Mine water prevention and control risk early warning method and system based on the integration of earthquake and geology

Abstract

The present application provides a mine water prevention and control risk warning method and system based on the integration of earthquakes and geology, belonging to the field of soil or rock drilling. The method includes: receiving real-time earthquake data from an earthquake monitoring module and geological exploration data from a geological exploration module, the geological exploration module including a borehole detection module and a hydrogeological analysis module; based on real-time earthquake data, geological exploration data and a preset water prevention and control risk warning model, obtaining a risk level including risk levels and corresponding water prevention and control execution measures; triggering target execution equipment such as drilling equipment to perform prevention and control according to the execution measures: at the first risk level, a monitoring hole is drilled and an optical fiber piezometer is installed to collect seepage pressure data; at the second risk level, a grouting hole is drilled to grout and seal the fissure; at the third risk level, a water diversion hole is constructed in the aquifer to guide groundwater to a safe area through a drainage pump group. This method integrates multi-source data to achieve graded and precise warning and prevention.

Description

Technical Field

[0001] The present application relates to the technical field of mine water prevention and control risk warning technology, and in particular to a mine water prevention and control risk warning method and system based on the integration of earthquake and geology. Background Art

[0002] Mine water hazard prevention and control is a key link in ensuring the safe mining of underground minerals. As the mining depth increases, the risks of disasters such as groundwater seepage and aquifer inrush increase, which puts higher requirements on the accurate identification of water hazard hazards and dynamic assessment of risk levels.

[0003] Existing technologies primarily use drilling and logging analysis to statically characterize the geological structure of a target area. Seismic monitoring relies on sensor networks to capture vibration signals generated by rock fractures, which are used to identify areas of tectonic stress concentration or potential water inrush channels. However, the data collection and processing of these two technologies are relatively independent: geological exploration focuses on static parameter measurement, while seismic monitoring focuses on dynamic signal capture. Consequently, a cross-modal data correlation analysis mechanism for water hazard risk has yet to be established.

[0004] Current technology faces several challenges: First, the integration of geological survey and seismic monitoring data is insufficient, lacking an assessment method that can comprehensively reflect the correlation between geological structural stability and seismic activity. This results in risk warnings failing to account for the coupled effects of static geological conditions and dynamic stress disturbances. Second, the matching accuracy between risk assessment results and prevention measures is insufficient. Existing drilling equipment operating modes fail to intelligently adjust based on the combined analysis of geological and seismic data, making it difficult to meet the precise prevention and control needs in different water hazard scenarios. These issues have led to delays in mine water prevention and control, including delayed warnings and poorly targeted measures. Summary of the Invention

[0005] In view of this, the purpose of the embodiments of the present application is to provide a mine water prevention and control risk warning method and system based on the integration of earthquake and geology to solve the above technical problems.

[0006] To achieve the above objectives, in a first aspect, embodiments of the present application provide a mine water risk warning method based on the integration of earthquake and geology, the method comprising:

[0007] Receive real-time seismic data transmitted from the seismic monitoring module and geological exploration data transmitted from the geological exploration module, wherein the geological exploration module includes a borehole detection module and a hydrogeological analysis module, which are used to detect data on the geological structure and hydrogeological conditions of the target mine area respectively;

[0008] Based on real-time seismic data, geological survey data and a preset water prevention and control risk warning model for the target mine area, a risk level is obtained, and corresponding mine water prevention and control implementation measures are determined according to the risk level;

[0009] According to the mine water prevention and control implementation measures, the target execution device is triggered to perform corresponding prevention and control treatment on the target mine area; the target execution device includes a drilling device, and the prevention and control treatment includes:

[0010] At a first risk level associated with seepage pressure, the drilling equipment drills monitoring holes in the target mine area, and sets a fiber optic piezometer in the monitoring hole to collect seepage pressure data;

[0011] At the second risk level associated with rock formation fissures, the drilling equipment performs grouting and plugging treatment on grouting holes drilled in the rock formation fissures;

[0012] At the third risk level associated with aquifers or water inrush risks, the drilling equipment constructs a water diversion hole in the aquifer and guides the groundwater to a safe area through a drainage pump group connected to the water diversion hole.

[0013] In a second aspect, a mine water risk warning system based on the integration of earthquakes and geology is provided, the system comprising:

[0014] A data acquisition and reception module, configured to receive real-time seismic data transmitted from the seismic monitoring module and geological exploration data transmitted from the geological exploration module; wherein the geological exploration module includes a borehole detection module and a hydrogeological analysis module; the borehole detection module is configured to detect geological structure data of the target mine area, and the hydrogeological analysis module is configured to detect hydrogeological condition data of the target mine area;

[0015] a risk assessment module, communicatively connected to the data acquisition and receiving module, having a built-in preset water prevention and control risk warning model, for obtaining a risk level based on the real-time seismic data, geological survey data, and the preset water prevention and control risk warning model, and determining corresponding mine water prevention and control implementation measures according to the risk level;

[0016] An execution control module, in communication with the risk assessment module, configured to trigger a target execution device to perform corresponding prevention and control treatment on the target mine area according to the mine water prevention and control implementation measures;

[0017] The target execution device includes a drilling device, and the drilling device is configured as follows:

[0018] When the risk level is the first risk level associated with seepage pressure, a monitoring hole is drilled in the target mine area, and an optical fiber piezometer is installed in the monitoring hole to collect seepage pressure data;

[0019] When the risk level is the second risk level associated with rock formation fissures, drilling grouting holes in the rock formation fissures and performing grouting to seal and fill the holes;

[0020] When the risk level is the third risk level associated with the aquifer or water inrush risk, a water diversion hole is constructed in the aquifer, and the groundwater is guided to a safe area by a drainage pump group connected to the water diversion hole.

[0021] The above technical solution has the following beneficial effects: By integrating real-time seismic data from the seismic monitoring module with borehole detection and hydrogeological analysis data from the geological exploration module, the present invention constructs a multi-source data-driven water prevention and control risk assessment model, achieving dynamic, graded early warning and precise prevention of mine water hazard risks. Based on different risk levels such as seepage pressure, rock fractures, and aquifer water inrush, the drilling equipment is intelligently triggered to perform differentiated operations (drilling monitoring holes, grouting holes, and water diversion holes). Combined with the coordinated application of equipment such as fiber optic piezometers and drainage pumps, this avoids the blindness of traditional single-method approaches and improves the adaptability and operational efficiency of drilling equipment in complex water hazard scenarios. Through cross-modal data fusion (seismic dynamic stress signals and static geological structure parameters), the limitations of single-parameter monitoring are avoided. Pre-set risk warning models are used to comprehensively analyze multi-dimensional indicators such as seepage pressure, fracture development, and aquifer connectivity, improving the accuracy and timeliness of water hazard risk level assessments. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0023] Figure 1 This is a flow chart of a mine water risk warning method based on the integration of earthquake and geology according to an embodiment of the present application;

[0024] Figure 2 This is a schematic structural diagram of a mine water risk warning system based on the integration of earthquake and geology according to an embodiment of the present application;

[0025] Figure 3 is a structural block diagram of a computer-readable storage medium according to an embodiment of the present application;

[0026] Figure 4 This is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0028] Figure 1 This is a flow chart of a mine water risk warning method based on the integration of earthquake and geology in an embodiment of the present application. Figure 1 As shown, a mine water risk warning method based on the integration of earthquake and geology may include the following steps:

