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

Acta Geophysica

Weixiong Cui¹  Mengbo Zhu²  Hui Yue²  Jianyuan Cheng³ 

[1] Engineering Group Corp;China Coal Research Institute;China Coal Technology &

关键词: In-seam seismic;    Love wave;    Dispersion;    Bayesian kriging;    Coal seam thickness;    Longwall panel;   

DOI  :  10.1007/s11600-019-00298-y

学科分类：地球科学(综合)

来源: Polska Akademia Nauk * Instytut Geofizyki

【 摘 要 】

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.

【 授权许可】

Unknown