Mine water inrush progressive composite early warning method based on micro-seismic monitoring

Abstract

The invention relates to a progressive composite early warning method for mine water inrush based on micro-seismic monitoring, which is characterized in that a high-precision micro-seismic monitoring system fully covering a top plate and a bottom plate can effectively and comprehensively collect full-seismic field information in real time, and can greatly improve the vertical positioning precision of a micro-seismic event; meanwhile, a comprehensive and rich micro-seismic data index library is established, a calculation method of a core data variation rate is provided, different early warning data core indexes and auxiliary indexes are matched for different water inrush types, and corresponding index early warning values are calculated; the development position and development degree of a potential water inrush channel are obtained through quantitative analysis of the damage degree of a floor water-resisting layer based on a micro-seismic monitoring system, and a four-level water inrush degree early warning level is formed; finally, the index early warning value and the channel early warning value are integrated, double early warning of the time progress and the space position is achieved, the corresponding early warning level is determined according to the floor water inrush composite early warning level table, progressive composite early warning is achieved, and safety production is guided to have a basis.

Description

Technical Field

[0001] The invention relates to the technical field of coal mine safety monitoring, and in particular to a progressive composite early warning method for mine water inrush based on microseismic monitoring. Background Art

[0002] The hidden danger of floor water inrush has become one of the important factors restricting the safe mining of deep coal resources in coal mines in the central and eastern regions. The process of coal mine floor water inrush is a process of damage and fracture caused by the coupling of mining disturbance and confined water infiltration in the floor water-proof rock layer. The mechanism of action is complex and has a great impact on the safe production of coal mines. For a long time, the research on the mechanism of coal mine floor water inrush has focused on the mining stress field, floor rock damage and confined water seepage field, but these factors cannot explain the entire mechanism of coal seam floor water inrush. The influence of roof collapse, rock burst pressure, etc. on floor water inrush is mainly due to dynamic load. When these dynamic manifestations occur, a large amount of energy will be released in a concentrated manner, involving a range of several hundred meters. The generated dynamic load may completely affect the floor water-bearing (impermeable) layer. It can be seen that there is a close relationship between the floor water inrush and dynamic load disturbance in the mining area.

[0003] The mining thickness of the deep fully mechanized caving working face is large. The hard and complete thick roof rock layer is not easy to collapse during the mining process due to its high strength, and a large area of ​​suspended roof is often formed. When the working face advances to a certain distance, the roof rock layer will break and collapse on a large scale, resulting in instantaneous instability of the large structure of the overburden, and even causing avalanche-like chain failure of a large range of suspended roofs, causing large-scale collapse of the roof rock layer. The collapsed roof rock mass moves rapidly to the goaf. Due to its large movement amplitude and high impact energy, the heavy and hard thick roof plate directly acts on the bottom rock layer, which will produce a huge impact dynamic load on the bottom plate of the mining area. The dynamic load generated is extremely destructive, sometimes causing the sudden cracking and bulging of the bottom plate to connect to the roof, and even causing water inrush accidents at the working face.

[0004] Previous studies have shown that the mine floor water inrush monitoring and early warning system based on microseismic monitoring technology is becoming more and more widely used. Its monitoring principle is that the floor water-blocking rock layer produces cracks under the coupling of mining disturbance and confined water infiltration. The stress waves generated during the rock mass rupture are collected by the microseismic monitoring system. The microseismic system determines the rupture information of the rock mass through positioning and energy calculation, and then evaluates whether the water-blocking rock layer can develop into a water inrush channel, and finally issues a water inrush early warning. As a powerful geophysical field monitoring method, microseismic monitoring technology establishes a rock mass spatial rupture field evolution model based on microseismic positioning results, and realizes advanced early warning of floor water inrush monitoring by multi-angle and multi-level display of microseismic events and multi-field (seepage field, stress field, etc.) coupling means.

[0005] To achieve accurate early warning, the following key issues need to be resolved: ① At present, the mechanical mechanism research of floor water inrush mostly considers the static load effects such as the support pressure and the pressure water pressure of the mining area, but does not consider the influence of strong dynamic disturbance on floor water inrush; floor water inrush is the result of the combined action of dynamic load and static load, and the theoretical research using dynamic load or static load alone cannot reflect the objective situation most realistically. It is necessary to fully analyze the impact of roof rock collapse that induces floor water inrush in the mining area; ② The vibration information collected by the microseismic monitoring system is very rich, including a large number of small energy events and a small proportion of large energy events. If all the small energy events caused by mining disturbance and construction impact are simply calculated during the early warning, it will have a great impact on the accuracy of the early warning results; ③ The early warning mechanism of floor water inrush under the combined action of dynamic and static loads is very complex. The early warning method that simply relies on indicator warning or channel warning has great limitations. It is urgent to propose a composite early warning method that integrates multiple early warning methods. Summary of the invention

[0006] In order to make up for the deficiencies in the prior art, the present invention provides a progressive composite early warning method for bottom plate water inrush based on microseismic monitoring, which includes indicator early warning and channel early warning.

[0007] (1) A high-precision microseismic monitoring system that fully covers the roof and floor of the coal seam

[0008] A broadband and high-precision microseismic monitoring system is adopted, and a spatial three-dimensional network is deployed around the main mining area to realize the collection of wide-band vibration signals generated by surrounding rock fractures during mining. The system monitoring results cover vibration events caused by micro-fractures of coal bodies and surrounding rocks (mainly presented as high-frequency, medium-high-frequency, small-energy events), vibration events caused by large-scale fractures of top and bottom plate rock strata (mainly presented as medium-low-frequency, low-frequency, large-energy events), and vibration events caused by large-scale structural mining activation (mainly presented as low-frequency, medium-low-frequency, large-energy events).

