Multi-source three-dimensional cooperative prevention and control method for composite disasters of coal mine with extremely thick aquifer

Abstract

The invention belongs to the technical field of three-dimensional cooperative prevention and control of disasters, and relates to a multi-source three-dimensional cooperative prevention and control method for composite disasters of a coal mine with a super-thick water-bearing stratum, which mainly comprises prevention and control of rock burst and water inrush accidents in a super-thick water-bearing stratum environment, and specifically comprises the following steps: acquiring multi-dimensional data of all positions of the earth surface and the rock stratum; based on the multi-dimensional data, carrying out three-dimensional yielding layout and sub-source pressure control, calculating an impact risk coefficient and a water inrush risk coefficient, establishing a risk level matrix by using the impact risk coefficient and the water inrush risk coefficient, and obtaining a current water inrush and rock burst risk level; wherein the sub-source pressure control comprises the steps of blasting pressure relief, pressurizing grouting and pressure relief groove supplement. Through the four-in-one three-dimensional cooperative prevention and control engineering design method of main control judgment, layout yielding, sub-source pressure control and monitoring and prevention mutual feedback, cooperative prevention and control of rock burst and water inrush disasters are achieved.

Description

Technical Field

[0001] This invention relates to the field of three-dimensional collaborative disaster prevention and control technology, and in particular to a multi-source three-dimensional collaborative prevention and control method for complex disasters in coal mines with thick aquifers. Background Technology

[0002] Mining of extremely thick aquifers (thickness > 50m, water content > 15%) faces the critical technical challenge of the coupled triggering of rockbursts and water inrush disasters. The coupling mechanism is complex: mining-induced stress field disturbances induce rock mass fracturing → water-conducting fractures penetrate the aquifer → water erosion weakens the rock mass strength → further inducing rockbursts (forming a positive feedback loop of "stress-seepage-damage"). This renders traditional single-hazard prevention and control models ineffective, for example:

[0003] Current prevention and control technologies suffer from several problems, including considering only hydrostatic pressure while neglecting the effects of dynamic stress waves, spatial conflicts between pressure relief and water plugging projects, and a disconnect between monitoring data and prevention and control actions. Furthermore, existing rockburst prevention and control technologies (such as pressure relief blasting) can exacerbate fracture development and increase the risk of water inrush, while water inrush prevention (such as grouting) leads to stress concentration, preventing the effective release of energy within the rock and ultimately inducing rockburst accidents.

[0004] Therefore, to overcome the bottleneck in the prevention and control of complex dynamic disasters in thick water-bearing rock strata, it is urgent to innovate a technical system of "precise main control identification, coordinated prevention and control layout, and real-time monitoring and response" to provide a better solution for the coupled problem of rockburst and water inrush disasters faced in mining under thick water-bearing rock strata. Summary of the Invention

[0005] To address the problems existing in the prior art, the purpose of this invention is to provide a multi-source, three-dimensional, collaborative prevention and control method for complex disasters in coal mines with thick aquifers. This method establishes a multi-field coupling criterion for rockburst and water inrush disasters, involving stress, seepage, and fractures, overcoming the technical bottleneck of traditional single-disaster prevention and control models that fail to identify the main controlling factors of complex dynamic disasters. Through a technical approach of "spatial pressure-yielding layout optimization + source-based pressure control and precise intervention," it achieves three-dimensional collaborative disaster prevention and control, reaching a dynamic equilibrium control of the stress field. Furthermore, it develops a real-time feedback system for "disaster evolution - prevention and control response," constructing a monitoring-prevention mutual feedback intelligent closed loop, forming a replicable engineering paradigm, and breaking down the coupling mechanism of complex disasters.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A multi-source, three-dimensional, and collaborative prevention and control method for complex disasters in coal mines with thick aquifers includes:

[0008] Multidimensional data is acquired at various locations on the surface and in the rock strata. Based on the multidimensional data, a three-dimensional pressure-relief layout and source-based pressure control are performed. A risk level matrix is ​​established to obtain the current risk level of water inrush and rock burst. When the current risk level of water inrush and rock burst is greater than the risk threshold, the rock strata are repaired to reduce the risk of water inrush and rock burst to a safe range.

