Search Results (15)

As shallow coal resources in China become increasingly depleted, deep coal mining in complex geological areas has become an inevitable trend. However, the technical challenges associated with deep mining are becoming more significant, particularly the issues related to mine water hazards. This study utilized hydrogeological data from the III3 Mining Area in the Zhuxianzhuang Coal Mine, Anhui Province, and employed GMS (Groundwater Modeling System) software to construct a numerical karst water flow model under deep mining conditions. By simulating variations in the flow field, the study verified the drainage potential of the limestone water at the base of Seam 10 and assessed the water conductivity and connectivity of the F22 fault. The following conclusions were obtained: The simulation effectively captured the formation process of the karst water drawdown cone in the study area. The observed water level variations in different monitoring wells aligned well with the engineering reality after validation. The limestone water at the base of Seam 10 in the III3 Mining Area exhibited good transmissivity, weak recharge, and high drainage potential. Although the F22 fault is a normal fault with a maximum displacement of 550 m, offsetting formations from Seam 3 to the Ordovician limestone, its connectivity and water conductivity are poor, exhibiting significant water-blocking properties. The specific capacity (q) ranges from 1.40 × 10⁻⁴ to 3.26 × 10⁻³ m³/(s·m), and the hydraulic conductivity (K) ranges from 2.10 × 10⁻⁵ to 6.80 × 10⁻⁵. Under deep coal mining conditions, the extraction of coal disturbs the underlying limestone, generally resulting in an increase in its permeability coefficient compared to pre-mining conditions. The permeability coefficient (K) from the measured data before mining impact ranged from 0.000067 to 0.0022, while the simulated values after mining impact ranged from 0.0021 to 0.09. Additionally, mining activities affect the hydraulic head, flow rate, and flow paths of the karst water; the floor karst water is easily drainable, effectively reducing water pressure and the inrush coefficient, thus lowering water hazard risks. Although the mining area is affected by the large F22 fault, its water-resisting properties under sufficient drainage conditions prevent direct connectivity between the coal seam and the aquifer, avoiding water hazards. As global coal resources continue to be exploited, deep mining will inevitably become a common trend in coal extraction worldwide. This study develops a hydrogeological model tailored to deep mining under fault conditions, offering a solid theoretical foundation and practical reference for the prevention and management of mine water hazards on a global scale. This advancement contributes to the development of sustainable mining practices across the global industry. Full article

As coal seams are mined at greater depths, the threat of high water pressure from the confined aquifer in the floor that mining operations face has become increasingly prominent. Taking the Madaotou mine field in the Datong Coalfield as the research object, in the context of mining under pressure, for the main coal seams in the mining area, first of all, an improved evaluation method for the vulnerability of floor water inrush is adopted for hazard prediction. Secondly, numerical simulation is used to conduct a simulation analysis on the fault zones in high-risk areas. By using the fuzzy C-means clustering method (FCCM) to improve the classification method for the normalized indicators in the original variable-weight vulnerability evaluation, the risk zoning for water inrush from the coal seam floor is determined. Then, through the numerical simulation method, a simulation analysis is carried out on high-risk areas to simulate the disturbance changes of different mining methods on the fault zones so as to put forward reasonable mining methods. The results show that the classification of the variable-weight intervals of water inrush from the coal seam floor is more suitable to be classified by using fuzzy clustering, thus improving the prediction accuracy. Based on the time effect of the delayed water inrush of faults, different mining methods determine the duration of the disturbance on the fault zones. Therefore, by reducing the disturbance time on the fault zones, the risk of karst water inrush from the floor of the fault zones can be reduced. Through prediction evaluation and simulation analysis, the evaluation of the risk of water inrush in coal mines has been greatly improved, which is of great significance for ensuring the safe and efficient mining of mines. Full article

