Gas Outburst Research Articles

Research on Coal and Gas Outburst Risk Warning Based on Multiple Algorithm Fusion

To improve the accuracy of gas outburst early warning, this paper proposes a gas outburst risk warning model based on XGBoost–GR–stacking. The statistic is based on gas outburst data from 26 mines and establishes a data generation model based on XGBoost. The obtained virtual datasets are analyzed through visualization analysis and ROC curve analysis with respect to the original data. If the augmented data has an ROC area under the curve of 1, it indicates good predictive performance of the augmented data. Grey correlation analysis is used to calculate the grey correlation degrees between each indicator and the “gas emission”. The indicator groups with correlation degrees greater than 0.670 are selected as the main control factor groups based on the sorting of correlation degrees. In this study, SVM, RF, XGBoost, and GBDT are selected as the original models for stacking. The original data and virtual data with correlation degrees greater than 0.670 are used as inputs for SVM, RF, XGBoost, GBDT, and stacking fusion models. The results show that the stacking fusion model has an MAE, MSE, and R2 of 0.031, 0.031, and 0.981. Comparing the actual and predicted values for each model, the stacking fusion model achieves the highest accuracy in gas outburst prediction and the best model fitting effect.

Regional outburst prevention technology of pre-drainage gas area in west well area of sihe coal mine

Coal and gas outburst is one of the main factors affecting the safe and efficient production of coal mines. With the increase of mining depth and mining speed, the dynamic phenomena of coal and gas outburst will become more and more serious. Through the study of various outburst prevention measures in the pre-drainage gas area such as surface drilling, bedding (directional) drilling, and cross-layer drilling, combined with the coal seam occurrence and mining technology of the West Mine Area, a feasible regional pre-drainage comprehensive outburst prevention mode suitable for the characteristics of the 3# coal seam in the West Mine Area has been obtained. This mode is based on pre-pumping of surface drilling first, directional long borehole along the reservoir and pre-pumping of cross-zone borehole, which provides reliable guarantee for safe and efficient production in outburst well area.

A theoretical calculation method for critical air velocity to prevent methane draft pressure-caused airflow reversion based on oscillation theory

Methane draft pressure is a secondary disaster for mine ventilation following coal and gas outbursts, which poses a long-term threat to coal mining and workers’ safety. To study the law of methane draft pressure-caused airflow variation, oscillation theory is introduced in this study. The vibration equation is used to deduct the basic equation of airflow oscillation in parallel upward ventilated airways, which regards the entire methane and air as one vibrating object in the loop of the parallel airways. The theoretical critical air velocity to prevent airflow reversion is calculated by the airflow oscillation equation using numerical methods. Furthermore, through dimensional analysis, a formula is given to calculate the critical velocity directly. The theoretical results were compared with experiments and good agreements were obtained, which verifies the rationality of the assumptions in the theoretical deduction process. The conclusion of this study indicates that, in a short time, oscillation theory can be used to predict the critical air velocity to prevent airflow reversion, and be feasible in revealing the essence of methane draft pressure-caused airflow reversion.

Experimental study on the transporting and crushing effect of gas on coal powder during the develop stage of coal and gas outburst in roadway.

In recent years, coal and gas outburst disasters are still occurring and difficult to prevent, seriously endangering the safety of coal mine production. It is well known that the transporting and crushing of outburst coal is the main pathway of energy dissipation during the coal and gas outburst process. However, a consensus regarding how much gas involves in outburst and affects energy dissipation is still lacking. Quantitative study on the gas effect on migration and fragmentation characteristics of outburst coal in restricted roadway space can improve the energy model and guide the prevention and control of gas outburst. In this paper, an improved visual coal and gas outburst dynamic effect simulation experiment system was used to conduct outburst simulation experiments at different gas pressure conditions. The results showed that the movement of outburst coal in the roadway has experienced various flow patterns. In the initial stage of the outburst, under low gas pressure condition, the motion of the outburst coal was dominated by stratified flow. However, as the gas pressure increases, the initial acceleration increases, and the outburst coal mainly move forward rapidly in the form of plug flow. The average velocity at 0.3, 0.5, and 0.8MPa gas pressure condition were 6.75, 22.22 and 35.81m/s, respectively. Gas also has a crushing effect on outburst coal. With increasing gas pressure, the number of coal powder particles of the same mass increased significantly, and the range of the particle size distribution of the particles decreaed, and the median particle size decreased. As the gas pressure increases, the outburst intensity gradually increases, and the total energy involved in the outburst work also increases. However, the energy dissipation pathways are different. At 0.3MPa, the energy dissipation is dominated by crushing energy, which is about six times the ejection energy. As the gas pressure increased to 0.8MPa, the proportion of the ejection energy gradually increases to about twice that of the crushing energy. Under the experimental conditions, 2.71-13.43% of the adsorbed gas involves in the outburst (AGIO) through rapid desorption, and the proportion increases with increasing gas pressure. This paper improves the energy model of coal and gas outburst, which is applicable to risk assessment and prevention of outburst disasters.

