A concealed disaster-causing factor census method for coal mine goaf water

Abstract

This invention relates to a method for investigating hidden disaster-causing factors of water in old coal mine workings, belonging to the field of coal mine safety and geological disaster prevention technology. It includes: collecting multi-source data to establish an initial ledger and delineate suspected areas; updating suspected areas through surface surveys and remote sensing interpretation; conducting regional scanning exploration using surface geophysical exploration; conducting advanced and detailed exploration using underground geophysical exploration; constructing verification boreholes based on geophysical exploration results to obtain key hydrogeological parameters; measuring the development characteristics of water-conducting channels; integrating all data for dynamic comprehensive evaluation and drawing dynamically updated hazard maps and three-line management maps; and finally integrating into a unified information platform to establish an intelligent risk early warning mechanism. This invention improves exploration accuracy through a ground-well collaborative feedback mechanism, achieves dynamic risk assessment and prediction through multi-source coupling and time-series analysis, and constructs an intelligent early warning system, significantly improving the accuracy, foresight, and proactive prevention and control capabilities of water hazards in old coal mine workings.

Description

Technical Field

[0001] This invention belongs to the field of coal mine safety and geological disaster prevention technology, and relates to a method for investigating hidden disaster-causing factors caused by water in old coal mine workings. Background Technology

[0002] Old mine workings water is a major type of mine water hazard. Due to its complex formation history, hidden spatial location, and unclear hydrological conditions, it is extremely prone to causing sudden water inrushes, flooding, and serious accidents resulting in casualties. Currently, the main technical bottlenecks in the general survey of old mine workings water are as follows: 1. Limited exploration methods and lack of systematic integration: Existing methods mostly rely on single technical means or simple combinations. Ground geophysical exploration and downhole exploration data are separated and lack systematic integration, making it difficult to form a holistic understanding of the three-dimensional spatial occurrence of old workings and water.

[0003] 2. Static risk assessment with poor predictability: Traditional risk assessment relies heavily on qualitative experience and cannot comprehensively consider the dynamic changes of multiple factors such as water volume, drainage channels, water supply, and the performance of the impermeable layer, making it difficult to predict risk trends.

[0004] 3. The early warning mechanism is passive and the response is lagging: the existing early warning is mostly based on static thresholds and lacks analysis of the time-series evolution of risk factors. The early warning thresholds are fixed and cannot adapt to the complex and ever-changing hydrogeological conditions of mines.

[0005] 4. Separation of results from application, resulting in weak decision support: The survey results are mostly presented in the form of static maps, which cannot be linked with real-time mining progress and monitoring data, making it difficult to form a complete technical closed loop from exploration to early warning. Summary of the Invention

[0006] In view of this, the purpose of this invention is to provide a method for investigating hidden disaster-causing factors of water in old coal mine workings, which solves the problems of scattered detection methods, static risk assessment and passive early warning response in the existing technology, and realizes accurate detection, dynamic assessment and intelligent early warning of water hazards in old coal mine workings.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A method for investigating hidden disaster-causing factors caused by water in old coal mine workings, the method comprising: Collect and integrate multi-source historical data of the target mining area, establish an initial old working water information ledger, and preliminarily delineate the suspected old working water area on the mining engineering plan; A ground survey was conducted on the target mining area and its surrounding areas. Combined with the interpretation of UAV remote sensing data, surface cracks, subsidence pits, old mine shafts and water bodies were identified, and the scope of suspected old mine water areas was updated. A survey network was deployed within the updated old goaf suspected area, and a scanning exploration was carried out using ground geophysical methods to delineate the boundaries of the water-rich anomaly area and the suspected goaf area, forming regional geophysical exploration results. Measurement points are set up in the underground mining face, and underground geophysical exploration methods are used to conduct directional exploration of the front of the tunnel, the top and bottom plates and sidewalls of the mining face, identify hidden water-conducting structures and local water-rich bodies, and form detailed underground exploration results. Based on the results of regional geophysical exploration and detailed downhole detection, verification boreholes were drilled in the delineated anomaly areas; the verification boreholes included surface boreholes and downhole directional boreholes. Observation holes are arranged in the working face of the target coal seam to measure the development height of the water-conducting fracture zone and / or the development depth of the mining-induced failure zone of the floor after the coal seam is mined. By integrating all the data obtained above, the spatial distribution, water accumulation, recharge sources and convection risks of old water inlets are dynamically assessed; based on the assessment results, a distribution map of potential old water inlets hazards, a water-rich zoning map, and a three-line management map including water accumulation line, water exploration line and warning line are drawn and dynamically updated. Establish an early warning mechanism for water hazard risks in old-type airfields based on real-time monitoring data and assessment models to provide risk warnings.