Understanding and predicting floor failure depth is crucial for both mitigating mine water inrush hazards and safeguarding groundwater resources. Mining activities can significantly disturb the geological strata, leading to shifts and damage that may result in floor cracks. These disruptions can extend to confined aquifers, thereby increasing the risk of water inrushes. Such events not only pose a threat to the safety of mining operations but also jeopardize the sustainability of surrounding groundwater systems. Therefore, accurately predicting floor failure depth to take effective coal seam floor management measures is the key to reducing the impact of coal seam mining on water resources. Seventy-eight sets of data on coal seam floor failure depth in China were collected, and the main controlling factors were considered: mining depth (D1), working face inclination length (D2), coal seam inclination (D3), and mining thickness (D4). Firstly, the distance evaluation function based on Euclidean distance was constructed as the clustering effectiveness index, and the optimal cluster number K = 3 was determined. The collected data were clustered into three categories using the K-means clustering algorithm. It was found that the clustering results were positively correlated with the size of D1, indicating that D1 played a dominant role in the clustering. The D1 dividing points of the three types of samples were between 407.7~414.9 m and 750~900 m. On this basis, the grey correlation analysis method was used to analyze the order of the influence weights of the main controlling factors of coal seam floor failure depth. For the first group, the order was D2 > D1 > D3 > D4, while, in the other two, it was D1 > D2 > D3 > D4. D1 emerged as the most influential factor, surpassing D2. Therefore, D1 between 407.7 and 414.9 m could be used as the boundary, the first group could be classified as shallow mining, and the second and third groups could be classified as deep mining. Based on this boundary, CatBoost prediction models for the depth of coal seam floor failure in deep and shallow parts were constructed and the prediction results of the model test set were compared with the calculation results of the empirical formula. These models exhibited superior accuracy with a lower mean squared error (MSE) and mean absolute error (MAE) and a higher R-squared (R²) compared to the empirical formula. This study helps to enhance the understanding of coal seam floor behavior, guide floor management, and protect groundwater resources by defining deep and shallow mining to accurately predict floor failure depth. Full article

This study addresses the complex hydrogeological conditions and frequent inrush water incidents in the Donghuantuo coal mine by proposing a novel spectral tracing technique aimed at rapidly and accurately identifying the sources of inrush water. Through the analysis of electrical data from the Donghuantuo mine, the electrical characteristics of the mine floor were examined. Systematic sampling of water from the primary aquifers within the mining area was conducted, followed by detailed spectral measurements, resulting in the establishment of a spectral database for inrush water sources in the Donghuantuo mine. The chaotic sparrow search optimization algorithm (CSSOA) was employed to optimize the key parameters of the random forest (RF) model, leading to the development of the CSSOA-RF spectral tracing identification model. This model demonstrated outstanding classification performance in the test set, achieving an accuracy of 100%. This research offers a novel, more accurate, and reliable method for identifying the sources of inrush water, facilitating the rapid identification of sources in coal-bearing regions of North China and reducing disaster losses. Although the geological structure of the study area is relatively simple, the research achieved significant results in identifying both single and mixed water sources. However, further validation and optimization are needed for its applicability in more complex geological conditions. The findings of this study provide crucial technical support for safe mining operations and hold significant reference value for water hazard prevention in similar regions. Full article

The essence of roof water inrush in coal mines fundamentally stems from the development of water-bearing fracture zones, facilitating the intrusion of overlying aquifers and thereby leading to water hazard incidents. Monitoring rock-fracturing conditions through the analysis of microseismic data can, to a certain extent, facilitate the prediction and early warning of water hazards. The water inflow volume stands as the most characteristic type of data in mine water inrush accidents. Hence, we investigated the feasibility of predicting water inrush events through anomalies in microseismic data from the perspective of water inflow volume variations. The data collected from the microseismic monitoring system at the 208 working face were utilized to compute localization information and source parameters. Based on the hydrogeological conditions of the working face, the energy screening range and its calculation grid characteristics were determined, followed by the generation of kernel density cloud maps at different depths. By observing these microseismic kernel density cloud maps, probabilities of roof water-conducting channel formation and potential locations were inferred. Subsequently, based on the positions of these roof water-conducting channels on the planar domain, the extension depth and expansion direction of the water-conducting channels were determined. Utilizing microseismic monitoring data, a quantitative assessment of water inrush risk was conducted, thereby establishing a linkage between microseismic data and water (inrush) data, which are two indirectly related datasets. The height of microseismic events was directly proportional to the trend of water inflow in the working face. In contrast, the occurrence of water inflow events and microseismic events exhibited a specific lag effect, with microseismic events occurring prior to water inrush events. Abnormalities in microseismic monitoring data partially reflect changes in water-conducting channel patterns. When connected with coal seam damage zones, water inrush hazards may occur. Therefore, abnormalities in microseismic monitoring data can be regarded as one of the precursor signals indicating potential floor water inrushes in coal seams. Full article