[0009] (2) Indicator warning method based on water inrush type and dominant factor analysis

[0010] 1) Classify the attributes of microseismic events; intelligently classify them according to the calculation results of the system (occurrence time, spatial location, energy, magnitude, main frequency, etc. of microseismic events), mainly into coal seam microfracture events, roof rock stratum microfracture events, floor rock stratum microfracture events, low-level roof rock stratum break events, high-level roof rock stratum break events, floor rock stratum break events, tectonic activation events, etc.;

[0011] 2) Establish a microseismic data index database

[0012] ① Total frequency of events per unit time (optional day, shift, etc.), total energy of events per unit time, average energy of events per unit time, variation rate of total frequency of events per unit time (percentage exceeding or below the average), variation rate of total energy of events per unit time, variation rate of average energy of events per unit time, total frequency of events per unit advancement (optional 5m, 10m, etc.), total energy of events per unit advancement, average energy of events per unit advancement, variation rate of total frequency of events per unit advancement, variation rate of total energy of events per unit advancement, variation rate of average energy of events per unit advancement;

[0013] ② Frequency of coal seam microfracture events per unit time, total energy of coal seam microfracture events per unit time, average energy of coal seam microfracture events per unit time, frequency of coal seam microfracture events per unit advancement, total energy of coal seam microfracture events per unit advancement, average energy of coal seam microfracture events per unit advancement, variation rate of coal seam microfracture event frequency per unit time, variation rate of total energy of coal seam microfracture events per unit time, variation rate of average energy of coal seam microfracture events per unit time, variation rate of coal seam microfracture event frequency per unit advancement, variation rate of total energy of coal seam microfracture events per unit advancement, variation rate of average energy of coal seam microfracture events per unit advancement;

[0014] ③ The frequency of roof rock microfracture events per unit time, the total energy of roof rock microfracture events per unit time, the average energy of roof rock microfracture events per unit time, the frequency of roof rock microfracture events per unit advancement, the total energy of roof rock microfracture events per unit advancement, the average energy of roof rock microfracture events per unit advancement, the variation rate of the frequency of roof rock microfracture events per unit time, the variation rate of the total energy of roof rock microfracture events per unit time, the variation rate of the average energy of roof rock microfracture events per unit time, the variation rate of the frequency of roof rock microfracture events per unit advancement, the variation rate of the total energy of roof rock microfracture events per unit advancement, and the variation rate of the average energy of roof rock microfracture events per unit advancement;

[0015] ④ The frequency of floor rock microfracture events per unit time, the total energy of floor rock microfracture events per unit time, the average energy of floor rock microfracture events per unit time, the frequency of floor rock microfracture events per unit advancement, the total energy of floor rock microfracture events per unit advancement, the average energy of floor rock microfracture events per unit advancement, the variation rate of the frequency of floor rock microfracture events per unit time, the variation rate of the total energy of floor rock microfracture events per unit time, the variation rate of the average energy of floor rock microfracture events per unit time, the variation rate of the frequency of floor rock microfracture events per unit advancement, the variation rate of the total energy of floor rock microfracture events per unit advancement, and the variation rate of the average energy of floor rock microfracture events per unit advancement;

[0016] ⑤ The frequency of low-level roof rock stratum breaking events per unit time, the total energy of low-level roof rock stratum breaking events per unit time, the average energy of low-level roof rock stratum breaking events per unit time, the frequency of low-level roof rock stratum breaking events per unit advancement, the total energy of low-level roof rock stratum breaking events per unit advancement, the average energy of low-level roof rock stratum breaking events per unit advancement, the variation rate of the frequency of low-level roof rock stratum breaking events per unit time, the variation rate of the total energy of low-level roof rock stratum breaking events per unit time, the variation rate of the average energy of low-level roof rock stratum breaking events per unit time, the variation rate of the frequency of low-level roof rock stratum breaking events per unit advancement, the variation rate of the total energy of low-level roof rock stratum breaking events per unit advancement, and the variation rate of the average energy of low-level roof rock stratum breaking events per unit advancement;

[0017] ⑥ The frequency of high-level roof rock stratum breaking events per unit time, the total energy of high-level roof rock stratum breaking events per unit time, the average energy of high-level roof rock stratum breaking events per unit time, the frequency of high-level roof rock stratum breaking events per unit advancement, the total energy of high-level roof rock stratum breaking events per unit advancement, the average energy of high-level roof rock stratum breaking events per unit advancement, the variation rate of the frequency of high-level roof rock stratum breaking events per unit time, the variation rate of the total energy of high-level roof rock stratum breaking events per unit time, the variation rate of the average energy of high-level roof rock stratum breaking events per unit time, the variation rate of the frequency of high-level roof rock stratum breaking events per unit advancement, the variation rate of the total energy of high-level roof rock stratum breaking events per unit advancement, and the variation rate of the average energy of high-level roof rock stratum breaking events per unit advancement;

[0018] ⑦ The frequency of floor rock breaking events per unit time, the total energy of floor rock breaking events per unit time, the average energy of floor rock breaking events per unit time, the frequency of floor rock breaking events per unit advancement, the total energy of floor rock breaking events per unit advancement, the average energy of floor rock breaking events per unit advancement, the variation rate of the frequency of floor rock breaking events per unit time, the variation rate of the total energy of floor rock breaking events per unit time, the variation rate of the average energy of floor rock breaking events per unit time, the variation rate of the frequency of floor rock breaking events per unit advancement, the variation rate of the total energy of floor rock breaking events per unit advancement, and the variation rate of the average energy of floor rock breaking events per unit advancement;