[0008] Furthermore, directional exploration of the tunneling front, the roof and floor of the mining face, and the sidewalls is conducted using downhole geophysical methods, including: For tunnel excavation faces, the mine transient electromagnetic method is used for sector detection to identify water-rich bodies and water-conducting structures ahead of the excavation. For longwall mining faces, radio wave tunnel fluoroscopy is used to detect geological anomalies in the coal seams inside the working face; and audio-frequency electromagnetic fluoroscopy or multi-component transient electromagnetic methods are used to detect the water-bearing properties of the sandstone aquifer on the roof and the rock strata on the floor of the working face.

[0009] Furthermore, information on geological anomalies and water-rich bodies obtained through downhole geophysical exploration methods will be used as known points or calibration points and fed back into the surface geophysical data inversion and interpretation process to correct the inversion parameters and interpretation models of the surface geophysical exploration.

[0010] Furthermore, based on regional geophysical exploration results and detailed downhole detection results, verification boreholes were drilled in the delineated anomaly areas, including: The construction involves drilling boreholes on the ground to verify the abnormal areas delineated by ground geophysical exploration; the boreholes penetrate the goaf of the target coal seam to directly reveal the location of the goaf, the filling material and water accumulation, and core samples are taken for lithological identification; after completion, the boreholes also serve as long-term hydrological observation wells to continuously acquire water level, water temperature and water quality data through automatic monitoring equipment. Directional drilling is carried out in the construction well to verify the anomalies discovered by the underground geophysical exploration and the risk zone ahead of the tunneling. The formed boreholes also serve as advance exploration and drainage holes. The location, volume, pressure, quality, and recharge conditions of the old hollow water space were obtained through drilling.

[0011] Furthermore, drilling was used to obtain the water pressure of the Ordovician limestone aquifer beneath the target coal seam floor.

[0012] Furthermore, by integrating ground geophysical exploration, downhole geophysical exploration, verification borehole and observation borehole measured data, a risk quantification model based on multi-source information coupling is used for dynamic comprehensive assessment. Based on the assessment results, a distribution map of old goaf water hazards, a water-rich zoning map and a three-line management map are drawn and dynamically updated; among them, the three-line management map is dynamically updated based on the boundary of the goaf water accumulation area obtained from the verification borehole.

[0013] Furthermore, the dynamic comprehensive assessment using a risk quantification model based on multi-source information coupling includes introducing a time-series evolution analysis module, arranging geophysical exploration, drilling, and monitoring data in chronological order to form time-series datasets for each risk factor; analyzing the time-series dependencies and evolution patterns among each risk factor; predicting the changing trends of each risk factor over a future period based on historical time-series data and current monitoring data; and dynamically adjusting the warning thresholds for different risk levels based on the risk trend prediction results. The risk factors include the amount of water accumulated in the old goaf, the relationship between the measured development height of the water-conducting fracture zone in the overlying strata and the distance to the goaf, the relationship between the depth of the floor failure and the thickness of the aquitard and the water pressure of the Ordovician limestone, the degree of development of the water-conducting structure, and the water inrush coefficient of the pressurized mining area. Dynamic updates to the three-line management map based on the boundary of the goaf water accumulation area obtained from the verification borehole include: marking the boundary of the goaf water accumulation area obtained from the verification borehole as the water accumulation line; using the water accumulation line as a reference, pushing it outward by a first preset safety distance to form a water exploration line; using the water exploration line as a reference, pushing it outward by a second preset safety distance to form a warning line; and as the mining face advances, correcting the water accumulation line, water exploration line, and warning line according to new drilling or geophysical exploration results.