Karst water in coal floors is the most common hazard in the coal fields of North China. Water inrush disasters always occur due to reductions in the efficacy of a coal floor’s water resistance ability, and have brought huge casualties and losses. The floor damage zone during mining disturbance is crucial to the formation of the water inrush pathway and is considered to be closely related with floor rock brittleness. To investigate the effects of coal floor brittleness on the hazard of water inrushes from underlying aquifers, four groups of numerical simulations are conducted in this study based on a finite-element method. These numerical simulations especially concern the contrastive analysis of brittle rock’s properties regarding the failure characteristics of rock samples, fracture development in layered rocks, the damage zone of the floor during mining disturbance, and the hazard of water inrush from the floor during mining. The results show that brittle rock is easier to destroy in comparison with ductile rock. Brittle layers are more likely to develop denser natural fractures than ductile layers. The more brittle the floor rock is, the larger the depth of floor damage will be. The brittle floor is verified to induce water inrush from an underlying aquifer more easily than the ductile floor. This study revealed the relationship between the brittle property of coal floors and the depth of mining-induced floor damage zones, providing a reference for hazard evaluation of water inrush from coal floors and control measures. Full article

Based on the complex hydrogeological conditions of the Chensilou mine, numerical simulations and field validation methods were used to study the mechanism of water inrush from the floor of the coal seam, which has faults and cracks, as well as the regional advanced grouting reinforcement technology during the coal mining process. The evolution laws of the roof stress field, displacement field, crack field, and plastic area are revealed at different mining distances. The coupling mechanism of floor water inrush channel formation under complex conditions is analyzed. Advanced grout filling reinforcement technology in the ground area is proposed, the slurry diffusion law of different grouting layers under different grouting pressures is revealed, and the grouting effect is evaluated, which provides a research basis for selecting a reasonable grouting pressure. Finally, the application of regional advanced grouting reinforcement technology was carried out at the site, and the grouting reconstruction effect was verified by the transient electromagnetic and three-dimensional DC resistivity method. The results show that the apparent resistivity of the floor after the grouting reinforcement is high, and the water yield of the verification borehole is less than 10 m³/h. The area where the three-dimensional direct current resistivity is less than 12 Ω·m only appears in the lower part of the middle of the working face, and there is no water in the verification borehole. Through our underground supplementary treatment and verification process, the initial water inflow meets the requirements of being less than 10 m³/h. It indicates that the ground regional advanced treatment project achieved significant results. The results of our research can also provide references for water hazard control in similar mines. Full article

The new Shanghai No. 1 Coal Mine is located in arid and semiarid area of northwest China, which is characterized by scarce rainfall, intense evaporation, and limited water resources. High-intensity coal mining has caused severe damage to groundwater resources. The Baotashan sandstone aquifer of the Jurassic system has abundant water resources, and they are stored in the floor strata of mining coal seams. This poses the risk of high-pressure build-up and water inrush hazards during the mining of coal. To avoid these, the Baotashan sandstone aquifer needs to be drained and depressurized, which can result in a huge waste of water resources. Thus, taking the New Shanghai No. 1 Coal Mine as the basis for the case study, the impact of coal mining on the underground water resources was quantified. Large-scale water release tests were performed under the shaft to determine the hydrogeological properties of the Baotashan sandstone aquifer and a three-dimensional numerical model of the groundwater system was established. The dynamic phenomenon of water drainage was simulated and the drained water discharge was predicted under the condition of safe mining. Full article

The more complex the hydrogeological conditions of a mine, the more likely the coal seam is to experience water inrush during the mining process, and the greater the degree of the water inrush hazard. The scientific and reasonable prediction of water inrush in mines with complex hydrogeological conditions is of great significance to the safe and efficient operation of coal mines. Taking the roof water inrush problem of the No. 3 lower coal seam in the Jisan Coal Mine as the research object, the factors affecting the roof water inrush of the coal seam were comprehensively considered from three aspects: the aquifer property, the mining fracture development and the geological structure. The evaluation index system was constructed by selecting 10 factors, including the aquifer depth and thickness, core recovery rate, brittle–plastic rock thickness ratio, number of water-resisting layers, development height of the water-conducting fracture zone, fault density, frequency density, scale index and variation coefficient of the coal seam floor dip angle. At the same time, based on the dual influence of subjective and objective weighting, the scientific and reasonable weight of each factor was ensured. The AHP-CRITIC composite weighting method was used to calculate the comprehensive weight of each factor. Finally, the roof water inrush risk prediction model was constructed. According to the prediction results, the study area was divided into a low-risk area, medium-risk area and high-risk area. Compared with the actual situation, the prediction results were basically consistent with the actual situation, and the prediction results can provide the basis for the prevention and control of water in a coal mine. Full article