[0029] S10: receiving real-time seismic data transmitted from the seismic monitoring module and geological exploration data transmitted from the geological exploration module, wherein the geological exploration module includes a borehole detection module and a hydrogeological analysis module, which are respectively used to detect data on the geological structure and hydrogeological conditions of the target mine area;

[0030] S20: Based on the real-time seismic data and geological survey data of the target mine area and a preset water prevention and control risk warning model, a risk level is obtained, and corresponding mine water prevention and control implementation measures are determined according to the risk level;

[0031] S30: triggering a target execution device to perform corresponding prevention and control treatment on the target mine area according to the mine water prevention and control implementation measures; the target execution device includes a drilling device, and the prevention and control treatment includes:

[0032] At a first risk level associated with seepage pressure, the drilling equipment drills monitoring holes in the target mine area, and sets a fiber optic piezometer in the monitoring hole to collect seepage pressure data;

[0033] At the second risk level associated with rock formation fissures, the drilling equipment performs grouting and plugging treatment on grouting holes drilled in the rock formation fissures;

[0034] At the third risk level associated with aquifers or water inrush risks, the drilling equipment constructs a water diversion hole in the aquifer and guides the groundwater to a safe area through a drainage pump group connected to the water diversion hole.

[0035] The following is a detailed description of the mine water risk warning method based on the integration of earthquake and geology in this embodiment:

[0036] First, the system collects data from the target mine area in real time through a seismic monitoring module and a geological exploration module. The seismic monitoring module, deployed in the mine tunnels and surrounding surface, contains distributed vibration sensors that collect seismic wave signals in real time at a sampling frequency of 100Hz. This data, including vibration amplitude, frequency, and propagation path, is then transmitted to the central processing system. The geological exploration module's borehole detection module uses existing exploration boreholes and newly added temporary exploration holes in the mine, using a three-dimensional imaging logging instrument to obtain images of the geological structure of the borehole walls. It then uses resistivity logging technology to detect geological structural data such as rock porosity and fracture development. The hydrogeological analysis module uses pressure sensors and water quality monitors deployed in the aquifer to collect real-time hydrogeological data such as groundwater pressure, water level, and mineralization. Both types of data are transmitted synchronously to the central processing system via industrial Ethernet.

[0037] After receiving the data, the central processing system activates a pre-set flood risk warning model for processing. This model, trained based on historical mine flood case data, features a three-layer neural network architecture. The input layer receives standardized seismic data (including vibration frequency and energy values) and geological data (rock fracture density, aquifer pressure gradient, etc.). The hidden layer fuses and calculates this data using a pre-set weight matrix, with seismic data accounting for 40% and geological data for 60%. The model focuses on the correlation between vibration energy values ​​and fracture density, and the coupling between aquifer pressure and earthquake frequency. The output layer, based on the calculated results, outputs a three-level risk level and / or corresponding implementation measures. When the vibration energy value is between 0.3-0.5J and the rock fracture rate is 5%-8%, it is judged as the first risk level, corresponding to the seepage pressure monitoring warning; when the fracture width is greater than 3mm and the earthquake frequency is greater than 5 times / hour, it is judged as the second risk level, triggering the rock fracture blocking warning; when the aquifer pressure is greater than 1.5MPa and the water quality mineralization drops sharply, it is judged as the third risk level, and the water inrush prevention and control warning is activated.

[0038] The central processing system automatically triggers target execution devices based on the risk level. If the risk level is determined to be Level 1, drilling equipment is dispatched to the risk area. Monitoring holes with a diameter of 75mm and a depth of 50-80 meters are drilled at standard intervals of 15-20 meters, with a verticality error of less than 1%. A fiber-optic piezometer (accuracy ±0.1% FS) is immediately lowered after the hole is completed and secured with a hole-sealing device. Real-time seepage pressure data is collected and connected to the monitoring network. For Level 2 risk, the drilling equipment is replaced with a diamond plywood drill bit. Grouting holes with a diameter of 90mm are drilled in areas with developed fractures, reaching a depth of 2-3 meters through the fracture zone. A dual-liquid grouting pump (flow rate of 50-100 L / min) is used to inject a cement-water glass slurry at a pressure of 2-3 MPa until slurry returns to the hole and the pressure remains stable for at least 5 minutes, effectively sealing and filling the fractures. When the third risk level is reached, the drilling equipment constructs a water diversion hole with a diameter of 150mm. The bottom of the hole needs to be more than 5 meters deep into the aquifer, and a blowout preventer is installed at the hole mouth; the water diversion hole is connected to the drainage pump group (total drainage capacity ≥200m³ / h) through a high-pressure hose. The pump group is installed 0.5 meters above the tunnel bottom plate. The PLC control system automatically starts and stops according to the water level sensor signal, and the groundwater is led to the surface sedimentation tank through a dedicated drainage pipeline to achieve active prevention and control of water inrush risks.

[0039] Throughout the entire process, the system displays the operating status of each module in real time through configuration software. Risk assessment results and implementation measures are simultaneously pushed to the mine's central control room and the mobile devices of relevant responsible personnel, forming a closed-loop management system. On-site operators can manually intervene in equipment operations through the human-machine interface, ensuring emergency response capabilities in the event of an emergency.

[0040] In some embodiments, the borehole detection module includes at least one of a well logging instrument, a sonic detector, and a tracer detection device.

[0041] In some embodiments, the logging instrument includes at least one of a resistivity logging instrument, a natural gamma ray logging instrument, and a sonic transit time logging instrument;

[0042] The resistivity logging instrument is used to obtain resistivity data of rock formations in the target mine area to identify the distribution of aquifers;

[0043] The natural gamma ray logging tool is used to obtain radioactivity intensity data of rock formations to identify lithology;

[0044] The acoustic time difference logging tool is used to obtain acoustic wave propagation time data of rock formations to determine the porosity of the rock formations.

[0045] For example, a resistivity logging tool is lowered into existing or newly constructed boreholes in a mine. The tool transmits current through its electrode system to the surrounding rock formations, collecting resistivity data in real time. Because aquifers differ in conductivity from other rock formations, analyzing the trends in this resistivity data allows precise identification of the distribution and location of aquifers within the target mine area.

[0046] During the detection process, a natural gamma logging instrument is lowered into the borehole along the drill pipe, using a gamma-ray detector to receive gamma rays produced by the decay of natural radionuclides in the rock formation. By recording and analyzing the radioactivity intensity data at different depths, the rock type can be effectively identified. For example, different rock types such as mudstone, sandstone, and limestone have different radioactivity intensity characteristics, providing basic lithology data for subsequent risk assessment.

[0047] When operating, the transit time logging tool transmits acoustic signals into the rock formation and simultaneously receives reflected waves. By precisely measuring the propagation time of the acoustic wave in the rock formation and combining it with the known formula for the propagation velocity of acoustic waves (which is relatively stable in specific media), the transit time data of the rock formation is calculated, thereby determining the porosity of the rock formation. Porosity data is useful for assessing the water storage capacity and permeability of the rock formation, providing key parameters for early warning of mine water risk.

[0048] In some embodiments, the acoustic wave detector includes an ultrasonic detector or an infrasonic wave detector; the acoustic wave detector is used to transmit acoustic wave signals to the rock formation in the target mining area and receive reflected echo signals, and determine the location, width and connectivity of rock formation cracks by analyzing the time delay, energy attenuation and frequency change of the reflected echo signals.