[0014] Furthermore, establishing an early warning mechanism for water hazard risks in old-age reservoirs based on real-time monitoring data and assessment models includes: A risk situation awareness layer is set up to collect multi-source data from geophysical exploration, drilling and monitoring in real time, and form a real-time risk situation map through data fusion processing. An intelligent analysis and decision-making layer is set up, which uses the time-series evolution analysis module and combines it with the real-time risk situation map to conduct risk trend analysis and early warning level determination; A tiered response execution layer is set up to automatically trigger corresponding prevention and control measures based on the warning level, including at least one of the following: automatically activating the emergency drainage system, adjusting the working face advance speed, or initiating a special exploration program.

[0015] The beneficial effects of this invention are as follows: (1) This invention establishes a collaborative feedback mechanism between ground and downhole geophysical data, and uses downhole measured data to dynamically correct the ground geophysical model. This overcomes the shortcomings of traditional methods, such as single exploration means and fragmented data, and realizes a three-dimensional and precise characterization of the spatial distribution of old working water and hydrogeological conditions from coarse to fine and iterative optimization, thereby improving the systematicness and accuracy of exploration.

[0016] (2) By integrating multi-source spatiotemporal data, this invention constructs a risk quantification model that couples multiple factors such as water accumulation, structure, and rock strata, and introduces time-series evolution analysis, which can dynamically assess the risk situation and predict its changing trend, and adaptively adjust the early warning threshold, thereby upgrading the risk assessment from static status analysis to dynamic trend prediction, enhancing the predictability and scientific nature of the prevention and control of water hazards in old caves.

[0017] (3) This invention establishes a closed-loop early warning system from real-time risk situation perception, intelligent analysis and decision-making to automatic hierarchical response. It can automatically trigger targeted prevention and control measures, change the passive prevention and control mode of manual dependence and delayed response, realize the transformation to proactive early warning and intelligent intervention, and improve the accuracy and intelligence level of coal mine water hazard prevention and control.

[0018] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0019] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is a schematic diagram of a method for investigating hidden disaster-causing factors caused by water in old coal mine workings, provided in an embodiment of the present invention. Figure 2 A schematic diagram illustrating the principle of the ground-well collaborative feedback mechanism; Figure 3 This is a multi-source coupled risk assessment and early warning system. Detailed Implementation

[0020] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0021] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0022] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0023] like Figure 1 As shown, this is a method for investigating hidden disaster-causing factors of old coal mine workings and water, provided by an embodiment of the present invention. The method is as follows: S1. Collect and integrate multi-source historical data of the target mining area, establish an initial old working water information ledger, and preliminarily delineate the suspected old working water area on the mining engineering plan.

[0024] Specifically, geological reports, mine excavation plans, hydrogeological records, historical water exploration and release records, and data on the closure of surrounding small coal mines are collected for the target mining area. A Geographic Information System (GIS) is used to integrate information on the location of all historical goaf areas, water accumulation, and poorly sealed boreholes to establish an initial old goaf water information ledger.

[0025] Based on the historical mining area, stratigraphic occurrence, and fault lines, the suspected old workings with water accumulation risk were initially delineated on the mining engineering plan, providing direction for subsequent detailed exploration.

[0026] S2. Conduct a ground survey of the target mining area and surrounding areas, and combine it with the interpretation of UAV remote sensing data to identify surface cracks, subsidence pits, old mine shafts and water distribution, and update the scope of suspected old workings and water areas.

[0027] Specifically, by interpreting remote sensing images and conducting on-site verification, the location, scale, and activity of surface cracks, subsidence pits, and old kiln wellheads can be accurately identified, while the distribution of surface rivers, reservoirs, and waterlogged depressions can be determined.

[0028] High-risk areas such as areas with severe surface deformation, dense old kiln sites, and areas adjacent to water bodies are overlaid onto the initially delineated suspected old cave-in and water-bearing areas, updating and narrowing the scope of the suspected old cave-in and water-bearing areas, thereby improving the targeting and efficiency of subsequent geophysical exploration work.

