A Novel Analytical Model of Mining Subsidence Considering Time Effect Based on the Probability Integral Theory

Abstract

Surface subsidence caused by underground coal mining has received wide attention due to its impact on the ecological environment. To obtain first-hand data on mining subsidence, we arranged line measurement stations in the mining area of the Weiqiang coalfield and implemented surface movement observation at its first mining working face and obtained the dynamic subsidence curve. The subsidence curves reflected the initial, active and declining stages of subsidence at each measurement point at a basic level, and were consistent with the general rule of surface subsidence. To accurately analyze the surface movement caused by coal mining, based on the probability integral method and considering the actual advancement progress of the working face, a new three-dimensional dynamic prediction model, namely the strip unit mining model, was proposed. The core assumption of this model was that the longwall mining is regarded as the result of superposition of many units of mining. Considering the influence of different mining times and periods after mining, the subsidence time function of two-time factors was introduced into the strip unit mining model, and the final formulation of the dynamic subsidence prediction of the three-dimensional surface is derived by considering the time factor. Based on the analysis of the measured data of the Weiqiang coalfield, the prediction parameters of surface movement were obtained, and the surface movement and deformation are predicted via the probability integral method. Finally, the measured surface subsidence was compared with the theoretically-predicted one. The good match showed that the parameters of the probability integral method, determined according to the measured data, meet the requirements of geological conditions and mining settings in the mining area, and the predicted subsidence curves agreed well with the field measurements, demonstrating the effectiveness of the newly-developed strip unit mining model.