An Experimental Study on the Effect of Magmatic Thermal Evolution on the Molecular Structure of Low-Rank Coal

Low-rank coal accounts for over half of China’s proven coal reserves. The possibility of coal and gas outbursts in low-rank coal is higher, especially in the m·agmatic thermal evolution area. The complexity of coal’s molecular structure is one of the reasons for problems during the process of mining operations. Different analysis techniques, including XRD, FTIR and Raman spectroscopy, were used to obtain the molecular characteristics of magmatic thermal evolution coal samples and normal coal samples, so that a comparative study could be carried out to investigate the influence of the magmatic thermal evolution effect on the molecular structure of low-rank coal. The ranges of the aromatic interlayer spacing (d002), average stacking heights (Lc) and stacking layer number (Nave) of the thermally evolved coal samples are 3.41–3.51 Å, 22.76–27.02 Å, and 6.68–7.70, respectively. The ranges of the full width at half maximum ratio (FD1/FG) and the peak integral intensity ratio (ID1/IG) are 2.16–2.19 and 1.55–1.84, respectively. Compared with the normal coal samples, those affected by magmatic thermal evolution have smaller d002, ID1/IG, and FD1/FG values, but larger Lc values. The results indicate that the thermally evolved coal samples have more ordered structures and more developed microcrystalline structure sizes than normal coal samples.

Influence of desorption hysteresis effects on coalbed methane migration and production based on dual-porosity medium model incorporating hysteresis pressure

Desorption hysteresis affects gas mass transfer and migration in coal seams, which is not considered in current dual-porosity medium models, leading to inaccurate assessment and prediction of gas extraction. This study proposed a desorption hysteresis pressure to address this issue of the gas mass transfer in the model. On this basis, two coupled gas migration models, considering (DGMH) and without considering (DGM) desorption hysteresis effects, were developed incorporating mass transfer, gas desorption, gas seepage, and permeability evolution. The models were solved and compared using the finite element method. The results demonstrate that the DGM model yields higher production assessment compared to the DGMH model. This discrepancy can be attributed to the hysteresis effects, which prevent the matrix gas from supplementing the fractures timely after fracture gas flows into the borehole. The DGMH model shows less mass transfer, coal seam permeability, and gas extraction compared to the DGM model. The desorption hysteresis effects are more pronounced in coal seams with higher permeability. In addition, neglecting hysteresis effects when calculating permeability from field gas production data may result in inaccurate values. The hysteresis effects is recommended to be considered in the prediction of coalbed methane extraction, permeability calculation, and risk control of delayed coal and gas outbursts.

Analysis of the Difference of Gas Extraction Quantity from Coal Seam under the Influence of Permeability, Gas Pressure, and Buried Depth of Coal Seam: A Case Study

Gas extraction quantity from coal seam is the key index to evaluating the effect of eliminating coal and gas outbursts. The prerequisite for increasing the gas extraction quantity and improving the effect of gas control is to make clear the influencing factors of gas extraction. The main factors affecting gas extraction are permeability, gas pressure, and buried depth of coal seam in this paper. The qualitative and quantitative analyses of gas extraction quantity by three factors are carried out according to the test data. The research results show that: (1) In the areas with high permeability and gas pressure, the gas extraction volume shows random characteristics, indicating clear regional differences. (2) The increase of buried depth of coal seam will reduce the fluctuation of gas extraction quantity, resulting in a lower extreme value of gas extraction quantity. The possibility of gas extraction at a lower level will be significantly increased. (3) The correlation analysis shows the change law of the positive correlation coefficient between gas extraction quantity, gas pressure, and permeability, and shows the opposite trend with the increase of the buried depth of coal seam. The results show an important guiding significance for improving the efficiency of gas control.

