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Resistivity imaging technique to delineate shallow subsurface cavities associated with old coal working: a numerical study

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Abstract

Subsidence is an environmental hazard due to subsurface cavities associated with abandoned coal workings in the Eastern Indian coalfields. These cavities pose danger to coal mining of deeper coal seams. Most of these subsurface cavities are unapproachable as no mine plans are available. Here, an attempt has been made to detect and possible delineation of air and as well as water filled cavities applying Electrical Resistivity Imaging (ERI) technique using dipole–dipole, pole–dipole and Wenner–Schlumberger arrays. Models are simulated with a reasonable resistivity value of formations considering board and pillar mining environment in multilayer earth. The inverted resistivity section corresponding to water filled cavities without a barrier could be able to detect three cavities for dipole–dipole and Wenner–Schlumberger arrays, whereas pole–dipole array could detect all four cavities. Later on, with inclusion of 1 m coal as a barrier in the model, the dipole–dipole array could be able to bring the signature of cavities, whereas pole–dipole and Wenner–Schlumberger configuration is unable to provide any signature. Similar resistivity responses are noticed for air filled cavities with and without barrier conditions. When all three arrays data are jointly inverted, there is a significant improvement in resistivity response which enables the detection of water filled as well as air filled cavities with and without a barrier.

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Acknowledgments

The authors are thankful to Department of Science and Technology (Project SR/S4/ES-656/2013), Government of India for supporting of this research work.

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  1. Department of Applied Geophysics, Indian School of Mines, Dhanbad, India

    Prasenjit Das & Priya R. Mohanty

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  1. Prasenjit Das
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Correspondence to Priya R. Mohanty.

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Das, P., Mohanty, P.R. Resistivity imaging technique to delineate shallow subsurface cavities associated with old coal working: a numerical study. Environ Earth Sci 75, 661 (2016). https://doi.org/10.1007/s12665-016-5404-0

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