Microseismic monitoring systems have been widely installed to monitor potential water hazards in limestone of the coal floor. The temporal and spatial distribution of rock fracture-induced microseismic events can be used as early warning indicators of potential water inrush from the coal floor. We established a microseismic monitoring system in the working face of Wangjialing coal mine. Besides traditional fluid-independent rock fracture-induced microseismic waveforms, fluid-dependent hybrid-frequency microseismic waveforms also play important roles in determining the microseismic precursors of water inrush. Hybrid-frequency microseismic waveforms have a sharp P wave and no obvious S wave phase. We infer that the first high-frequency signal is caused by the brittleness of the rock in the floor under the influence of the water pressure. The second low-frequency signal is caused by the water oscillations in the fractures. These hybrid-frequency waveforms represent the development of fracturing. In addition, the lifting height of the complete aquiclude above the confined water is very limited, and the water inrush from the floor is often closely related to these hidden faults. Therefore, the activation signal of hidden faults in the working face of coal mining can be monitored to effectively warn about the water inrush from the coal seam floor caused by faults. By analyzing different microseismic events, the monitoring and early warning of water disaster in the coal mine floor can be improved. This will help in taking measures in advance within the mine to ensure personnel safety and to reduce property losses. Full article

Coal-mining areas are widely distributed in Northern China, but are under threat from confined water in the mining operation, resulting in a series of floor water- inrush hazards. Therefore, it is significant to effectively evaluate the floor water inrush to ensure safe and efficient coal mining. The 182602 working face of the Wutongzhuang coal mine served as the background for our research. The concept of “pre-mining microseisms” was proposed, and based on this, microseismic monitoring equipment was arranged on site. The correlation between microseismic events and the water abundance of an aquifer was analyzed, and a floor water inrush evaluation method was constructed based on the three elements of an aquifer and pre-mining microseisms. The main results are as follows: first, the microseismic events were excited by artificial disturbances before the mining of the working face including slurry diffusion and neighboring mining, which had the characteristics of sporadicity, clustering, and periodicity. Second, the regional distribution of water abundance was determined by taking the water inflow, water pressure, and grouting volume as the outward performance characteristics of water abundance in the Shanvuqing aquifer. Furthermore, the correlation coefficient between the pre-mining microseisms and the three elements of the aquifer (water inflow, water pressure, and grouting volume) was larger than 0.7. On this basis, an evaluation method associated with the water inrush risk along the strike of the working face was established based on pre-mining microseisms, dividing the working face into dangerous zones, suspected dangerous zones, and safe zones. Furthermore, pre-mining microseisms, water abundance, and structures were introduced as risk-evaluation indices, and the complete weight was calculated using an analytic hierarchy process and entropy-weight technique, before a vulnerability index model of floor water inrush was built. Finally, targeted treatment procedures were efficiently implemented to ensure the safe mining of working face 182602 due to the successful prediction of potential water risk zones. The research results provide scientific and technological support for pre-mining microseisms combined with water abundance as a technical method to prevent floor water inrush. Full article

Evaluations of the risk of fault-induced water inrush hazard is an important issue for mining engineering applications. According to the characteristics of the seam floor during mining advancing, a mechanical model of fault activation is built to obtain the equations of normal stress and shear stress on the surface of fault, as well as the mechanics criterion of fault activation. Furthermore, using FLAC^3D numerical software, the stress variation on the surface of fault under two different mining advancing directions are numerically simulated, and the distribution characteristics of the plastic failure zone of the roof and floor near the fault are obtained. The results show that: (1) When mining advances from the hanging wall, the normal stress increases more greatly than that from the foot wall, the shear stress distribution changes drastically with a large peak, and it is more likely to cause fault activation. (2) When mining advances from the hanging wall and approaches the fault, the normal stress and shear stress within the fault first increases, and then decreases suddenly. When mining advances from the foot wall, the normal stress and shear stress increases constantly, and the fault zone stays in the compaction state where the hanging wall and foot wall are squeezed together, which is unfavorable for water inrush hazard. (3) When mining advances from the hanging wall, the deep-seated fault under the floor is damaged first, and the plastic failure zone of the floor increases obviously. When mining advances from the foot wall, the shallow fault under the floor is damaged first, and the plastic failure zone of roof increases obviously. (4) For a water-conducting fault, the waterproof coal pillar size of the mining advancing from the hanging wall should be larger than that from the foot wall. (5) The in-situ monitoring results are in agreement with the simulation results, which proves the effectiveness of the simulation. Full article

