Coal Mine Disaster Research Articles

Multi-method Coal Seam Floor Water Inrush Risk Evaluation Based on Variable Weight Theory

Frequent water inrush disasters in deep coal seam mining pose a significant threat to the safety of coal extraction operations. Due to the complexity and non-linearity of water inrush factors, evaluating the risk of water inrush in coal seam floor is challenging and the results can vary significantly. To achieve more accurate evaluations, the weighted rank-sum method and Grey-TOPSIS method were employed, alongside a master control indicator variable-weight model, for assessing the risk of water inrush in coal seam floor. Validation of the evaluation zoning map against actual conditions revealed that both methods produced accurate assessment results, thus affirming the reliability of the new evaluation approach. Compared with the water inrush coefficient method, the diversification of index factors weakened the absolute control effect of the water inrush threshold. The evaluation outcomes were more systematic and comprehensive, providing a new methodology and perspective for deep coal seam mining.

Effect of Thick–Hard Main Roof Fracturing on the Spatiotemporal Evolution of Overburden Fractures

Gas gushing and the co-mining of coal and gas outbursts are common disasters in coal mines. The weakening of thick–hard main roof fracturing can effectively alleviate the gas overrun in the initial mining stage. Four numerical simulation schemes were designed to determine the optimal fracturing treatment scheme for the gas overrun problem in the initial mining stage of the 6505# working face in the Huanghou Coal Mine. Compared with the scheme of the non-fracturing main roof, the weakening of the main roof fracturing could alleviate the concentration of advanced abutment stress. The fissure ratio of the overburden was solved by the binary method, and the dominant channels of gas migration and their morphological evolution under different fracturing schemes were obtained. On this basis, the permeability model of “permeability–fissure ratio–fractal dimension” was established. The results show that the overburden fracture network of the horizontal fracturing scheme has a larger fractal dimension, indicating that the overburden fracture under the scheme is more fully developed and more conducive to gas migration. The research results provide valuable reference for the design of the gas extraction scheme.

Effect of Sandstone Pore Morphology on Mechanics, Acoustic Emission, and Energy Evolution

Roadway section form is an important part of the underground engineering structure, and it directly affects the overall stability of the roadway and the occurrence of underground disasters in coal mines. Based on this, this paper adopts a TYJ-500 electro-hydraulic servo rock shear rheology testing machine to conduct a uniaxial compression test on sandstone containing different prefabricated hole section morphology and analyzes the damage characteristics seen during the damage evolution process, with the help of a high-speed camera and acoustic emission monitoring equipment. The test results show that the pore morphology is the main factor affecting the mechanical parameters of sandstone, and the peak stress and elastic modulus of sandstone with pore sections have the characteristics of increasing and decreasing at the same time, except for the intact rock samples. The pore morphology exhibits central symmetry (circular holes and rectangular holes) damage, more pressure-shear cracks and shear cracks, and the acoustic emission characteristics of high-energy–low-amplitude–low-count of the “two low-trend and one high-trend characteristic curves” attributes; moreover, due to the special existence of its pore morphology, it leads to the rock samples having less energy accumulation and release. The axisymmetric hole types (trapezoidal holes and straight-wall domed holes) are damaged by tensile cracks and shear cracks, and their acoustic emission characteristics show the characteristic properties of “three high-trend characteristic curves” of high-energy–high-amplitude–high-count, and there is a strong elastic energy accumulation and output. The conclusions of this article can provide a certain theoretical basis for the design of coal mine roadway sections in underground structures, failure analysis, and stability evaluation of roadway structures.

Influence of roof confined water drainage on stress distribution in coal seam

Coal and gas outbursts, along with rock bursts, are common dynamic disasters in coal mining, threatening the safety and green production of coal mines. The distribution of coal seam stress is an external factor contributing to coal mine power disasters. The drainage of confined water in coal seam roof is the primary factor of coal seam stress changes. Using theoretical analysis and numerical simulations, the influence of roof confined water on coal seam stress by looking at the law of stress and stress conservation transfer in the drainage layer is investigated. Our results show that: (1) after drainage, there is an increase in the local stress within the coal seam, with a stress concentration factor of 1.35. The influence range of theoretically calculated stress is consistent with the measured results. (2) the maximum value of drainage boundary stress correlated positively with the angle of the water-rich abnormal area, with a linear fitting of R2 = 0.98. These findings hold significant theoretical and practical implications for preventing and controlling dynamic disasters during the mining of water-rich coal seams.