[0049] Specifically, the acoustic wave detector group includes two types of equipment: ultrasonic detectors and infrasonic detectors. The ultrasonic detectors operate in the 20-50kHz frequency range, and the infrasonic detectors operate in the 5-20Hz frequency range. During implementation, measurement points are arranged in a 10m x 10m grid on the sidewalls of the mine tunnels. The ultrasonic detectors use pulse transmission mode, emitting 0.1ms-wide acoustic pulse signals at a peak power of 500W toward the rock formation. The infrasonic detectors use a continuous frequency sweep mode to emit low-frequency acoustic beams with a period of 1-5 seconds.

[0050] After being received by a highly sensitive piezoelectric sensor, the reflected echo signal is converted into a digital signal using a 1MHz sampling rate via a 16-bit analog-to-digital sampling module. For ultrasonic echoes, the system first records the time difference between the transmitted wave and the first reflected wave. Using this time difference, the system calculates the straight-line distance between the fracture interface and the detection point, based on a preset average rock velocity of 5200 m / s. This accuracy allows for a positioning accuracy of ±0.3 meters. For infrasonic echoes, Fourier spectrum analysis is used to extract the energy attenuation characteristics of the 0.5-15Hz frequency band. When the energy attenuation rate in a specific frequency band exceeds 30% of the baseline value for intact rock formations, a through-fissure greater than 5mm in width is determined to be present in the area.

[0051] Furthermore, the system achieves accurate measurement of fracture parameters through dual-frequency coupling analysis. Specifically, 28kHz ultrasonic waves and 8Hz infrasonic waves are emitted synchronously to the same measuring point to capture the phase distortion characteristics of the high-frequency signal and the group velocity change of the low-frequency signal, respectively. When the width of the rock fracture is in the range of 1-10mm, the attenuation rate of the component above 3kHz in the frequency component of the ultrasonic reflection signal is linearly related to the fracture width, and when the decrease in the infrasonic group velocity exceeds 12%, it is determined that the fracture has hydraulic connectivity. In some embodiments, the tracer detection equipment includes a tracer injection device and a tracer monitoring device; the tracer injection device is used to inject fluorescent tracers, radioactive tracers or chemical tracers into the aquifer or fracture zone in the target mine area; the tracer monitoring device is used to determine the infiltration path of groundwater or the water conductivity of the fracture by detecting the tracer concentration and migration trajectory in the groundwater or rock pores.

[0052] Specifically, the tracer injection device consists of a dual-channel hybrid grouting pump equipped with a corrosion-resistant fluid storage tank and a flow control module. During implementation, the type of tracer is selected based on the depth of the target aquifer: for shallow fractured zones (burial depth less than 200 meters), a 5% sodium fluorescein solution is used as the tracer, injected continuously for 30 minutes at an injection pressure of 0.5 MPa through a 50 mm diameter grouting pipe. For deep, high-pressure aquifers (burial depth ≥ 500 meters), an iodine-131 radioactive tracer with a half-life of 12 hours is selected and injected at a pressure of 8-12 MPa through a high-pressure sealed grouting system, with the injection volume per hole controlled within the range of 200-300 mL.

[0053] The tracer monitoring system comprises a distributed detection network: eight detection units are radially arranged within 50 meters downstream of the grouting hole, each consisting of a fluorescence spectrometer, a gamma-ray detector, and an ion chromatograph. For fluorescent tracers, the monitoring units illuminate the water sample with a 470nm wavelength excitation light source, and a photomultiplier tube measures the fluorescence intensity in the 520-550nm band, with a sensitivity of 0.01ppb. For radioactive tracers, a sodium iodide scintillation detector continuously monitors gamma-ray intensity in counts per second mode, with a detection limit of 0.1Bq / L. For chemical tracer detection, an ion-selective electrode array measures chloride and sulfate ion concentrations in real time, with a resolution of 0.1mg / L.

[0054] During data analysis, the system reconstructs the groundwater migration trajectory based on the temporal and spatial distribution characteristics of the tracer concentration. When the peak concentration of the fluorescent agent appears in the second monitoring unit in the northeast direction within 2 hours after grouting, it is determined that the fracture water channel in this direction is the main infiltration path; if the radioactive tracer shows an exponential decay curve in the three monitoring units at the same time, and the half-life is shortened to 8.5 hours, it indicates the existence of a multi-branch strong water-conducting fracture network. Further calculations are made through Darcy's law inversion. When the tracer front migration velocity is greater than 0.5m / min, it is determined that the equivalent permeability coefficient of the water-conducting fracture exceeds 5× cm / s, the system automatically marks it as a high-risk water channel. In some embodiments, the borehole detection module also includes a formation dip logging instrument. The formation dip logging instrument determines the dip angle and distribution characteristics of the rock formation in the target mining area by measuring the formation dip direction and dip angle data at multiple depth points in the borehole.

[0055] Specifically, the formation inclination logging tool utilizes a four-arm caliper combined with a triaxial accelerometer and magnetometer. A sensor array is placed every 0.5 meters on the surface of the measuring rod. During implementation, vertical boreholes are arranged in a 50-by-50-meter grid in the target mine area. The logging tool is lowered at a speed of 0.3 meters per second and continuously measures along the borehole wall. Each measuring point simultaneously records the change in borehole diameter, the gravity acceleration vector, and the geomagnetic field component data, with a measurement accuracy of ±0.5 degrees.

[0056] During data acquisition, the system eliminates geomagnetic interference using a magnetic azimuth compensation algorithm. At each depth point, the true north azimuth is calculated using the horizontal component of the geomagnetic field measured by the magnetometer. Combined with the toolface angle data measured by the accelerometer, the raw tilt data is converted to a geographic coordinate system. When the caliper detects a wellbore collapse, it automatically triggers an intensified measurement mode, shortening the measurement interval to 0.1 meters. Three measurements are repeated in that section, and the median value is taken to ensure the reliability of the tilt data.

[0057] During data processing, a sliding window statistical method is used to calculate the rate of change of inclination per meter of the well section, creating a dip rose diagram and a three-dimensional pole density map. When the intersection analysis of the dip vectors of adjacent boreholes indicates a stratum dip gradient exceeding 5 degrees per 10 meters, the system automatically marks it as a structural fracture zone boundary. Using the Kriging interpolation algorithm, the discrete point data is converted into regional stratum occurrence contour maps, visually displaying the dip distribution characteristics of key structures such as the anticline axis and the fault hanging wall.

[0058] In practice, the project plan is optimized based on the dip measurement results. For example, if the angle between the rock formation dip and the tunnel axis is detected to be less than 30 degrees, the system automatically adjusts the grouting hole spacing from the designed value of 5 meters to 3 meters. If the overlap between the reverse dip area and the seismic anomaly zone exceeds 60%, a red alert is triggered, requiring the construction company to add a 15-degree correction angle to the drilling trajectory planning to ensure that the grouting holes penetrate the high-angle fracture zone.

[0059] In some embodiments, the logging instrument also includes a magnetic positioning logging instrument, which calculates the distribution depth of each rock layer in the borehole by measuring the magnetic signal of the casing coupling in the borehole and combining it with the known casing length; and uses the measurement data of the resistivity logging instrument and the natural gamma logging instrument at different depths to construct a continuous rock layer profile and determine the contact relationship between the rock layers.