[0019] ⑧ Frequency of structural activation events per unit time, total energy of structural activation events per unit time, average energy of structural activation events per unit time, frequency of structural activation events per unit advancement, total energy of structural activation events per unit advancement, average energy of structural activation events per unit advancement, variation rate of structural activation event frequency per unit time, variation rate of total energy of structural activation events per unit time, variation rate of average energy of structural activation events per unit time, variation rate of structural activation event frequency per unit advancement, variation rate of total energy of structural activation events per unit advancement, variation rate of average energy of structural activation events per unit advancement;

[0020] (3) Calculation of core data mutation rate

[0021] The core data anomaly rate of microseismic events is calculated based on the microseismic system monitoring results and the data indicator library.

[0022] ① Basic data: frequency of events per unit time N T , the frequency of events within a unit advancement degree N S , the frequency unit average value N of the event in n unit time TA , the frequency unit average value of events within n unit advancement N SA , the total energy of the event per unit time E TZ , the total energy of events within a unit of advancement E SZ , the total energy unit average value E of the event in n unit time TZA , the total energy unit average value E of events within n unit advancement SZA , the average energy of the event per unit time E TP , the average energy of events per unit propulsion degree E SP , the average energy of events in n unit time, the average value E TPA , the average energy unit average value E of events within n unit advancement SPA ;

[0023] ②Frequency variation rate δ N , including the frequency variation rate of events per unit time δ NT , the frequency variation rate of events within a unit advancement degree δ NS ;

[0024] ③Energy variation rate δ E , including the total energy variation rate of events per unit time δ ETZ , the total energy variation rate of events within a unit advancement degree δ ESZ , the average energy variation rate of events per unit time δ ETP , the average energy variation rate of events within a unit advancement degree δ ESP .

[0025] The core data mutation rate calculation formula includes the frequency mutation rate formula and the energy mutation rate formula.

[0026] The frequency variation rate calculation formula is:

[0027]

[0028] The total energy variation rate calculation formula is:

[0029]

[0030] The calculation formula of average energy variation rate is:

[0031]

[0032] Among them: δ-variability, N-frequency, T-time, S-advancement, E-energy, Z-total (energy), P-average (energy), A-average value.

[0033] (4) Analysis of water inrush types and dominant factors

[0034] The formation process of the bottom plate water inrush channel is a process in which the bottom plate water-blocking rock layer is damaged and fractured by the coupling effect of mining disturbance and pressurized water infiltration. The action mechanism is complex and affected by many factors. If all data indicators are used for early warning, the data volume will be huge, the processing process will be complex, the pertinence will not be strong, and the early warning efficiency will be low. Therefore, it is necessary to analyze the type of water inrush threat faced by the monitored working face and the main factors restricting this type of water inrush.

[0035] ① Simple bottom plate driven type: This type of bottom plate water inrush is mainly caused by the rupture of the bottom plate impermeable rock layer during the stress field adjustment process under mining disturbance; the geological and hydrogeological characteristics of the working face where this type of water inrush occurs are: shallow burial depth, low strength of the top plate rock layer, insignificant dynamic load effect, the destruction of the bottom plate rock layer is mainly caused by the concentrated stress generated by static load, the bottom plate impermeable layer rock mass is relatively complete (no or few geological defects), the water pressure of the aquifer is large or the water inrush coefficient is large, etc.

[0036] ② Roof dynamic load driven type: This type of bottom plate water inrush is mainly caused by the strong dynamic load generated by roof collapse, mine earthquake, etc., which causes impact damage to the bottom plate water-proof rock layer. On the basis of static load, the degree of bottom plate damage increases suddenly, forming a water inrush channel; the geological and hydrogeological characteristics of the working face where this type of water inrush occurs are: large burial depth, single or multiple thick hard rock layers on the roof, obvious dynamic load effect caused by overburden collapse during mining, the destruction of the bottom plate rock layer is caused by the combined action of dynamic and static loads, the bottom plate water-proof layer rock mass is relatively intact (no or few geological defects), the water pressure of the aquifer is large or the water inrush coefficient is large, etc.

[0037] ③ Structural activation driven type: This type of bottom plate water inrush is mainly caused by the activation of regional structures under the influence of mining to form water inrush channels. The existence of geological structures has destroyed the integrity of the impermeable layer, reducing the strength and water-proof performance of the rock mass in a certain area, and faults and other structures have shortened the distance between the coal seam and the aquifer, resulting in a significant increase in the possibility of the formation of water inrush channels. The geological and hydrogeological characteristics of the working face of this type of water inrush are: there are many structures or concealed structures in the mining area, faults and other structures have shortened the relative distance between the coal seam and the aquifer, the water pressure in the aquifer is large or the water inrush coefficient is large, etc.

[0038] ④ Dynamic load and structure complex type: This type of floor water inrush is dominated by two factors: dynamic load and structure. For example, the structure within a certain working face is complex and the dynamic load effect of mining is obvious. The dynamic load formed by mining activities may cause structural activation to form a water inrush channel.