Grouting is one of the main technical means to prevent water inrush hazards in coal seam floor aquifers. It is of great significance to elucidate the diffusion law of slurry in the process of grouting in fractured aquifers for safe mining in coal mines. In this paper, the mechanism of slurry diffusion in horizontal fractures of fractured aquifers was studied based on the Bingham slurry with time-varying characteristics; additionally, a one-dimensional seepage grouting theoretical model considering the temporal and spatial variation of slurry viscosity under constant grouting rate was established. In this model, the grouting pressure required by the predetermined slurry diffusion radius can be obtained by knowing the grouting hole pressure and injection flow. Slurry properties, fracture parameters, grouting parameters, and water pressure were the parameters affecting the slurry diffusion process. Looking at the problem of water disaster prevention of coal seam floor in the Working Face 2509 of the Chensilou Coal Mine, according to the aquifer parameters and model calculation results, a grouting scheme with a slurry diffusion radius of 20 m and grouting pressure of 12 MPa was proposed. Finally, with the comparative analysis of the transient electromagnetic method (TEM) and water inflow before and after grouting, it was verified that the design grouting pressure and the spacing of grouting holes were reasonable and the grouting effect was good. Full article

Water inrush hazards can be effectively reduced by a reasonable and accurate soft-measuring method on the water inrush quantity from the mine floor. This is quite important for safe mining. However, there is a highly nonlinear relationship between the water outburst from coal seam floors and geological structure, hydrogeology, aquifer, water pressure, water-resisting strata, mining damage, fault and other factors. Therefore, it is difficult to establish a suitable model by traditional methods to forecast the water inrush quantity from the mine floor. Modeling methods developed in other fields can provide adequate models for rock behavior on water inrush. In this study, a new forecast system, which is based on a hybrid genetic algorithm (GA) with the support vector machine (SVM) algorithm, a model structure and the related parameters are proposed simultaneously on water inrush prediction. With the advantages of powerful global optimization functions, implicit parallelism and high stability of the GA, the penalty coefficient, insensitivity coefficient and kernel function parameter of the SVM model are determined as approximately optimal automatically in the spatial dimension. All of these characteristics greatly improve the accuracy and usable range of the SVM model. Testing results show that GA has a useful ability in finding optimal parameters of a SVM model. The performance of the GA optimized SVM (GA-SVM) is superior to the SVM model. The GA-SVM enables the prediction of water inrush and provides a promising solution to the predictive problem for relevant industries. Full article

The stability of underground openings is pivotal to sustainable safe mining in underground coal mines. To determine the stability and tunneling safety issues in 800-m-deep underground openings through large fault zones in argillaceous rocks in the Guqiao Coal Mine in East China, the pilot industrial test, laboratory experimentation, and field measurements were used to analyze the large deformations and failure characteristics of the surrounding rock, the influence factors of safe excavation and stability of underground openings, and to study the stability control countermeasures. The main factors influencing the stability and tunneling safety include large fault zones, high in situ stress, poor mechanical properties and engineering performance of the argillaceous rock mass, groundwater inrush and gas outburst. According to the field study, the anchor-ability of cables and the groutability of cement-matrix materials in the argillaceous rock in the large fault zones were extremely poor, and deformations and failure of the surrounding rock were characterized by dramatic initial deformation, high long-term creep rate, obviously asymmetric deformations and failure, rebound of roof displacements, overall loosened deformations of deep surrounding rock on a large scale, and high sensitivity to engineering disturbance and water immersion. Various geo-hazards occurred during the pilot excavation, including roof collapse, groundwater inrush, and debris flow. Control techniques are proposed and should be adopted to ensure tunneling safety and to control the stability of deep underground openings through large fault zones, including regional strata reinforcement technique such as ground surface pre-grouting, primary enhanced control measures, floor grouting reinforcement technique, and secondary enclosed support measures for long-term stability, which are critical for ensuring the sustainable development of the coal mine. Full article