Monitoring water infiltration in multiple layers of sandstone coal mining model with cracks using ERT

Abstract Many engineering disasters are related to water infiltration in cracks. Understanding the water infiltration in multi-layered sandstone cracks is crucial for monitoring and preventing water-related disasters in coal mines. In this study, we utilized the electrical resistivity tomography (ERT) technique to conduct a water infiltration monitoring experiment on the 2d-strata-model with cracks. The electrical resistivity ratio profiles with respect to the background unveiled the existence of three cracks. Model photography demonstrates two cracks of those cracks. The infiltration cracks exhibit distinct shape of a stripe or island chain electrical change ratio anomaly in the resistivity ratio profiles. Electrical resistivity change ratio is associated with the infiltration within the cracks. As the infiltration progresses, the resistivity change ratios relative to the background gradually decreases. This is evident in the reduction in ratios in the original stripe or island chain areas in the electrical resistivity ratio profiles. The diminished range expands, manifesting as an increase in the area of the original stripe or island chain. The infiltration patterns of the cracks can be categorized into three types: a stripe pattern, island chain and stripe pattern, and island chain pattern. The preferential flow paths along the crack are related to both the infiltration time and the volume of infiltration. In the early stages, there are clear preferential flow paths along cracks. However, as infiltration time and volume increase, these preferential flow paths along the cracks become less pronounced and may even disappear. The findings prove that ERT is suitable for monitoring water infiltration along the cracks in multi-layered sandstone in the early infiltration stage. Experiment results monitoring water infiltration cracks on the 2D-model show that the ERT and 2D-model are suitable for studying water infiltration along the cracks. This research can provide valuable reference for preventing engineering disaster.

Development Law of Water-Conducting Fracture Zones in Overburden above Fully Mechanized Top-Coal Caving Face: A Comprehensive Study

Although it is of great significance to master the height of the water-conducting fracture zone (WCFZ) to prevent coal mine disasters and ensure safe production, the most important thing is to predict the height and range of the WCFZ ahead of the working face design before coal mining. Therefore, the 150313 fully mechanized top-coal caving working face of the Yinying coal mine was taken as the engineering background. The development laws of WCFZ were studied using comprehensive research methods, including similar simulation experiments, key strata theory, the experience formula, the numerical simulation, etc. The results show that the WCFZ evolution stage is “goaf–caving zone–fracture zone” and the developing pattern is in a non-isosceles trapezoid gradually developing upward and forward. The height of the WCFZ in the 150313 working face is 89.36 m, and the fracture/mining ratio is 12.46, which is consistent with the actual production. Apparently, the set of indoor research methods in this paper is feasible to predict the height and scope of the WCFZ. The research results can provide a scientific reference for safe mining of the 15# coal seam in Shanxi Province and the prevention and control of roof water hazards.

Promoting Sustainable Development of Coal Mines: CNN Model Optimization for Identification of Microseismic Signals Induced by Hydraulic Fracturing in Coal Seams

Borehole hydraulic fracturing in coal seams can prevent dynamic coal mine disasters and promote the sustainability of the mining industry, and microseismic signal recognition is a prerequisite and foundation for microseismic monitoring technology that evaluates the effectiveness of hydraulic fracturing. This study constructed ultra-lightweight CNN models specifically designed to identify microseismic waveforms induced by borehole hydraulic fracturing in coal seams, namely Ul-Inception28, Ul-ResNet12, Ul-MobileNet17, and Ul-TripleConv8. The three best-performing models were selected to create both a probability averaging ensemble CNN model and a voting ensemble CNN model. Additionally, an automatic threshold adjustment strategy for CNN identification was introduced. The relationships between feature map entropy, training data volume, and model performance were also analyzed. The results indicated that our in-house models surpassed the performance of the InceptionV3, ResNet50, and MobileNetV3 models from the TensorFlow Keras library. Notably, the voting ensemble CNN model achieved an improvement of at least 0.0452 in the F1 score compared to individual models. The automatic threshold adjustment strategy enhanced the identification threshold’s precision to 26 decimal places. However, a continuous zero-entropy value in the feature maps of various channels was found to detract from the model’s generalization performance. Moreover, the expanded training dataset, derived from thousands of waveforms, proved more compatible with CNN models comprising hundreds of thousands of parameters. The findings of this research significantly contribute to the prevention of dynamic coal mine disasters, potentially reducing casualties, economic losses, and promoting the sustainable progress of the coal mining industry.