[0060] Specifically, in some embodiments, the logging instrument is equipped with a magnetic positioning logging tool to accurately determine the depth distribution of rock formations and construct a continuous rock formation profile. During actual logging, the magnetic positioning logging tool is integrated with the resistivity logging tool and the natural gamma logging tool into the same logging probe and lowered into the borehole via a cable. Before logging, the casing coupling parameters must be calibrated. Given a standard casing length of 9.6 meters, the magnetic signal at the coupling location exhibits distinct peak-to-valley variations (positive pulse amplitude ≥ 20mV). During logging, the magnetic positioning logging tool captures the magnetic signal of the casing coupling at a sampling frequency of 20Hz. When the probe passes over a coupling, the magnetic sensor detects a sudden change in magnetic field intensity. Combined with the cable lowering speed (consistently controlled at 0.5 m / s) and the coupling spacing, the depth coordinate corresponding to each coupling is calculated through cumulative calculation (accuracy ±0.1m). Based on this, a corresponding relationship between the drilling depth and the rock formation position is established. For example, if the depth of the first coupling is 15.2 meters, its corresponding casing connection point is determined, and the range of 4.8 meters above and below is the rock formation section covered by a single casing.

[0061] When constructing a rock formation profile, the measurement data of the resistivity logging tool (such as the dual lateral resistivity probe) and the natural gamma logging tool (NaI scintillation detector) at the same depth are collected simultaneously. The depth coordinates provided by the magnetic positioning logging tool are used as a unified scale to align the resistivity curve (reflecting the conductivity of the rock formation) and the natural gamma curve (reflecting the radioactivity intensity) according to the depth to form a continuous logging data sequence. When the resistivity value at a certain depth changes from 50 ohms to 100 ohms, the resistivity value at the depth changes from 50 ohms to 100 ohms. rice( or ohmm) dropped to 20 ohms rice( When the natural gamma ray count increases from 80 API to 120 API, combined with magnetic positioning depth data, the location can be determined as the interface between mudstone and sandstone. By analyzing the changes in logging parameters at different depths, the location of the rock interface can be identified, and the contact relationship between the rock layers can be determined, such as conformable contact (gradual transition of the curve) or unconformable contact (abrupt interval of the curve).

[0062] In some embodiments, the borehole detection module also includes a borehole television imager, which acquires an image of the borehole wall by emitting visible light or infrared light into the borehole, identifies the rock layer interface based on image analysis, and measures the rock layer thickness; and, through the morphological characteristics of the rock layer interface in the image of the borehole wall, determines the contact relationship between the rock layers, wherein the contact relationship includes conformable contact, unconformable contact, or fault contact.

[0063] Specifically, in some embodiments, the borehole detection module incorporates a borehole television imager to enable visual detection and analysis of the borehole wall. This instrument utilizes a borehole television imager, whose front-end probe integrates a high-resolution color camera and a ring-shaped LED light source (visible light wavelength 500-700nm). It supports 360-degree panoramic photography and an imaging resolution of 1920×1080, enabling clear capture of subtle features of the borehole wall.

[0064] During actual operation, a borehole TV imager is lowered into the borehole via a wireline or cable. The probe is slowly raised from the bottom of the hole to the hole mouth at a constant speed of 0.3 meters per minute, continuously emitting visible light toward the hole wall. The camera captures images formed by light reflected from the hole wall in real time, capturing 25 frames per second and transmitting the image data via a cable to a ground control host. The ground control host is equipped with dedicated image acquisition and processing software, automatically storing image data and supporting real-time preview. The operator can adjust the light source brightness and shooting parameters to suit image quality.

[0065] To identify rock interfaces and measure thickness, the image processing software uses an edge detection algorithm to analyze captured images. When an area with abrupt changes in color, texture, or structure appears in the image, the system automatically marks it as a potential rock interface. For example, at the transition from the grayish-white, granular texture of sandstone to the grayish-black, fine texture of mudstone, the software accurately identifies the interface location by calculating the differences in RGB values ​​and texture characteristics between adjacent pixels. Furthermore, by combining the probe lift speed and the image acquisition interval, the thickness of each rock layer can be accurately calculated. For example, if the image duration of a rock layer during a 10-minute lift is 2 minutes, the corresponding rock layer thickness is 0.6 meters.

[0066] To determine rock layer contact relationships, the morphological characteristics of the rock layer interfaces in borehole wall images are analyzed. If the rock layer interface is smooth and continuous, with gradual transitions in color and texture, it is considered a conformable contact. If the interface exhibits significant angular differences, discontinuities, or signs of weathering and erosion, it is considered an unconformable contact. If the interface exhibits signs of fracture, dislocation, and significant differences in color and texture between the two layers, it is considered a fault contact. These analysis results are verified with data obtained from other equipment, such as magnetic positioning logging tools and resistivity logging tools, providing an accurate basis for geological structure analysis and water control risk assessment in the target mining area.

[0067] In some embodiments, when drilling a monitoring hole at the first risk level, the depth of the monitoring hole is determined based on the aquifer burial depth and aquiclude thickness parameters in the geological exploration data, and the diameter of the monitoring hole matches the outer diameter of the fiber optic piezometer; the fiber optic piezometer is lowered to the bottom of the monitoring hole through the built-in channel of the drill pipe and is fixed to a predetermined position of the monitoring hole using an inflatable packer.

[0068] Specifically, in some embodiments, when the system determines that the target mine area is at the first risk level associated with seepage pressure, it is necessary to accurately drill monitoring holes and install fiber optic piezometers based on geological survey data. The specific steps are as follows:

[0069] First, the depth of the monitoring wells was determined based on the aquifer depth and aquiclude thickness parameters obtained by the geological exploration module. A resistivity log was used to identify the aquifer's distribution. Combined with the rock formation depth coordinates calculated using a magnetic positioning log, the top of the aquifer was determined to be H meters deep and the aquiclude thickness to be T meters. The monitoring wells were designed to have a depth of H + T / 2 meters, ensuring the bottom of the hole was located in the stable central region of the aquiclude to avoid interference with aquifer seepage. A directional drill was used for drilling. Based on the size of the fiber optic piezometer, the borehole diameter was set to 75 mm, leaving a 43 mm annular space for packer installation and cement slurry filling.

[0070] During drilling, the borehole location is first determined using the mine's high-precision positioning system (with an accuracy of ±0.5 meters), and the drill rig's verticality is adjusted to a deviation of ≤1°. During drilling, a borehole television imager monitors the rock structure of the borehole wall in real time. When the drill bit enters the aquiclude at a predetermined depth (determined by gamma ray logging data indicating a stable radioactivity level of 100-150 API), drilling is stopped and the hole is cleaned. A fiber optic piezometer (40 mm diameter) is then lowered through a channel built into the drill pipe to the bottom of the hole, with the sensor at the end of the piezometer pointing toward the aquifer. When the piezometer reaches the predetermined position (confirmed by the depth scale marked on the magnetic positioning logging instrument), the surface hydraulic pump is activated to pressurize the drill pipe to 8 MPa, forcing the inflatable packer into contact with the borehole wall, forming a sealed isolation section.

[0071] After the packer is secured, a cement slurry with a water-cement ratio of 1:1.5 is injected through the drill pipe to seal the orifice. The grouting depth covers an area 5 meters below the orifice. After the cement slurry solidifies (curing time ≥ 24 hours), the drill pipe is removed and a waterproof protective casing is installed. A fiber optic piezometer is connected to the ground data acquisition system via an armored optical cable, collecting real-time seepage pressure data (accuracy ±0.1% FS). The data transmission frequency is set to once per minute, providing continuous groundwater pressure change parameters to the risk warning model, enabling dynamic monitoring of seepage pressure risks.