[0039] (5) Warning data indicator matching

[0040] After determining the type of water inrush and the dominant factors of the working face, it is necessary to match the data indicators required for early warning for the working face:

[0041] ①Simple bottom plate driven matching index;

[0042] Core indicators (two categories): 12 sub-indicators in indicator library ④ and 12 sub-indicators in indicator library ⑦;

[0043] Auxiliary indicators (two categories): 12 sub-indicators in indicator library ① and 12 sub-indicators in indicator library ②.

[0044] ②Top plate dynamic load drive type matching index;

[0045] Core indicators (two categories): 12 sub-indicators in indicator library ⑥ and 12 sub-indicators in indicator library ④;

[0046] Auxiliary indicators (two categories): 12 sub-indicators in indicator library ⑦ and 12 sub-indicators in indicator library ⑤.

[0047] ③Construct activation-driven matching indicators;

[0048] Core indicators (two categories): 12 sub-indicators in indicator library ⑧ and 12 sub-indicators in indicator library ④;

[0049] Auxiliary indicators (two categories): 12 sub-indicators in indicator library ⑦ and 12 sub-indicators in indicator library ①.

[0050] ④ Dynamic load structure composite matching index;

[0051] Core indicators (two categories): 12 sub-indicators in indicator library ⑥ and 12 sub-indicators in indicator library ⑧;

[0052] Auxiliary indicators (two categories): 12 sub-indicators in indicator library ④ and 12 sub-indicators in indicator library ⑦.

[0053] (6) Determine the indicator warning level

[0054] For different types of water inrush, select appropriate indicator library data according to the early warning data indicator matching standard to calculate the indicator warning and obtain the indicator warning value:

[0055] δ=δ N +δ EZ +δ EP

[0056] Based on laboratory tests and engineering experience, the initial value of the indicator warning is determined to be X. When δ<X, no warning is given. When X<δ<2X, it is a first-level warning. When 2X<δ<3X, it is a second-level warning. When δ>3X, it is a third-level warning.

[0057] (7) Quantitative analysis of the degree of damage to the bottom waterproof layer and early warning of water inrush channels

[0058] The fracture network in each combined rock layer of the bottom plate aquiclude is vertically penetrated, which is a potential water inrush channel. The quantitative calculation of the damage degree of the entire aquiclude and the prediction of the location of the potential water inrush channel are divided into the following steps:

[0059] 1 Based on the geological drilling data in the working face, the aquiclude is vertically divided into several aquicludes of the same thickness. In the quantitative analysis process, the lithology of each aquiclude needs to be defined;

[0060] 2. For the microseismic events captured by the microseismic monitoring system during the mining process of the working face, they are divided into each water-proof layer according to their spatial position, and the plane distribution results of the energy kernel density value of each water-proof layer are calculated. On this basis, contour lines are drawn and filled into cloud maps with gradient color bars; on the premise of clarifying the lithology of the water-proof layer, the initial damage warning value WJ / m2 of the corresponding water-proof layer is determined through laboratory tests and engineering experience (that is, the area ≥ the warning value has met the conditions for being a water inrush channel), and in the process of applying the initial warning value, it is continuously optimized and corrected in combination with the engineering situation;

[0061] 3. Keep the plane coordinates consistent, superimpose the plane cloud map results of all water-blocking layers in the vertical position, and display them in a three-dimensional effect. According to the damage areas delineated by each water-blocking layer, analyze their overlap in the vertical position to obtain the development position and development degree of the potential water inrush channel;

[0062] 4 Based on the analysis results of the third step (i.e., the overlap of the damage areas of each water-proof layer in the vertical position), the bottom plate water inrush warning level is set, and the ratio of the number of water-proof layers with overlapping damage areas in the vertical position to the total number of water-proof layers is set to K. When K < 1 / 4, it is considered that there is no water inrush danger at this location (no warning); when 1 / 4 ≤ K < 1 / 2, it is considered that there is a weak water inrush danger at this location (level 1 warning); when 1 / 2 ≤ K < 3 / 4, it is considered that there is a moderate water inrush danger at this location (level 2 warning); and when K ≥ 3 / 4, it is considered that there is a strong water inrush danger at this location (level 3 warning).

[0063] 5 As the working face advances, the number of microseismic events in the impermeable layer collected by the microseismic monitoring system continues to increase. It is necessary to recalculate the distribution of the energy kernel density values ​​of each impermeable layer at a certain interval (which can be set), and repeat the third and fourth steps to achieve dynamic early warning during mining.

[0064] (8) A progressive composite warning method for bottom water inrush based on microseismic monitoring, which includes indicator warning and channel warning, is proposed. The indicator warning value and channel warning value are combined to realize dual warning of time progress and spatial position. A composite warning level table for bottom water inrush is defined. The corresponding warning level can be determined according to the composite superposition result of the two values, thus realizing a progressive composite warning.

[0065] The beneficial effects of the present invention are as follows: the system and analysis method are mainly used to comprehensively monitor the roof movement and floor damage during the mining process of the working face. The high-precision microseismic monitoring system that fully covers the roof and floor can effectively and comprehensively collect the entire vibration field information in real time, and can greatly improve the vertical positioning accuracy of microseismic events; at the same time, the present invention establishes a comprehensive and rich microseismic data indicator library, proposes a calculation method for the core data variation rate, matches different early warning data core indicators and auxiliary indicators for different water inrush types, and calculates corresponding indicator warning values; through quantitative analysis of the degree of damage to the floor aquiclude based on the microseismic monitoring system, the development position and degree of potential water inrush channels are obtained, and a four-level water inrush degree warning level is formed; finally, the indicator warning value and the channel warning value are combined to realize the dual warning of time progress and spatial position, and according to the floor water inrush composite warning level table, the corresponding warning level is determined to realize progressive composite warning, so as to provide guidance for safe production. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a schematic diagram of the structure of the full-coverage high-precision microseismic monitoring system of the present invention;

[0067] Figure 2 This is a three-dimensional rendering of the development of the water-inrushing channel of the bottom plate of the present invention;

[0068] Figure 3 This is a composite early warning flow chart for monitoring water inrush from the bottom plate in the present invention;

[0069] Figure 4 It is the warning level table of the present invention. DETAILED DESCRIPTION

[0070] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Generally, the components of the embodiments of the present invention described and shown in the accompanying drawings here can be arranged and designed in various different configurations.