Prevention and Control of Coal and Gas Outburst by Directional Hydraulic Fracturing through Seams and Its Application.

The regionalized pressure relief, permeability enhancement, and outburst prevention of "three high and one low" coal seams with high gas, high ground stress, high outburst risk, and low permeability have become important problems to be solved urgently in realizing the sustainable development of coal mines. In this study, a combination of theoretical research, RFPA2D-Flow numerical simulation, and field test was used to study the initiation mechanism and propagation law of directional hydraulic fracturing fractures through the seam. The results show that fracture initiation depends on the axial and radial horizontal stress of the fracture hole, the physical and mechanical properties of coal and rock, and the inside of the weakest layer. Single-hole hydraulic fracturing can achieve a pressure relief radius of 7-8 m, but there is a stress concentration zone outside, which is not conducive to regional pressure relief and permeability enhancement. Directional hydraulic fracturing with multiple holes produces an approximate cylindrical compression and crushing ring and a penetrating fracture surface along the center line of the pressure crack hole and the directional hole, which better eliminates the phenomenon of stress concentration in nondirectional hydraulic fracturing. The technology was applied to the 2238 auxiliary roadway of Chengzhuang Mine of Jinmei Group, and the field implementation results showed that field implementation results showed that directional hydraulic fracturing through the seam reduced the gas content in the coal seam to a great extent, and the coal seam gas content was reduced by about 42.3%, indicating that the technology can effectively reduce the risk of coal and gas outbursts.

Nano-scale pore distribution characterisation of coal using small angle X-ray scattering

In the process of coal seam fracturing with liquid nitrogen (LN2), the change of coal pore structure has an important influence on the efficiency of coalbed methane (CBM) extraction. The nano-scale pore size distribution (PSD) in coal particles before and after freezing with LN2 are experimentally studied in this work. Coal samples are collected from four coal mines, where coal and gas outburst accidents have occurred. Small angle X-ray scattering technology (SAXS) and scanning electron microscopy (SEM) are used to study the pore structure changes of coal samples quantitatively and qualitatively. It is found that the scattering intensity of coal samples increases after freezing. The PSD of all samples significantly changes in the range of 0.8–7 nm, showing new pore spaces in 0.8–4 nm and fewer pores in the 4–7 nm range. Both the pore fractal dimension and the radius of gyration of coal samples increase after freezing and are mainly affected by the changes in pores and the anisotropy of the coal matrix. Crack expansion and pore connections are observed in the surface structure of the coal sample using SEM. This study provides a better understanding of the nano-scale mechanism of coal seam fracturing with LN2 for the prevention of coal and gas outbursts.

In-situ gas contents of a multi-section coal seam in Sydney basin for coal and gas outburst management

The gas content is crucial for evaluating coal and gas outburst potential in underground coal mining. This study focuses on investigating the in-situ coal seam gas content and gas sorption capacity in a representative coal seam with multiple sections (A1, A2, and A3) in the Sydney basin, where the CO2 composition exceeds 90%. The fast direct desorption method and associated devices were described in detail and employed to measure the in-situ gas components (Q1, Q2, and Q3) of the coal seam. The results show that in-situ total gas content (QT) ranges from 9.48 m3/t for the A2 section to 14.80 m3/t for the A3 section, surpassing the Level 2 outburst threshold limit value, thereby necessitating gas drainage measures. Among the gas components, Q2 demonstrates the highest contribution to QT, ranging between 55% and 70%. Furthermore, high-pressure isothermal gas sorption experiments were conducted on coal samples from each seam section to explore their gas sorption capacity. The Langmuir model accurately characterizes CO2 sorption behavior, with fit coefficients (R2) greater than 0.99. Strong positive correlations are observed between in-situ gas content and Langmuir volume, as well as between residual gas content (Q3) and sorption hysteresis. Notably, the A3 seam section is proved to have a higher outburst propensity due to its higher Q1 and Q2 gas contents, lower sorption hysteresis, and reduced coal toughness f value. The insights derived from the study can contribute to the development of effective gas management strategies and enhance the safety and efficiency of coal mining operations.