[0009] The source-controlled pressure includes: blasting pressure relief, pressurized grouting, and additional pressure relief tanks.

[0010] Optionally, the multidimensional data includes: microseismic monitoring data and multi-source data;

[0011] The microseismic monitoring data includes: rock mass fracturing events and microseismic energy changes;

[0012] The multi-source data includes: dynamic distribution of mining stress field, changes in aquifer water pressure, fracture connectivity rate, fracture roughness coefficient, and tensile strength of rock mass.

[0013] Optionally, the three-dimensional pressure relief layout based on the multi-dimensional data includes:

[0014] The multidimensional data is comprehensively analyzed. Based on the analysis results, the width of the isolation coal pillar is increased, and the panel size and the width of the isolation coal pillar are adjusted to control the subsidence of the goaf roof and the fracture of the overlying strata.

[0015] Optionally, source-specific pressure control based on the multidimensional data includes:

[0016] Based on the multidimensional data, blasting is carried out to relieve pressure. When the micro-vibration energy in the multidimensional data reaches the first target value, the stress source is blasted to relieve pressure, that is, the roof of the goaf is blasted to relieve pressure, and the water seepage and water inrush channel is controlled.

[0017] Based on the multidimensional data, pressurized grouting is performed. When the aquifer water pressure in the multidimensional data reaches the second target value, high-pressure grouting is performed on the soft rock layer below the aquifer to seal the water-conducting fracture channels.

[0018] Based on the multidimensional data, a pressure relief groove is added. When the stress difference in the multidimensional data reaches the third target value, high water pressure is applied to the roof of the goaf to induce fracturing and form a pressure relief groove.

[0019] Optionally, during high-pressure grouting of the soft rock strata below the aquifer, the grouting pressure is dynamically adjusted:

[0020] P g =1.3P w +ΔP;

[0021] Among them, P gFor grouting pressure, P w ΔP represents the permeation water pressure in the rock fractures, and ΔP is the correction amount for grouting and fracturing.

[0022] Optionally, establishing the risk level matrix includes: calculating the impact risk coefficient and the water inrush risk coefficient based on the multidimensional data, and using the impact risk coefficient and the water inrush risk coefficient to establish the risk level matrix.

[0023] Optionally, calculating the impact risk coefficient includes:

[0024]

[0025] Where, σ max For the peak value of mining-induced stress, σ c ε is the uniaxial compressive strength of the rock mass, β is the plastic strain sensitivity coefficient of the rock mass, and ε p The cumulative plastic strain of the rock mass.

[0026] Optionally, calculating the water inrush risk coefficient includes:

[0027]

[0028] Among them, P w C is the aquifer water pressure. d σ represents the fracture connectivity, JRC represents the fracture roughness coefficient, and σ represents the fracture roughness coefficient. t This represents the tensile strength of the rock mass.

[0029] Optionally, obtaining the current risk level of water inrush and rock burst includes:

[0030] A risk level matrix is ​​established using the ratio between the impact risk coefficient and the water inrush risk coefficient. The risk levels of water inrush and rockburst are dynamically analyzed based on the risk level matrix to obtain the current risk levels of water inrush and rockburst.

[0031] Optionally, the method further includes:

[0032] Obtain the stress concentration factor, verify the stress field uniformity based on the stress concentration factor, assess the disaster prevention and control indicators, and optimize the pressure relief groove spacing and grouting pressure;

[0033] The disaster prevention and control indicators include: frequency of high-energy micro-earthquakes, accuracy of water inrush warning, and delay in prevention and control response.