[0071] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0072] Figure 1-Figure 4 This is a specific embodiment of the present invention, which is mainly aimed at coal seams threatened by floor pressurized water. By adopting the floor water inrush composite warning method based on microseismic monitoring and dynamic load analysis described in this embodiment, it is possible to comprehensively monitor the roof movement and floor damage during the working face mining process, and conduct effective indicator warnings; quantitatively calculate the degree of damage in different areas of the floor through the floor water inrush channel warning method, and conduct graded warnings; use the indicator warning results and channel warning results to achieve dual warnings of spatial position and time progress, and determine the corresponding warning level according to the floor water inrush composite warning level table to achieve progressive composite warnings. The specific implementation methods are as follows:

[0073] Step 1: Use a broadband and high-precision microseismic monitoring system. The system structure is as follows: Figure 1 As shown. A three-dimensional network is deployed around the main mining area to collect wide-band vibration signals generated by surrounding rock fractures during mining. The system monitoring results cover vibration events caused by micro-fractures of coal bodies and surrounding rocks (mainly presented as high-frequency, medium-high-frequency, small-energy events), vibration events caused by large-scale fractures of top and bottom plate rock layers (mainly presented as medium-low-frequency, low-frequency, large-energy events), and vibration events caused by large-scale structural mining activation (mainly presented as low-frequency, medium-low-frequency, large-energy events).

[0074] Step 2: Classify the attributes of microseismic events

[0075] Based on the system's calculation results (occurrence time, spatial position, energy, magnitude, main frequency, etc. of microseismic events), intelligent classification is performed, mainly divided into coal seam micro-fracture events, roof rock stratum micro-fracture events, floor rock stratum micro-fracture events, low-level roof rock stratum breakage events, high-level roof rock stratum breakage events, floor rock stratum breakage events, tectonic activation events, etc.

[0076] Step 3: Establish a microseismic data index database

[0077] Eight microseismic data indicator libraries are established for overall events, coal seam microfracture events, roof rock microfracture events, floor rock microfracture events, low-level roof rock break events, high-level roof rock break events, floor rock break events, and tectonic activation events.

[0078] Step 4: Determine the water inrush type, analyze the dominant factors and match the early warning data indicator library

[0079] Analyze the types of water inrush threats faced by the monitored working face and the main factors restricting this type of water inrush, and match the early warning data indicator library.

[0080] ①Simple bottom plate driven matching index;

[0081] Core indicators (two categories): 12 sub-indicators in indicator library ④ and 12 sub-indicators in indicator library ⑦;

[0082] Auxiliary indicators (two categories): 12 sub-indicators in indicator library ① and 12 sub-indicators in indicator library ②.

[0083] ②Top plate dynamic load drive type matching index;

[0084] Core indicators (two categories): 12 sub-indicators in indicator library ⑥ and 12 sub-indicators in indicator library ④;

[0085] Auxiliary indicators (two categories): 12 sub-indicators in indicator library ⑦ and 12 sub-indicators in indicator library ⑤.

[0086] ③Construct activation-driven matching indicators;

[0087] Core indicators (two categories): 12 sub-indicators in indicator library ⑧ and 12 sub-indicators in indicator library ④;

[0088] Auxiliary indicators (two categories): 12 sub-indicators in indicator library ⑦ and 12 sub-indicators in indicator library ①.

[0089] ④ Dynamic load structure composite matching index;

[0090] Core indicators (two categories): 12 sub-indicators in indicator library ⑥ and 12 sub-indicators in indicator library ⑧;

[0091] Auxiliary indicators (two categories): 12 sub-indicators in indicator library ④ and 12 sub-indicators in indicator library ⑦.

[0092] Step 5: Calculation of core data mutation rate

[0093] The core data anomaly rate of microseismic events is calculated based on the monitoring results of the microseismic system and the data indicator library. The core data anomaly rate calculation formula includes the frequency anomaly rate formula and the energy anomaly rate formula.

[0094] The frequency variation rate calculation formula is:

[0095]

[0096] The total energy variation rate calculation formula is:

[0097]

[0098] The calculation formula of average energy variation rate is:

[0099]

[0100] Among them: δ-variability, N-frequency, T-time, S-advancement, E-energy, Z-total (energy), P-average (energy), A-average value.

[0101] Step 6: Determination of indicator warning level

[0102] For different types of water inrush, select appropriate indicator library data according to the early warning data indicator matching standard to calculate the indicator warning and obtain the indicator warning value:

[0103] δ=δ N +δ EZ +δ EP

[0104] Based on laboratory tests and engineering experience, the initial value of the indicator warning is determined to be X. When δ<X, no warning is given. When X<δ<2X, it is a first-level warning. When 2X<δ<3X, it is a second-level warning. When δ>3X, it is a third-level warning.