Research and Application of Comprehensive Early Warning System for Coal and Gas Outburst

Coal and gas outburst is an extremely complex dynamic phenomenon in the production process of coal mines. In order to further accelerate the intelligent construction of coal mines, taking Xinjing Coal Mine as an example, the online comprehensive analysis and warning indicator system and rules for coal and gas outburst applicable to Xinjing Coal Mine were studied, and a comprehensive warning system for coal and gas outburst in Xinjing Coal Mine was established. Through on-site application, it has been shown that the system has achieved real-time intelligent warning of the danger of outburst in the working face, standardized and dynamic management of outburst prevention information in the working face, as well as real-time dynamic update and sharing of outburst prevention information, improving the efficiency of mine outburst prevention management and the level of mine safety.

Experimental Study on the Determinant Factors and Energy Criterion of Coal and Gas Outbursts.

A series of coal and gas outburst tests were conducted on coal seams in north China to determine the important order of gas pressure, in situ stress, and coal strength during coal and gas outbursts. And the typical phenomena of coal and gas outbursts were investigated. In addition, improved outburst energy equations were built to study the coal energy evolution process during coal and gas outbursts. The results show that the coal strength has the strongest influence on coal and gas outbursts, followed by the gas pressure and the in situ stress. The weights of pulverized coal with a particle size of less than 0.28 mm are consistent with the changing trend of the total weights of the pulverized coal particles in the corresponding outburst interval. Furthermore, the results suggest that the gas pressure monitored by the sensors close to the outburst hole begins to drop first and lasts for the longest time. The outburst coal presents obvious fracture and pulverization damage characteristics, and the pulverization damage features of the coal near the outburst hole are more obvious. In addition, the improved outburst energy equation was established, and the rationality of the improved outburst energy equation was verified by using the outburst orthogonal simulation experimental data and the on-site outburst accident cases. The results of this experiment have important guiding significance for preventing and controlling the occurrence of coal and gas outbursts and ensuring safe and efficient mining of coal mines.

A novel combined intelligent algorithm prediction model for the risk of the coal and gas outburst

The mechanism of coal and gas outburst disasters is perplexing, and the evaluation methods of outburst disasters based on various sensitive indicators often have some imprecision and fuzziness. With the concept of accurate and intelligent mining in coal mines proposed in China, selecting quantifiable parameters for machine learning risk prediction can avoid the deviation caused by human subjectivity, and improve the accuracy of coal and gas outburst prediction. Aiming at the shortcomings of the support vector machine (SVM) such as low noise resistance and being prone to be influenced by parameters easily, this research proposed a prediction method based on a grey wolf optimizer to optimize the support vector machine (GWO-SVM). To coordinate the global and local optimization ability of the GWO, Tent Chaotic Mapping and DLH strategies were introduced to improve the optimization ability of the GWO and reduce the local optimal probability. The improved prediction model IGWO-SVM was used to predict the coal and gas outburst. The results showed that this model has faster training speed and higher classification prediction accuracy than the SVM and GWO-SVM models, which the accuracy rate reaching 100%. Finally, to obtain the correlation between the parameters of the coal and gas outburst prediction parameters, the random forest algorithm was used for training, and the three parameters with the highest feature importance were selected to rebuild the data set for machine learning. The accuracy of the IGWO-SVM outburst prediction model based on Random Forest was still 100%. Therefore, even if some prediction parameters are missing, the outburst can still be effectively predicted by using the RF-IGWO-SVM model, which is beneficial for the model application and underground safety management.

Evolution from gas outburst to coal outburst: An analysis from the perspective of asynchronous transfer difference of gas mass and coal deformation