[0029] S3. Within the updated suspected old goaf area, a survey network is deployed, and ground geophysical exploration methods are used for scanning exploration to delineate the boundaries of water-rich anomaly areas and suspected goaf areas, forming regional geophysical exploration results.

[0030] Specifically, a survey network is systematically deployed within the updated area of ​​suspected old goaf and water-bearing zones. Transient electromagnetic methods or controlled-source audio-frequency magnetotellurics are preferred for area exploration. By measuring the electrical differences in the subsurface medium, the boundaries of low-resistivity water-bearing anomaly zones and suspected goaf zones with abrupt resistivity changes are delineated, forming a regional geophysical exploration map.

[0031] S4. Set up measuring points at the underground mining face and use underground geophysical exploration methods to conduct directional exploration of the front of the tunnel, the top and bottom plates of the mining face and the sidewalls, identify hidden water-conducting structures and local water-rich bodies, and form detailed underground exploration results.

[0032] For tunnel excavation faces, the mine transient electromagnetic method is used for multi-directional and multi-angle fan-shaped exploration to identify water-rich bodies and water-conducting structures within a range of 100-150 meters ahead of the excavation.

[0033] For longwall mining faces, radio wave tunnel peeping (TPT) is used to detect geological anomalies such as collapse columns and faults in the coal seams inside the working face; and audio-visual spectroscopy or multi-component transient electromagnetic method is used to detect the water-bearing properties of the sandstone aquifer on the roof and the rock strata on the floor of the working face.

[0034] In this embodiment, as Figure 2As shown, the precise location and water abundance of the structures and water-rich areas actually revealed by downhole geophysical exploration in the tunnel are fed back as known points to the surface geophysical data inversion and interpretation process in step three, to correct the inversion parameters and interpretation model of the surface geophysical exploration. Specifically, the precise location and water abundance (e.g., unit water inflow) of the structures (e.g., faults) and water-rich areas actually revealed by downhole geophysical exploration in the tunnel in step four are used as "known points" or "calibration points." This real geological-hydrological information is fed back to the surface geophysical data inversion and interpretation process in step three, to correct the inversion parameters (e.g., layer resistivity in the initial geoelectric model) and interpretation model of surface geophysical exploration (e.g., transient electromagnetic method). Through this iterative process of "downhole measurement constraining surface inversion," the reliability and resolution of the surface geophysical exploration results in interpreting water-rich anomalies in unmined areas are significantly improved.

[0035] S5. Based on the regional geophysical exploration results and the results of detailed downhole exploration, verification boreholes are drilled in the delineated anomaly areas. Verification boreholes include surface boreholes and downhole directional boreholes, which are used to directly expose the goaf, take core samples, conduct hydrogeological tests, and obtain water level, water quality, and water quantity parameters.

[0036] Specifically, based on the anomaly areas identified in steps three and four, verification boreholes are constructed following a hierarchical principle: First, surface boreholes are drilled to verify the anomaly areas delineated by surface geophysical exploration. The boreholes penetrate the goaf of the target coal seam, directly revealing the location of the goaf, its filling material, and water accumulation. Core samples are taken for lithological identification. After completion, the boreholes also serve as long-term hydrological observation wells, equipped with automatic monitoring equipment to continuously acquire water level, temperature, and quality data.

[0037] In underground roadways, for local anomalies discovered by underground geophysical exploration and risk areas ahead of tunneling, measurement while drilling (MWD) technology is used to construct long directional boreholes (e.g., 300-500 meters). The boreholes can be precisely controlled in trajectory, allowing for "targeted" verification of anomalies and also serving as advance exploration and drainage holes.

[0038] Through drilling, key hydrogeological parameters such as the spatial location of the old cavern, water volume, water pressure, water quality, and recharge conditions were finally obtained.

[0039] In other embodiments, the hydrogeological parameters may also include the water pressure of the Ordovician limestone aquifer beneath the target coal seam floor (Ordovician limestone water pressure).

