Quantitative predication on the water abundance of coal seam roof based on TEM

DOI

10.2991/iceeg-16.2016.43How to use a DOI?

Keywords

TEM, pumping test,water abundance, quantitative estimates

Abstract

With the depth of Coal mining deepen, it becomes a greater challenge to prevent and control water. Quantitative predication on the water abundance of coal seam rapid has become a serious problem. However, since inherent limitations of the method, only qualitative judgments can be done. Based on the numerical simulation, transient electromagnetic method and pumping tests are combined in this paper. Using many data of unit Inflow of drilling pumping test and apparent resistivity values measured near the borehole by TEM, the regression equation was set up. From the regression equation and the apparent resistivity values of remaining positions, quasi unit Inflows at other locations were quantitatively estimated, which can be used to quantitatively estimate the entire survey area. The result shows transient electromagnetic response can well reflect the changing nature of the aqueous layer of low resistivity. For complex aqueous region, finer quantitative information of the water abundance of aquifer can be given by quasi unit Inflow. The method in a coal mine in Inner Mongolia have been exploratory applications, and achieved rich water of coal seam roof of rapid quantitative assessment.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Kang Chen
AU  - Guoqiang Xue
PY  - 2016/06
DA  - 2016/06
TI  - Quantitative predication on the water abundance of coal seam roof based on TEM
BT  - Proceedings of the 7th International Conference on Environment and Engineering Geophysics & Summit Forum of Chinese Academy of Engineering on Engineering Science and Technology
PB  - Atlantis Press
SP  - 156
EP  - 159
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceeg-16.2016.43
DO  - 10.2991/iceeg-16.2016.43
ID  - Chen2016/06
ER  -