Evolution characteristics of an induced electric charge signal and identification method of charge for instability failure in loaded coal

A coal-loaded charge induction monitoring system is developed to effectively forecast the dynamic disasters caused by coal failure. Specifically, a digital finite impulse response (FIR) filter is designed to denoise and filter the signal, and the time-frequency domain evolution of induced charge signals is analyzed during coal failure experiments. The quantitative relationships between the induced electric charge and stress-strain energy, and ultimately, between induced electric charge and coal deformation/failure, are revealed. Ultimately, the electric charge sensor exhibits high signal collection frequency and high sensitivity, and the FIR low-pass filter constructed in MATLAB effectively denoises and filters induced charge signals. The main frequency range of the white noise is 50–500 Hz, and the main frequency of the charge signal induced by coal deformation and failure is concentrated in the range of 0–50 Hz. The optimal distances for monitoring cubic and cylindrical raw coal samples using this sensor are 9 mm and 11 mm, respectively. Notably, strain energy is released faster when it can dissipate more readily, and induced charge pulses become denser when more intense signals produce large fluctuations. A method is proposed to identify coal deformation and failure based on changes in the induced electric charge. This study provides a new means of monitoring the early warning signs of dynamic coal mine disasters. Based on our experimental results and conclusions, a new method is proposed to identify coal deformation and failure based on changes in the induced electric charge. The precursor to the moment of coal failure can be identified by monitoring the amplitude of the induced charge, the dynamic trend of fluctuation, and the cumulative number of induced electric charge pulses during the process of coal deformation.

Scale parameters of soft structures for surrounding rock erosion prevention in rockburst-prone roadways

Practical experience in coal mines has suggested that establishing a loose and soft structure in the surrounding rock of roadways can play a role in wave attenuation, energy absorption and erosion prevention, which is conducive to the prevention of and reduction in the severity of rockburst disasters in coal mines. The scale parameters of soft structures includes two aspects: the size and the fracture degree of soft structures. The FLAC3D numerical simulation software was used to study the failure characteristics of roadways with different impact positions (roof impact, side impact) and different impact energies (104, 105, 106, and 107 J). The stress reduction rates of soft structures with different sizes and fracture degrees were calculated. Based on the stress reduction rate of the soft structure, the energy absorption effect of the soft structure around the roadway was obtained as a logarithmic function of the soft structure size, which is a power function related to its fracture degree, and the intersection range of the two curves was fitted. The stress reduction rate was 30% when the soft structure size of the surrounding rock of the roadway was 10–15 m and the fracture degree was represented by 30–40% of the coal strength, which was the most reasonable range of scale parameters. The research conclusions provide a parametric basis for improving the theory and practice of rockburst prevention and support in coal mine roadways.

The Influence of the Fire Point on the Thermal Dynamic Disaster in the Goaf

A thermal dynamic disaster in the goaf is one of the most serious coal mine disasters formed by coal spontaneous combustion and gas interweaving. However, the influence of the high-temperature hidden fire source formed in the goaf on the evolution law of thermal dynamic disasters is not clear, and effective prevention and control measures cannot be taken. Therefore, this paper uses the experimental platform of thermal dynamic disaster in the goaf to study the influence of different fire point positions on the development of thermal dynamic disaster in the goaf through a similar simulation experiment of thermal dynamic disaster evolution in the goaf and analyzes the corresponding relationship between temperature and CO concentration in the upper corner. The results show that under different locations of heat source, the high-temperature heat source of coal spontaneous combustion migrates to the air leakage side with sufficient oxygen supply, and an oxygen-poor circle is formed near the ignition point. Under the action of air leakage flow, CH4 accumulates in the deep part of the goaf on the return air side. Due to the increase in coal, part of CH4 is produced, which leads to the increase in concentration of CH4 at the ignition point. Under the action of different heat sources, the changing trend of concentration of CO and temperature in the return air corner is the same, but the temperature change in the return air corner shows a lag compared with the change in the concentration of CO, so concentration monitoring of CO can reflect the evolution process of the fire field in the goaf more quickly than temperature monitoring.

