Mine water inrush grading early warning method and system based on microseismic fissure connectivity determination

Abstract

The application provides a mine water inrush grading early warning method based on microseismic fissure connectivity determination, comprising obtaining real-time microseismic event data; constructing a microseismic radiation distance quantification model for determining the spatial connectivity of rock mass fissures between adjacent microseismic points; analyzing the vertical space-time evolution of microseismic events based on the law that microseismic events occur first in the shallow part and then in the deep part to determine the vertical penetration path and penetration degree of the surrounding rock fissures; analyzing the response relationship between microseismic events and the position of the mining line based on the space-time distribution law that microseismic events and mining advance occur in front and lag behind in the rear to demarcate the mining influence range and the main penetration direction of the mining fissures; determining the water disaster danger level according to the preset grading standard, and determining the water inrush early warning level in combination with the predicted water inrush position and the predicted water inrush time. The application provides technical support for dynamic evaluation of surrounding rock stability and water disaster early warning, and effectively improves the accuracy and foresight of deep mining safety control.

Description

Technical Field

[0001] This invention relates to the field of mine water hazard monitoring technology, and in particular to a graded early warning method and system for mine water inrush based on the determination of microseismic fracture connectivity. Background Technology

[0003] Microseismic waves are elastic wave signals generated during the microfracture process inside the rock mass. As a direct physical response to the evolution of surrounding rock fracture, their spatial radiation range and spatiotemporal distribution are closely related to the formation, development and penetration process of the surrounding rock fracture network. They have become an important technical basis for evaluating the stability of deep surrounding rocks and predicting water hazard risks.

[0004] Currently, existing microseismic monitoring technologies are mostly focused on the location of microseismic events, parameter inversion, and simple statistical analysis. A systematic technical solution for determining the connectivity of rock fissures and providing early warning of water inrush in deep mining has not yet been developed, resulting in the following prominent technical problems: First, there is a lack of quantitative standards for defining microseismic radiation distance, making it impossible to clearly determine whether rock fissures between adjacent microseismic points are effectively connected, and making it difficult to accurately characterize the spatial connectivity of rock fractures; second, there is insufficient research on the triggering sequence of deep and shallow microseismic events, making it impossible to reveal the vertical evolution mechanism of rock fractures and the vertical connection law of fissures; third, the response relationship between microseismic activity and mining advance is not clearly defined, making it difficult to accurately identify the main connection direction of mining-induced fissures and the three-dimensional impact range of mining, thus leading to insufficient accuracy and reliability in the evaluation of rock stability and early warning of water hazards in deep mining, failing to meet the actual needs of safe production in deep mines.

[0005] Therefore, it is urgent to develop relevant technologies and methods to accurately determine the connectivity of surrounding rock fissures and the scope of mining impact by quantifying the microseismic radiation distance and clarifying the spatiotemporal evolution of microseismic events. This will provide core technical support for the dynamic evaluation of surrounding rock stability and water hazard monitoring and early warning in deep mines, ensuring the safe and efficient mining of deep mineral resources. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention provides a method and system for graded early warning of mine water inrush based on the determination of microseismic fracture connectivity, which can effectively improve the safety management level in the process of deep mining and provide strong technical support for safe production in mines.

[0007] The technical solution of this invention is as follows: A method for graded early warning of mine water inrush based on microseismic fracture connectivity determination includes the following steps: Acquire real-time microseismic event data; A microseismic radiation distance quantification model was constructed to determine the spatial connectivity of rock mass fractures between adjacent microseismic points; Based on the pattern that shallow microseismic events occur first and deep microseismic events occur later, the vertical spatiotemporal evolution of microseismic events is analyzed to determine the vertical penetration path and degree of penetration of surrounding rock fractures. Based on the spatiotemporal distribution pattern of microseismic events and mining progress, which shows that they occur ahead of time and behind time, we can analyze the response relationship between microseismic events and mining line location, and delineate the range of mining impact and the main penetration direction of mining fractures. Based on the spatial connectivity of the rock mass fissures, the vertical penetration path and degree of penetration of the surrounding rock fissures, and the main penetration direction of the mining-induced fissures, the water hazard risk level is determined according to the preset classification standards. The water inrush warning level is determined by combining the predicted water inrush location and predicted water inrush time, and the corresponding water inrush warning signal is output according to the level. Preferably, the specific method for constructing the microseismic radiation distance quantification model is as follows: extract the source energy, P-wave velocity, and rock mass damping coefficient from the microseismic event data to construct the microseismic radiation distance quantification model, with the formula as follows:

