A Method for Predicting Surface Subsidence in Closed Mine

Abstract

A method for predicting surface subsidence in closed underground mines is suitable for use in underground coal mines. Using InSAR technology to obtain the surface subsidence of closed underground mines; constructing a prediction model of surface subsidence in closed underground mines; inverting model parameters based on InSAR monitoring results; predicting methods for surface subsidence of closed underground mines. It has the advantages of high prediction accuracy, few model parameters, simple process operation, easy realization, and high technical content. It is the first time to propose a prediction model for surface subsidence in closed underground mines, which fills the gap in the prediction of surface subsidence after mine closure, and extends the existing The theoretical and technical framework of mining subsidence provides technical means for the prediction of surface subsidence after mine closure.

Description

technical field [0001] The invention relates to a method for predicting surface subsidence in closed underground mines, and is particularly suitable for a method for predicting surface subsidence in closed underground mines in which a surface subsidence prediction model for closed underground mines is combined with InSAR monitoring results. [0002] technical background [0003] With the continuous development of my country's coal resources (especially the high-intensity mining of the golden decade), the reserves of some mines have declined sharply, forming resource-depleted coal mines, and some mines do not meet the requirements for safe production, or have high mining costs and serious losses. closed or obsolete. In particular, the coal production capacity reduction policy implemented in recent years has prompted the closure of a number of mines and open pits due to the withdrawal of excess production capacity, resulting in a large number of closed / abandoned mines. After th...

AI Technical Summary

Problems solved by technology

Because the model parameters of the surface subsidence prediction model in closed mines are seriously affected by hydrogeological mining conditions, rock lithology, mining overlying rock structure, and geological structure, it is difficult to determine the appropriate model parameters in actual use

Moreover, traditional deformation monitoring technologies (such as leveling, GNSS, 3D laser scanning, total station, etc.) have low coverage of deformation space and low sampling density, and the inversion model parameters have relatively large limitations.

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