[0072] In some embodiments, when drilling a grouting hole at the second risk level, the drilling equipment performs the following synchronous drilling and grouting process:

[0073] The drilling equipment is equipped with a dual-channel drill pipe, where the first channel is used to drive the drill bit to rotate, and the second channel is connected to the grouting pump;

[0074] When the drill bit reaches a preset fracture depth, slurry is injected into the fracture through the second channel, while the drill bit promotes the diffusion of the slurry in a vibration mode;

[0075] The grouting pressure is dynamically adjusted according to the rock formation vibration frequency in the real-time seismic data.

[0076] Specifically, in some embodiments, for the second risk level associated with rock formation fissures, the drilling equipment uses a synchronous drilling and grouting process to achieve fissure sealing. The specific implementation steps are as follows:

[0077] The drilling equipment used was a dual-channel intelligent drilling rig equipped with a customized dual-channel drill pipe (89mm outer diameter, 40mm inner diameter of the first channel for power transmission, and 25mm inner diameter of the second channel for connecting to the grouting pipeline). The drill bit was a vibrating composite drill bit (90mm diameter, with a built-in electromagnetic vibrator and an adjustable vibration frequency of 0-100Hz). Before construction, the target depth for the grouting holes was set at 1.5 meters below the bottom of the fracture zone, based on the fracture distribution imagery identified by the borehole television imager and the depth coordinates determined by the magnetic positioning logging tool, ensuring that the drill bit fully entered the fracture-prone area.

[0078] During drilling, the drill bit's hydraulic motor drives the first channel at 150 rpm, breaking the rock. The second channel remains closed to prevent rock dust from entering the grouting line during drilling. When the drill bit reaches the preset depth (confirmed by real-time depth data from the magnetic positioning logging instrument), the rig control system automatically switches to grouting mode. In grouting mode, the dual-liquid grouting pump is activated, injecting a cement-water-glass slurry (cement slurry with a water-cement ratio of 1:1, a water-glass concentration of 35°Be', and a volume ratio of 1:0.8) into the fracture through the second channel. Simultaneously, the drill bit's electromagnetic vibrator is activated, generating axial vibrations at a frequency of 50 Hz and an amplitude of ±2 mm. This mechanical disturbance promotes the diffusion of the slurry into the fracture branches.

[0079] Grouting pressure is dynamically adjusted based on the rock formation vibration frequency captured by real-time seismic data. Specifically, when the seismic monitoring module data received by the central processing system indicates a rock formation vibration frequency of 10Hz, the initial grouting pressure is set to 1.5MPa. If the frequency increases to 20Hz, indicating increased connectivity within the rock formation fractures, the control system automatically increases the grouting pressure to 2.5MPa to ensure effective grouting of the highly permeable channels. When the frequency drops below 5Hz, the pressure is gradually reduced to 1.0MPa to prevent excessive pressure from causing rock formation fractures. During the grouting process, a pressure sensor (accuracy of ±0.05MPa) mounted on the rear end of the drill pipe provides real-time pressure feedback. When continuous grouting occurs at the orifice and the pressure remains stable for more than three minutes, the fracture filling is determined to be satisfactory, grouting is stopped, and the drill is slowly withdrawn.

[0080] After the drill is withdrawn, a quick-setting sealant (initial setting time: 30 seconds) is injected through a second channel to seal the 0-2 meter section of the hole. Once the sealant solidifies, the grouting pipeline is removed, completing the grouting hole. This process enables simultaneous drilling and grouting, improving the efficiency and density of crack sealing through vibration-assisted diffusion and dynamic pressure regulation.

[0081] In some embodiments, when drilling a water guide hole under the third risk level, the drilling equipment adopts a directional drilling system, and the directional drilling system includes: a measurement while drilling module, which is used to obtain deviation data between the drilling trajectory and the spatial position of the aquifer in real time; a guidance controller, which is used to adjust the drill bit azimuth according to the deviation data so that the water guide hole penetrates the aquifer; and an anti-collapse wall protection device, which is used to install a water guide pipe with a screen after drilling, and the water guide pipe is fixed along the hole wall of the water guide hole.

[0082] Specifically, in some embodiments, for the third risk level associated with aquifers or water inrush risks, the drilling equipment uses a directional drilling system to achieve precise construction of water guide holes. The specific implementation steps are as follows:

[0083] The directional drilling system integrates a measurement-while-drilling (MWD) module, a steering controller, and a collapse prevention and wall protection device. The MWD module utilizes a wired MWD instrument with a built-in high-precision three-axis gyroscope and accelerometer. It collects in-real-time data on the borehole trajectory's inclination, azimuth, and toolface angle at a rate of five times per second, transmitting this data to the ground control system via a cable within the drill pipe. The ground control system pre-stores a three-dimensional spatial model of the aquifer in the target mine area (based on resistivity logging data from the borehole detection module and horizon inversion results from the seismic monitoring module). The control system calculates the spatial deviation between the borehole trajectory and the aquifer's top and bottom surfaces in real time, triggering a steering control command when it detects that the borehole deviates from the designed aquifer path by more than 1.5°.

[0084] The steering controller utilizes an automatic steering mechanism connected to an adjustable bend at the rear of the drill bit, enabling a 0-3° deflection capability. Upon receiving deviation data, the steering controller adjusts the bend angle via a hydraulic servo system, altering the drill bit's drilling direction. If the deviation indicates the hole is tilted upwards by more than 2°, the bend is deflected downwards by 1.2°, correcting the drill bit's trajectory at a rate of -0.8° / meter. If the azimuth deviates from the aquifer's central axis by more than 5°, the tool face angle is adjusted by rotating the drill pipe until the hole trajectory aligns with the aquifer's spatial position. During drilling, a diamond core bit (150mm diameter) is used, and the drilling speed is controlled at 0.8m / minute to ensure accurate trajectory adjustment.

[0085] After drilling is complete, the anti-collapse wall protection system is activated and a screened water pipe is installed. The water pipe is constructed of φ140mm polyethylene tubing with evenly distributed φ10mm drainage holes (30% porosity) on the outer wall. It is wrapped with an 80-mesh stainless steel screen to prevent clogging by rock debris. The water pipe is lowered into the hole using the drilling rig's hoisting device and secured with a combination of expansion bolts and cement grout. A set of three expansion bolts (spaced 120 degrees apart) is installed every two meters along the outer wall of the water pipe. After expansion, the bolts form a tight contact with the hole wall. Simultaneously, cement grout (water-cement ratio 0.45) is injected through the drill pipe into the annular gap between the hole wall and the water pipe at a pressure of 1.0 MPa until grout returns to the hole mouth. After the grout solidifies (curing for four hours), a stable wall structure is formed. The top of the water pipe is 0.5 meters above the tunnel floor and is connected to the high-pressure hose of the drainage pump group through a flange. The bottom end penetrates more than 5 meters into the aquifer (confirmed by the depth data of the drilling measurement module), ensuring that groundwater is filtered through the screen and then introduced into the drainage system through the water pipe, realizing the safe drainage of aquifer water.

