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Acta Geophysica

, Volume 67, Issue 3, pp 825–836 | Cite as

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

  • Mengbo Zhu
  • Jianyuan ChengEmail author
  • Weixiong Cui
  • Hui Yue
Research Article - Applied Geophysics
  • 54 Downloads

Abstract

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.

Keywords

In-seam seismic Love wave Dispersion Bayesian kriging Coal seam thickness Longwall panel 

Notes

Acknowledgements

The authors gratefully acknowledge the financial support from the National Key Research and Development Plan (No. 2018YFC0807804) and the Guizhou Science and Technology Major Project (No. [2018]3003-1). Special thanks are given to the anonymous reviewers for their assistance, comments and suggestions.

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Copyright information

© Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2019

Authors and Affiliations

  1. 1.China Coal Research InstituteBeijingChina
  2. 2.Xi’an Research InstituteChina Coal Technology & Engineering Group CorpXi’anChina

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