A Non-Source Optical Fiber Sensor for Multi-Point Methane Detection.

Fast, accurate, real-time measurement of gas concentration is an important task for preventing coal mining disasters. In order to develop an accurate monitoring method for methane gas concentration at different locations in a mine environment, a non-source optical fiber sensor for multi-point methane detection has been developed in this paper. A 16-channel fiber splitter and a multi-channel time-sharing acquisition module are employed within the sensor, enabling simultaneous detection of methane gas at 16 points by a host. Furthermore, the methane sensors are connected to the monitoring host via an all-optical method, achieving non-source and long-range detection of methane. To assess the performance of the methane gas sensor, experiments were conducted to evaluate its detection range, response time, and stability. The results indicated that the average detection error was approximately 1.84% across the full range, and the response time did not exceed 10 s. The minimum detection limit of the sensor, as determined by the 1σ criteria, was obtained as 58.42 ppm. Additionally, the concentrations of methane gas measured at varying distances (1 km, 2 km, 5 km) were found to be essentially consistent over an extended period. These results suggest that the development of this non-source optical fiber sensor holds significant potential for providing a method for mine environment, multi-point online methane gas detection.

Study on methane degradation by microbial agents based on chelating wetting agent carriers

Due to the low permeability characteristics of the deep gas-containing coal seam, the conventional prevention and control measures that cannot solve the problems of gas outbursts are unsatisfactory for the prevention and control of the coal and gas outbursts disaster. Therefore, in this study, a strain of methane-oxidizing bacteria M07 with high-pressure resistance, strong resistance, and high methane degradation rate was selected from coal mines. The growth and degradation abilities of M07 in chelating wetting agent solutions to assess its adaptability and find the optimal agent-to-M07 ratio. It provides a new method for integrating the reduction of impact tendency and gas pressure in deep coal mines. The experimental results show that M07 is a Gram-positive bacterium of the genus Bacillus, which has strong resistance and adaptability to high-pressure water injection. By degrading 70 mol of methane, M07 produces 1 mol of carbon dioxide, which can reduce gas pressure and reduce the risk of gas outbursts in coal mines. As the experiment proves, the best effect was achieved when the M07 concentration of the chelating wetting agent was 0.05%. The methane-oxidizing bacteria based on the chelating wetting agent as carriers prove a new prevention and control method for the integrated prevention and control of coal and gas outbursts in coal mines and also provide a new idea for microbial application in coal mine disaster control.

Study on temporal and spatial response of pressure stimulated current induced by coal deformation and rupture

The pressure stimulated current (PSC) signal emitted during the deformation and fracture processes of coal and rock materials holds significant importance for monitoring dynamic disasters in coal mines. However, the spatial response characteristics remain inadequately explored, posing significant challenges to the identification of risk-prone areas for underground dynamic disasters. To study the temporal and spatial response characteristics of PSC signal, the PSC response experiment in the failure process of raw coal under load was carried out, PSC signals from various spatial positions of coal were collected throughout the loading process. The results show that the sudden increase of axial PSC and the sudden decrease of transverse PSC appear with the sudden increase of acoustic emission (AE) hit rates, which is the main characteristic of the aggravation of coal internal fracture degree. The PSCs are closely related to the damage characteristics of the sample in terms of its corresponding position and drop time, which can better reflect the fracture concentration location of the coal sample. Building upon this foundation, the paper explained the internal factors contributing to variations in PSC spatial response characteristics of coal samples during load failure and emphasizes the inhibitory effect of crack development on PSC changes.

Analysis of stage parameters of low-temperature oxidation of water-soaked coal based on kinetic principles