[0008] Where R is the effective radiation distance threshold of the microseismic event, α is the lithology correction factor, E is the source energy, ρ is the rock mass density, and V is the seismic source energy. p β is the P-wave velocity of the rock mass, and β is the damping correction factor. The effective radiation distance threshold R of each microseismic point is calculated according to the microseismic radiation distance quantification model; the spatial straight-line distance between each pair of adjacent microseismic points is calculated; the spatial straight-line distance is compared with the effective radiation distance threshold of the adjacent microseismic points; if the spatial straight-line distance is less than or equal to the effective radiation distance, it is determined that the rock mass fractures between the two microseismic points are in a connected state; if the spatial straight-line distance is greater than the effective radiation distance, it is determined that the rock mass fractures between the two microseismic points are in a disconnected state. Preferably, the lithology correction coefficient α is determined by field testing, and the value range is 1.2 to 1.8 for moderately fractured rock masses; the value range of the damping correction coefficient β is 0.6 to 0.9 for brittle rock masses, 0.9 to 1.2 for moderately ductile rock masses, and 1.2 to 1.6 for ductile rock masses. Preferably, analyzing the vertical spatiotemporal evolution of microseismic events based on the pattern of shallower microseismic events occurring first and deeper microseismic events occurring later, and determining the vertical penetration path and degree of penetration of surrounding rock fractures, specifically includes: obtaining geological profile maps and borehole columnar sections; mapping microseismic events to the geological profile maps and borehole columnar sections based on the location information of the microseismic events; determining the vertical depth range of each aquifer and impermeable layer based on the geological profile maps and borehole columnar sections, as the basis for dividing microseismic event segments; classifying microseismic events according to their occurrence depth into different microseismic event segments, generating microseismic event plan maps and profile maps for each segment; and analyzing the distribution trend of microseismic events in different segments over time based on the pattern of shallower microseismic events occurring first and deeper microseismic events occurring later, and determining the vertical penetration path and degree of penetration of surrounding rock fractures. Preferably, the analysis of the response relationship between microseismic events and the mining line location is based on the spatiotemporal distribution pattern of microseismic events occurring ahead of time and lagging behind in the mining advance, delineating the mining impact range and the main penetration direction of mining fractures. Specifically, this includes: acquiring mining advance information of the working face; using the real-time coordinates of the mining line as a benchmark, dividing time windows according to the mining cycle, and statistically analyzing the distribution density of microseismic events in the strike, dip, and vertical directions of each time window to achieve precise spatiotemporal correspondence between microseismic event clusters and mining spatial locations; using the spatial envelope of microseismic events as boundaries, combined with the microseismic event density and event gradient, defining the critical position where microseismic events significantly attenuate along the strike; defining the outer edge of the dense microseismic zone in the two roadways of the working face along the dip; determining the influence depth of the roof and floor along the vertical direction based on the elevation interval where microseismic events are concentrated; and delineating the mining impact range through the intersection of multiple profiles. Linear fitting and trend analysis of microseismic events during continuous advance period are performed to determine the main development direction of mining-induced fractures. The extension trend of high-density distribution zone of microseismic events and energy release sequence are used to determine the expansion path and penetration sequence of mining-induced fractures. The spatiotemporal penetration advantage of mining-induced fractures is inverted by combining advance speed. Preferably, the step of determining the water hazard risk level according to a preset classification standard based on the spatial connectivity of the rock mass fissures, the vertical penetration path and degree of penetration of the surrounding rock fissures, and the main penetration direction of the mining-induced fissures, specifically involves: The risk level of water damage is preset into four levels; The connectivity status of microseismic points, the spatiotemporal patterns of microseismic events, the planar positional relationship between strong aquifer events and the mining line, and hydrological information are used as the criteria for determining the degree of water hazard risk. When determining the water hazard risk level as Level 4 or Level 3, four conditions for achieving the water hazard risk level corresponding to that level must be met simultaneously. When determining the level of water hazard risk as Level II or Level I, any two or more of the conditions corresponding to the level of water hazard risk must be met simultaneously to achieve the judgment. Preferably, the judgment conditions for the water hazard risk level based on the connectivity state of microseismic points are as follows: When the distance d between more than 80% of microseismic events satisfies 1.5R < d ≤ 2R, local microfractures are determined, there is no effective water-conducting channel, and the water hazard risk level is level four; when the distance d between more than 80% of microseismic events satisfies R < d ≤ 1.5R, it is determined that the fissures are intermittently connected, the water-conducting channel is initially formed but unstable, and the water hazard risk level is level three; when the distance d between more than 80% of microseismic events satisfies 0.5R < d ≤ R, it is determined that the fissures are widely connected, the water-conducting channel is continuously connected, and the water hazard risk level is level two; when the distance d between more than 80% of microseismic events satisfies d ≤ 0.5R, it is determined that the fissures are globally connected, the water-conducting channel is directly connected to the aquifer / old goaf water, and the water hazard risk level is level one; Preferably, the judgment conditions for the water hazard risk level based on the spatio-temporal law of microseismic events are as follows: When deep microseismic events are discrete and sporadically distributed, there is no obvious chronological order between the deep and shallow parts, and there is no vertical connection trend, the water hazard risk level is determined to be level four; when deep microseismic events are locally concentrated, deep events occur occasionally, the proportion of small energy is ≥60%, large energy events begin to appear, but there is no continuous vertical migration, the water hazard risk level is determined to be level three; when microseismic events are distributed in a band or planar shape, the phenomenon that shallow events occur first and deep events occur later persists, the increase of large energy events is 30% - 80%, and there is obvious vertical directional migration, the water hazard risk level is determined to be level two; when deep and shallow microseismic events are first dense and continuous, as mining progresses, the frequency of deep events decreases, large energy events decrease to disappear, and vertical connection has been achieved, the water hazard risk level is determined to be level one; Preferably, the judgment conditions for the water hazard risk level based on the planar position relationship between the strong aquifer event and the mining line and hydrographic information are as follows: When the distance between the strong aquifer event and the mining line ≥80m, and the continuous decline amplitude of the water level is small or the water level remains stable without rising, the water hazard risk level is determined to be level four; when 50m ≤ the distance between the strong aquifer event and the mining line < 80m, and the water level drops continuously for 3 days or more, the water hazard risk level is determined to be level three; when 30m ≤ the distance between the strong aquifer event and the mining line < 50m, and the water level drops continuously for 5 days or more, or the water level should rise but the decline amplitude is large, the water hazard risk level is determined to be level two; when the distance between the strong aquifer event and the mining line < 30m, and the water level drops continuously for 7 days or more, the water hazard risk level is determined to be level one; Preferably, determining the water inrush warning level by combining the predicted water inrush location and the predicted water inrush time, and outputting the corresponding water inrush warning signal according to the level specifically includes: When the water hazard risk level reaches level four, and the distance between the predicted water inrush location and the mining line ≥50m, and the predicted water inrush time is ≥7 days away from the current time, a blue warning signal is issued; When the water hazard risk level reaches level three, the distance between the predicted water inrush location and the mining line is ≥35m, and the predicted water inrush time is ≥3 days from the current time, a yellow warning signal will be issued. When the water hazard risk level reaches level two, and the distance between the predicted water inrush location and the mining line is ≥25m, and the predicted water inrush time is ≥1 day from the current time, an orange warning signal will be issued. A red warning signal is issued when the water hazard risk level reaches level one, the distance between the predicted water inrush location and the mining line is ≥10m, and the predicted water inrush time is ≥0.5 days from the current time.