[0034] The beneficial effects of this invention are as follows:

[0035] This invention utilizes a four-in-one, three-dimensional, collaborative prevention and control engineering design method—"master control identification, layout pressure yielding, source-based pressure control, and monitoring and prevention feedback"—to achieve coordinated prevention and control of rockburst and water inrush disasters. Specific beneficial effects are reflected in:

[0036] Stress adjustment and energy release: Through the stress adjustment and energy release mechanism of low-level rock strata blasting and expansion, the expansion and development of rock strata fractures are effectively controlled, the disaster risk caused by stress concentration in the rock strata is reduced, the stress field distribution during the mining process is optimized, and sudden rock strata rupture is avoided.

[0037] High-level grouting modification and seepage prevention technology: The application of high-level grouting technology effectively improves the permeability of rock strata, enhances the seepage prevention effect, reduces the risk of water flowing into the mine, and improves mine safety. Grouting modification effectively prevents water inrush, reduces the intrusion rate of groundwater, and ensures the safety of the working environment.

[0038] Three-dimensional coordinated prevention and control: By combining low-level roof blasting with high-level grouting to block seepage, a three-dimensional system for preventing and controlling impact and water inrush disasters has been formed. This system effectively controls the high-stress areas caused by rock strata fracturing and also forms effective isolation in potential water source areas. The synergistic effect significantly improves the disaster prevention and control effect.

[0039] Multi-level identification and layout strategy: Through a design approach that integrates primary control identification, layout pressure reduction, source-based pressure control, and monitoring-prevention feedback, precise prevention and control measures can be implemented at different stages and in different regions. This phased and source-based control method helps to cope with complex and ever-changing geological environments, ensuring the flexibility and effectiveness of the prevention and control plan.

[0040] Reduce the frequency of vibration and disasters: Through the application of technology, the frequency of high-energy vibrations is reduced, significantly reducing the probability of disasters caused by vibration, avoiding sudden disasters that may occur during mining, and ensuring the stability and safety of mine operations. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a schematic diagram of a multi-source, three-dimensional, collaborative prevention and control method for complex disasters in coal mines with thick aquifers, according to an embodiment of the present invention.

[0043] Figure 2 This is a flowchart illustrating a multi-source, three-dimensional, collaborative prevention and control method for complex disasters in coal mines with thick aquifers, according to an embodiment of the present invention.

[0044] Among them, 1. a very thick aquifer; 2. an ultrasonic water level gauge; 3. a water pressure sensor; 4. a soft rock layer; 5. a three-dimensional laser scanner; 6. fissures in the overlying rock layer; 7. a digital twin platform intelligent processing system; 8. a goaf; 9. a water-conducting fissure channel; 10. a grouting pipeline; 11. a microseismic monitor; 12. a blasting and pressure relief device for the roof of the goaf; and 13. a fiber optic grating stress meter. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0047] like Figure 1 As shown in the figure, this embodiment discloses a multi-source, three-dimensional, collaborative prevention and control method for complex disasters in coal mines with thick aquifers, including:

[0048] After the working face is mined, a large area of ​​goaf is formed with the rock strata above it suspended. Under the action of ground stress, the overlying rock strata in the suspended area continue to sink, causing energy to accumulate inside the goaf roof and forming a stress concentration phenomenon, which may break rapidly at any time and generate rock burst hazards. In addition, during the sinking process of each rock stratum, it is affected by deformation and damage, and local fractures form water-conducting fissure channels 9.

[0049] Microseismic monitors 11 are deployed at various locations on the surface and in the rock strata to form a microseismic monitoring array, collecting real-time data on rock fracturing events and microseismic energy changes. Fiber optic stress gauges 13 are deployed near the goaf to monitor the dynamic distribution of the mining-induced stress field. Ultrasonic water level gauges 2 are installed at the top of the thick aquifer 1 to track and record changes in aquifer water pressure. Through the collected data, real-time acquisition of multi-source data and calculation of dual-threshold criteria for composite disasters are achieved, enabling dynamic analysis of the risk levels of water inrush and rockburst. Aquifer water pressure P w Monitoring was implemented by embedding a water pressure sensor 3 in a borehole; fracture connectivity C d The fracture roughness coefficient JRC was obtained by inversion using a 3D laser scanner; the tensile strength σ of the rock mass was measured by a fracture surface profiler; and the tensile strength σ of the rock mass was measured by inversion using a 3D laser scanner. t Calibration was achieved through laboratory Brazilian splitting tests and acoustic emission system calibration.

