Abstract

Determining the geographic location and spatial distribution of underground goaf is of great significance for the prevention of mining subsidence hazards and the detection of illegal mining. However, traditional goaf detection techniques mainly focus on geophysical methods that are labor intensive, have low efficiency, and are expensive. Due to the large range and off-site monitoring capability of interferometric synthetic aperture radar (InSAR) techniques, research on goaf location detection based on InSAR measurements has been increasing. This paper proposes a new method for locating underground goaf based on cross-iteration and InSAR measurements. Firstly, the functional relationship between the geometric parameters of the goaf and the line of sight (LOS) deformation retrieved by InSAR techniques is constructed. Then, the three initial model parameters of the probability integration method (PIM) are determined by mining geological conditions. Finally, the cross-iteration method is used to determine the parameters to characterize the spatial location of underground goaf. The experimental results show that the average relative errors of the simulated experiment and the real experiment are 1.5% and 5.1%, respectively, and the inverted goaf parameters are in good agreement with the real values. Moreover, the proposed method only requires the main lithology of the overlying rock in the goaf and does not depend on the accuracy of PIM model parameters. Therefore, this method has engineering application value for the detection of goaf lacking actual measurement data or that caused by illegal mining.

Highlights

  • Underground coal mining is the main way to obtain coal resources

  • We found that the horizontal displacement constant b had a greater impact on the coal seam mining height m than other initial model parameters, and the subsidence factor q and tangent of major influence angle tan β had a greater impact on the dip angle α than the horizontal displacement constant b

  • This paper proposes a cross-iteration method to determine the spatial location of the underground goaf

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Summary

Introduction

The underground cavities formed by the mining of coal seams are called goafs. With the large-scale mining of coal, a large number of unknown goafs mainly caused by illegal mining activities have been generated in the world. The destruction or loss of ancient coal seam mining records make it difficult to know the actual situation of many abandoned goafs. These unknown goafs may endanger people’s lives and property and destroy surface infrastructure, and cause landslides, surface subsidence, and other geological disasters. Determining the geographic location and spatial distribution of underground goafs is of great significance for the early warning and management of geological disasters

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