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Periods of refracted P waves in coal seams and their applications in coal thickness estimations

Liu Zuiliang, Wang Ji

Acta Geophysica

2020

Vol. 68, no. 6

1753--1762

The direct and accurate estimations of coal thicknesses are prerequisites for intelligent mining practices. One of the most efective 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 refection of the P-waves between the coal and rock interfaces of roof and foor 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 diferent 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 identifed and processed. Overall, the proposed method was found to be a simple application process for accurate coal thickness estimations.

Comprehensive prediction of coal seam thickness by using in‑seam seismic surveys and Bayesian kriging

Zhu Mengbo, Cheng Jianyuan, Cui Weixiong, Yue Hui

Acta Geophysica

2019

Vol. 67, no. 3

825--836

Quantitative determination of the coal seam thickness distribution within the longwall panel is one of the primary works before integrated mining. In-seam seismic (ISS) surveys and interpolations are essential methods for predicting thickness. In this study, a new quantitative method that combines ISS and Bayesian kriging (BK), called ISS–BK, is proposed to determine the thickness distribution. ISS–BK consists of the following six steps. (1) The group velocity of Love waves is plotted by using the simultaneous iterative reconstruction technique under a constant frequency value. (2) An approximate quantitative relationship between the thickness and the group velocity is fitted based on sampling points of the coal seam thickness, which are measured during the process of entry development. (3) The group velocity map is translated into a primary thickness map according to the above-mentioned fitted equation. (4) By subtracting the ISS prediction result from the actual thickness at a sampling point, the residual variable is created. (5) The residual distribution is interpolated within the whole longwall panel by applying BK. The residual map establishes the interconnection between the ISS survey and BK. (6) A refined thickness distribution map can be obtained by overlapping the primary thickness map and the residual map. The application of this method to the No. 2408 longwall panel of Yuhua Coal Mine using ISS–BK showed a considerable improvement in thickness prediction accuracy over ISS. The residuals of ISS and ISS–BK mainly lie in the intervals (− 3.0, 3.0 m) and (− 1.0, 3.0 m), respectively. The accurate prediction rates [where the residual lies in the interval (0, 0.1 m)] of ISS and ISS–BK are 9.39% and 50.28%, respectively, and the effective prediction rates (where the residual is less than 1.0 m) of ISS and ISS–BK are 61.88% and 77.90%, respectively. All the above statistics reflect a considerable improvement in the ISS–BK method over the ISS method.