[0009] This invention also provides another technical solution: A microseismic-based fracture connectivity determination and water inrush classification early warning system includes: The microseismic data acquisition module is used to acquire real-time microseismic event data; The fracture connectivity determination module is used to construct a microseismic radiation distance quantification model and determine the spatial connectivity of rock fractures between adjacent microseismic points based on this model. The vertical evolution analysis module is used to analyze the vertical spatiotemporal evolution of microseismic events based on the pattern that shallow microseismic events occur first and deep microseismic events occur later, and to identify the vertical penetration path and degree of penetration of surrounding rock fractures. The mining impact analysis module is used to analyze the response relationship between microseismic events and mining line location based on the spatiotemporal distribution pattern of microseismic events and mining progress, which show that they occur ahead of time and behind time. It also delineates the mining impact range and the main penetration direction of mining fractures. The module for predicting the location and time of water inrush is used to obtain the predicted location and time of water inrush. The early warning level determination module is connected to the fracture connectivity determination module, the vertical evolution analysis module, and the mining impact analysis module, respectively. It is used to receive the output results of the above four modules, determine the level of water hazard according to the preset grading standard, and output the corresponding water inrush early warning signal according to the level.

[0010] The beneficial effects of this invention are as follows: By constructing a microseismic radiation distance quantification model, this invention clarifies the correspondence between the effective radiation range of microseismic activity and the range of mining-induced impact, accurately determines the development status and expansion path of mining-induced fractures, solves the technical pain points of traditional microseismic monitoring that cannot accurately determine the connection status of fractures and is difficult to delineate the range of mining-induced impact, and fills the gap in existing coal mine microseismic monitoring technology.

[0011] Compared to traditional microseismic monitoring methods, this solution, by clarifying the quantitative standards for microseismic radiation distance and establishing a precise correspondence between microseismic events and the scope of mining impact, can accurately capture the development patterns of fractures during coal mining, significantly improving the scientific rigor and accuracy of coal mine surrounding rock stability evaluation. This provides reliable technical support for the safety management of deep coal mining, effectively avoids safety hazards during coal mining, ensures coal mine production safety, simplifies the monitoring process, improves monitoring efficiency, adapts to the actual production needs of coal mines, provides practical technical support for safe coal mine production, and helps coal mines achieve safe and efficient mining. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A flowchart of a mine water inrush classification and early warning method based on microseismic fracture connectivity determination is provided for an embodiment of the present invention. Figure 2 This is a structural diagram of a mine water inrush classification and early warning system based on microseismic fracture connectivity determination, provided as an embodiment of the present invention. Detailed Implementation

[0014] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0015] like Figure 1 As shown, this embodiment of the invention provides a graded early warning method for mine water inrush based on the determination of microseismic fracture connectivity.

[0016] First, in step S0, real-time microseismic event data is acquired. This microseismic data can be collected based on an existing on-site microseismic monitoring system in the mine. It should be noted that steps S1, S2, and S3 are not sequential; they are only numbered for ease of explanation. In reality, steps S1, S2, and S3 can be performed simultaneously or separately in any order.

[0017] like Figure 1In step S1, a microseismic radiation distance quantification model is constructed to determine the spatial connectivity of rock mass fractures between adjacent microseismic points. One implementation method provided in this embodiment includes: Core parameters such as source energy, P-wave velocity, and rock mass damping coefficient are extracted from the microseismic event data. Combined with the elastic wave energy attenuation theory, a microseismic radiation distance quantification model is constructed, with the following formula:

[0018] Where R is the effective radiation distance threshold of the microseismic event, α is the lithology correction factor, E is the source energy, ρ is the rock mass density, and V is the seismic source energy. p Let be the P-wave velocity of the rock mass, and β be the damping correction factor.

