A Method and System for Determining Disaster-Inducing Strata Based on Energy Evolution and Overburden Faulting

Abstract

This application proposes a method and system for determining the disaster-causing strata of overburden roof fracture based on energy evolution. The method includes: constructing a three-dimensional numerical simulation model incorporating the geological conditions of the target working face, and setting the corresponding boundary conditions and constitutive model; embedding an energy evolution tracking module into the model to calculate the elastic strain energy accumulation and plastic dissipation energy of each unit body of the overburden in real time during simulated mining; running the working face mining simulation process to monitor the evolution data of energy accumulation and dissipation characteristics of each stratum within the overburden fracture zone; and determining the disaster-causing strata and their degree of hazard based on the ratio of the energy dissipation characteristics of each stratum to the energy dissipation characteristics of the benchmark stratum. This method can quantify the energy accumulation and dissipation characteristics during overburden fracture, accurately identify the disaster-causing strata and assess the degree of hazard, and avoid misjudgment of the disaster-causing strata.

Description

Technical Field

[0001] This application relates to the field of coal mine disaster prevention and control technology, and in particular to a method and system for determining the disaster-causing strata of overburden roof fracture based on energy evolution. Background Technology

[0002] Currently, identifying the fault-causing strata of the overlying roof is a core aspect of disaster prevention and control in deep coal mining, directly impacting the effectiveness of preventing major dynamic disasters such as rockbursts and mine tremors. With increasing mining depth, related technologies typically employ a collaborative approach combining key layer theory, on-site microseismic monitoring, and numerical simulation to construct a prevention and control system encompassing geological assessment and real-time early warning. Specifically, this system covers the entire process from rock structure analysis and microseismic signal acquisition to disaster mechanism deduction, including key aspects such as thick and hard rock layer identification, energy accumulation monitoring, and fault morphology inversion.

[0003] However, the disaster-causing stratum identification schemes in related technologies directly rely on the determination of key stratum locations or the statistics of single microseismic events. They do not conduct refined quantification of the energy evolution mechanism throughout the entire process of overburden fracturing. This may lead to misjudgment of the disaster-causing stratum under the disturbance of thick and hard rock strata, or insufficient assessment of the potential degree of danger, thereby affecting the pertinence and effectiveness of subsequent roof cutting and pressure relief measures, making it difficult to fundamentally curb the occurrence of roof dynamic disasters. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art.

[0005] Therefore, the first objective of this application is to propose a method for determining the disaster-causing strata of the overlying roof based on energy evolution.

[0006] The second objective of this application is to propose a system for determining the disaster-causing strata of the overlying roof based on energy evolution.

[0007] The third objective of this application is to propose an electronic device.

[0008] The fourth objective of this application is to provide a computer-readable storage medium.

[0009] To achieve the above objectives, the first aspect of this application is to propose a method for determining the disaster-causing strata of the overlying roof based on energy evolution, comprising the following steps:

[0010] A three-dimensional numerical simulation model containing the geological conditions of the target working face is constructed, and the boundary conditions and constitutive model corresponding to the three-dimensional numerical simulation model are set. An energy evolution tracking module is embedded in the three-dimensional numerical simulation model. The energy evolution tracking module is used to calculate the elastic strain energy accumulation and plastic dissipation energy of each unit of the overburden in real time during the simulated mining process. The working face mining simulation process is run based on the three-dimensional numerical simulation model embedded with the energy evolution tracking module, and the evolution data of energy accumulation and energy dissipation characteristics of each rock layer within the overlying fracture zone are monitored. Based on the ratio of the energy dissipation characteristics of each rock stratum to the energy dissipation characteristics of the benchmark rock stratum, the disaster-causing strata and the degree of disaster risk of overburden fracture are determined.

[0011] To achieve the above objectives, a second aspect of this application also proposes a system for determining the disaster-causing strata of the overlying roof based on energy evolution, comprising the following modules: The construction module is used to construct a three-dimensional numerical simulation model containing the geological conditions of the target working face, and to set the boundary conditions and constitutive model corresponding to the three-dimensional numerical simulation model. An embedding module is used to embed an energy evolution tracking module into the three-dimensional numerical simulation model, wherein the energy evolution tracking module is used to calculate the elastic strain energy accumulation and plastic dissipation energy of each unit of the overburden in real time during the simulated mining process. The simulation module is used to run the working face mining simulation process based on the three-dimensional numerical simulation model embedded in the energy evolution tracking module, and to monitor the evolution data of energy accumulation and energy dissipation characteristics of each rock layer within the overlying fracture zone. The determination module is used to determine the disaster-causing strata and the degree of disaster risk based on the ratio of the energy dissipation characteristics of each rock stratum to the energy dissipation characteristics of the benchmark rock stratum.

[0012] To achieve the above objectives, a third aspect of this application also proposes an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method for determining the disaster-causing stratum based on energy evolution of the overlying roof as described in any one of the first aspects above.

[0013] To achieve the above objectives, the fourth aspect of this application also proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for determining the disaster-causing strata based on energy evolution of the overburden roof fracture, as described in any one of the first aspects above.