[0105] Step 7: Quantitatively calculate the degree of damage to each aquiclude and determine the location of potential water inrush channels

[0106] The fracture network within each combined rock layer of the bottom plate aquiclude penetrates vertically, which is a potential water inrush channel.

[0107] ① Based on the geological drilling data in the working face, the aquiclude is vertically divided into several aquicludes of the same thickness. The lithology of each aquiclude needs to be defined in the quantitative analysis process;

[0108] ② For the microseismic events captured by the microseismic monitoring system during the mining process of the working face, they are divided into each water-proof layer according to their spatial position, and the plane distribution results of the energy kernel density value of each water-proof layer are calculated. On this basis, the contour lines are drawn and filled into a cloud map with gradient color bars; on the premise of clarifying the lithology of the water-proof layer, the initial damage warning value WJ / m2 of the corresponding water-proof layer is determined through laboratory tests and engineering experience (that is, the area ≥ the warning value has met the conditions for being a water inrush channel), and in the process of applying the initial warning value, it is continuously optimized and corrected in combination with the engineering situation;

[0109] ③ Keep the plane coordinates consistent, superimpose the plane cloud map results of all water-blocking layers in the vertical position, and display them in a three-dimensional effect. According to the damage area delineated by each water-blocking layer, analyze its overlap in the vertical position to obtain the development position and development degree of the potential water inrush channel. Figure 2 shown.

[0110] Step 8: Quantitatively calculate the damage degree of the entire aquifer and determine the channel warning level

[0111] (1) Based on the analysis results of step 7 (i.e., the overlap of the damaged areas of each water-proofing layer in vertical position), set the warning level of floor water inrush, such as Figure 4 As shown in the figure, the ratio of the number of water-insulating layers overlapping the damaged areas in the vertical position to the total number of water-insulating layers is set to K. When K < 1 / 4, it is considered that there is no danger of water inrush at this location (no warning); when 1 / 4 ≤ K < 1 / 2, it is considered that there is a weak danger of water inrush at this location (first-level warning); when 1 / 2 ≤ K < 3 / 4, it is considered that there is a moderate danger of water inrush at this location (second-level warning); and when K ≥ 3 / 4, it is considered that there is a strong danger of water inrush at this location (third-level warning).

[0112] (2) As the working face advances, the number of microseismic events in the impermeable layer collected by the microseismic monitoring system continues to increase. It is necessary to recalculate the distribution of the energy kernel density values ​​of each impermeable layer at a certain interval (which can be set), and repeat the third and fourth steps to achieve dynamic early warning during mining.

[0113] Step 9: Based on microseismic monitoring, the progressive composite warning of floor water inrush includes indicator warning and channel warning. The comprehensive indicator warning value and channel warning value are used to realize the dual warning of time progress and spatial position, and the floor water inrush composite warning level table is defined. According to the composite superposition result of the two values, the corresponding warning level can be determined to realize the progressive composite warning. For the specific composite warning process, see Figure 3 .

Claims

1. A progressive composite early warning method for mine water inrush based on microseismic monitoring, characterized in that: The following steps are involved: S1, using a broadband and high-precision microseismic monitoring system, with a spatial three-dimensional network deployed around the main mining area, to collect broadband vibration signals generated by surrounding rock fractures during mining; the system monitoring results cover vibration events caused by microfractures of coal bodies and surrounding rocks, vibration events caused by large-scale fractures of roof and floor rock layers, and vibration events caused by large-scale structural mining activation; S2, classify the attributes of microseismic events, and intelligently classify them according to the calculation results of the system into coal seam microfracture events, roof rock stratum microfracture events, floor rock stratum microfracture events, low-level roof rock stratum breakage events, high-level roof rock stratum breakage events, floor rock stratum breakage events, and tectonic activation events; S3, establish a microseismic data index library, and establish 8 microseismic data index libraries for overall events, coal seam microfracture events, roof rock microfracture events, floor rock microfracture events, low-level roof rock break events, high-level roof rock break events, floor rock break events, and tectonic activation events; S4, determination of water inrush type, analysis of dominant factors and matching with early warning data indicator library, analysis of the type of water inrush threat faced by the monitored working face and the main factors restricting this type of water inrush, and matching with the early warning data indicator library; S5, calculate the core data abnormality rate, and calculate the core data abnormality rate of microseismic events according to the microseismic system monitoring results and the data indicator library; S6, determine the indicator warning level, for different water inrush types, select appropriate indicator library data according to the warning data indicator matching standard to calculate the indicator warning, and obtain the indicator warning value: d=d N +d EZ +d EP According to laboratory tests and engineering experience, the initial value of the indicator warning is determined to be X. When δ<X, no warning is given. When X<δ<2X, a first-level warning is given. When 2X<δ<3X, a second-level warning is given. When δ>3X, a third-level warning is given. S7, quantitatively calculate the degree of damage of each aquiclude and determine the location of the potential water inrush channel. The fracture network in each combined rock layer of the bottom plate aquiclude is a potential water inrush channel if it penetrates vertically; S8, quantitatively calculate the damage degree of the entire aquiclude and determine the channel warning level; S9, based on microseismic monitoring, a progressive composite warning of bottom water inrush is provided, which includes indicator warning and channel warning. The indicator warning value and channel warning value are integrated to realize the dual warning of time progress and spatial position. A composite warning level table of bottom water inrush is defined. According to the composite superposition result of the two values, the corresponding warning level is determined to realize a progressive composite warning.