[0019] The model can adjust the correction coefficients according to different lithologies (such as sandstone, shale, and coal seams) and geostress conditions to achieve dynamic calculation of the radiation distance threshold.

[0020] The lithology correction factor α is related to the rock mass type and the degree of fracture development, and is dimensionless. It can be determined through field testing, and is typically taken as 1.2 to 1.8 for rock masses with moderate fracture development.

[0021] The damping correction factor β is a dimensionless quantity, and its value can be taken with reference to the physical and mechanical parameters of the rock mass. It is generally 0.6 to 0.9 for brittle rock mass, 0.9 to 1.2 for moderately ductile rock mass, and 1.2 to 1.6 for ductile rock mass.

[0022] The effective radiation distance threshold R of each microseismic point is calculated according to the formula; and the spatial straight-line distance d between each pair of adjacent microseismic points is calculated. The spatial straight-line distance d is compared with the effective radiation distance threshold R of the microseismic point. If the spatial straight-line distance is less than or equal to the effective radiation distance, it is determined that the rock mass fractures between the two microseismic points have formed an effective connection and are in a connected state, indicating that the internal fractures of the rock mass have formed a continuous channel; if the spatial straight-line distance is greater than the effective radiation distance, it is determined that the rock mass fractures between the two microseismic points have not formed an effective connection and are in a non-connected state, indicating that the rock mass fractures are discretely distributed.

[0023] like Figure 1 In step S2, based on the pattern that shallow microseismic events occur first and deep microseismic events occur later, the vertical spatiotemporal evolution of microseismic events is analyzed to determine the vertical penetration path and degree of penetration of the surrounding rock fissures.

[0024] Under deep mining conditions, the vertical stress distribution of the surrounding rock exhibits the characteristics of "high stress in the deep and unloading in the shallow," and microseismic events follow a spatial evolution pattern of "shallow triggering first and deep lagging response." Shallow surrounding rock undergoes shear fracturing first due to mining disturbance, generating microseismic events and serving as the starting area for fracturing evolution. As stress is transferred and fractures expand, the fracturing gradually extends to deeper stress concentration areas, structural zones, or geologically weak areas. Deep surrounding rock subsequently experiences microfractures, triggering microseismic events, forming a progressively advancing vertical spatiotemporal sequence of "shallow first, deep later," directly reflecting the vertical path of surrounding rock fracturing.

[0025] This embodiment acquires raw data of microseismic events while simultaneously collecting information on working face advance, mining progress, and geological profiles. Microseismic events are then subjected to location correction, energy classification, and temporal filtering to eliminate environmental noise and mechanical interference events, resulting in a reliable spatiotemporal dataset of microseismic events.

[0026] After locating the microseismic events, their distribution is plotted on engineering drawings. Combined with the aquifers and impermeable layers of the working face, borehole columnar sections, etc., the microseismic events are divided into layers. Planar and cross-sectional views of the microseismic events are generated according to different layers. The spatial evolution of the microseismic events and the changing trends in layer distribution over time are analyzed. Specific steps include: Step S21: Obtain geological profile and borehole columnar section; Step S22: Based on the location information of the microseismic events, map the microseismic events onto the geological profile and borehole columnar section. Step S23: Based on the geological profile and borehole columnar section, determine the vertical depth range of each aquifer and impermeable layer as the basis for dividing the microseismic event segments; Step S24: Assign the microseismic events to different microseismic event segments according to their occurrence depth, and generate microseismic event plan and profile views for each segment; Step S25: Based on the pattern that microseismic events occur first in shallow areas and later in deep areas, analyze the distribution trend of microseismic events in different layers as a function of time series, and determine the vertical penetration path and degree of penetration of the surrounding rock fissures.

[0027] like Figure 1 In step S3, based on the spatiotemporal distribution pattern of microseismic events and the advance of mining, which shows that they occur ahead of time and behind time, the response relationship between microseismic events and the mining line location is analyzed, and the range of mining influence and the main penetration direction of mining fractures are delineated.

[0028] Mining disturbance is the core factor inducing surrounding rock fracturing. Microseismic activity and mining advance exhibit a time response relationship of "leading ahead and lagging behind." Before mining advance, the surrounding rock ahead develops microfractures due to pre-concentration of mining stress, with microseismic events occurring ahead of the mining line location. The lead distance is positively correlated with mining depth and advance speed. After mining advance, the stress release and secondary adjustment of the surrounding rock behind continuously generate microfractures, with microseismic events lagging behind the mining line location. The lag time increases with increasing mining depth and faster advance speed.

[0029] By coupling analysis of microseismic events with mining line locations, the impact range of mining activities can be accurately delineated, and the spatiotemporal penetration direction of mining-induced fractures can be identified. Based on reliable microseismic spatiotemporal datasets, the following analysis is performed: (1) Coupling and matching of microseismic events and mining line locations Based on the real-time coordinates of the mining line, a spatiotemporal correspondence between mining advance and microseismic response is established. Time windows are divided according to the mining cycle, and the distribution density of microseismic events in the strike, dip, and vertical directions of each time window is statistically analyzed to achieve precise coupling between microseismic event clusters and mining spatial locations.

