formed to find the microseismic events that may form through-fissures in the longitudinal area within the search area, and the distance h between all microseismic events that may form through-fissures and the coal seam is obtained. (j) , select the distance h (j) The maximum value h max , where j represents the sequence number of the microseismic event that may form a through-fracture;

[0054] Step 6: Calculate the coupling water inrush coefficient η according to the following formula. If the coupling water inrush coefficient η is less than 0.6, there is no water inrush. Otherwise, water inrush may occur.

[0055] η=(h max +h') / H0.

[0056] Preferably, when the calculated coupling water inrush coefficient η is greater than 0.6, when the coupling water inrush coefficient η belongs to different ranges, the possibility of water inrush represented is different. The larger the coupling water inrush coefficient η, the greater the possibility of water inrush. In engineering practice, when η≥0.9, the red light is on; when 0.9>η≥0.8, the orange light is on; when 0.8>η≥0.7, the yellow light is on; when 0.7>η≥0.6, the blue light is on; these indicate the possibility of water inrush from large to small, respectively, and then prompt the on-site operators to take corresponding countermeasures.

[0057] In this application, firstly, a microseismic monitoring system is used to monitor in real time whether there are microseismic events that may form through cracks in the roof rock layer to determine whether there is water inrush; then a resistivity monitoring system is used to monitor in real time the resistivity change data D in the roof rock layer. i , by comparing the resistivity change data D i and initial resistivity to determine whether there is water inrush. Finally, microseismic events that may form through-fissures are found in the search area formed by the lowest resistivity point O as the center of the circle, and the distance h between each microseismic event that may form through-fissures and the coal seam is calculated. (j) , and then calculate the coupled water inrush coefficient η to determine whether there is a water inrush situation, which realizes the quantitative reflection of the probability of water inrush events, more accurately locates the water conduction channel, obtains early warning conditions, and solves the technical problem that the existing mine water hazard monitoring methods cannot judge the water inrush phenomenon in real time and accurately.

[0058] In the above technical solution, the necessary conditions for the occurrence of water sudden disasters are: water body and fissure channel.

[0059] First, under non-mining conditions, the resistivity can be used to detect water bodies in the mining area by deploying resistivity. The resistivity in and near the water body will be significantly lower than that in other locations, and then it will envelop a rough bottom area of ​​the aquifer. At the same time, under the influence of mining, the bottom area of ​​the aquifer will become larger due to the influence of water pressure and mine pressure, and approach the empty area of ​​the coal mining face.

[0060] Microseismic detection is used to detect cracks formed by mining, and mining cracks develop from the roof near the coal mining face to the long distance (near the water body). That is to say, the closer to the void area formed by mined coal (coal mining face), the more cracks there will be. However, as they continue upward (closer to the shallow water body at a distance from the roof), they will gradually decrease and disappear. Even if there is water in the mining area, if the cracks formed by our mining disappear before reaching the bottom of the aquifer, that is to say, the mining cracks have not developed near the water body, or the connectivity between the mining damage obtained by microseismic detection is very poor, then water inrush will not occur.

[0061] Therefore, the two resistivity tests and microseismic monitoring are combined. If the range of the water body and the range of the mining cracks overlap in space, then different degrees of early warning should be given. And it should also be combined with the crack connectivity recognized by microseismic.

[0062] In other words, the resistivity detects the presence of water, but the channel is not affected and water inrush will not occur. Furthermore, even if the mining fissures are very high and extend very far to the roof, there is no need to consider early warning if the water body does not change and there is no water. This solves the problem of two-way constraints on the formation of water hazards.

[0063] The construction of the microseismic monitoring system includes the following steps: laying microseismic detectors along the roof drilling to the key layer, and connecting the lines to the signal receiver, underground stations and ground data monitoring and processing host; arranging the microseismic detectors on the rock wall within the fractured rock mass; laying shielded communication cables, connecting the microseismic detectors, underground stations and ground data monitoring and processing host in sequence; installing data substations and underground monitoring hosts at the bottom of the project to obtain and transmit real-time data to the surface data storage and processing terminal; completing the correspondence between the microseismic detectors and each workstation through active tapping debugging; and obtaining energy waveform data (i.e., roof rupture signals) during the mining process in real time.

[0064] The construction of the microseismic monitoring system includes the following steps: laying electrodes along the top plate through drilling holes to the key layer, connecting the signal receiver, underground stations and the ground data monitoring and processing host; arranging the electrodes and microseismic detectors at intervals; installing data substations and underground monitoring hosts at the bottom of the project to obtain and transmit real-time data to the surface data storage and processing terminal.

[0065] The above-mentioned construction of the microseismic monitoring system and the method of constructing the microseismic monitoring system can be specifically referred to the following papers and Chinese patents CN202010731695.6, CN201811093560.0, CN201811093419.0 and CN202410850990.1;

[0066] [1] Li Nan, Wang Enyuan, GE Mao-chen. Microseismic monitoring technology and its application status and prospects in coal mines [J]. Journal of China Coal Society, 2017, 42(S1): 83-96. DOI: 10.13225 / j.cnki.jccs.2016.0852.

