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Research on surface deformation characteristics and mining be-havior of multi-coal seam mining based on InSAR technology

InSAR; 3D decomposition; deformation monitoring; goaf; multi-seam mining; finite element

With the increasing demand of coal resources, multi-coal seam mining is more and more common, and the geological disasters caused by it are more and more serious. Consequently, this study leverages advanced Small Baseline Subset (SBAS) InSAR technology alongside finite element numerical simulations. Focused on the mining operations and surface alterations of the Fa'er coal mine spanning from February 2017 to September 2020, our investigation delves into the nuances of vertical surface deformation. Through this analysis, we elucidate the dynamics of surface movements and undertake a comprehensive inversion analysis of mining processes. Our findings underscore the efficacy of employing time-series InSAR coupled with two-dimensional decomposition techniques, yielding a remarkable improvement in surface deformation monitoring accuracy with a negligible error rate of 1.5%. Furthermore, the inversion of the vertical deformation field unveils a progression in the surface movement basin expansion, transitioning gradually from horizontal expansion to vertical subsidence. Notably, in the third mining area, characterized by shallow coal seam burial depths, extensive goaf ranges, concentrated distribution of goafs, and the extraction of multiple coal seams, we observed maximum subsidence reaching 448mm, accompanied by a peak deformation rate of 135mm/year. To mitigate the limitations of InSAR in surface deformation monitoring, we employ finite difference simulations to model the mining area and invert the underground mining processes. The comparison of mining simulation outcomes with InSAR monitoring results reveals strikingly similar overall trends, validating the feasibility of mining simulation in tracking evolving surface deformations and overlying rock displacements. The insights gleaned and results obtained from this study hold profound implications for the assessment and prediction of disasters in mined-out areas across China.