Study On Mining Subsidence Law Of Ordos Mining Area Based On SAR And Leveling Data

Over the years,the high intensity mining of coal resources has led to an increasing decrease in the reserves of coal resources in the eastern mining area of China,even facing the risk of coal resource depletion.The strategic westward movement of the coal industry has become a significant demand for ensuring national energy security.The western mining area of China are rich in coal resources,and there are many large national coal bases,which are qualified to undertake the important task of the national coal industry strategy to move west.The future development prospects are broad.However,due to the differences in geological and mining conditions in the eastern and western mining areas,the laws of surface movement and deformation caused by mining in the western mining areas are different from those in the eastern mining areas.In order to guide the subsequent development and utilization of coal resources in the western mining areas and the protection of ground structures in the goaf,this thesis takes Yingpanhao coal mine,Zhuanlongwan coal mine,and Shilawusu coal mine in the Ordos Mining Area of Inner Mongolia as the research objects,Carry out research on the monitoring methods of surface subsidence and the laws of surface movement and deformation in the western mining area.Based on the Interferometric Synthetic Aperture Radar(InSAR)technology,combined with leveling data and probability integral method,monitor the surface deformation in the study area,and reveal the laws of surface movement and deformation in the study area.The main research work and achievements are as follows:(1)The geological and mining data of the study area and the measured data from observation stations were analyzed,and the movement and deformation laws along the surface observation lines of each working face were summarized.This thesis sorts out and analyzes the measured leveling data from the ground observation stations at the2101 and 2201 working faces of Yingpanhao coal mine,the 221 up 03 and 221 up 08 working faces of Shilawusu coal mine,and the 23103 working face of Zhuanlongwan coal mine,and draws the dynamic subsidence,inclination and curvature change curves along the surface observation lines of each working face,as well as the dynamic subsidence and subsidence velocity curves at the maximum subsidence point of each observation line,The predicted parameters of the probability integral method for each working face are obtained through inversion.(2)A phase optimization method combining phase linking and non-local mean filter is studied.Based on the phase linking optimization method and the adaptive spatial non-local mean filter phase optimization method,this thesis improves the nonlocal mean filter by introducing structural similarity,and combines the improved filter method with the phase linking optimization method to construct a fusion phase optimization method.It has been verified that the fusion phase optimization method can effectively optimize the phase of Distributed Scatterers(DS)pixel,significantly improving the quality of interferograms,and its phase optimization effect is superior to the eigenvalue decomposition and phase linking methods.Based on this,this thesis adds the fusion phase optimization method to the DS-InSAR process.Based on 54 Sentinel-1A SAR images covering Yingpanhao coal mine from September 2017 to June 2019,the surface deformation information of the study area during this period is obtained.Compared with the leveling data,the correlation coefficient between the two is 0.97.(3)A method for calculating probability integral method parameters of mining area based on distance weighted GWO is studied.This thesis improves the position update equation of the grey wolf to solve the problems of premature convergence and low quality solutions of the classical Grey Wolf Optimization Algorithm(GWO)in solving high dimensional complex multimodal problems.A probability integral parameter calculation method based on distance weighted GWO is constructed.Simulation experiments and practical engineering applications have verified that the results of the method in this thesis are accurate and reliable.Based on this,this thesis uses this method to obtain the probability integral parameters of the 23103 working face in Zhuanlongwan coal mine,and then predicts the complete subsidence basin on the surface of the 23103 working face,making up for the lack of DS-InSAR in monitoring large gradient deformation in the mining area.(4)A whole basin surface subsidence monitoring method combining DS-InSAR and probability integral method is studied.Considering the limitation that the DSInSAR method cannot monitor the large gradient deformation in the central area of a sinking basin,and taking into account the shortcomings of the probability integral method converges too quickly at the edge of the predicting sinking basin and the monitoring accuracy is not high,this thesis proposes a method for monitoring the surface subsidence of the entire mining basin by combining DS-InSAR and probability integral method,and uses this method to obtain a complete sinking basin on the surface of the 221 up 03 working face of Shilawusu coal mine.The joint method uses DSInSAR technology to monitor small gradient deformation at the edge of a sinking basin,while the large gradient deformation near the center of the sinking basin is predicted using probability integral method.Finally,based on the deformation gradient theory,the monitoring results of the two methods are fused according to a certain threshold to obtain a complete surface subsidence basin in the study area.The experimental results show that the combined method can effectively compensate for the shortcomings of a single monitoring method,obtaining a complete subsidence basin on the surface of the mining area,and its overall basin subsidence monitoring accuracy is significantly improved compared to a single method.This thesis includes 80 figures,21 tables,and 92 references.