[0030] (2) Precise delineation of the impact range of mining activities The boundary is determined by combining the spatial envelope of microseismic events with the event density gradient.

[0031] Along the strike: the boundary is the critical point where microseismic events significantly attenuate; Along the dip: the outer edge of the dense microseismic zone in the two roadways of the working face is the boundary of influence; Along the vertical direction: the depth of influence of the top / bottom plate is determined by the elevation range where microseismic events are concentrated.

[0032] Finally, the three-dimensional mining impact range was delineated using the multi-section intersection method.

[0033] (3) Identification of the spatiotemporal connection direction of mining-induced fractures Linear fitting and trend analysis were performed on microseismic events during the continuous advance period to determine the main development direction; the extension trend of the event-dense zone and the energy release sequence were used to determine the fracture propagation path and the sequence of fracture penetration; and the dominant orientation of fracture spatiotemporal penetration was inverted by combining the advance speed.

[0034] The specific steps of this embodiment include: S31, Obtain information on the progress of mining operations at the working face; S32 uses the real-time coordinates of the mining line as a benchmark, divides the time window according to the mining cycle, and counts the distribution density of microseismic events in the strike, dip, and vertical directions of each time window, so that the microseismic event clusters and the mining spatial location can achieve precise spatiotemporal correspondence. S33. Taking the spatial envelope of microseismic events as the boundary, combining the microseismic event density and event gradient, with the critical position of significant attenuation of microseismic events as the boundary along the strike; with the outer edge of the microseismic intensive zone in the two roadways of the working face as the boundary along the dip; and determining the influence depths of the roof and floor along the vertical direction based on the elevation interval where microseismic events are intensively developed; demarcating the mining-induced influence range through the intersection of multiple profiles. S34. Conduct linear fitting and trend analysis on microseismic events within a continuous advancing period to determine the main development direction of mining-induced fractures. Judging the expansion path and penetration sequence of mining-induced fractures based on the extension trend of the high-density distribution zone of microseismic events and the time sequence of energy release, and inversely calculating the dominant azimuth of the spatio-temporal penetration of mining-induced fractures in combination with the advancing speed.

[0035] Such as Figure 1 In step S4: According to the spatial connectivity of the rock mass fractures, the vertical penetration path and penetration degree of the surrounding rock fractures, and the main penetration direction of the mining-induced fractures, determine the water hazard risk level according to the preset grading standard, determine the water inrush warning level in combination with the predicted water inrush location and predicted water inrush time, and output the corresponding water inrush warning signal according to the level.

[0036] The predicted water inrush location and predicted water inrush time can be obtained through the mine hydrogeological conditions, the mining scale parameters of the working face, and other monitoring systems, etc., which are well-known technologies in the field and will not be elaborated here.

[0037] Conduct hierarchical early warning according to the water hazard risk level. The levels are from low to high, namely blue, yellow, orange, and red warnings. The water hazard risk level is preset to four levels; when the water hazard risk level reaches level four, issue a blue warning; when the water hazard risk level reaches level three, issue a yellow warning; when the water hazard risk level reaches level two, issue an orange warning; when the water hazard risk level reaches level one, issue a red warning.

[0038] Take the connectivity state of microseismic points, the spatio-temporal law of microseismic events, the planar position relationship between strong aquifer events and the mining line, and hydrological information as the judgment conditions for achieving the water hazard risk level. When determining that the water hazard risk level is level four or level three, it is necessary to simultaneously meet the four judgment conditions corresponding to the water hazard risk level of its level. When determining that the water hazard risk level is level two or level one, it is necessary to simultaneously meet any two or more judgment conditions corresponding to the water hazard risk level of its level.

[0039] Exemplarily, taking the connectivity state of microseismic points as the condition to divide the water hazard risk level is specifically as follows: When the distance d between more than 80% of microseismic events satisfies 1.5R < d ≤ 2R, judge local microfractures, no effective water-conducting channels, and the water hazard risk level is level four. When the distance d between more than 80% of the microseismic events satisfies R < d ≤ 1.5R, it is determined that the fractures are intermittently connected, the water-conducting channel is initially formed but unstable, and the degree of water hazard risk is level three; When the distance d between more than 80% of the microseismic events satisfies 0.5R < d ≤ R, it is determined that the fractures are widely connected, the water-conducting channel is continuously connected, and the degree of water hazard risk is level two; When the distance d between more than 80% of the microseismic events satisfies d ≤ 0.5R, it is determined that the fractures are fully connected throughout the area, the water-conducting channel is directly connected to the aquifer / old goaf water, and the degree of water hazard risk is level one.