Mine fires caused by spontaneous coal combustion are major disasters in coal mines. The staged oxidation kinetic parameters of various coal samples at oxygen concentrations of 21 %, 15 %, 10 %, 5 %, and 3 % were analyzed using a programmed temperature testing system. Herein, the temperature increase rate of coal, the temperature difference between the furnace and coal, and the oxygen consumption characteristics were obtained. Based on the amount of CO produced and the temperature sensitivity coefficient, three characteristic temperatures and four stages of low-temperature oxidation (LTO) were identified. The results showed that at a critical temperature (TC), the amount of CO gas released from the coal samples increased with increasing oxygen concentration, and the difference in the oxygen consumption rate increased. After the limit temperature (Tu), the amount of CO gas increased steadily, and the increase in the oxygen consumption rate stagnated. CO production, the maximum heating rate, and the maximum heat release rate were positively correlated with the oxygen concentration. As the oxygen concentration increased, the activation energy during the oxygen absorption stage gradually decreased. The average reaction enthalpy (ΔH) of pre-oxidized water-immersed coal was 19.37 kJ/kg greater than that of raw coal. The equation for the conservation of energy of the coal oxidation warming process was normalized. The theoretical values of the awakening stage and the stable stage were τν and τν (1-B), respectively. When B was >1, pre-oxidized water-immersed coal at a low oxygen concentration was prone to crossover points during the oxygen absorption stage, which increased the risk of coal spontaneous combustion (CSC). The research results could provide a theoretical basis for the staged control of the spontaneous combustion of water-immersed coal in goaf areas.

Research on the spontaneous combustion of the goaf at different advancing distances based on the dynamic evolution of porosity

Spontaneous combustion of residual coal in the goaf is one of the main disasters in coal mines. Understanding the law of spontaneous combustion of residual coal can effectively prevent coal mine fires. This paper establishes a dynamic evolution model of overburden caving and porosity in the goaf using PFC numerical simulation software, and compares and analyzes the dynamic changes in porosity and the spontaneous combustion zone at advancing distances of 50 m, 70 m, and 100 m. The results show that when the working face advances 100 m, the porosity in the caving zone of the goaf decreases from 0–0.6 to 0.16–0.3. The range of the spontaneous combustion zone on the return air side expands from 42m-50 m to 39m–61 m, and on the inlet side, it expands from 0 to 22m–50 m. With increased exposure time, the spontaneous combustion zone range shifts slightly forward to 32m–55 m on the inlet side and 21m–49 m on the return side. This study reveals the dynamic evolution law of the spontaneous combustion zone in the goaf under the influence of different advancing distances and exposure times, which can assist in preventing goaf fires.

Construction and application of a novel WGAN-CNN-based predicting approach for dust concentration at underground coal mine working faces.

To enhance the real-time monitoring and early-warning capabilities for dust disasters in underground coal mine, this paper presents a novel WGAN-CNN-based prediction approach to predict the dust concentration at underground coal mine working faces. Dust concentration, wind speed, temperature, and methane concentration were collected as the original data due to their nonlinear relationship. The consistency between the generated and original data distributions was verified through PCA dimensionality reduction analysis. The predictive performance of this approach was assessed using five metrics (R2, EVS, MSE, RMSE, and MAE) and compared with three other algorithms (Random Forest Regressor, MLP Regressor, and LinearSVR). The findings indicate that a majority of the generated data falls within the distribution range of the real dataset, exhibiting reduced levels of volatility and dispersion. The R2 values of prediction results are all above 98%, and the MSE values are between 0.0007 and 0.0106. The proposed approach exhibits superior predictive accuracy and robust model generalization capabilities compared to alternative algorithms, thereby enhancing the real-time monitoring and early-warning level of dust disasters in underground coal mine. This will facilitate the realization of advanced prevention and control measures for dust disasters, showcasing a wide range of potential applications.

Drill tools sticking prediction based on adaptive long short-term memory

As one of the most severe disasters in deep coal mining, rockburst can be prevented through drill-hole pressure relief. However, the coal mine is characterized by high crustal stress and changeable mechanical properties of surrounding rock, which will cause drill rod deflection phenomenon, then lead to rod-deflection sticking accidents. This paper proposes a prediction method based on adaptive long short-term memory (ALSTM) for rod-deflection sticking accidents to improve drilling efficiency and reduce sticking accidents. Firstly, the sticking data is collected through the intelligent drilling condition simulation experimental platform, and then the sticking features are extracted based on the sticking data. Secondly, the sticking factor is constructed, and the sticking critical line is set. Thirdly, the good-point set and the proposed random perturbation algorithm are employed to improve the spotted hyena optimizer (SHO) to obtain the improved SHO (ISHO). Finally, we use the ISHO to optimize the hyperparameters of the long short-term memory and then establish the sticking prediction model based on ALSTM. The experimental results show that the proposed prediction model meets the demands for sticking prediction very well.