[0067] [2] Duan Jianhua. Comprehensive monitoring technology of water inrush from coal seam floor and its application[J]. Coal Geology and Exploration, 2020, 48(04): 19-28.

[0068] [3] Jin Dewu, Zhao Chunhu, Duan Jianhua, et al. Research on three-dimensional monitoring and intelligent early warning system of coal seam floor water hazards[J]. Journal of China Coal Society, 2020, 45(06): 2256-2264. DOI: 10.13225 / j.cnki.jccs.ZN20.0309.

[0069] [4] JIN Dewu, DUAN Jianhua, LI Lianchong, et al. Research on the identification technology of floor mining crack expansion and water channel based on microseismic[J]. Journal of Engineering Geology, 2021, 29(04): 962-971. DOI: 10.13544 / j.cnki.jeg.2021-0330.

[0070] [5] Duan Jianhua, Cheng Jianyuan, Wang Yunhong, et al. Automatic identification technology of microseismic events based on STA / LTA method [J]. Coal Geology and Exploration, 2015, 43(01): 76-80+85.

[0071] The microseismic events that may form through-cracks in the roof rock layer are screened according to the microseismic event parameters, specifically including the following steps:

[0072] S1, screen out the microseismic events within 0-2 m above the top plate of the working face to form a spatial domain #1, and calculate the connectivity α of any two microseismic events in the spatial domain #1 according to formula (1). If α is greater than 1, the two microseismic events are considered to be microseismic events that may form through-fissures; if α is less than 1, the two microseismic events are considered to be microseismic events that cannot form through-fissures;

[0073]

[0074] Where:

[0075] R iand R j are the source radii of two microseismic events respectively;

[0076] x i , y i and z i are the coordinates of the microseismic event;

[0077] x j , y j and z j are the coordinates of the microseismic event;

[0078] S2. Screen out the microseismic events within n to (n + 2) meters on the roof of the working face to form a spatial domain m. Calculate the connectivity α between any microseismic event in the spatial domain (m - 1) and any microseismic event in the spatial domain m using formula (1). If the connectivity α between any two microseismic events satisfies α < 0.7, there is no water inrush situation; if there is a connectivity α greater than 1, it is considered that the two microseismic events corresponding to this connectivity α are microseismic events that may form through-going fractures; if there is 0.7 ≤ α < 1, then take the two microseismic events corresponding to the maximum value of the connectivity α that satisfy this condition as the microseismic events that may form through-going fractures;

[0079] wherein, the value range of n is 2, 4, 6...; the value range of m is 2, 3, 4...;

[0080] S3. Let n = n + 2, m = m + 1, return to S2 until n + 2 is equal to the thickness of the roof rock stratum, and enter step four.

[0081] In the above technical solution, the larger the α value, the greater the probability that the microseismic events penetrate and cross to form cracks.

[0082] Determine the initial resistance value of the roof rock stratum according to the resistivity change data and determine the distance h' between the point O with the lowest resistivity and the roof water body, which specifically includes the following steps:

[0083] Q1. Before the start of mining, the resistivity monitoring system obtains the initial resistance value of the roof rock stratum;

[0084] The initial resistance value of the roof rock stratum includes the resistivity D1 of the roof water body and the resistivity D2 of the roof rock stratum;

[0085] Q2. Judge whether the resistivity change data D i collected by the resistivity monitoring system in real time within the roof rock stratum i satisfies D i < D1. If it is satisfied, then take the spatial coordinates C di (x di , y di , zdi ) As the point O with the lowest resistivity, enter Q4; if not satisfied, enter Q3.

[0086] In Q3, judge the resistivity change data D of the roof rock formation collected in real time by the resistivity monitoring system i Whether it satisfies D1 < D i < D2. If satisfied, take the spatial coordinates C i corresponding to the resistivity change data D di (x di , y di , z di ) as the point O with the lowest resistivity, enter Q4. If not satisfied, there is no water inrush situation.

[0087] In Q4, calculate the distance h' between the point O with the lowest resistivity and the roof water level.

[0088] In the above technical solution, different rock masses will show different resistivity states. Especially under the influence of water, their overall resistivity will be relatively small. When there is no mining, the resistivity of the intact roof rock formation in the stope will generally be larger than that near the water body. At this time, there will be a large difference in resistivity as approaching the water body. The resistivity of the roof water body is determined as D1, and the resistivity of the roof rock formation is set as D2. By collecting the roof resistivity distribution during the mining process, the relative magnitudes of the resistivity at different positions and the resistivity of the aquifer can be obtained. If it is smaller than or close to it, etc., then there may be a water body in the roof rock formation.