[0040] S6. Arrange observation holes at the working face of the target coal seam to measure the development height of the water-conducting fracture zone and / or the development depth of the mining-induced failure zone of the floor after coal seam mining.

[0041] The observation wells are arranged as follows at the working face of the target coal seam: The measured height of the water-conducting fracture zone can be determined using the underground double-end sealing segmented water injection test method: before mining, observation holes are constructed at the surface of the working face or in adjacent roadways to a predetermined stratum above the coal seam roof. During mining, the leakage of each segment of the rock strata is continuously monitored, thereby directly and accurately determining the height of the water-conducting fracture zone.

[0042] The depth of the mining-induced failure zone in the floor can be determined by the borehole segmented water pressure test method: before mining, boreholes are drilled in the floor roadway of the working face, and segmented water pressure tests are conducted on the floor strata before and after mining. By comparing the changes in permeability, the depth of mining-induced failure in the floor strata can be determined.

[0043] S7. Integrate all the data obtained in steps one to six to dynamically assess the spatial distribution, water accumulation, replenishment sources, and convection risks of old water inlets; based on the assessment results, draw and dynamically update the distribution map of old water inlet hazards, the water-rich zoning map, and the three-line management map including the water accumulation line, the water exploration line, and the warning line.

[0044] Specifically, all spatial data, attribute data, and measured parameters obtained in steps one through six are integrated into a three-dimensional geological modeling and risk assessment platform for dynamic comprehensive evaluation. A risk quantification model based on multi-source information coupling, such as a reinforcement learning model, neural network, or mathematical model, is adopted. This model considers at least the following factors for risk classification: the amount of water accumulated in the old goaf, the relationship between the measured development height of the water-conducting fracture zone in the overlying strata and the distance to the goaf, the relationship between the depth of floor failure and the thickness of the aquitard and the water pressure of the Ordovician limestone layer, and the degree of development of water-conducting structures.

[0045] The assessment results are visualized on the three-line management chart in the form of a risk level map.

[0046] Dynamically draw and update management maps, including: distribution map of old water-related hazards and water-rich zoning map.

[0047] The risk quantification model incorporates a time-series evolution analysis module, which uses machine learning algorithms to analyze the dynamic trends of each risk factor and establish the relationship between each risk factor over time. Based on historical time-series data and current monitoring data, it predicts the trends of each risk factor in a specific future time period. Based on the risk trend prediction results, it dynamically adjusts the warning thresholds for different risk levels to achieve adaptive optimization of the warning thresholds.

[0048] The warning threshold adjustment method is as follows: First, time-series datasets of various risk factors are constructed by arranging historical geophysical exploration, drilling, and real-time monitoring data in chronological order. Machine learning algorithms are then used to analyze the temporal dependencies and evolution patterns among these factors. For example, by learning from historical data, it was found that when "roof pressure" increases and "water level in a certain observation well" decreases by 0.5 meters per day, a sudden water inrush often occurs three days later. Based on current monitoring data such as water level and water pressure, models such as recurrent neural networks or long short-term memory networks are used to predict water pressure values ​​or water accumulation within a specific future time period.

[0049] Scenario A (Slow Rise): The current water pressure in an old vacant area is 1.8 MPa, and it is predicted to rise to 1.9 MPa in the next 3 days (still 2 MPa lower than the initial value). The system determines that the risk is stable and may keep the actual response warning threshold unchanged or slightly increase it.

[0050] Scenario B (Accelerated Increase): The current water pressure in the same old empty area is 1.8 MPa, but it is predicted to surge to 2.2 MPa in the next 3 days (exceeding the initial value of 2 MPa). The risk is judged to be rising sharply. In order to prevent accidents before reaching 2.0 MPa, the system will automatically lower the actual warning threshold and trigger the warning in advance, leaving a time window for emergency response.

