Abstract

The direct and accurate estimations of coal thicknesses are prerequisites for intelligent mining practices. One of the most effective methods for detecting the distributions of coal thicknesses in coal mining panels is the in-seam seismic (ISS) method. In the present study, after examining the formation processes and propagation characteristics of refracted P-waves in ISS data, it was concluded that the refracted P-waves in coal seams are mainly formed by the multiple transmission and reflection of the P-waves between the coal and rock interfaces of roof and floor at critical angles. This results in the refracted P-waves having strong periodicity, and these periods are proportional to the coal thicknesses. This study adopted numerical simulation models with different coal thicknesses, and the aforementioned periodicity characteristics were examined. It was found that the coal seam thicknesses could be calculated using the periods of the refracted P-waves. However, in thin- or medium-thick coal seams, it was found that multiple transmitted P-waves overlapped and the periods could not be read directly. Therefore, in order to solve this problem, this study composed source wavelets with the main frequency of the source signals and then composite synthetic P-waves by convoluting the source wavelets with the sequences of various coal thicknesses. The suitable estimated coal thickness corresponded to the minimum value of the errors between the synthetic and actual refracted P-waves. An experiment was conducted in the No. 42224 panel of the Chaigou Coal Mine in order to validate the proposed method. The experimental results revealed that the estimated coal thicknesses from the refracted P-waves were consistent with the actual geologic conditions in the coal mine. Due to the fact that the refracted P-waves arrive earlier than other waves in seismic records, the refracted P-waves could be easily identified and processed. Overall, the proposed method was found to be a simple application process for accurate coal thickness estimations.

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