[0050] The method for calculating the impact risk coefficient of the dual-threshold criterion for composite disasters is as follows:

[0051]

[0052] In the formula, σ max The peak value of the mining-induced stress (maximum monitored value) is σ, MPa; c ε is the uniaxial compressive strength of the rock mass, MPa; β is the plastic strain sensitivity coefficient of the rock mass; ε p The cumulative plastic strain of the rock mass.

[0053] Among them, the maximum value of mining stress σ max The uniaxial compressive strength σ of the rock mass is monitored in real time using a fiber optic stress gauge 13. c The rock mass plastic strain sensitivity coefficient β was calibrated through laboratory core tests and in-situ fracturing; it was fitted by triaxial rheological tests; and the cumulative plastic strain ε of the rock mass was determined. p Using the microseismic energy-strain transformation model Measured; k is the impact tendency coefficient, E i It is the ratio of the impact kinetic energy of the coal sample to the total input energy (determined by a drop hammer test).

[0054] The calculation method for the water inrush risk coefficient of the dual threshold criterion for composite disasters is as follows:

[0055]

[0056] When K W An early warning is triggered when P > 0.8; where P is the value of P. w The aquifer pressure is measured in MPa; C d σ is the fracture connectivity; JRC is the fracture roughness coefficient; t denoted as the tensile strength of the rock mass, in MPa.

[0057] The impact risk coefficient and water inrush risk coefficient are calculated and updated in real time. The ratio of the two is used to establish a risk level matrix and to conduct dynamic analysis of the risk levels of water inrush and rockburst.

[0058] Table 1

[0059] <![CDATA[K I / K W ]]> ＜0.5 0.5～0.8 ＞0.8 ＜1.0 Green (Safe) Blue (Attention) Yellow (Sudden Flood Warning) 1.0～1.5 Blue (Attention) Yellow (Double Low Risk) Orange (Complex Medium Risk) ＞1.5 Yellow (Impact Warning) Orange (Complex Medium Risk) Red (Combined High Risk)

[0060] Based on the risk level matrix values ​​in Table 1, the risk of the overlying rock strata is classified. Then, the system automatically identifies the risk level and performs repair operations on rock strata with a yellow or higher risk level, thereby reducing the risk of water inrush and rock bursts to a safe range.

[0061] Based on the comprehensive analysis of microseismic monitoring data and aquifer water pressure and other multi-source data, the impact risk coefficient and water inrush risk coefficient are calculated and updated in real time. The risk level matrix is ​​established using the ratio of the two, and the risk coefficient classification values ​​in the table are obtained by dynamically analyzing the risk levels of water inrush and rock pressure.

[0062] By using methods such as filling to increase the width of the isolation coal pillar, and controlling the dual parameter thresholds of the panel size and the width of the isolation coal pillar, the stress of the roof of the goaf 8 is transferred to the isolation coal pillar and its surrounding rock mass, thereby controlling the roof subsidence and the fracture of the overlying strata and inhibiting the generation of water-conducting fracture channels.

[0063] By employing directional blasting pressure relief technology, stress sources are regulated. Specifically, the roof of the goaf is blasted to relieve pressure (12), and the water seepage and inrush channels are regulated through an intelligent grouting pressure regulation system. Directional hydraulic fracturing technology is used to induce high-pressure fracturing in the roof of the goaf (8), forming a pressure relief groove to alleviate stress concentration and control roof subsidence. High-pressure grouting is then performed on the soft rock layer (4) below the aquifer (10) using grouting pipelines (10) to seal water-conducting fracture channels (9), preventing water from spreading through fluid channels under high pressure and causing a water inrush accident. This dual prevention and control model, combining low-level roof blasting with high-level grouting for seepage prevention, forms a three-dimensional system for preventing and controlling impact and water inrush disasters. It effectively controls high-stress areas generated by rock fractures and also effectively isolates potential water source areas, significantly improving disaster prevention and control effectiveness through synergistic effects.

