Abstract

Land subsidence is generally caused by stress concentration of the overlying strata, which may reach the rock failure limit, causing surface collapse. The Liaohe Plain is an important resource producing area in China. Concentrated exploitation of underground resources leads to the generation of underground cavities, and surface subsidence gradually occurs as cavities increase. We used small baseline subsets synthetic aperture radar interferometry to monitor large-scale surface deformation on the Liaohe Plain. Field investigations found that the spatial distribution of land subsidence on the Liaohe Plain is highly correlated with coal mining areas. Taking the interferometric synthetic aperture radar deformation as the real constraint, a nonlinear Bayesian inversion algorithm was used to reconstruct underground reservoir parameters, such as the position and attitude of underground coal seams, based on a multi-source dislocation model. The R2 between observed and modeled deformation in multiple coal mining areas was above 0.9. On this basis, relying on the Coulomb failure stress (CFS) criterion, the elastic model parameters and regional geological data were used to calculate the stress field caused by underground resource exploitation on the ground surface. The results show that the CFS fields of multiple groups of coal seams at close distances have mutual influence, and it is more concentrated at the perimeters than in the central portions of the subsidence area. The proposed dislocation model of closely spaced multiple coal seams improved the inversion accuracy of complex mining conditions, and would provide important information for risk assessment and prevention from the perspective of geodesy.

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