[0051] The dynamic updating method of the three-line management map is as follows: the boundary of the goaf water accumulation area actually exposed by the borehole in step five is marked as the water accumulation line; based on this water accumulation line, a first preset safety distance is pushed outward to form the water exploration line; based on this water exploration line, a second preset safety distance is pushed outward to form the warning line; and the three lines are corrected in real time as mining activities and new exploration results are obtained. Specifically, as the mining face advances, when new drilling or geophysical exploration results (such as new advance drilling confirming a new water accumulation area ahead) are input into the system, the water accumulation line, water exploration line, and warning line are automatically corrected. Simultaneously, the time-series evolution analysis module predicts the potential risk changes that this new water accumulation area may cause to adjacent working faces.

[0052] The dynamic comprehensive assessment also includes calculating the water inrush coefficient of the pressurized mining area. :

[0053] in, The pressure of the Ordovician limestone water is (MPa). The thickness (m) of the aquitard layer at the coal seam floor is given. The calculated water inrush coefficient is compared with the safety threshold value as a key indicator for assessing the risk of water inrush at the floor, thus providing a more comprehensive consideration of the threat from high-pressure limestone water at the floor in the risk quantification model.

[0054] S8, such as Figure 3As shown, the three-line management map, data and assessment model generated by the census will be integrated into a unified water prevention and control information platform to establish an early warning mechanism for water hazard risks in old-fashioned areas based on real-time monitoring data and risk quantification models.

[0055] The old-style flood risk early warning mechanism includes establishing a multi-level early warning and response system based on spatiotemporal big data, as detailed below: 1) Risk Situation Awareness Layer: Collects multi-source data such as geophysical exploration, drilling, and monitoring in real time, and forms a real-time risk situation map through data fusion processing; 2) Intelligent Analysis and Decision-Making Layer: Utilizing the time-series evolution analysis module, combined with real-time risk situation maps, risk trend analysis and early warning level determination are performed; The judgment principle is as follows: the judgment of the early warning level of the old-type water hazard adopts a comprehensive judgment principle of "multi-factor coupling + temporal trend + spatial constraint". ①Based on risk factors obtained through real-time monitoring, geophysical exploration, drilling, and field measurements; ②The risk trend prediction based on the time-series evolution analysis module is dynamic; ③The spatial relationship of the three-line management map (water accumulation line, water exploration line, and warning line) is used as a constraint. ④ The system uses a tiered threshold + trend overlay method to avoid misjudgment by a single indicator and achieves a four-level early warning system from low to high.

[0056] The warning level classification divides the risk of water damage from old airfields into four levels from low to high: Level IV Blue Warning (Attention), Level III Yellow Warning (Alert), Level II Orange Warning (Alert), and Level I Red Warning (Emergency).

[0057] The warning level determination index system uses data obtained in steps S1–S7 without introducing external parameters. The indicators include: 1) Hydrological risk factors: total water accumulation in old workings, aquifer water level / pressure, water pressure of Ordovician limestone in the foundation, and water inrush coefficient; 2) Geological and mining factors: development height of water-conducting fracture zones, depth of mining-induced damage zones in the foundation, and development degree of water-conducting faults / fractures / collapse columns; 3) Temporal evolution factors: rate of rise in water level / pressure, rate of change of water inrush coefficient, and predicted risk factor values ​​for the next 7 days / 15 days.

[0058] The classification rules are as follows: I. Blue Alert (Level IV, Attention) is determined if any of the following conditions are met: 1) The water inrush coefficient reaches 80% to 90% of the critical value; 2) The area of ​​the local water-rich abnormal zone expands slightly, but there are no obvious signs of conduction; 3) The water level / water pressure rises slowly, and the rate of rise is less than 50% of the safety threshold; 4) The mining face enters a certain range outside the warning line, but does not enter the warning line.

[0059] II. Yellow Alert (Level III, Warning, determined by meeting any of the following conditions: 1) The water inrush coefficient reaches or exceeds the safety threshold; 2) A single risk factor continues to increase and is predicted to approach the danger level within 7 days; 3) Geophysical exploration / downhole detection discovers a new local water-rich anomaly, which is suspected to be connected to the old goaf; 4) The mining face has entered the warning line but has not entered the water exploration line.