Claims

1. A method for predicting water inrush from coal seam roof based on microseismic and resistivity monitoring, characterized in that: The underground geological distribution from bottom to top is coal seam, roof rock layer and roof water body, which specifically includes the following steps: Step 1: determine the water-bearing characteristics of the overlying rock formations on the working face, determine the distribution of abnormally water-rich areas in the mining area, the development of geological structures, and the conductivity and water-bearing properties of geological structures, and determine the distance H0 between the coal seam and the roof water body; Step 2: deploying microseismic monitoring system and resistivity monitoring system in underground tunnels; Step 3: The microseismic monitoring system acquires and processes the energy waveform data in real time, and performs filtering processing on it to determine the microseismic event parameters. According to the microseismic event parameters, it is judged whether there is a microseismic event that may form a through-crack in the roof rock layer. If yes, a microseismic event that may form a through-crack in the roof rock layer is obtained; otherwise, there is no water inrush. The microseismic event parameters include the number of microseismic events, the spatial location of each microseismic event, the source parameters of each microseismic event and the time when each microseismic event occurs; Step 4: The resistivity monitoring system obtains and processes the resistivity change data in real time, determines the initial resistance value of the roof rock formation according to the resistivity change data, and judges the resistivity change data D in the roof rock formation collected in real time according to the initial resistance value of the roof rock formation i whether it satisfies D i < D1 or D1 < D i < D2. If so, the spatial coordinates C i corresponding to the resistivity change data D di (x di , y di , z di ) are used as the point O with the lowest resistivity, and the distance h' between the point O with the lowest resistivity and the roof water body is calculated. Otherwise, there is no water inrush situation; The initial resistance value of the roof rock layer includes the resistivity D1 of the roof water body and the resistivity D2 of the roof rock layer; Step 5: Find the microseismic events that may form through-fissures in the search area, and calculate the distance h between each microseismic event that may form through-fissures and the coal seam. (j) , select the distance h (j) The maximum value h max , where j represents the sequence number of the microseismic event that may form a through-fracture; The search area is a cylinder formed vertically upward with O, the lowest resistivity point, as the center and R=10 as the search radius; Taking the lowest resistivity point O as the starting point and R = 10 as the cylindrical search radius, a search area is formed, and microseismic events that may form through-fissures in the longitudinal area within the search area are found, and the distance h between all microseismic events that may form through-fissures and the coal seam is obtained. (j) , select the distance h (j) The maximum value h max , where j represents the sequence number of the microseismic event that may form a through-fracture; Step 6: Calculate the coupling water inrush coefficient η according to the following formula. If the coupling water inrush coefficient η is less than 0.6, there is no water inrush. Otherwise, water inrush may occur. η=(h max +h') / H0.

2. The method for predicting water inrush from coal seam roof based on microseismic and resistivity monitoring as claimed in claim 1, characterized in that: The method of screening and obtaining microseismic events that may form through-fissures in the roof rock layer according to microseismic event parameters specifically includes the following steps: S1, screen out the microseismic events within 0-2 m above the top plate of the working face to form a spatial domain #1, and calculate the connectivity α of any two microseismic events in the spatial domain #1 according to formula (1). If α is greater than 1, the two microseismic events are considered to be microseismic events that may form through-fissures; if α is less than 1, the two microseismic events are considered to be microseismic events that cannot form through-fissures; Where: R i and R j are the focal radii of the two microseismic events respectively; x i ,y i and z i are the coordinates of the microseismic event; x j ,y j and z j are the coordinates of the microseismic event; S2, screen out the microseismic events within n to (n+2) meters on the top plate of the working face to form a spatial domain m, and calculate all the microseismic events in the spatial domain (m-1) with any microseismic event in the spatial domain m using formula (1) to obtain the connectivity α of any two microseismic events in the two spatial domains. If the connectivity α of any two microseismic events satisfies α<0.7, there will be no water inrush. If there is a connectivity α greater than 1, the two microseismic events corresponding to the connectivity α are considered to be microseismic events that may form through-fissures. If there is 0.7≤α<1, the two microseismic events corresponding to the maximum connectivity α that satisfies this condition are considered to be microseismic events that may form through-fissures. Among them, the value range of n is 2, 4, 6...; the value range of m is 2, 3, 4...; S3, let n=n+2, m=m+1, return to S2, until n+2 is equal to the thickness of the roof rock layer, and enter step 4.

3. The method for predicting water inrush from coal seam roof based on microseismic and resistivity monitoring as claimed in claim 1, characterized in that: Determining the initial resistance value of the roof rock layer and the distance h' between the lowest resistivity point O and the roof water body according to the resistivity change data specifically includes the following steps: Q1, before starting mining, the resistivity monitoring system obtains the initial resistance value of the roof rock layer; The initial resistance value of the roof rock layer includes the resistivity D1 of the roof water body and the resistivity D2 of the roof rock layer; Q2. Determine whether the resistivity change data D collected in real time by the resistivity monitoring system in the roof rock formation i satisfies D i < D1. If it is satisfied, the corresponding spatial coordinates C i of the resistivity change data D di (x di , y di , z di ) are used as the point O with the lowest resistivity and enter Q4; if not satisfied, enter Q3. Q3, determine whether the resistivity change data D collected in real time by the resistivity monitoring system in the roof rock formation i satisfies D1 < D i < D2. If it is satisfied, the corresponding spatial coordinates C i of the resistivity change data D di (x di , y di , z di ) are taken as the point O with the lowest resistivity, and enter Q4. If not satisfied, there is no water inrush situation; Q4, calculate the distance h' between the lowest resistivity point O and the top water level.

Images