[0014] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects: This application can quantify the energy accumulation and dissipation characteristics during the overburden fracturing process, accurately identify the disaster-causing strata and assess the degree of danger, and effectively overcome the defects of traditional methods that are prone to misjudgment and difficult to quantify.

[0015] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0016] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a method for determining the disaster-causing strata based on energy evolution of the overlying roof fracture, as proposed in an embodiment of this application. Figure 2 This is a schematic diagram of an energy dissipation module calling process proposed in an embodiment of this application; Figure 3 This is a rock overburden columnar diagram proposed in an embodiment of this application; Figure 4 This is a schematic diagram of a numerical model proposed in an embodiment of this application; Figures 5(a) to 5(d) are cloud maps of overburden energy dissipation during a simulation process proposed in an embodiment of this application; Figure 6 This is a schematic diagram illustrating the peak variation of energy dissipation density in various rock strata, as proposed in an embodiment of this application. Figure 7 This is a schematic diagram of the vertical distribution of microseismic activity at a working face, as proposed in an embodiment of this application. Figure 8 This is a schematic diagram of a system for determining the disaster-causing strata of the overlying roof based on energy evolution, as proposed in an embodiment of this application. Detailed Implementation

[0017] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0018] The following description, with reference to the accompanying drawings, describes a method and system for determining the disaster-causing strata of the overlying roof based on energy evolution, as proposed in an embodiment of this application.

[0019] Example 1 Figure 1This is a flowchart illustrating a method for determining the disaster-causing strata based on energy evolution of the overlying roof fracture, as proposed in an embodiment of this application. Figure 1 As shown, the method includes the following steps: Step S101: Construct a three-dimensional numerical simulation model that includes the geological conditions of the target working face, and set the boundary conditions and constitutive model corresponding to the three-dimensional numerical simulation model.

[0020] Specifically, this step aims to reconstruct the spatial structure and mechanical environment of the overburden in underground mining areas using digital means, providing an accurate physical field basis for subsequent energy evolution analysis.

[0021] Specifically, the process first determines the spatial geometry of the model based on the actual occurrence of the target working face to ensure that the simulation range covers the key areas affected by mining. Then, constraints consistent with the in-situ stress state are applied to the model's boundaries. These typically include fixed boundaries restricting bottom displacement and stress boundaries simulating the interaction of gravity and tectonic stress in the overlying strata. The lateral pressure coefficient must reflect the characteristics of the regional tectonic stress field. Simultaneously, based on the lithological physical and mechanical parameters of each overlying stratum, corresponding constitutive relations are matched to different rock strata units in the model to describe the stress-strain response and failure mechanism of the rock mass under mining disturbance.

[0022] As a specific implementation method, FLAC can be used. 3D A three-dimensional model is created using numerical simulation software, and the model size is set to... The model has a fixed boundary at the bottom, and stress boundaries at the top and bottom. The lateral pressure coefficient is set to 1.2. The overlying rock is characterized by the Mohr-Coulomb constitutive model, in which the rock layer structure can contain multiple layers of sandstone and mudstone of different thicknesses.

[0023] Therefore, the numerical simulation model constructed in the above manner can accurately reproduce the structural characteristics and initial stress field of overburden under complex geological conditions, eliminating simulation errors caused by model simplification or distortion of boundary conditions. It provides a reliable computing platform for accurately tracking the accumulation and dissipation evolution of overburden energy during mining, thereby ensuring the accuracy and engineering applicability of the disaster-causing strata identification results.

[0024] Step S102: Embed an energy evolution tracking module into the three-dimensional numerical simulation model. The energy evolution tracking module is used to calculate the elastic strain energy accumulation and plastic dissipation energy of each unit of the overburden in real time during the simulated mining process.

[0025] Specifically, an energy evolution tracking module is embedded in the three-dimensional numerical simulation model to quantify the dynamic energy conversion mechanism inside the overburden during mining in real time through numerical calculations. Based on the principles of continuum mechanics, this module constructs an energy balance equation by calling the stress tensor and strain increment data of each unit in the simulation model, thereby converting the work done by external loads into two parts: elastic strain energy accumulation and plastic dissipation energy inside the unit.

[0026] Specifically, based on the limit principle, this module divides the stress process of the rock mass into stress increase and stress decrease stages. It performs integral calculations or discrete accumulation on the average stress and strain increment at different time periods to obtain the energy accumulation and total dissipation energy. Furthermore, it deducts the residual strain energy after rock mass failure to obtain the full-cycle dissipation energy characterizing the rock mass damage evolution.

[0027] As a specific implementation method, such as Figure 2 As shown, it can be based on FLAC 3D The software's stress-strain interface extracts the three principal stresses of each element block. , and Using the formula The average principal stress over the calculation period is combined with the elastic strain increment. With plastic strain increment ,pass and Calculate the energy accumulation and total energy dissipation separately, and then... The residual strain energy is obtained, and finally... The plastic dissipation energy was obtained.