[0040] Exemplarily, the degree of water hazard risk is specifically divided based on the spatio-temporal law of microseismic events as follows: When the deep microseismic events are discrete and sporadically distributed, there is no obvious chronological order between the deep and shallow parts, and there is no vertical connection trend, it is determined that the degree of water hazard risk is level four; When the deep microseismic events are locally aggregated, the deep events occur occasionally, the proportion of small-energy events ≥ 60%, large-energy events start to appear, but there is no continuous vertical migration, it is determined that the degree of water hazard risk is level three; When the microseismic events are distributed in a band or planar shape, the phenomenon that shallow events occur first and deep events occur later persists, the increase rate of large-energy events is 30% - 80%, and the vertical directional migration is obvious, it is determined that the degree of water hazard risk is level two; When the deep and shallow microseismic events are first dense and contiguous, as the mining progresses, the frequency of deep events decreases, the large-energy events decrease to disappear, and the vertical connection has been achieved, it is determined that the degree of water hazard risk is level one.

[0041] The spatio-temporal law of microseismic events comes from the determination results of step S2 and step S3.

[0042] Exemplarily, the degree of water hazard risk is specifically divided based on the planar position relationship between the strong aquifer events and the mining line and the hydrographic information as follows: When the distance between the strong aquifer events and the mining line ≥ 80m, and the continuous decline amplitude of the water level is small or the water level remains stable without rising, it is determined that the degree of water hazard risk is level four; When 50m ≤ the distance between the strong aquifer events and the mining line < 80m, and the water level drops continuously for 3 days or more, it is determined that the degree of water hazard risk is level three; When 30m ≤ the distance between the strong aquifer events and the mining line < 50m, and the water level drops continuously for 5 days or more, or the water level should rise but the decline amplitude is large, it is determined that the degree of water hazard risk is level two; When the distance between the strong aquifer events and the mining line < 30m, and the water level drops continuously for 7 days or more, it is determined that the degree of water hazard risk is level one.

[0043] When the flood hazard level is determined to be Level IV or Level III, all four flood hazard hazard conditions must be met simultaneously to avoid issuing too many alarms and affecting work efficiency; when the flood hazard level is determined to be Level II or Level I, any two or more flood hazard hazard conditions must be met simultaneously to ensure the timeliness of the early warning.

[0044] The specific water hazard risk levels in this embodiment are shown in the table below:

[0045] According to the embodiments provided by the present invention, a graded early warning system can be implemented based on the level of water hazard risk, combined with the predicted location and time of water inrush, specifically as follows: A blue alert will be issued when the water hazard risk level reaches level four, the predicted water inrush location is ≥50m away from the mining line, and the predicted water inrush time is ≥7 days away from the current time. A yellow alert is issued when the water hazard risk level reaches level three, the predicted water inrush location is ≥35m away from the mining line, and the predicted water inrush time is ≥3 days away from the current time. When the water hazard risk level reaches level two, and the predicted water inrush location is ≥25m away from the mining line, and the predicted water inrush time is ≥1 day away from the current time, an orange alert will be issued. A red alert is issued when the water hazard risk level reaches Level 1, the predicted water inrush location is ≥10m away from the mining line, and the predicted water inrush time is ≥0.5 days away from the current time.

[0046] like Figure 2 As shown, another embodiment of the present invention provides a graded early warning system for mine water inrush based on the determination of microseismic fracture connectivity. Specifically, it includes: The microseismic data acquisition module is used to acquire real-time microseismic event data; The fracture connectivity determination module is used to construct a microseismic radiation distance quantification model and determine the spatial connectivity of rock fractures between adjacent microseismic points based on this model. The vertical evolution analysis module is used to analyze the vertical spatiotemporal evolution of microseismic events based on the pattern that shallow microseismic events occur first and deep microseismic events occur later, and to identify the vertical penetration path and degree of penetration of surrounding rock fractures. The mining impact analysis module is used to analyze the response relationship between microseismic events and the mining line position based on the spatiotemporal distribution pattern of microseismic events and the mining advance, which show that they occur ahead of time and behind time. It also delineates the mining impact range and the main penetration direction of mining fractures. The module for predicting the location and time of water inrush is used to obtain the predicted location and time of water inrush. The early warning level determination module is connected to the fracture connectivity determination module, the vertical evolution analysis module, and the mining impact analysis module, respectively. It is used to receive the output results of the above four modules, determine the level of water hazard according to the preset grading standard, and output the corresponding water inrush early warning signal according to the level.

[0047] The operation of the early warning system in this embodiment relies on data support and coordination from existing systems deployed at the coal mine site, such as the mine microseismic monitoring system, the mine geological survey information system, the mining dynamic monitoring and management system, and the mine hydrological dynamic monitoring system. These systems work in conjunction with the modules of the early warning system in this embodiment to achieve multi-source data collaboration and inter-module linkage, ensuring the accuracy and reliability of judgments and early warnings.

[0048] The mine microseismic monitoring system, as the core data source, is mainly responsible for collecting various microseismic data generated by microfractures in the rock mass underground in coal mines, providing basic data input for the early warning system; the mine geological survey information system provides underground geological background data to assist in optimizing the judgment model and analysis logic; the mining dynamic monitoring and management system synchronously feeds back relevant data on mining operations, realizing the synchronous linkage between monitoring and production; and the mine hydrological dynamic monitoring system collects hydrological parameters in real time, providing the core basis for water inrush early warning classification.

[0049] It should be noted that the method flow steps and system modules of the embodiments of the present invention are implemented by computer software, or they can be implemented by combining computer software with necessary hardware.