[0086] In some embodiments, the hydrogeological analysis module includes:

[0087] Sensor network, used to collect raw data, including:

[0088] Groundwater level sensor, using capacitive water level sensor or piezoresistive water level sensor, is used to collect groundwater level values ​​in real time;

[0089] Flow direction sensor, using pressure sensor or magnetometer, is used to collect the pressure difference and groundwater flow direction in real time;

[0090] Flow sensor, using electromagnetic flowmeter or ultrasonic flowmeter, is used to collect the flow velocity of groundwater in real time;

[0091] Permeability sensor, using porosity sensor, is used to measure the porosity of geotechnical media;

[0092] The data analysis module is connected to the sensor network and is used to analyze the original data collected by the sensor network to obtain groundwater flow parameters, which include groundwater level, groundwater flow direction, groundwater flow rate and permeability coefficient.

[0093] Specifically, in some embodiments, the hydrogeological analysis module works in conjunction with the data analysis module through a sensor network to achieve accurate collection and analysis of groundwater parameters in the target mine area.

[0094] The sensor network consists of various types of sensors deployed at key monitoring points. The groundwater level sensor uses a capacitive water level sensor, installed in a monitoring well in the aquifer. The sensor probe is immersed in water and measures the change in capacitance between the electrodes to reflect the water level. The resolution is 1mm, and the water level data is transmitted in real time to the central processing system via a 485 bus. The flow direction sensor uses a pressure gradient sensor, with two pressure measurement points spaced 5 meters apart horizontally. The main flow direction of groundwater is determined by measuring the pressure difference between the two points (accuracy ±0.01kPa) and the direction of the pressure gradient, combined with the Bernoulli equation. The data is updated once. / minute; the flow sensor uses an electromagnetic flowmeter, which is installed in a fixed flow measurement section of the mine's main drainage channel. The inner wall lining of the sensor is made of acid and alkali-resistant rubber. The flow rate is calculated by measuring the electromotive force generated by the conductive groundwater cutting the magnetic flux lines (range 0.1-10m / s), and the real-time water flow is converted based on the cross-sectional area; the permeability sensor uses a porosity sensor, which is integrated into the logging probe of the drilling detection module. It measures the pore volume ratio of the rock and soil medium through the principle of neutron scattering, with a measurement accuracy of ±2%. Porosity data at different depths are acquired synchronously with drilling construction.

[0095] The data analysis module runs dedicated hydrogeological analysis software on an industrial control computer and communicates with the sensor network in real time. The software first filters the water level sensor data (removing outliers outside ±3σ) and then calculates the real-time water level using a calibrated capacitance-water level conversion curve. The pressure difference data from the flow sensor is Gaussian smoothed, and the groundwater flow direction vector is determined using a vector synthesis algorithm and output as an azimuth angle (0-360°). The electromotive force signal from the flow sensor is amplified and filtered, and then converted to the value based on the sensor's built-in calibration coefficient (K=0.012m³ / (V s)) and multiplying it by the cross-sectional area of ​​the flow measurement (preset at 2.5 m²) to obtain the water flow rate. The permeability coefficient is calculated by combining porosity sensor data with Darcy's law, using water level gradient and flow data from the same monitoring point. An iterative algorithm is used to invert the permeability coefficient of the rock and soil (in m / d). All analysis results are stored in a database in real time and displayed as curves and graphs, providing dynamic hydrogeological parameter support for water control risk assessment models.

[0096] In some embodiments, the data analysis module specifically includes:

[0097] a groundwater level analysis unit, configured to determine the groundwater level distribution using a time series analysis method based on the groundwater level value;

[0098] a groundwater flow direction analysis unit, configured to determine the groundwater flow direction based on the pressure difference, flow velocity, and water level difference; the water level difference is obtained by comparing groundwater level values ​​between multiple monitoring points;

[0099] a groundwater flow analysis unit, configured to determine the groundwater flow rate based on the flow velocity, cross-sectional area, and water flow model; the cross-sectional area refers to a cross section of the groundwater flow area;

[0100] The permeability coefficient analysis unit is used to determine the permeability coefficient of groundwater according to the porosity of the rock and soil medium, the flow velocity and the groundwater flow direction.

[0101] Specifically, in some embodiments, the data analysis module performs in-depth processing on the raw data collected by the sensor network through four functional units to provide accurate groundwater flow parameters for risk assessment.

[0102] The groundwater level analysis unit is used to construct a time series analysis model. First, the minute-level water level data collected by the capacitive water level sensor is preprocessed, and the high-frequency noise is filtered out by the sliding average method (window size is 15 minutes). In combination with the historical calibration data, outliers outside ±2 times the standard deviation are marked and interpolated to complete the data. Subsequently, the automatic autoregressive integral sliding average model is used to fit the preprocessed data. The model automatically identifies the periodicity and trend terms of water level changes. During the analysis process, the system generates a water level distribution heat map every hour. Based on the mine coordinate system, the water level values ​​of discrete monitoring points are interpolated to the entire target area through the Kriging interpolation method, which intuitively displays the height and gradient changes of groundwater, providing a basis for judging the pressure status of the aquifer.

[0103] The groundwater flow direction analysis unit arranges at least three water-level monitoring points spaced 50 meters apart in the target mine area (forming a triangular monitoring grid). The unit calculates the water-level difference (with an accuracy of ±1 cm) by comparing the real-time water-level values ​​at each point. For example, when the water level at monitoring point A is 120.5 meters, at monitoring point B is 120.3 meters, and at monitoring point C is 120.8 meters, the water-level gradient in the A-B direction is calculated to be (120.5-120.3) / 50=0.004, and the gradient in the A-C direction is calculated to be (120.8-120.5) / 50=0.006. Combining the pressure difference between the two points measured by the pressure gradient sensor (e.g., a pressure difference of 0.05 kPa at points A and B) with the flow velocity data from the electromagnetic flowmeter (0.8 m / s), the unit uses a vector synthesis algorithm to determine the primary groundwater flow direction. The flow direction is consistent with the vector sum of the water-level and pressure gradients. This is ultimately output as an azimuth (e.g., 30° east of north), and the streamline distribution is dynamically displayed within the 3D geological model.

[0104] The groundwater flow analysis unit first uses a laser rangefinder to measure the cross-sectional parameters of the groundwater flow area (for example, the width of the tunnel drainage channel is 4 meters, the height is 3 meters, and the wet perimeter is 10 meters), and the cross-sectional area is calculated to be 12 square meters. For the flow velocity data collected by the electromagnetic flowmeter (resolution 0.01m / s), the system automatically performs sediment content correction (the preset correction coefficient K=1.15, applicable to scenarios with sediment content ≤5%). The corrected velocity value is multiplied by the cross-sectional area to obtain the real-time flow rate (unit: m³ / s). When the water flow model is judged to be uniform flow in an open channel, the Manning formula is used to verify the flow calculation result: the Manning coefficient n is 0.013 (applicable to concrete-lined channels), the hydraulic radius R=cross-sectional area / wet perimeter=1.2 meters, and the flow rate is calculated as follows (i is the hydraulic gradient). If the deviation from the sensor's measured value exceeds 5%, the data calibration process is triggered to ensure the accuracy of the flow calculation. The wetted perimeter refers to the circumference of the fluid-solid boundary at the flow section.

[0105] The permeability coefficient analysis unit combines the porosity of the rock and soil medium measured by the porosity sensor (accuracy ±2%), the flow velocity data from the electromagnetic flowmeter, and the hydraulic gradient value output by the flow direction analysis unit to invert the permeability coefficient K based on Darcy's law. The specific steps are as follows: first, obtain the porosity distribution of the target area from the borehole detection module (for example, the porosity of a monitoring point is 20%), determine the hydraulic gradient i at that point based on the flow direction (for example, 0.005), and substitute the measured average flow velocity v (0.5m / s) into the Darcy formula v=K i / ( μ / ρg)(where μ The K value is determined using an iterative algorithm, where ρ is the dynamic viscosity coefficient, ρ is the water density, and g is the acceleration of gravity (all values ​​are taken as standard values ​​at room temperature). If the K value measured multiple times at the same monitoring point fluctuates by more than 10%, the system automatically initiates multi-point data fitting, using the least squares method to perform regression analysis on the v and i data of three or more adjacent monitoring points. The system ultimately outputs the permeability coefficient of the area (in m / d), providing parameters for assessing rock permeability and water inrush risk.