[0060] III. Orange Alert (Level II, Warning): The following conditions must be met for a judgment to be made: 1) The water inrush coefficient exceeds the critical value and continues to rise; 2) At least two risk factors exceed the standard at the same time, and the time-series predicted risk will rapidly expand; 3) The water-conducting fracture zone / floor damage zone is close to or suspected to be connected to the aquifer / old working water accumulation area; 4) The mining face has entered the water exploration line, but has not yet entered the water accumulation line.

[0061] IV. Red Alert (Level I, Emergency): The following conditions must be met for a red alert to be issued: 1) The water inrush coefficient reaches the critical value of danger, or the water accumulation area has the conditions for instantaneous water inrush; 2) Drilling / monitoring directly confirms that the old working water and the water diversion channel have been connected; 3) Sudden change in water level / water pressure and abnormal increase in water volume, with obvious signs of water inrush; 4) The mining face enters or approaches the water accumulation line.

[0062] In addition, spatial location is used as a mandatory constraint in the risk level determination: if the working face is outside the warning line, the spatial risk factor is low; if the working face enters the warning line, the spatial risk factor is increased by one level; if the working face enters the water exploration line, the spatial risk factor is increased by two levels; if the working face approaches the water accumulation line, a high-level warning is directly triggered.

[0063] After determining the warning level, the system outputs the following: 1) Warning level; 2) Main risk factors and their exceedance status; 3) Risk location and spatial range; 4) Risk change trend; 5) Recommended prevention and control measures. These are then visually rendered in different colors on the real-time risk situation map in GIS. 3) Tiered response execution layer: Automatically triggers corresponding prevention and control measures based on the warning level, including at least one of the following: automatically starting the emergency drainage system, adjusting the working face advance speed, or starting a special exploration program.

[0064] For example, if the updated three-line map shows that mining activities have entered the warning line and the risk prediction level is high, the early warning mechanism will be activated immediately. The intelligent analysis and decision-making layer can determine it as an orange warning, and the hierarchical response execution layer will automatically trigger the instructions to "adjust the working face advance speed" and "start the special encrypted exploration program", forming a closed-loop control.

[0065] Finally, it should be noted that 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 present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A coal mine goaf water hidden disaster-causing factor census method, characterized in that, Collect and integrate multi-source historical data of the target mining area, establish an initial old working water information ledger, and preliminarily delineate the suspected old working water area on the mining engineering plan; A ground survey was conducted on the target mining area and its surrounding areas. Combined with the interpretation of UAV remote sensing data, surface cracks, subsidence pits, old mine shafts and water bodies were identified, and the scope of suspected old mine water areas was updated. A survey network was deployed within the updated old goaf suspected area, and a scanning exploration was carried out using ground geophysical methods to delineate the boundaries of the water-rich anomaly area and the suspected goaf area, forming regional geophysical exploration results. Measurement points are set up in the underground mining face, and underground geophysical exploration methods are used to conduct directional exploration of the front of the tunnel, the top and bottom plates and sidewalls of the mining face, identify hidden water-conducting structures and local water-rich bodies, and form detailed underground exploration results. Based on regional geophysical exploration results and detailed downhole detection results, verification boreholes were drilled in the delineated anomaly areas; the verification boreholes included surface boreholes and downhole directional boreholes. Observation holes are set up at the working face of the target coal seam to measure the development height of the water-conducting fracture zone and / or the development depth of the mining-induced failure zone of the floor after the coal seam is mined. By integrating all the data obtained above, the spatial distribution, water accumulation, recharge sources and convection risks of old water inlets are dynamically assessed; based on the assessment results, a distribution map of potential old water inlets hazards, a water-rich zoning map, and a three-line management map including water accumulation line, water exploration line and warning line are drawn and dynamically updated. Establish an early warning mechanism for water hazard risks in old-type airfields based on real-time monitoring data and assessment models to provide risk warnings.