[0064] The intelligent grouting pressure regulating system dynamically adjusts the grouting pressure via an electric pressure regulating valve (response time <1 min).

[0065] P g =1.3P w +ΔP;

[0066] In the formula, P w ΔP represents the permeation water pressure in fracture 6 of the overlying rock strata; ΔP is the grouting and fracturing correction amount, MPa (corrected in real time according to the fracture opening).

[0067] Furthermore, the control actions for parameters such as microseismic energy, water pressure rise, and stress difference are respectively directional blasting for pressure relief, and pressurized grouting (P... g The conditions for triggering the control action are: 20% increase), addition of a pressure relief tank, and micro-vibration energy > 10. 4 J. Water pressure rise > 0.2 MPa and stress difference > 10 MPa.

[0068] Furthermore, the prevention and control effectiveness evaluation model is as follows:

[0069]

[0070] Where η represents the evaluation result of the prevention and control effectiveness.

[0071] By employing a closed-loop mechanism of quantitative assessment, error attribution, and targeted optimization, the shortcomings of traditional prevention and control systems in dynamically adapting to change are addressed. The model's reliability has been verified through laboratory experiments and field industrial trials. Its threshold setting and optimization methods are supported by robust industry standards and experimental validation. Laboratory Experiment: In a 1:100 physical model with 20 preset disaster events, after model optimization, η changed from 0.28 to 0.9. Field Industrial Trial: "The assessment model triggers parameter optimization when the error >30% (η<0.7), increasing the accuracy of the prevention and control system from 58% to 82% and reducing the major accident rate by 85%, meeting the requirements of AQ 1058-2018 standard."

[0072] The system monitors microseismic energy, water pressure rise, and stress changes in real time using microseismic monitors 11, water pressure sensors 3, and fiber optic stress gauges 13. If any parameter exceeds the monitoring range, the system automatically triggers the adjustment action for the corresponding parameter and updates the prevention and control effect evaluation model in real time.

[0073] The prevention and control information is transmitted to the intelligent processing system 7 of the digital twin platform via signal transmission devices such as optical fibers. The system uses a stress cloud map scanner to detect the stress concentration coefficient based on the received signal and verifies the stress field uniformity. If the verification does not meet the safety requirements, the spacing of the pressure groove and the grouting pressure are further optimized.

[0074] In addition, disaster prevention and control indicators such as the frequency of high-energy microseismic events, the accuracy of water inrush early warning, and the delay in prevention and control response were assessed through methods such as monthly statistics of the microseismic system, hydrological monitoring and on-site verification, and comparison of action command timestamps. Then, disaster scenarios were simulated based on a digital twin platform to optimize parameters such as the spacing of the grouting trench and the grouting pressure.

[0075] Prevention and control information refers to the use of technical means to control the stress state of the roof in the post-mining goaf, the stress distribution of the overlying strata, permeability, and the frequency of micro-seismic events. The stress concentration factor includes the stress concentration factors of the roof and the overlying strata.

[0076] like Figure 2 As shown, the multi-source three-dimensional collaborative water control and anti-scour layout process of the present invention includes the following specific steps: main control identification and quantitative analysis, three-dimensional pressure relief layout design, precise execution of sub-source pressure control, monitoring and prevention feedback closed-loop control, and effect verification and optimization.

[0077] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A multi-source three-dimensional collaborative prevention and control method for thick aquifer coal mine composite disasters, characterized in that, The method comprises the following steps: acquiring multi-dimensional data at each position of the ground surface and rock stratum, performing three-dimensional pressure relief layout and source-controlled pressure relief based on the multi-dimensional data, establishing a risk level matrix, obtaining a current water inrush and rock burst risk level, and performing a rock stratum repair operation when the current water inrush and rock burst risk level is greater than a risk threshold, so that the water inrush and rock burst risk of the rock stratum is reduced to within a safe range; wherein the source-controlled pressure relief comprises blasting pressure relief, pressure-increasing grouting, and additional pressure relief grooves.