[0106] In some embodiments, step S20 specifically includes:

[0107] generating a fused data set of the target mine area based on the real-time seismic data and the geological survey data of the target mine area, wherein the fused data set represents a matching relationship between the real-time seismic data and the geological survey data;

[0108] Performing feature extraction processing on the fused data set to obtain a key feature data set;

[0109] The key feature data set is input into a preset water prevention and control risk early warning model to obtain a risk level.

[0110] In some embodiments, the preset water control risk warning model is constructed by training with historical data. The specific training process is as follows:

[0111] First, a training dataset was constructed. Multi-source data was extracted from the mine's historical database, covering seismic data from the target mine area and a 3-kilometer radius over a five-year period. This data included 200,000 waveforms and characteristic parameters, including vibration frequency, energy value, and focal depth. The borehole detection module integrated data from 300 exploration boreholes to obtain 80,000 logging curves and imaging data, including rock fracture density, width, porosity, and lithology. The hydrogeological analysis module also collected 150,000 monitoring records of groundwater pressure, water level gradient, permeability coefficient, and water flow during different rainfall and mining phases. Combining 50 historical flood accident reports, manual inspection records, and expert assessments, each data sample was labeled with a risk level of one to three, with 30% of samples being positive and 70% being negative, ultimately forming a dataset of tens of thousands of labeled records.

[0112] During data preprocessing and feature engineering, continuous features such as seismic energy (mean 0.4 J, standard deviation 0.15 J) and groundwater pressure (mean 1.2 MPa, standard deviation 0.3 MPa) were first normalized using the Z-score method, ensuring that the data distribution conforms to a standard normal distribution with a mean of 0 and a standard deviation of 1. For discrete features such as lithology, a one-hot encoding technique was used to generate 10-dimensional feature vectors. For example, lithology classes such as mudstone, sandstone, and limestone were converted into mutually exclusive binary vector representations. Coupled features were further constructed based on multi-source data, including correlation features between fracture density and vibration frequency, and combined features between water level gradient and permeability coefficient. By calculating the correlation coefficient between each feature and risk level, 28 key features with a correlation greater than 0.6 were selected, covering seismic parameters, rock structure parameters, hydrogeological parameters, and their cross-derivative parameters. This ultimately formed the input feature matrix for model training.

[0113] The model architecture was then designed and trained. A three-layer fully connected neural network was used. The input layer contained 28 neurons corresponding to key features. The hidden layer had 128 neurons, using the ReLU (Rectified Linear Unit) activation function. A dropout layer with a dropout rate of 0.3 was added to prevent overfitting, and batch normalization was introduced to improve stability. The output layer had three neurons corresponding to the three risk levels, using a softmax activation function to output probability values. Training used the Adam (Adaptive Moment Estimation) optimizer with a learning rate of 0.001 and a cross-entropy loss function. The batch size was set to 128, and training was repeated for 100 epochs. Accuracy, precision, and recall were calculated on a 20% validation set for each epoch. Training was terminated when the validation set accuracy improved by less than 0.1% over five consecutive epochs.

[0114] Finally, the model is deployed and updated. The trained model is encapsulated as a dynamic link library and integrated into the mine's central processing system. In some other embodiments, the preset water risk warning model uses a physical constraint neural network (Physics-Informed Neural Networks, PINN). Specifically, the seepage mechanics equations (such as Darcy's law) and rock mechanics theory (such as the fracture propagation model) are embedded in the neural network loss function to force the model output to conform to the laws of hydrogeology and physics. For example, when calculating the risk level, the mathematical relationship between seepage pressure and fracture development is constrained to improve the model's compatibility with domain knowledge and predictive reliability.

[0115] Figure 2 This is a schematic diagram of the structure of a mine water risk warning system based on the integration of earthquake and geology in an embodiment of the present application. Figure 2 As shown, the embodiment of the present application provides a mine water prevention and control risk early warning system based on the integration of earthquake and geology, which may include:

[0116] A data acquisition and reception module, configured to receive real-time seismic data transmitted from the seismic monitoring module and geological exploration data transmitted from the geological exploration module; wherein the geological exploration module includes a borehole detection module and a hydrogeological analysis module; the borehole detection module is configured to detect geological structure data of the target mine area, and the hydrogeological analysis module is configured to detect hydrogeological condition data of the target mine area;

[0117] a risk assessment module, which is in communication with the data acquisition and receiving module and has a built-in preset water prevention and control risk warning model, and is used to obtain a risk level based on the real-time seismic data, geological survey data and the preset water prevention and control risk warning model, and to determine corresponding mine water prevention and control implementation measures according to the risk level;

[0118] An execution control module, in communication with the risk assessment module, configured to trigger a target execution device to perform corresponding prevention and control treatment on the target mine area according to the mine water prevention and control implementation measures;

[0119] The target execution device includes a drilling device, and the drilling device is configured as follows:

[0120] When the risk level is the first risk level associated with seepage pressure, a monitoring hole is drilled in the target mine area, and an optical fiber piezometer is installed in the monitoring hole to collect seepage pressure data;

[0121] When the risk level is the second risk level associated with rock formation fissures, drilling grouting holes in the rock formation fissures and performing grouting to seal and fill the holes;

[0122] When the risk level is the third risk level associated with the aquifer or water inrush risk, a water diversion hole is constructed in the aquifer, and the groundwater is guided to a safe area by a drainage pump group connected to the water diversion hole.

[0123] Through the embodiments of the present application, the real-time seismic data and geological exploration data of the target mine area are combined to realize multi-dimensional fusion data analysis, make early predictions of water prevention and control in the target mine area, obtain the risk level in advance, and provide early warning information according to the risk level (including mine water prevention and control execution measures corresponding to the risk level). Then, the target execution equipment of mine water prevention and control in the target mine area is adjusted according to the early warning information, thereby realizing water prevention and control management of the target mine area, improving the safety of mines in the target mine area, and reducing the occurrence of mine accidents.

[0124] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the method embodiment below, and will not be repeated here.

[0125] The present application also provides a computer-readable storage medium 300. Figure 3 As shown, the computer-readable storage medium 300 stores program code 301 for executing each step in the method embodiment of the present invention. When the program code 301 is executed by the processor, each step of the above-mentioned mine water risk warning method based on the fusion of earthquake and geology is implemented.

[0126] The computer program includes computer program code, which may be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium may include any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium.

[0127] The embodiment of the present application further provides an electronic device 400, such as Figure 4 As shown, it includes one or more processors 401 , a communication interface 402 , a memory 403 and a communication bus 404 , wherein the processor 401 , the communication interface 402 , and the memory 403 communicate with each other via the communication bus 404 .

[0128] Storage 403, for storing computer programs;

[0129] The processor 401 is configured to implement the steps of the above-mentioned mine water prevention and control risk early warning method based on the integration of earthquake and geology when executing the program stored in the memory 403.

