A sufficient accuracy of subsidence prediction depends on mathematical model developed and subsidence parameters used in the model. Among many subsidence prediction methods, the influence function method is more fundamentally reliable and flexible for the prediction of mining subsidence. It has become the most widely used method for predicting surface subsidence when an underground coal seam is extracted. However, the final subsidence parameters in the influence function method are empirical and quite different from one area to another, directly affecting the predicted results. For predicting the mining subsidence in northeast coal field of China, the previously developed comprehensive and integrated subsidence prediction model (CISPM) for US coal field was improved by updating the final subsidence parameters, including subsidence factor (a), horizontal displacement factor (b), angle of major influence (β), and offset distance of influence point (d). By incorporating the subsidence parameters into the influence function model, major efforts have been made to derive the parameters and calibrate the model with a case study using the measured data from monitoring stations in the targeted area.

1. Introduction

Based on geographical, cultural and geological factors, the area of coal reserves in China can be divided into six coal fields with certain uniform characteristic for each. (Wang and Zhu, 1992). Northeast coal field is one of them and primarily locates in northeast part of China covering Helongjiang, Jilin, Liaoning provinces and east part of Inner Mongolia. Associated with underground mining activities, the movement and deformation of the overburden strata often cause surface subsidence and even collapse and consequently lead to damage to surface structure and building of the village in local mining area (Liu and Sun, 2009). In this regards, since the 1950s, nearly 200 surface movement observation stations have been established for the purpose of collecting in-situ data related to surface subsidence due to underground mining activities (Liu, 2001). Though a great number of measured data have been obtained, data used for predicting and analyzing surface subsidence was limited to coal mines individually. In order to study the subsidence characteristic of the coal mines in the northeast coal field as whole, the collected data should be sorted and analyzed uniformly and comprehensively.

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