[0028] Therefore, this step, by establishing an embedded energy evolution tracking mechanism, achieves refined quantification of the energy accumulation and release process during overburden fracturing, overcoming the shortcomings of traditional simulation methods that can only qualitatively describe the damage range but cannot accurately calculate energy evolution, and providing reliable physical quantity basis for subsequent accurate identification of high disaster-risk strata.

[0029] Step S103: Run the working face mining simulation process based on the three-dimensional numerical simulation model with embedded energy evolution tracking module, and monitor the evolution data of energy accumulation and energy dissipation characteristics of each rock layer within the overlying fracture zone.

[0030] Specifically, the core of this step lies in dynamically reproducing the mechanical response behavior of the overburden medium under changes in the mining stress field through numerical iterative calculations. This step relies on a pre-constructed three-dimensional numerical simulation model and an embedded energy evolution tracking module. During the simulated mining process, stress and strain state data are automatically retrieved according to the set calculation step size or number of cycles to continuously track the target rock strata located within the influence range of the water-conducting fracture zone.

[0031] The monitoring process aims to acquire the energy state variables of the rock strata throughout their entire life cycle, specifically including the accumulation of elastic strain energy, which characterizes the elastic deformation capacity of the rock mass, and the plastic dissipation energy, which characterizes the degree of damage and fracture of the rock mass. By recording the variation curves of these energy parameters with the mining distance or time step, the complete evolution law of different rock strata from energy accumulation and peak storage to sudden release and dissipation can be quantitatively revealed, thereby capturing the key energy thresholds for the transformation of rock strata from a stable state to instability and fracture.

[0032] As a specific implementation method, the vertical range of the fracture zone can be determined based on the empirical formula for the height of the water-conducting fracture zone in fully mechanized longwall mining of thick coal seams. Virtual survey lines are then arranged in the middle of each rock stratum above the coal seam within this range. The length of the survey lines is set to cover the area affected by the advancement of the working face. In this way, elastic energy and damage dissipation energy data of each rock stratum are collected throughout the entire mining process, forming an energy evolution sequence that is dynamically updated with the mining progress.

[0033] Therefore, this step, through full-cycle and layered energy characteristic monitoring, achieves precise quantification of energy accumulation and dissipation behavior during overburden fracturing, overcoming the shortcomings of traditional methods that are difficult to dynamically capture the details of rock stratum damage evolution, and providing detailed and reliable data support for subsequent accurate identification of disaster-causing strata and assessment of hazard level based on energy ratio relationships.

[0034] Step S104: Based on the ratio of the energy dissipation characteristics of each rock layer to the energy dissipation characteristics of the benchmark rock layer, determine the disaster-causing strata and the degree of disaster risk caused by overburden fracture.

[0035] Specifically, the core of this step lies in constructing a quantitative criterion for stratigraphic hazard based on relative energy indices. This step extracts energy dissipation evolution data of each stratum within the overlying fracture zone under mining disturbance during numerical simulation, selects a representative benchmark stratum as a reference object, and calculates the ratio of the energy dissipation characteristic value of the target stratum to that of the benchmark stratum. This eliminates the uncertainty of absolute energy values ​​caused by differences in model scale or geological conditions, and achieves a normalized comparative analysis of the hazard potential among different strata.

[0036] Furthermore, by setting a reasonable ratio threshold, rock strata with energy dissipation significantly higher than the baseline level are identified as potential fault-causing strata, and the degree of disaster risk is classified according to the ratio gradient. The larger the ratio, the more concentrated the destructive energy accumulated and released by the rock strata, and the higher the risk of dynamic disasters.

[0037] As a specific implementation method, the peak energy dissipation of each rock stratum during the entire mining cycle can be statistically analyzed. The peak energy dissipation of the immediate roof stratum is selected as the benchmark value. The ratio of the peak energy dissipation of each upper rock stratum to the peak energy dissipation of the immediate roof stratum is calculated. When the ratio exceeds the preset critical value, the corresponding rock stratum is determined to be a fault-causing stratum.

[0038] Therefore, this step, by introducing relative ratio analysis, transforms abstract energy evolution data into intuitive disaster risk assessment indicators, effectively overcoming the shortcomings of a single absolute energy indicator in making it difficult to horizontally compare the degree of danger of different rock strata. It significantly improves the accuracy and quantification level of identifying disaster-causing strata due to overburden fracture, and provides a reliable theoretical basis for formulating targeted roof disaster prevention and control measures.

[0039] Example 2 Based on the above embodiments, this embodiment provides a detailed description of the specific implementation of the step S101 above, which involves "constructing a three-dimensional numerical simulation model containing the geological conditions of the target working face and setting corresponding boundary conditions and constitutive models".

[0040] In this embodiment, a three-dimensional numerical simulation model incorporating the geological conditions of the target working face is constructed, and boundary conditions and constitutive models corresponding to the three-dimensional numerical simulation model are set, including: using FLAC 3D Numerical simulation software is used to establish a three-dimensional numerical model. The size of the three-dimensional numerical model is determined according to the working face conditions. The lower part of the model is set as a fixed boundary, and the four sides and the upper part of the model are set as stress boundaries. The lateral pressure coefficient of the three-dimensional numerical model is set to 1.2, and the mechanical properties of the overburden are defined by the Mohr-Coulomb constitutive model to obtain a three-dimensional numerical simulation model with a specific geomechanical environment.