[0050] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for graded early warning of mine water inrush based on the determination of microseismic fracture connectivity, characterized in that, Includes the following steps: Acquire real-time microseismic event data; A microseismic radiation distance quantification model was constructed to determine the spatial connectivity of rock mass fractures between adjacent microseismic points; Based on the pattern that shallow microseismic events occur first and deep microseismic events occur later, the vertical spatiotemporal evolution of microseismic events is analyzed to determine the vertical penetration path and degree of penetration of surrounding rock fractures. Based on the spatiotemporal distribution pattern of microseismic events and mining progress, which shows that they occur ahead of time and behind time, we can analyze the response relationship between microseismic events and mining line location, and delineate the range of mining impact and the main penetration direction of mining fractures. Based on the spatial connectivity of the rock mass fissures, the vertical penetration path and degree of penetration of the surrounding rock fissures, and the main penetration direction of the mining-induced fissures, the water hazard risk level is determined according to the preset grading standards. The water inrush warning level is determined by combining the predicted water inrush location and predicted water inrush time, and the corresponding water inrush warning signal is output according to the level.

2. The method according to claim 1, characterized in that, The specific method for constructing the microseismic radiation distance quantification model is as follows: From the microseismic event data, source energy, P-wave velocity, and rock mass damping coefficient are extracted to construct a microseismic radiation distance quantification model, the formula of which is: ； Where R is the effective radiation distance threshold of the microseismic event, α is the lithology correction factor, E is the source energy, ρ is the rock mass density, and V is the seismic source energy. p β is the P-wave velocity of the rock mass, and β is the damping correction factor. The effective radiation distance threshold R for each microseismic point is calculated based on the microseismic radiation distance quantification model. Calculate the spatial straight-line distance between each pair of adjacent microseismic points; The spatial straight-line distance is compared with the effective radiation distance threshold of the adjacent microseismic points. If the spatial straight-line distance is less than or equal to the effective radiation distance, the rock mass fissure between the two microseismic points is determined to be in a connected state; if the spatial straight-line distance is greater than the effective radiation distance, the rock mass fissure between the two microseismic points is determined to be in a non-connected state. The lithology correction coefficient α was determined through field testing, with a value range of 1.2 to 1.8 for moderately fractured rock masses; the damping correction coefficient β ranged from 0.6 to 0.9 for brittle rock masses, 0.9 to 1.2 for moderately ductile rock masses, and 1.2 to 1.6 for ductile rock masses.

3. The method according to claim 1, characterized in that, The analysis of the vertical spatiotemporal evolution of microseismic events based on the pattern of shallow microseismic events occurring first and deep microseismic events occurring later, and the determination of the vertical penetration path and degree of penetration of surrounding rock fractures, specifically includes: Obtain geological profiles and borehole columnar sections; Based on the location information of the microseismic events, the microseismic events are mapped onto the geological profile and borehole columnar section; Based on the geological profile and borehole columnar section, the vertical depth range of each aquifer and impermeable layer is determined as the basis for dividing the microseismic event segments; The microseismic events are classified into different microseismic event segments according to their depth of occurrence, and a microseismic event plan view and cross-sectional view are generated for each segment. Based on the pattern that microseismic events occur first in shallow areas and later in deep areas, the distribution trend of microseismic events in different layers with time series is analyzed to determine the vertical penetration path and degree of penetration of surrounding rock fractures.

4. The method according to claim 1, characterized in that, The analysis of the spatiotemporal distribution patterns of microseismic events and mining advance, characterized by their advanced occurrence at the front and delayed occurrence at the rear, reveals the response relationship between microseismic events and the mining line location. This analysis delineates the mining-induced influence range and the main penetration direction of mining-induced fractures. Specifically, this includes: Obtain information on the progress of mining operations at the working face; Based on the real-time coordinates of the mining line, time windows are divided according to the mining cycle. The distribution density of microseismic events in the strike, dip, and vertical directions of each time window is statistically analyzed to achieve a precise spatiotemporal correspondence between microseismic event clusters and mining spatial locations. Using the spatial envelope of microseismic events as the boundary, and combining the microseismic event density and event gradient, the boundary is defined along the strike by the critical position where the microseismic events significantly attenuate; along the dip by the outer edge of the dense microseismic zone in the two roadways of the working face; along the vertical direction by the elevation interval where microseismic events are concentrated, the influence depth of the roof and floor is determined; and the mining influence range is delineated by the intersection of multiple profiles. Linear fitting and trend analysis of microseismic events during continuous advance period are performed to determine the main development direction of mining-induced fractures. The extension trend of high-density distribution zone of microseismic events and energy release sequence are used to determine the expansion path and penetration sequence of mining-induced fractures. The dominant orientation of spatiotemporal penetration of mining-induced fractures is inverted by combining advance speed.

5. The method according to claim 1, characterized in that, The water hazard risk level is determined according to a preset grading standard based on the spatial connectivity of the rock mass fissures, the vertical penetration path and degree of penetration of the surrounding rock fissures, and the main penetration direction of the mining-induced fissures. Specifically: The risk level of water damage is preset into four levels; The connectivity status of microseismic points, the spatiotemporal patterns of microseismic events, the planar positional relationship between strong aquifer events and the mining line, and hydrological information are used as the criteria for determining the degree of water hazard risk. When determining the water hazard risk level as Level 4 or Level 3, four conditions for achieving the water hazard risk level corresponding to that level must be met simultaneously. When determining the level of water hazard risk as Level II or Level I, any two or more of the conditions corresponding to the level of water hazard risk must be met simultaneously to achieve the judgment.

