Study on the gas outflow pattern and outflow prediction model of the return mining face under complex geological conditions.

Abnormal gas emissions at the mining face under intricate geological conditions pose significant challenges to coal mine safety and operational efficiency. To explore the impact of fault structures on gas migration in mining areas, a two-dimensional geological framework incorporating fault features was established using COMSOL Multiphysics software. Simulations were conducted to analyze gas movement at different proximities to the fault, identifying key factors that affect gas dispersion in mining environments with complex geological characteristics. A predictive model was subsequently developed by integrating fault-induced gas migration effects. The findings reveal that as the mining face advances to nearly 100 m from the fault, the surrounding stress intensifies to about 21 MPa, creating a pronounced stress concentration. At a distance of approximately 50 m from the fault, the stress concentration becomes even more severe than at 100 m, with stress levels reaching nearly 39 MPa, approximately double that at 100 m. Additionally, within the initial 10 m of the mining face, a region of high gas concentration is observed. At 50 m from the fault, gas pressure is about 20% higher than at 100 m, while gas migration velocity is approximately 2.4 times greater. As the coal seam near the fault exhibits increased gas occurrence, the coal structure becomes more fractured with proximity to the fault, further intensifying gas outflow at the mining face. A comparative assessment of the KPCA-WOA-BP neural network model against the BP, ACO-BP, and FA-BP models demonstrated their respective average relative errors as 22.46%, 9.66%, 5.64%, and 2.84%. The proposed model exhibited superior predictive accuracy and computational efficiency, making it a reliable tool for forecasting gas emissions at the mining face under complex geological conditions.