[0041] The process involves setting the lower part of the model as a fixed boundary and the surrounding and upper parts as stress boundaries. This includes applying constrained fixed boundary conditions to the lower part of the three-dimensional numerical model, applying stress boundary conditions to the surrounding and upper parts of the three-dimensional numerical model, and setting the upper vertical stress to 13.1 MPa. Based on geological exploration data, a three-layered hard sandstone structure containing 16.1 m thick fine sandstone, 9.5 m thick siltstone, and 14.2 m thick coarse sandstone is constructed in the three-dimensional numerical model. The remaining overburden strata are filled with sandy mudstone and sandstone material parameters to obtain a three-dimensional numerical simulation model that reflects the actual rock layer distribution of the target working face.

[0042] Specifically, this embodiment first inputs the geological occurrence data of the target working face as the modeling basis, and then calls FLAC. 3D Numerical simulation software was used to create a three-dimensional mesh model, with the model dimensions set to 600m in length, 400m in width, and 240m in height. This size covers the main area affected by the mining face.

[0043] Then, boundary conditions are applied to the model. The lower nodes of the model are set as fully constrained fixed boundaries, restricting their displacement in the X, Y, and Z directions, which serve as the reference surface for mechanical calculations. The four sides and the upper part of the model are set as stress boundaries. Based on the weight of the overlying rock strata and the characteristics of the tectonic stress field, the upper vertical stress is set to 13.1 MPa, and the lateral pressure coefficient is set to 1.2, thereby generating corresponding horizontal stress loads at the model boundaries to simulate the original rock stress environment of deep mining.

[0044] Next, the constitutive model and rock strata structure were defined. The Mohr-Coulomb constitutive model was used to describe the shear failure and plastic flow characteristics of the overlying strata. Based on geological exploration data, a specific rock strata distribution was constructed within the model, focusing on three thick, hard sandstone layers: a 16.1m thick fine sandstone, a 9.5m thick siltstone, and a 14.2m thick coarse sandstone. The remaining overlying strata were filled with material parameters of sandy mudstone and sandstone, including density, elastic modulus, Poisson's ratio, internal friction angle, and cohesion. After the above processing, a three-dimensional numerical simulation model was output, which accurately reflects the actual rock strata distribution and stress state of the target working face, possessing a specific geomechanical environment. This model serves as the direct input basis for subsequent energy evolution tracking and mining simulation calculations.

[0045] Therefore, this implementation method constructs a high-fidelity three-dimensional numerical simulation environment by precisely setting the model size, boundary stress state, and spatial distribution of key thick and hard rock layers. It effectively restores the original rock stress field and overburden structure characteristics under deep mining conditions, providing a reliable mechanical calculation model basis for accurately tracking the energy evolution law during the overburden fracture process and accurately identifying the disaster-causing strata.

[0046] Example 3 Based on the above embodiments, this embodiment provides a detailed description of the specific implementation of step S102, "embedding an energy evolution tracking module in the three-dimensional numerical simulation model to calculate the elastic strain energy accumulation and plastic dissipation energy of each unit of the overburden in real time during the simulated mining process".

[0047] In this embodiment, an energy evolution tracking module is embedded in the three-dimensional numerical simulation model to calculate the elastic strain energy accumulation and plastic dissipation energy of each unit of the overburden in real time. Specifically, this is achieved by calling FLAC. 3D The internal stress and strain data are collected and integrated in stages.

[0048] First, the input source is each unit block during the numerical simulation process. Time and Three principal stress data at time 1 , and The processing action involves extracting the aforementioned data based on the stress-strain method and calculating the average principal stress over the time period. The output result is the average principal stress. Its calculation follows the formula ,in and These correspond to the principal stress values ​​at the start and end times, respectively.

[0049] Then, the elastic strain increment of the unit cell is obtained based on the same time step. With plastic strain increment As input, the total strain increment is obtained through linear superposition. .

[0050] Next, based on the characteristics of the stress-strain variation curve of the unit rock mass, the stress evolution process is divided into a stress increase stage and a stress decrease stage. Using the previously calculated average principal stress and total strain increment as inputs, the two stages are accumulated separately, and the energy accumulation of the stress increase stage is output. and the total energy during the stress reduction phase .

[0051] Based on this, the strain after plastic failure of the unit cell and the elastic modulus after attenuation are introduced. As a parameter, the magnitude of the residual strain energy of the calculated unit rock mass .

[0052] Finally, set the number of steps per loop. Control model every operation Each call to the energy dissipation code subtracts the residual strain energy from the calculated total energy, i.e., executes... The differential processing ultimately outputs the quantized magnitude of the overburden's total lifecycle dissipation energy. This allows for the accurate tracking of overlying rock energy evolution data.

[0053] Therefore, this specific implementation method, through a calculation logic that combines phased integration with residual energy correction, achieves a refined quantification of the entire process of energy accumulation and dissipation during overburden fracturing, effectively solving the technical problem that traditional methods cannot distinguish between elastic release energy and plastic dissipation energy, and significantly improving the accuracy of disaster-causing strata identification.