6. The method according to claims 2 and 5, characterized in that, The specific criteria for determining the degree of water hazard risk in the interconnected state of the microseismic points are as follows: When the distance d between more than 80% of the microseismic events satisfies 1.5R < d ≤ 2R, it is determined that there is a local micro-fracture with no effective water-conducting channel, and the water hazard level is level four. When the distance d between more than 80% of the microseismic events satisfies R < d ≤ 1.5R, it is determined that the fracture is intermittently connected, the water-conducting channel is initially formed but unstable, and the water hazard level is three. When the distance d between more than 80% of the microseismic events satisfies 0.5R < d ≤ R, it is determined that the fractures are widely interconnected, the water-conducting channels are continuously connected, and the water hazard level is level two. When the distance d between more than 80% of the microseismic events satisfies d ≤ 0.5R, it is determined that the fracture is fully connected, the water-conducting channel is directly connected to the aquifer / old cavity water, and the water hazard level is level one.

7. The method according to claims 3 to 5, characterized in that, The specific criteria for determining the degree of water hazard risk based on the spatiotemporal patterns of the microseismic events are as follows: When deep microseismic events are discrete and sporadic, with no clear sequence between deep and shallow events and no vertical connection, the water hazard risk level is determined to be level four. When deep microseismic events are locally concentrated, deep events occur sporadically, small energy events account for ≥60%, and large energy events begin to appear, but there is no continuous vertical migration, the water hazard risk level is determined to be level three. When microseismic events are distributed in a banded or planar pattern, and the phenomenon of shallow events occurring first and deep events occurring later persists, with a 30% to 80% increase in high-energy events and obvious vertical directional migration, the water hazard risk level is determined to be Level II. When deep and shallow microseismic events are initially dense and continuous, the frequency of deep events decreases as mining progresses, and high-energy events decrease until they disappear, and vertical connection is achieved, the water hazard risk level is determined to be Level 1.

8. The method according to claim 5, characterized in that, The specific criteria for determining the relationship between the strong aquifer event and the planar location of the mining line, and the degree of water hazard risk based on hydrological information, are as follows: When a strong aquifer event is ≥80m away from the mining line, and the water level continues to drop but not by much or the water level continues to rise steadily, the water hazard level is determined to be Level IV. When the distance from the strong aquifer event to the mining line is less than 80m and the water level drops for 3 consecutive days or more, the water hazard level is determined to be level three. When the distance from the strong aquifer event to the mining line is less than 50m and the water level drops for 5 consecutive days or more, or when the water level should have risen but the drop is large, the water hazard level is judged to be level two. When a strong aquifer event is less than 30m from the mining line and the water level drops for 7 consecutive days or more, the water hazard level is determined to be Level 1.

9. The method according to claim 5, characterized in that, The process of determining the flood inrush warning level by combining the predicted location and time of the flood inrush, and outputting a corresponding flood inrush warning signal based on the level, specifically includes: When the water hazard risk level reaches level four, the distance between the predicted water inrush location and the mining line is ≥50m, and the predicted water inrush time is ≥7 days from the current time, a blue warning signal will be issued. When the water hazard risk level reaches level three, the distance between the predicted water inrush location and the mining line is ≥35m, and the predicted water inrush time is ≥3 days from the current time, a yellow warning signal will be issued. When the water hazard risk level reaches level two, and the distance between the predicted water inrush location and the mining line is ≥25m, and the predicted water inrush time is ≥1 day from the current time, an orange warning signal will be issued. A red warning signal is issued when the water hazard risk level reaches level one, the distance between the predicted water inrush location and the mining line is ≥10m, and the predicted water inrush time is ≥0.5 days from the current time.

10. A graded early warning system for mine water inrush based on microseismic fracture connectivity determination, characterized in that, include: The microseismic data acquisition module is used to acquire real-time microseismic event data; The fracture connectivity determination module is used to construct a microseismic radiation distance quantification model and determine the spatial connectivity of rock fractures between adjacent microseismic points based on this model. The vertical evolution analysis module is used to analyze the vertical spatiotemporal evolution of microseismic events based on the pattern that shallow microseismic events occur first and deep microseismic events occur later, and to identify the vertical penetration path and degree of penetration of surrounding rock fractures. The module for predicting the location and time of water inrush is used to obtain the predicted location and time of water inrush. The mining impact analysis module is used to analyze the response relationship between microseismic events and mining line location based on the spatiotemporal distribution pattern of microseismic events and mining progress, which show that they occur ahead of time and behind time. It also delineates the mining impact range and the main penetration direction of mining fractures. The early warning level determination module is connected to the fracture connectivity determination module, the vertical evolution analysis module, the mining impact analysis module, and the predicted water inrush location and predicted water inrush time acquisition module, respectively. It is used to receive the output results of the above four modules, determine the water hazard risk level according to the preset grading standard, and output the corresponding water inrush early warning signal according to the level.

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