A Prediction Method for Surface Subsidence at Deep Mining Areas with Thin Bedrock and Thick Soil Layer Considering Consolidation Behavior

Abstract

Among the various hazards induced by underground coal mining, surface subsidence tends to cause structural damage to the ground. Therefore, accurate prediction and evaluation of surface subsidence are significant for ensuring mining security and sustainable development. Traditional methods like the probability integral method provide effective predictions. However, these methods do not take into account the consolidation behavior of thick soil layers. In this study, based on the principle of superposition, an improved probability integral method that includes surface subsidence caused by rock layer movement and the consolidation behavior of thick soil layers is developed. The proposed method was applied in the Zhaogu No. 2 coal mine, located in the Jiaozuo mining area. Utilizing unmanned surface vehicle measurement technology, it was found that the maximum subsidence values of the two survey lines were 5.441 m and 4.842 m, with maximum subsidence rate of 62.9 mm/day at observation points. Experimental tests have shown that surface subsidence in deep mining areas with thin bedrock and thick soil layers exhibited a large subsidence coefficient and a wide range of subsidence, closely related to the consolidation behavior of thick soil layers. After verification, compared to the probability integral method, the improved probability integral method incorporating soil consolidation showed a 14.7% reduction in average error and a 22% reduction in maximum error. Therefore, the improved probability integral method proposed can be a very promising tool for forecasting and evaluating potential geohazards in coal mining areas.