[0054] Example 4 Based on the above embodiments, this embodiment provides a detailed description of the specific implementation of step S103 above, which involves "running the working face mining simulation process and monitoring the evolution data of energy accumulation and energy dissipation characteristics of each rock layer within the overlying fracture zone".

[0055] In this embodiment, the evolution data of energy accumulation and dissipation characteristics of each rock stratum within the overlying fracture zone are monitored, including: calculating the range of the fracture zone based on the empirical formula for the height of the water-conducting fracture zone in fully mechanized longwall mining of thick coal seams; arranging survey lines at the middle position of the coal seam strata within the fracture zone in the calculated overlying strata, setting the survey line length to 400m; simulating the longwall mining process, and monitoring each rock stratum within the fracture zone in real time through the survey lines, collecting data on the elastic energy accumulated and the damage dissipation energy of each rock stratum, to obtain energy evolution monitoring data of each rock stratum within the overlying fracture zone.

[0056] Specifically, first, input the coal seam mining thickness data of the target working face. The processing involves analyzing the overlying lithology classification information and calculating the vertical range of the fracture zone based on an empirical formula for the height of the water-conducting fracture zone in fully mechanized longwall mining of thick coal seams. Specifically, when the overlying strata are hard rock layers, the formula is used... Calculations are performed; when the overlying strata are medium-hard or weak, the formula is used. The calculation is performed, and the output result is the determined boundary value of the overburden fracture zone height.

[0057] Furthermore, using the fracture zone range calculated above as the input source, the processing action involves horizontally arranging monitoring lines at the midpoint of each coal seam stratum within this range, and setting the length of the monitoring lines to... The output is a spatially fixed energy evolution monitoring survey line network.

[0058] Subsequently, a three-dimensional numerical simulation model was launched to execute the working face mining process. Using the pre-arranged survey lines as data acquisition channels, the processing action was to track and monitor each rock layer within the fracture zone in real time, collecting data on the elastic energy accumulated by each rock layer under mining disturbance and the dissipated energy data caused by damage. The output result is a data set of energy evolution monitoring of each rock layer within the overlying fracture zone containing time series data. This data set fully records the dynamic changes in energy accumulation and dissipation of each rock layer from the start of mining to the stabilization period, providing a quantitative basis for the subsequent determination of the disaster-causing strata.

[0059] Therefore, this implementation method accurately defines the monitoring range of the fracture zone through empirical formulas and combines it with fixed-length measuring lines for layered real-time monitoring, which effectively avoids data redundancy caused by blind monitoring of the entire model, and ensures the targeted and accurate collection of energy evolution data, thereby providing a reliable data foundation for quantitatively assessing the degree of disaster risk caused by overlying rock fracture.

[0060] Example 5 Based on the above embodiments, this embodiment provides a detailed description of the specific implementation of step S104 above, which involves "determining the disaster-causing stratum and the degree of disaster risk of overburden fracture based on the ratio of the energy dissipation characteristics of each rock stratum to the energy dissipation characteristics of the reference rock stratum".

[0061] In this embodiment, the disaster-causing strata and their degree of hazard are determined based on the ratio of the energy dissipation characteristics of each rock layer to the energy dissipation characteristics of the reference rock layer. This includes: statistically analyzing the peak energy dissipation of each rock layer in the overburden based on numerical simulation results; selecting the immediate overlying rock layer as the reference rock layer and calculating the ratio of the peak energy dissipation of each rock layer to the peak energy dissipation of the immediate overlying rock layer; determining whether each rock layer in the overburden has a hazard based on the calculated ratio of peak energy dissipation; identifying the strata with a peak energy dissipation ratio higher than other rock layers as disaster-causing strata in the overburden, and quantifying the degree of hazard based on the ratio value.

[0062] Specifically, the input source is the energy evolution monitoring data of each rock layer within the overlying fracture zone generated after the working face mining simulation in step S103 above. The processing action is to traverse the monitoring time series, extract the maximum value of plastic dissipation energy of each rock layer during the entire mining cycle, and output the dataset of peak dissipation energy corresponding to each rock layer.

[0063] For example, in a simulation of a working face in a coal mine, the peak dissipation energy of a 16.1m thick fine sandstone layer was found to be 109.3 kJ / m³, the peak dissipation energy of a 14.2m thick coarse sandstone layer was 98.8 kJ / m³, and the peak dissipation energy of the 4.7m thick sandy mudstone layer, which serves as the immediate roof, was 40.7 kJ / m³. Next, using the peak dissipation energy of the immediate roof layer output from the previous sub-step as the baseline input, the processing involves dividing the peak dissipation energy of each other rock layer within the overlying fracture zone by this baseline value, performing a normalized ratio calculation, and outputting a sequence of peak dissipation energy ratios for each rock layer relative to the immediate roof. For example, the ratio for the fine sandstone layer is 109.3 divided by 40.7, resulting in 2.68; the ratio for the coarse sandstone layer is 98.8 divided by 40.7, resulting in 2.42; while the ratios for other weak rock layers such as mudstone and interbedded sandstone are all below 1.5.