Considering that coal and gas outburst is a highly complex nonlinear process, the synchronous energy criterion based on the gas expansion energy and the coal deformation potential energy is often adopted to evaluate the hazard. However, the synchronous energy criterion without considering the transfer difference of gas mass and coal deformation has defects in describing the evolution characteristics of coal-rock gas dynamic disasters. Hence, it is necessary to investigate the asynchronous characteristics of the gas expansion energy and the coal deformation potential energy. In this study, the deformation characteristics of coal injected with He and CH4 were measured respectively with the aid of a self-developed device for observing the asynchronous characteristics of effective stress and adsorption-induced deformation. Besides, the differentiated propagation characteristics of gas pressure and adsorption-induced deformation were obtained, and the asynchronous propagation starting point and propagation rate difference between them were analyzed and determined. Furthermore, based on the calculation formula of gas expansion energy and coal deformation potential energy, the values and propagation differences of the two types of energy at different times were revealed. Finally, the typical outburst phenomena were explained using the energy asynchronous theory. The following research findings were yielded. The adsorption-induced expansion process lasts longer than the gas pressure reduction process, which is the reason for asynchronous propagation of gas expansion energy and coal deformation potential energy. The coal deformation potential energy can be further divided into mechanical compression strain energy and desorption shrinkage strain energy. In the initial stage of outburst, the main sources of energy are free gas expansion energy and mechanical compression strain energy. As time progresses, the effect of desorption gas expansion energy and desorption shrinkage strain energy gradually strengthens. From the perspective of energy asynchrony, outburst occurrence at a low gas concentration in deep regions and delayed outburst in cross-cut coal uncovering can be explained as the result of dynamic load instability in surrounding stopes brought about by lagging superimposed deformation disturbances after gas desorption, or the result of self-induced lagging shrinkage deformation formed under special boundary conditions. The findings of this study are helpful to guide the design and connection of the prevention and control methods of deep coal-rock gas dynamic disasters.

Coal and Gas Outburst Risk Assessment Using Cluster Analysis Method

Mining has historically been known as a high-risk industry. Coal and gas outbursts are one of the most significant accidents that occur in underground coal mines. Despite many years of research, the resources and mechanisms of this phenomenon are not well understood. Thus, it is difficult to forecast and control these events. As the mining depth and density increase, initial gas pressure and gas content of coal seams continue to increase, and the risk of explosion increases. Hence, explosion-prone areas expand gradually. As a result, a dynamic phenomenon has emerged in areas where there is no danger of outbursts. The risk of outbursts becomes more and more serious in coal mines. A coal outburst risk assessment includes evaluating the risk factors to what degree are present and then determining the risk areas of the mine. In this study, the Cluster Analysis method was implemented to identify the risk level of coal seams based on the evaluation of the outburst risk factors for an underground coal mine. Coal and gas outbursts occurring in Zonguldak hard coal basin were divided into two clusters, Cluster A and Cluster B. Coal seams in Cluster A were determined riskier than Cluster B coal seams.

A dynamic model of coalbed methane emission from boreholes in front of excavation working face: numerical model and its application.

China's current energy consumption is primarily fueled by coal, increasing coal mining with growing energy demand. Coal and gas outburst accidents are common problems in coal mining, and prediction methods are fundamental for preventing such accidents. The gas emission characteristics of boreholes are a combination of comprehensive coal properties and coal seam gas occurrence status; thus, the accurate prediction of gas emissions from boreholes is crucial for preventing such hazards. This paper presents a method for measuring the gas flow rate in continuous boreholes, which is used to predict outburst danger in front of the working face. The model was compared with field measurement data and found suitable for research. The effects of different initial gas pressures, different borehole radius, and different burial depths on gas emissions from boreholes were studied. The results showed that (1) initial gas pressure is the main influencing factor of gas gushing. The amount of gas emission during drilling and the attenuation of gas pressure are more sensitive to pressure. An increase in gas pressure considerably increases the amount of gas gushing out of drilling holes. (2) The increase in the drilling radius increases the generation of coal cuttings, the area of the drilling hole wall, and the degree of damage to the drilling hole wall. Consequently, the amount of gas gushing out of the drilling hole increases. (3) In situ stress occurs mainly because of the increase in gas pressure with an increase in burial depth and the increase in gas desorption caused by the increase in damage to the borehole wall. This study provides a new outburst prediction method, which involves identifying outburst hazards through the gas gushing out of the borehole. The results are expected to aid the control of underground coal and gas outbursts and ensure the safe production of coal mines.

Comprehensive Gas Prevention and Control Technique for Mining the First Seam in Short-Distance Outburst Coal Seam Groups.

Coal and gas outbursts are a phenomenon whereby broken coal and gas suddenly erupt from the coal body into the mining space under pressure. The Diandong mining area is a group of close-range outburst coal seams in which the gas content is up to 20 m3/t and gas pressure can reach 3 MPa. Research has been conducted on engineering challenges such as advanced detection and prevention of interlayer excavation in close-range coal seam groups, improvement of gas extraction quality and efficiency in low-permeability coal seam groups, and traceability and evaluation of joint extraction of coal seam groups. Through this study, advanced detection technology with full coverage in front of the excavation working face has been constructed as well as advanced pre-extraction technology for adjacent coal seams and this coal seam in ultraclose layers. We have developed a method for achieving the standard of cross-layer fixed-point hole expansion and permeability enhancement for the first mining of coal seams in a coal seam group. A combined process of graded enhanced pre-extraction and segmented regulation and extraction was proposed, which included "fixed-point control section sealing pre-extraction of coal seam groups and secondary sealing and extraction of mining pressure relief orifice."