2. The method of claim 1, wherein, Oriented exploration of the tunneling front, roof and floor of the longwall face, and sidewalls using downhole geophysical methods includes: For tunnel excavation faces, the mine transient electromagnetic method is used for sector detection to identify water-rich bodies and water-conducting structures ahead of the excavation. For longwall mining faces, radio wave tunnel fluoroscopy is used to detect geological anomalies in the coal seams inside the working face; and audio-frequency electromagnetic fluoroscopy or multi-component transient electromagnetic methods are used to detect the water-bearing properties of the sandstone aquifer on the roof and the rock strata on the floor of the working face.

3. The method of claim 2, wherein, Information on geological anomalies and water-rich bodies obtained through downhole geophysical exploration methods is used as known points or calibration points and fed back into the process of surface geophysical data inversion and interpretation to correct the inversion parameters and interpretation models of surface geophysical exploration.

4. The method of claim 3, wherein, Based on regional geophysical exploration results and detailed downhole detection results, verification boreholes were drilled in the delineated anomaly areas, including: The construction involves drilling boreholes on the ground to verify the abnormal areas delineated by ground geophysical exploration; the boreholes penetrate the goaf of the target coal seam to directly reveal the location of the goaf, the filling material and water accumulation, and core samples are taken for lithological identification; after completion, the boreholes also serve as long-term hydrological observation wells to continuously acquire water level, water temperature and water quality data through automatic monitoring equipment. Directional drilling is carried out in the construction well to verify the anomalies discovered by the underground geophysical exploration and the risk zone ahead of the tunneling. The formed boreholes also serve as advance exploration and drainage holes. The location, volume, pressure, quality, and recharge conditions of the old hollow water space were obtained through drilling.

5. The method of claim 4, wherein, The drilling also obtained the water pressure of the Ordovician limestone aquifer beneath the bottom of the target coal seam.

6. The method of claim 5, wherein, By integrating ground geophysical exploration, downhole geophysical exploration, verification borehole and observation borehole measured data, a risk quantification model based on multi-source information coupling is used for dynamic comprehensive assessment. Based on the assessment results, distribution maps of old goaf water hazards, water-rich zoning maps and three-line management maps are drawn and dynamically updated; among them, the three-line management map is dynamically updated based on the boundary of the goaf water accumulation area obtained from the verification borehole.

7. The method of claim 6, wherein, The dynamic comprehensive assessment using a risk quantification model based on multi-source information coupling includes introducing a time-series evolution analysis module, which arranges the geophysical exploration, drilling, and monitoring data in chronological order to form a time-series dataset for each risk factor. Analyze the temporal dependencies and evolution patterns among various risk factors; predict the changing trends of each risk factor over a future period based on historical time-series data and current monitoring data; and dynamically adjust the early warning thresholds for different risk levels based on the risk trend prediction results. The risk factors include the amount of water accumulated in the old goaf, the relationship between the measured development height of the water-conducting fracture zone in the overlying strata and the distance to the goaf, the relationship between the depth of the floor failure and the thickness of the aquitard and the water pressure of the Ordovician limestone, the degree of development of the water-conducting structure, and the water inrush coefficient of the pressurized mining area. Dynamic updates to the three-line management map based on the boundary of the goaf water accumulation area obtained from the verification borehole include: marking the boundary of the goaf water accumulation area obtained from the verification borehole as the water accumulation line; using the water accumulation line as a reference, pushing it outward by a first preset safety distance to form a water exploration line; using the water exploration line as a reference, pushing it outward by a second preset safety distance to form a warning line; and as the mining face advances, correcting the water accumulation line, water exploration line, and warning line according to new drilling or geophysical exploration results.

8. The method according to claim 6, characterized in that, Establishing an early warning mechanism for water hazard risks in old-age reservoirs based on real-time monitoring data and assessment models includes: A risk situation awareness layer is set up to collect multi-source data from geophysical exploration, drilling and monitoring in real time, and form a real-time risk situation map through data fusion processing. An intelligent analysis and decision-making layer is set up, which uses the time-series evolution analysis module and combines it with the real-time risk situation map to conduct risk trend analysis and early warning level determination; A tiered response execution layer is set up to automatically trigger corresponding prevention and control measures based on the warning level, including at least one of the following: automatically activating the emergency drainage system, adjusting the working face advance speed, or initiating a special exploration program.

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