[0064] Finally, using the calculated peak dissipation energy ratio sequence as input, the processing involves setting a disaster risk assessment threshold, marking layers with ratios significantly higher than other rock layers and exceeding the preset threshold as potential disaster-causing layers, and linearly quantifying the disaster risk level based on the ratio value. The output is the final list of overburden fracture disaster-causing layers and their hazard levels. In this example, fine sandstone and coarse sandstone layers with ratios greater than 2 are identified as fracture disaster-causing layers. Among them, the fine sandstone layer is identified as a key layer with a higher disaster risk level due to its higher ratio, thus completing the logical closed loop from energy data to disaster-causing layer determination.

[0065] Therefore, this implementation method eliminates the uncertainty of absolute energy values ​​affected by model size and boundary conditions by introducing the immediate top rock layer as a benchmark for normalized ratio calculation, making the disaster-causing hazards between different rock layers comparable; at the same time, it directly quantifies the degree of hazard by using the magnitude of the peak dissipation energy ratio, realizing the accurate identification and classification evaluation of the disaster-causing layers of overburden fracture, and providing a clear quantitative basis for formulating targeted roof disaster prevention and control measures.

[0066] Example 6 This embodiment will describe in detail the complete implementation of the method for determining the disaster-causing strata of overburden fracture based on energy evolution of this application. The method takes the X working face of Coal Mine A as a specific engineering background. By constructing a high-precision three-dimensional numerical model, embedding a custom energy evolution tracking module, arranging targeted monitoring lines, and combining on-site microseismic data for verification, the method can accurately identify the disaster-causing strata of overburden fracture and quantify the degree of danger.

[0067] In this embodiment, the first step is to determine the model parameters. Referring to the geological data of the X working face of Coal Mine A, the model coal seam thickness is set to 5.2m, and the main rock strata of the model are as follows: Figure 3 As shown, the model parameters are set according to the lithology, and a model is constructed as follows. Figure 4 The numerical model is shown. Based on the empirical formula for the height of the water-conducting fracture zone under hard roof conditions, the height of the water-conducting fracture zone at working face X is calculated to be approximately 71.25 m. Therefore, the model layout and survey line location parameters are shown in Table 1 below: Table 1. Parameters for the Layout of Survey Lines in the Overburden Rock

[0068] Furthermore, the overall height of the monitored overburden is approximately 80.6m, encompassing the rock strata within the entire fracture zone.

[0069] The second step is to conduct a working condition simulation. The total advance distance of the simulated working face is 400m. As shown in Figure 5(a), when the working face advances 100m, the basic roof stratum (16.1m of fine sandstone) quickly enters a plastic state, with a dissipated energy density of 62kJ / m³. 3 This layer becomes a high-energy-dissipation layer. When the working face advances 200m, the 9.5m siltstone layer becomes a high-energy-dissipation layer, as shown in Figure 5(b), with a dissipation energy density of 62 kJ / m³. 3 When the working face advanced to 300m, as shown in Figure 5(c), the 14.2m coarse sandstone became a new high-energy-dissipation layer, with a peak energy dissipation of 110 kJ / m. 3 As shown in Figure 5(d), no new high-energy-dissipating layers were generated when the working face advanced to 300m.

[0070] The third step is the identification of the disaster-causing strata. This involves determining the energy dissipation density of the overlying roof of the X working face in Coal Mine A, combined with... Figure 6 It can be seen that the energy dissipation density of the 16.1m fine sandstone, 9.5m siltstone, and 14.2m coarse sandstone is significantly higher than that of other rock layers. The degree of disaster risk caused by overlying rock fracture is further determined based on the overlying rock energy dissipation density ratio, and the calculation results are shown in Table 2 below: Table 2. Results of dissipated energy ratio and determination of disaster-causing strata in overlying strata.

[0071] The calculation results show that the overall energy dissipation ratio of the 16.1m siltstone and the 14.2m coarse sandstone is greater than 2, which is significantly higher than that of other rock layers. Moreover, these two rock layers are located within the fracture zone. Therefore, these two rock layers are determined to be fault-causing layers.

[0072] The fourth step is the microseismic data verification process. This involves analyzing the on-site microseismic data, from... Figure 7 The vertical distribution characteristics, energy magnitude, and distribution proportion of microseismic events at different heights shown in the figure are used to verify the determination of the disaster-causing strata in the overburden. Based on Table 3 below, high-energy microseismic events (>10) in the overburden are identified. 3 Based primarily on J), these microseismic events were further analyzed according to the proportion of overburden height, thus determining the disaster-causing layers. Furthermore, as shown in Table 4 below, the selected disaster-causing layers correspond to the overburden height ranges of 0–20 m and 40–60 m, respectively. Within these ranges, the proportion and average impact energy of microseismic events are higher than in the 40–60 m range. Therefore, the accuracy of the selected disaster-causing layers can be verified.