2. The progressive composite early warning method for mine water inrush based on microseismic monitoring according to claim 1 is characterized by: The system monitoring results of the vibration events caused by the micro-fracture of the coal body and surrounding rock in S1 are presented as high-frequency, medium-high-frequency small-energy events, the system monitoring results of the vibration events caused by the large-scale fracture of the top and bottom plate rock layers are presented as medium-low-frequency, low-frequency large-energy events, and the system monitoring results of the vibration events caused by large-scale structural mining activation are presented as low-frequency, medium-low-frequency large-energy events.

3. The progressive composite early warning method for mine water inrush based on microseismic monitoring according to claim 1 is characterized by: The microseismic data index library in S3 includes: Index library ①: total frequency of events per unit time, total energy of events per unit time, average energy of events per unit time, variation rate of total frequency of events per unit time, variation rate of total energy of events per unit time, variation rate of average energy of events per unit time, total frequency of events per unit advancement, total energy of events per unit advancement, average energy of events per unit advancement, variation rate of total frequency of events per unit advancement, variation rate of total energy of events per unit advancement, variation rate of average energy of events per unit advancement; Index library ②: frequency of coal seam microfracture events per unit time, total energy of coal seam microfracture events per unit time, average energy of coal seam microfracture events per unit time, frequency of coal seam microfracture events per unit advancement, total energy of coal seam microfracture events per unit advancement, average energy of coal seam microfracture events per unit advancement, variation rate of coal seam microfracture event frequency per unit time, variation rate of total energy of coal seam microfracture events per unit time, variation rate of average energy of coal seam microfracture events per unit time, variation rate of coal seam microfracture event frequency per unit advancement, variation rate of total energy of coal seam microfracture events per unit advancement, variation rate of average energy of coal seam microfracture events per unit advancement; Index library ③: frequency of roof rock microfracture events per unit time, total energy of roof rock microfracture events per unit time, average energy of roof rock microfracture events per unit time, frequency of roof rock microfracture events per unit advancement, total energy of roof rock microfracture events per unit advancement, average energy of roof rock microfracture events per unit advancement, variation rate of frequency of roof rock microfracture events per unit time, variation rate of total energy of roof rock microfracture events per unit time, variation rate of average energy of roof rock microfracture events per unit time, variation rate of frequency of roof rock microfracture events per unit advancement, variation rate of total energy of roof rock microfracture events per unit advancement, variation rate of average energy of roof rock microfracture events per unit advancement; Index database ④: frequency of floor rock microfracture events per unit time, total energy of floor rock microfracture events per unit time, average energy of floor rock microfracture events per unit time, frequency of floor rock microfracture events per unit advancement, total energy of floor rock microfracture events per unit advancement, average energy of floor rock microfracture events per unit advancement, frequency variation rate of floor rock microfracture events per unit time, variation rate of total energy of floor rock microfracture events per unit time, variation rate of average energy of floor rock microfracture events per unit time, frequency variation rate of floor rock microfracture events per unit advancement, variation rate of total energy of floor rock microfracture events per unit advancement, variation rate of average energy of floor rock microfracture events per unit advancement; Index library ⑤: frequency of low-level roof rock stratum breaking events per unit time, total energy of low-level roof rock stratum breaking events per unit time, average energy of low-level roof rock stratum breaking events per unit time, frequency of low-level roof rock stratum breaking events per unit advancement, total energy of low-level roof rock stratum breaking events per unit advancement, average energy of low-level roof rock stratum breaking events per unit advancement, frequency variation rate of low-level roof rock stratum breaking events per unit time, total energy variation rate of low-level roof rock stratum breaking events per unit time, average energy variation rate of low-level roof rock stratum breaking events per unit time, frequency variation rate of low-level roof rock stratum breaking events per unit advancement, total energy variation rate of low-level roof rock stratum breaking events per unit advancement, average energy variation rate of low-level roof rock stratum breaking events per unit advancement; Index library ⑥: frequency of high-position roof rock stratum breaking events per unit time, total energy of high-position roof rock stratum breaking events per unit time, average energy of high-position roof rock stratum breaking events per unit time, frequency of high-position roof rock stratum breaking events per unit advancement, total energy of high-position roof rock stratum breaking events per unit advancement, average energy of high-position roof rock stratum breaking events per unit advancement, variation rate of frequency of high-position roof rock stratum breaking events per unit time, variation rate of total energy of high-position roof rock stratum breaking events per unit time, variation rate of average energy of high-position roof rock stratum breaking events per unit time, variation rate of frequency of high-position roof rock stratum breaking events per unit advancement, variation rate of total energy of high-position roof rock stratum breaking events per unit advancement, variation rate of average energy of high-position roof rock stratum breaking events per unit advancement; Index library ⑦: frequency of floor rock breaking events per unit time, total energy of floor rock breaking events per unit time, average energy of floor rock breaking events per unit time, frequency of floor rock breaking events per unit advancement, total energy of floor rock breaking events per unit advancement, average energy of floor rock breaking events per unit advancement, variation rate of floor rock breaking event frequency per unit time, variation rate of total energy of floor rock breaking events per unit time, variation rate of average energy of floor rock breaking events per unit time, variation rate of floor rock breaking event frequency per unit advancement, variation rate of total energy of floor rock breaking events per unit advancement, variation rate of average energy of floor rock breaking events per unit advancement; Index library⑧Frequency of structural activation events per unit time, total energy of structural activation events per unit time, average energy of structural activation events per unit time, frequency of structural activation events per unit advancement degree, total energy of structural activation events per unit advancement degree, average energy of structural activation events per unit advancement degree, variation rate of frequency of structural activation events per unit time, variation rate of total energy of structural activation events per unit time, variation rate of average energy of structural activation events per unit time, variation rate of frequency of structural activation events per unit advancement degree, variation rate of total energy of structural activation events per unit advancement degree, variation rate of average energy of structural activation events per unit advancement degree.

