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Prediction of coal-bearing strata characteristics using multi-component seismic data—a case study of Guqiao coalmine in China

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Abstract

The longwall mining method has been widely used in underground mining of coal seams. For longwall mining, the stability of coal-seam roofs and hardness of coal rocks in coal-bearing strata are particularly important. High-precision multi-component seismic exploration technology can obtain more parameters for characterizing coalbed reservoirs than conventional methods, and it is gradually replacing conventional P-wave technology in coalfield exploration. We have obtained multi-component seismic data from the central mining area of Guqiao Coal Mine, in the Huainan area, China. Using constraints from logging information, and seismic data, joint PP- and PS-wave inversion and interpretation have been performed. The coal seam 13-1, located in a Permian formation, was studied to determine the lithology of the coal-seam roof and floor, evaluate the stability of the coal-seam roof, and determine the hardness of coal rocks in coal seam 13-1. The distribution characteristics of lithology, roof stability, and hardness of coal rocks in coal seam 13-1 were also investigated. To achieve this, we used P- to S-wave velocity ratios to identify the lithology, evaluated the roof stability with parameters LambdaRho and MuRho, and used Young’s modulus to evaluate the hardness of the coal rocks. Our predicted results are in good agreement with the interpretative results from logging information, which shows the accuracy of our method. The joint PP- and PS-wave inversion and interpretation used in this paper can obtain more accurate information for evaluating coalbed reservoirs than conventional methods, which are valuable in assessing mine safety.

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Acknowledgments

We gratefully thank Huainan Mining Group for providing us the research data.

Funding

This research was supported by the National Natural Science Foundation of China (Nos. 41574126, 41425017) and the Fundamental Research Funds for the Central Universities (No. 2-9-2017-452).

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Authors and Affiliations

  1. School of Energy Resources, China University of Geosciences (Beijing), Beijing, 100083, China

    Shu Xiong, Jun Lu & Yun Qin

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  1. Shu Xiong
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  2. Jun Lu
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  3. Yun Qin
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Correspondence to Jun Lu.

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Xiong, S., Lu, J. & Qin, Y. Prediction of coal-bearing strata characteristics using multi-component seismic data—a case study of Guqiao coalmine in China. Arab J Geosci 11, 408 (2018). https://doi.org/10.1007/s12517-018-3767-0

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  • DOI: https://doi.org/10.1007/s12517-018-3767-0

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