Effect of Desorption Damage on the Kinetic Characteristics of Coal Particle Gas Desorption.

There is a positive feedback mechanism of desorption, pulverization, and redesorption in the process of coal and gas outburst. The coal pore structure changes to some extent in the process of coal pulverization and has a related impact on the dynamic parameters of coal particle gas desorption. To understand the impact of desorption damage on the dynamic characteristics of coal particle gas desorption, in this paper, a self-developed coal particle gas desorption test device is used to measure the amount of methane desorption of different coal samples repeatedly desorbed under the same adsorption equilibrium pressure. The results show that the methane desorption kinetic curves of the four coal samples based on desorption damage basically have the same trend. Nie's diffusion model can better describe the methane desorption characteristics of coal particles. After desorption, the methane desorption amount, initial desorption velocity, diffusion ability, and ultimate amount of methane desorption of the coal samples are greater than those before desorption. The desorption damage affects the relevant dynamic parameters of the coal particle gas diffusion model, and its impact on the outburst coal is greater than that on raw coal. In addition, the pore size distribution and change characteristics of the coal samples before and after desorption are analyzed quantitatively via a low-temperature liquid nitrogen adsorption test and fractal dimension-related theory. It was found that the pore volume peak area of the coal samples affected by desorption damage within each pore size range was significantly larger than that before desorption. Among them, micropores have the most significant impact on the desorption damage of coal samples, and the peak area of the pore volume of protruding coal is greater than that of raw coal, indicating that the internal pores of coal after desorption damage are more developed than those of raw coal.

Coal and Gas Outburst Prediction Model Based on Miceforest Filling and PHHO–KELM

Coal and gas outbursts are some of the most serious coal mine disasters, and effective prediction of coal and gas outbursts can reduce the likelihood of accidents and fatalities. Previously conducted studies have established that machine learning has achieved results in the prediction of coal and gas outbursts, but there is a problem that the available accident data of coal and gas outbursts are diminished or missing. This paper proposes a prediction model based on multiple filling of chained equations for random forests (miceforest) and the Harris Hawk optimization algorithm with Piecewise chaos mapping (PHHO) to optimize the kernel extreme learning machine (KELM) to solve the problem of missing data in coal and gas outburst prediction and to improve prediction accuracy in the case of missing data. Firstly, the miceforest algorithm was adopted to fill missing values in the salient samples, and then the PHHO algorithm was used to optimize the parameters of KELM. Finally, the datasets before and after filling were input into the PHHO–KELM model for experimentation and comparison with other models. The results show that miceforest filling is effective in improving the salient sample accuracy and overall accuracy of predictions, but the improvement is not significant for non-salient samples. The use of the PHHO–KELM model can effectively avoid falling into a local optimum and further improve the prediction accuracy of the KELM algorithm. The salient sample accuracy and overall accuracy of the miceforest–PHHO–KELM model prediction are 96.77% and 98.50%. And an effective coal and gas outburst model has been proposed, which is the miceforest–PHHO–KELM model.

Risk Assessment of Compound Dynamic Disaster Based on AHP-EWM

The coal mine in deep mining can easily form a compound dynamic disaster with the characteristics of rock burst and gas outburst. In this paper, the analytic hierarchy process (AHP) and the entropy weight method (EWM) are combined, and the fuzzy comprehensive evaluation (FCE) secondary evaluation model of compound dynamic disaster is proposed to evaluate the risk of compound dynamic disaster, which avoids the problems of the imperfect evaluation index system and strong subjectivity of index weight. Based on the statistical analysis of typical compound dynamic disaster cases in China, three first-level indicators were established, and sixteen second-level indicators were developed. The verification results show that the accuracy and weight are better than the traditional evaluation methods. Combined with geological and mining data, the compound dynamic disaster risk assessment was carried out on the second mining area of mine B, in the Pingdingshan mining area, and the result was grade II (weak risk). Corresponding prevention measures and parameters were implemented, and no compound dynamic disaster occurred during the working face excavation.