4. The progressive composite early warning method for mine water inrush based on microseismic monitoring according to claim 1 is characterized by: In S5, the frequency N of the event per unit time is set T , the frequency of events within a unit advancement degree N S , the frequency unit average value N of the event in n unit time TA , the frequency unit average value of events within n unit advancement N SA , the total energy of the event per unit time E TZ , the total energy of events within a unit of advancement E SZ , the total energy unit average value E of the event in n unit time TZA , the total energy unit average value E of events within n unit advancement SZA , the average energy of the event per unit time E TP , the average energy of events per unit propulsion degree E SP , the average energy of events in n unit time, the average value E TPA , the average energy unit average value E of events within n unit advancement SPA ; Frequency mutation rate δ N , including the frequency variation rate of events per unit time δ NT , the frequency variation rate of events within a unit advancement degree δ NS ; Energy mutation rate δ E , including the total energy variation rate of events per unit time δ ETZ , the total energy variation rate of events within a unit advancement degree δ ESZ , the average energy variation rate of events per unit time δ ETP , the average energy variation rate of events within a unit advancement degree δ ESP ; The core data mutation rate calculation formula in S5 includes a frequency mutation rate formula and an energy mutation rate formula; The frequency variation rate calculation formula is: The total energy variation rate calculation formula is: The calculation formula of average energy variation rate is: Among them: δ-variability, N-frequency, T-time, S-advancement, E-energy, Z-total energy, P-average energy, A-average value.

5. The progressive composite early warning method for mine water inrush based on microseismic monitoring according to claim 1 is characterized by: The water inrush types in S4 include simple bottom plate driven matching index, top plate dynamic load driven matching index, structure activation driven matching index and dynamic load structure composite matching index; The water inrush type matching warning data indicator library is as follows: Pure bottom plate driven matching indicators: Two types of core indicators: 12 sub-indicators in indicator library ④ and 12 sub-indicators in indicator library ⑦; Two types of auxiliary indicators: 12 sub-indicators in indicator library ① and 12 sub-indicators in indicator library ②; Top plate dynamic load drive type matching indicators: Two types of core indicators: 12 sub-indicators in indicator library ⑥ and 12 sub-indicators in indicator library ④; Two types of auxiliary indicators: 12 sub-indicators in indicator library ⑦ and 12 sub-indicators in indicator library ⑤; Structural activation driven matching indicators: Two types of core indicators: 12 sub-indicators in indicator library ⑧ and 12 sub-indicators in indicator library ④; Two types of auxiliary indicators: 12 sub-indicators in indicator library ⑦ and 12 sub-indicators in indicator library ①. Dynamic load structure composite matching index: Two types of core indicators: 12 sub-indicators in indicator library ⑥ and 12 sub-indicators in indicator library ⑧; Two types of auxiliary indicators: 12 sub-indicators in indicator library ④ and 12 sub-indicators in indicator library ⑦.

6. The progressive composite early warning method for mine water inrush based on microseismic monitoring according to claim 1 is characterized by: The S7 is specifically: S701, based on the geological drilling data in the working face, the aquiclude is vertically divided into several aquicludes of equal thickness. The lithology of each aquiclude needs to be defined in the quantitative analysis process; S702: For the microseismic events captured by the microseismic monitoring system during the mining process of the working face, they are divided into each water-proof layer according to their spatial position, and the plane distribution results of the energy kernel density value of each water-proof layer are calculated. On this basis, contour lines are drawn and filled into a cloud map with gradient color bars; on the premise of clarifying the lithology of the water-proof layer, the initial damage warning value WJ / m2 of the corresponding water-proof layer is determined through laboratory tests and engineering experience, that is, the area ≥ the warning value has met the conditions for being a water inrush channel, and in the process of applying the initial warning value, it is continuously optimized and corrected in combination with the engineering situation; S703, keeping the plane coordinates consistent, superimpose the plane cloud map results of all water-blocking strata in the vertical position, and display them in a three-dimensional effect. According to the damaged areas delineated by each water-blocking stratum, analyze their overlap in the vertical position to obtain the development position and degree of potential water inrush channels.

7. The progressive composite early warning method for mine water inrush based on microseismic monitoring according to claim 1 is characterized by: The S8 is specifically: S801, based on the analysis results of S7, i.e., the overlap of the damaged areas of each water-insulating layer in the vertical position, set the warning level of the bottom plate water inrush, and set the ratio of the number of water-insulating layers with overlapping damaged areas in the vertical position to the total number of water-insulating layers as K. When K < 1 / 4, it is considered that there is no water inrush danger at this location, i.e., no warning is given; when 1 / 4 ≤ K < 1 / 2, it is considered that there is a weak water inrush danger at this location, i.e., a first-level warning; when 1 / 2 ≤ K < 3 / 4, it is considered that there is a moderate water inrush danger at this location, i.e., a second-level warning; when K ≥ 3 / 4, it is considered that there is a strong water inrush danger at this location, i.e., a third-level warning; S802: As the working face advances, the number of microseismic events in the impermeable layer collected by the microseismic monitoring system continues to increase. It is necessary to recalculate the distribution of energy kernel density values ​​of each impermeable layer at certain intervals, and repeat S3 and S4 to achieve dynamic early warning during mining.

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