Nonlinear evolution characteristics and seepage mechanical model of fluids in broken rock mass based on the bifurcation theory

With the deep extension of coal mining in China, fault water inrush has become one of the major disasters threatening the safety production of coal mine. Based on the control equations of steady state and non-Darcy seepage in fractured rock mass, the multi-parameter nonlinear dynamic seepage equations of fractured rock mass are established in this paper. Based on the nonlinear dynamics theory, the function of the state variable in the system is derived, and the influence of the gradual change of non-Darcy flow factors on the structural stability of seepage system is studied. The research achievements show that there are three branches in the equilibrium state of the seepage system. Specifically, the stability of the equilibrium state changes abruptly near the limit parameter. The seepage dynamic system of fractured rock mass has the delayed bifurcation, and the coal mine disaster such as fault water inrush occurs easily at the bifurcation point. The research results are of great significance to enrich the theory of fault water inrush in coal mine, and to reveal the disastrous mechanism of fault water inrush and guide its prevention and control technology in coal mine, which can provide the theoretical reference for predicting the water seepage stability in fractured rock mass.

Study on Spontaneous Combustion Risk Areas in Narrow Coal Pillar-Utilized Deep Mining and Double-Pipe Liquid CO2 Injection Technology

ABSTRACT Coal spontaneous combustion (CSC) in goafs, one of the most serious disasters in coal mines, not only wastes resources and destroys the ecological environment, but also causes casualties. As global underground mining gradually shifts to the deep, this problem becomes increasingly prominent. Deep mining is operated in a complex mechanical environment characterized with high stress, high permeability, high temperature, and strong mining disturbance. To avoid stress concentration areas, narrow coal pillars are often utilized in roadway excavation along the goaf. However, narrow coal pillars are likely to fracture and lose stability during the mining process. Consequently, goaf areas of two adjacent working faces might connect, which promotes the CSC risk in the goaf. Most of the current researches are focused on CSC risk areas under shallow mining conditions and the CSC-gas coupling disasters, yet research on CSC risk areas in the goaf triggered by narrow coal pillars under deep mining conditions is rarely reported. Moreover, there is a lack of relevant means to prevent and extinguish fires. This study takes the narrow coal pillar-utilized 130,205 working face in Yangchangwan Coal Mine as the research object. First, the development of coal pillar fractures was simulated by adopting the discrete element method of PFC. Besides, on-site monitoring and FLUENT numerical simulation were conducted to identify CSC risk areas in the goaf of the narrow coal pillar-utilized working face. Finally, a double-pipe liquid CO2 injection technology was proposed for fire prevention and extinguishing. The following beneficial results were obtained. Affected by high stress in deep mining, the coal pillar collapses, which expands the range of the oxidation zone on the return side. Meanwhile, the adjacent goaf is also exposed to CSC risk. Double-pipe liquid CO2 injection can effectively reduce air leakage near the working face and suppress spontaneous combustion of residual coal by inerting the goaf. This study can provide guidance and reference for fire prevention and extinguishing in goafs under the condition of narrow coal pillar-utilized deep mining.

Numerical Multifield Coupling Model of Stress Evolution and Gas Migration: Application of Disaster Prediction and Mining Sustainability Development

At present, coal mining is gradually shifting towards deep areas, and coal mines under deep mining conditions are more prone to coal and gas outburst accidents. In this research, we aim to explain the causes and mechanisms of dynamic disasters, which are caused by the combined action of static load, gas, and dynamic load on tectonic regions in complex stress field environments. Through numerical simulation using COMSOL Multiphysics software, based on the geological conditions of a mine in Jilin Province, it was found that faults lead to abnormal stress in tectonic regions. The combined action of dynamic and static loads results in excessive stress, causing the fragmentation and displacement of the coal body, leading to coal mine disasters, thus disrupting sustainability. Additionally, the coal matrix gas entering fractures raises the gas pressure and leads to the accumulation of methane near earthquake sources. Dynamic loads accelerate gas desorption in coal and increase porosity and permeability, facilitating rapid gas migration. This influx of gas into the roadways exceeds safety limits. Then, based on these findings and on-site conditions, a set of sustainable measures for coal mines has been proposed. This research offers theoretical guidance for enhancing safety, stability, and sustainability in coal mining processes.