2. The multi-source three-dimensional collaborative prevention and control method for the thick aquifer coal mine composite disaster according to claim 1, characterized in that, The multi-dimensional data comprises microseismic monitoring data and multi-source data. The microseismic monitoring data comprises rock mass fracture events and microseismic energy variation. The multi-source data comprises dynamic distribution of mining-induced stress field, variation of aquifer water pressure, fracture connectivity rate, fracture connectivity rate, fracture roughness coefficient, and rock mass tensile strength.

3. The multi-source three-dimensional collaborative prevention and control method for the thick aquifer coal mine composite disaster according to claim 1, characterized in that, Performing three-dimensional pressure relief layout based on the multi-dimensional data comprises: comprehensively analyzing the multi-dimensional data, increasing the width of the isolated coal pillar, and adjusting the panel size and the width of the isolated coal pillar to control the roof subsidence of the goaf and the breakage of the overlying rock stratum.

4. The multi-source three-dimensional collaborative prevention and control method for the thick aquifer coal mine composite disaster according to claim 1, characterized in that, Performing source-controlled pressure relief based on the multi-dimensional data comprises: performing blasting pressure relief on the stress source, i.e., blasting pressure relief on the goaf roof, to regulate and control the water inrush channel of the water source seepage when the microseismic energy in the multi-dimensional data reaches a first target value; performing high-pressure grouting on the soft rock stratum below the aquifer to block the water-conducting fracture channel when the aquifer water pressure in the multi-dimensional data reaches a second target value; performing high-water pressure fracturing on the goaf roof to form a pressure relief groove when the stress difference in the multi-dimensional data reaches a third target value.

5. The multi-source three-dimensional collaborative prevention and control method for the thick aquifer coal mine composite disaster according to claim 4, characterized in that, During the high-pressure grouting on the soft rock stratum below the aquifer, the grouting pressure is dynamically adjusted. P g = 1.3P w + ΔP; Where P g is the grouting pressure, P w is the water pressure in the rock fissure, and ΔP is the grouting pressure correction amount.

6. The multi-source three-dimensional collaborative prevention and control method for the thick aquifer coal mine composite disaster according to claim 1, characterized in that, Establishing the risk level matrix comprises calculating an impact risk coefficient and a water inrush risk coefficient based on the multi-dimensional data, and establishing the risk level matrix using the impact risk coefficient and the water inrush risk coefficient.

7. The multi-source three-dimensional collaborative prevention and control method for the thick aquifer coal mine composite disaster according to claim 6, characterized in that, Calculating the impact risk coefficient comprises: where σ max is the peak stress, σ c is the uniaxial compressive strength of the rock mass, β is the plastic strain sensitivity coefficient of the rock mass, and ε p is the cumulative plastic strain of the rock mass.

8. The multi-source three-dimensional collaborative prevention and control method for the thick aquifer coal mine composite disaster according to claim 6, characterized in that, Calculating the water inrush risk coefficient comprises: where P w is the water pressure of the aquifer, C d is the fracture connectivity, JRC is the fracture roughness coefficient, and σ t is the tensile strength of the rock mass.

9. The multi-source three-dimensional collaborative prevention and control method for the thick aquifer coal mine composite disaster according to claim 6, characterized in that, acquiring the current water inrush and rock burst risk level comprises: establishing a risk level matrix using the ratio between the impact risk coefficient and the water inrush risk coefficient, dynamically analyzing the water inrush and rock burst risk level based on the risk level matrix, and obtaining the current water inrush and rock burst risk level.

10. The multi-source three-dimensional collaborative prevention and control method for the thick aquifer coal mine composite disaster according to claim 1, characterized in that, The method further comprises: acquiring a stress concentration coefficient, verifying stress field balance based on the stress concentration coefficient, and evaluating disaster prevention and control indicators to optimize the pressure relief groove spacing and grouting pressure; wherein the disaster prevention and control indicators comprise high-energy microseismic frequency, water inrush early warning accuracy, and prevention and control response delay.

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