[0073] Table 3. Spatiotemporal distribution characteristics of microseismic events

[0074] Table 4. Vertical Distribution of High-Energy Microseismic Events

[0075] In summary, the method for determining the disaster-causing strata based on overburden fracture according to energy evolution in this application realizes the quantitative tracking of energy accumulation and dissipation during overburden fracture by constructing a refined three-dimensional numerical model and embedding an energy dissipation calculation module; and accurately identifies the disaster-causing strata by establishing a criterion based on the dissipation energy ratio. fine sandstone and Coarse sandstone was identified as the key disaster-causing stratum, and its effectiveness was verified by combining field microseismic data. This method overcomes the shortcomings of traditional key stratum theory in misjudging disaster-causing strata and difficulty in quantifying the degree of danger under complex geological conditions. It provides a scientific basis for the precise prevention and control of dynamic disasters on the roof of coal mines, and can effectively guide the targeted implementation of control measures such as roof cutting and pressure relief, thereby reducing the probability of rockbursts and mine earthquakes.

[0076] To achieve the above embodiments, this application also proposes a system for determining the disaster-causing strata based on energy evolution of overlying roof fracture. Figure 8 This is a schematic diagram of a system for determining the disaster-causing strata based on the energy evolution of the overlying roof fracture, as proposed in an embodiment of this application. Figure 8 As shown, the system includes: The construction module 100 is used to construct a three-dimensional numerical simulation model containing the geological conditions of the target working face, and to set the boundary conditions and constitutive model corresponding to the three-dimensional numerical simulation model. Embedded module 200 is used to embed an energy evolution tracking module into the three-dimensional numerical simulation model, wherein the energy evolution tracking module is used to calculate the elastic strain energy accumulation and plastic dissipation energy of each unit of the overburden in real time during the simulated mining process. The simulation module 300 is used to run the working face mining simulation process based on the three-dimensional numerical simulation model embedded in the energy evolution tracking module, and to monitor the evolution data of energy accumulation characteristics and energy dissipation characteristics of each rock layer within the overlying fracture zone. The determination module 400 is used to determine the disaster-causing strata and the degree of disaster risk based on the ratio of the energy dissipation characteristics of each rock stratum to the energy dissipation characteristics of the reference rock stratum.

[0077] It should be noted that the explanation of the aforementioned embodiment of the method for determining the disaster-causing stratum based on the energy evolution of the overlying stratum also applies to the system of this embodiment, and will not be repeated here.

[0078] In summary, the overburden roof fracture disaster-causing stratum determination system based on energy evolution of this application overcomes the shortcomings of traditional key layer theory in misjudging disaster-causing strata and difficulty in quantifying the degree of danger under complex geological conditions. It provides a scientific basis for the precise prevention and control of dynamic disasters of coal mine roof and can effectively guide the targeted implementation of governance measures such as roof cutting and pressure relief, thereby reducing the probability of rockburst and mine earthquake disasters.

[0079] To implement the above embodiments, this application also proposes an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method for determining the disaster-causing stratum based on overburden roof fracture according to any one of the first aspect embodiments described above.

[0080] To implement the above embodiments, this application also proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for determining the disaster-causing stratum based on the energy evolution of the overlying roof fracture as described in any one of the first aspects of the embodiments above.

[0081] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0082] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0083] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0084] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0085] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0086] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0087] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0088] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for determining the disaster-causing strata of overlying roof fracture based on energy evolution, characterized in that, Includes the following steps: A three-dimensional numerical simulation model containing the geological conditions of the target working face is constructed, and the boundary conditions and constitutive model corresponding to the three-dimensional numerical simulation model are set. An energy evolution tracking module is embedded in the three-dimensional numerical simulation model. The energy evolution tracking module is used to calculate the elastic strain energy accumulation and plastic dissipation energy of each unit of the overburden in real time during the simulated mining process. The working face mining simulation process is run based on the three-dimensional numerical simulation model embedded with the energy evolution tracking module, and the evolution data of energy accumulation and energy dissipation characteristics of each rock layer within the overlying fracture zone are monitored. Based on the ratio of the energy dissipation characteristics of each rock stratum to the energy dissipation characteristics of the benchmark rock stratum, the disaster-causing strata and the degree of disaster risk of overburden fracture are determined.

2. The method according to claim 1, characterized in that, The construction of a three-dimensional numerical simulation model containing the geological conditions of the target working face, and the setting of the boundary conditions and constitutive model corresponding to the three-dimensional numerical simulation model, includes: Using FLAC 3D Numerical simulation software is used to establish a three-dimensional numerical model. The size of the three-dimensional numerical model is determined according to the working surface assignment. The lower part of the model is set as a fixed boundary, and the four sides and the upper part of the model are set as stress boundaries. The lateral pressure coefficient of the three-dimensional numerical model is set to 1.2, and the mechanical properties of the overlying rock as a whole are defined using the Mohr-Coulomb constitutive model to obtain a three-dimensional numerical simulation model with a specific geomechanical environment.