[0130] The processor 401 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0131] Memory 403 may include a large-capacity memory for data or instructions. By way of example, and not limitation, memory 403 may include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disk, a magneto-optical disk, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 403 may include removable or non-removable (or fixed) media. In certain embodiments, memory 403 is non-volatile solid-state memory. In certain embodiments, memory 403 includes read-only memory (ROM). Where appropriate, the ROM may be mask-programmable ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0132] The communication bus 404 includes hardware, software, or both for coupling the above components to each other. For example, the bus may include an accelerated graphics port (AGP) or other graphics bus, an enhanced industry standard architecture (EISA) bus, a front-side bus (FSB), a HyperTransport (HT) interconnect, an industry standard architecture (ISA) bus, an InfiniBand interconnect, a low pin count (LPC) bus, a memory bus, a microchannel architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standard association local (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, the bus may include one or more buses. Although the embodiments of the present application describe and illustrate specific buses, the present application contemplates any suitable bus or interconnect.

[0133] Specific embodiments are used in this application to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A mine water prevention and control risk early warning method based on the integration of earthquake and geology, characterized by: The method comprises: Receive real-time seismic data transmitted from the seismic monitoring module and geological exploration data transmitted from the geological exploration module, wherein the geological exploration module includes a borehole detection module and a hydrogeological analysis module, which are used to detect data on the geological structure and hydrogeological conditions of the target mine area respectively; Based on real-time seismic data, geological survey data and a preset water prevention and control risk warning model for the target mine area, a risk level is obtained, and corresponding mine water prevention and control implementation measures are determined according to the risk level; According to the mine water prevention and control implementation measures, the target execution device is triggered to perform corresponding prevention and control treatment on the target mine area; the target execution device includes a drilling device, and the prevention and control treatment includes: At a first risk level associated with seepage pressure, the drilling equipment drills monitoring holes in the target mine area, and sets a fiber optic piezometer in the monitoring hole to collect seepage pressure data; At the second risk level associated with rock formation fissures, the drilling equipment performs grouting and plugging treatment on grouting holes drilled in the rock formation fissures; At the third risk level associated with aquifers or water inrush risks, the drilling equipment constructs a water diversion hole in the aquifer and guides the groundwater to a safe area through a drainage pump group connected to the water diversion hole.

2. The method according to claim 1, characterized in that The borehole detection module includes at least one of a well logging instrument, an acoustic wave detector, and a tracer detection device.

3. The method according to claim 2, characterized in that The logging instrument includes at least one of a resistivity logging instrument, a natural gamma logging instrument, and a time-of-flight acoustic logging instrument; The resistivity logging instrument is used to obtain resistivity data of rock formations in the target mine area to identify the distribution of aquifers; The natural gamma ray logging tool is used to obtain radioactivity intensity data of rock formations to identify lithology; The acoustic time difference logging tool is used to obtain acoustic wave propagation time data of rock formations to determine the porosity of the rock formations.

4. The method according to claim 2, characterized in that The acoustic wave detector includes an ultrasonic wave detector or an infrasonic wave detector; The acoustic wave detector is used to transmit acoustic wave signals to the rock formation in the target mine area and receive reflected echo signals. By analyzing the time delay, energy attenuation and frequency change of the reflected echo signals, the location, width and connectivity of the rock formation cracks are determined.

5. The method according to claim 2, characterized in that The tracer detection device includes a tracer injection device and a tracer monitoring device; The tracer injection device is used to inject a fluorescent tracer, a radioactive tracer or a chemical tracer into the aquifer or fracture zone of the target mine area; The tracer monitoring device is used to determine the groundwater infiltration path or the water conductivity of the fracture by detecting the tracer concentration and migration trajectory in the groundwater or rock pores.

6. The method according to claim 1, characterized in that When drilling a monitoring hole at the first risk level, the depth of the monitoring hole is determined based on the aquifer depth and aquiclude thickness parameters in the geological exploration data, and the diameter of the monitoring hole matches the outer diameter of the fiber optic piezometer; The optical fiber piezometer is lowered to the bottom of the monitoring hole through the built-in channel of the drill pipe and is fixed to a predetermined position of the monitoring hole by using an expansion packer.

7. The method according to claim 1, characterized in that When drilling grouting holes at the second risk level, the drilling equipment performs the following synchronous drilling and grouting process: The drilling equipment is equipped with a dual-channel drill pipe, where the first channel is used to drive the drill bit to rotate, and the second channel is connected to the grouting pump; When the drill bit reaches a preset fracture depth, slurry is injected into the fracture through the second channel, while the drill bit promotes the diffusion of the slurry in a vibration mode; The grouting pressure is dynamically adjusted according to the rock formation vibration frequency in the real-time seismic data.

8. The method according to claim 1, characterized in that When drilling a water guide hole under the third risk level, the drilling equipment adopts a directional drilling system, and the directional drilling system includes: The measurement while drilling module is used to obtain the deviation data between the drilling trajectory and the spatial position of the aquifer in real time; a steering controller, configured to adjust the drill bit azimuth according to the deviation data so that the water guide hole penetrates the aquifer; The anti-collapse wall protection device is used for installing a water pipe with a screen after drilling a hole, and the water pipe is fixed along the hole wall of the water hole.

9. The method according to claim 2, characterized in that The hydrogeological analysis module includes: Sensor network, used to collect raw data, including: Groundwater level sensor, using capacitive water level sensor or piezoresistive water level sensor, is used to collect groundwater level values ​​in real time; Flow direction sensor, using pressure sensor or magnetometer, is used to collect the pressure difference and groundwater flow direction in real time; Flow sensor, using electromagnetic flowmeter or ultrasonic flowmeter, is used to collect the flow velocity of groundwater in real time; Permeability sensor, using porosity sensor, is used to measure the porosity of geotechnical media; The data analysis module is connected to the sensor network and is used to analyze the original data collected by the sensor network to obtain groundwater flow parameters, which include groundwater level, groundwater flow direction, groundwater flow rate and permeability coefficient.

10. A mine water prevention and control risk early warning system based on the integration of earthquake and geology, characterized by: The system comprises: A data acquisition and reception module, configured to receive real-time seismic data transmitted from the seismic monitoring module and geological exploration data transmitted from the geological exploration module; wherein the geological exploration module includes a borehole detection module and a hydrogeological analysis module; the borehole detection module is configured to detect geological structure data of the target mine area, and the hydrogeological analysis module is configured to detect hydrogeological condition data of the target mine area; a risk assessment module, communicatively connected to the data acquisition and receiving module, having a built-in preset water prevention and control risk warning model, for obtaining a risk level based on the real-time seismic data, geological survey data, and the preset water prevention and control risk warning model, and determining corresponding mine water prevention and control implementation measures according to the risk level; An execution control module, in communication with the risk assessment module, configured to trigger a target execution device to perform corresponding prevention and control treatment on the target mine area according to the mine water prevention and control implementation measures; The target execution device includes a drilling device, and the drilling device is configured as follows: When the risk level is the first risk level associated with seepage pressure, a monitoring hole is drilled in the target mine area, and an optical fiber piezometer is installed in the monitoring hole to collect seepage pressure data; When the risk level is the second risk level associated with rock formation fissures, drilling grouting holes in the rock formation fissures and performing grouting to seal and fill the holes; When the risk level is the third risk level associated with the aquifer or water inrush risk, a water diversion hole is constructed in the aquifer, and the groundwater is guided to a safe area by a drainage pump group connected to the water diversion hole.

Images