Abstract
The stability of flooded coal pillars has long been a challenging issue in coal pillar research, especially during the recovery of production after water inrush disasters. Due to the harsh on-site conditions, it is difficult to directly collect samples for analysis, which brings numerous challenges in both design and production. Based on the engineering background of the 1314 working face of Xiaoyun Coal Mine, this paper proposes a clustering optimization algorithm and successfully uses microseismic data collected on-site to identify the boundary of the flooded coal pillar, validating the results through simulation comparisons. The study found that the flooded state within the coal pillar can be classified into saturated flooded zones, unsaturated flooded zones, and dry zones. The characteristics of the flooded coal pillar during the early stage of mining are more complex, with irregular variations in the flood boundary and local phenomena of sudden changes. Through the analysis of stress and delamination data, the primary controlling factors of this phenomenon are identified and the causes are explained. The research not only demonstrates the feasibility of using microseismic data to identify the flooding status of coal pillars but also provides valuable insights for analyzing the flooded state of coal pillars during the recovery of production after water inrush incidents. This study, particularly regarding coal pillar monitoring and safety control, presents new challenges.