3. The method according to claim 2, characterized in that, The step of setting the lower part of the model as a fixed boundary and the four sides and the upper part of the model as stress boundaries includes: Constraint fixed boundary conditions are applied to the lower part of the three-dimensional numerical model, and stress boundary conditions are applied to the four sides and the upper part of the three-dimensional numerical model, with the upper vertical stress set to 13.1 MPa; Based on geological exploration data, a three-layered hard sandstone structure consisting of 16.1m thick fine sandstone, 9.5m thick siltstone, and 14.2m thick coarse sandstone was constructed in the three-dimensional numerical model. The remaining overburden layers were filled with sandy mudstone and sandstone material parameters to obtain a three-dimensional numerical simulation model that reflects the actual rock layer distribution of the target working face.

4. The method according to claim 1, characterized in that, The above includes: Based on FLAC 3D The stress-strain call algorithm in numerical simulation software obtains the three principal stresses inside each element block. , and And calculate the time t and t+ based on the three principal stresses. Mean principal stress at time t ,in, Let t be the time and t+ The principal stress of the element at time t; Calculate time t and t+ The strain increment within the time period corresponding to time t ,in, and These represent the elastic strain increment and the plastic strain increment, respectively. Based on the stress-strain variation curve of the unit rock mass, the stress change period is divided into a stress increase stage and a stress decrease stage. Based on the mean principal stress and the strain increment, the energy accumulation of the unit rock mass during the stress increase stage is calculated respectively. And the total energy of the unit rock mass during the stress reduction stage. , of which 1 to n This refers to the time period during the stress increase phase. n +1 to m This refers to the time period during the stress increase phase. Calculate the magnitude of residual strain energy of the unit rock mass ,in, The modulus of elasticity after attenuation; Set the number of loop steps in the simulation process. When the number of calculations in the 3D numerical model reaches the set number of loop steps, call the energy dissipation code once to dissipate energy. W d and W e By subtracting the values, the total energy dissipation of the overburden over the entire cycle can be calculated.

5. The method according to claim 1, characterized in that, The evolution data on the energy accumulation and dissipation characteristics of each rock layer within the monitored overlying fracture zone include: The range of the fracture zone is calculated based on the empirical formula for the height of the water-conducting fracture zone in fully mechanized longwall mining of thick coal seams. A survey line was laid out in the middle of the coal seam strata within the fracture zone of the overlying strata, with a length of 400m. The simulation of the working face mining process involves real-time monitoring of each rock layer within the fracture zone using the aforementioned survey lines. Data on the accumulated elastic energy and damage dissipation energy of each rock layer are collected to obtain energy evolution monitoring data for each rock layer within the overburden fracture zone.

6. The method according to claim 1, characterized in that, The determination of the disaster-causing strata and the degree of disaster risk based on the ratio of the energy dissipation characteristics of each rock stratum to the energy dissipation characteristics of the benchmark rock stratum includes: The peak energy dissipation values ​​of each overburden stratum were statistically analyzed based on numerical simulation results. The immediate top rock layer was selected as the benchmark rock layer, and the ratio of the peak energy dissipation of each rock layer to the peak energy dissipation of the immediate top rock layer was calculated. Based on the calculated peak dissipation energy ratio, it is determined whether each layer of the overburden has a disaster-causing hazard. Layers with a peak dissipation energy ratio higher than other layers are identified as overburden fracture disaster-causing layers, and the degree of disaster-causing hazard is quantified according to the ratio value.

7. The method according to claim 1, characterized in that, After determining the fault-causing strata and the degree of hazard caused by overlying strata fracturing, the following is also included: Acquire on-site microseismic monitoring data of the target working face and conduct statistical analysis on the energy and spatial distribution characteristics of overburden microseismic events; The vertical distribution characteristics of high-energy microseismic events in the field microseismic monitoring data are compared with the spatial location of the overburden fracture disaster-causing strata to verify the accuracy of the preliminarily determined overburden fracture disaster-causing strata. If the high-incidence area of ​​microseismic events spatially coincides with the determined disaster-causing strata, the disaster-causing strata identification result is confirmed to be valid.

8. A system for determining the disaster-causing strata of overlying roof fracture based on energy evolution, characterized in that, Includes the following modules: The construction module is used to construct a three-dimensional numerical simulation model containing the geological conditions of the target working face, and to set the boundary conditions and constitutive model corresponding to the three-dimensional numerical simulation model. An embedding module is used to embed an energy evolution tracking module into the three-dimensional numerical simulation model, wherein the energy evolution tracking module is used to calculate the elastic strain energy accumulation and plastic dissipation energy of each unit of the overburden in real time during the simulated mining process. The simulation module is used to run the working face mining simulation process based on the three-dimensional numerical simulation model embedded in the energy evolution tracking module, and to monitor the evolution data of energy accumulation and energy dissipation characteristics of each rock layer within the overlying fracture zone. The determination module is used to determine the disaster-causing strata and the degree of disaster risk based on the ratio of the energy dissipation characteristics of each rock stratum to the energy dissipation characteristics of the benchmark rock stratum.

9. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the method for determining the disaster-causing strata based on energy evolution of the overlying roof as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for determining the disaster-causing strata based on the fracturing of the overlying roof as described in any one of claims 1-7.

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