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Abstract

Summary

The rapid increase in the country’s energy demands has catalyzed the commercial coal mining in India, which has resulted in various Indian energy players and Government of India to expedite and advance the conventional methods of coal exploration beyond drilling by introducing the 2D/3D seismic methods. The aim was to minimize the drilling cost and to enhance the resolution of geological model and the same has been discussed in the present study through a case study of Kartala block situated in the Mand Raigarh coalfield. The objective of the present study was to integrate the results of 2D seismic survey with the drill data to generate the geological model for future mine planning. A total of seven numbers of coal seams were identified from PSTM seismic section, which was integrated with the drill cores and geophysical logs to reveal the geological structures of the minable coal seams in the entire coal block. Thus, the aforesaid study helped in obtaining a confident geological model for reserve estimation and mine planning.

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/content/papers/10.3997/2214-4609.202375047
2023-11-07
2025-07-08
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References

  1. Mondal, D., Srivardhan, V., Singh, B.B., 2017. Enhanced lithology identification from well log using Artificial Neural Network and Fuzzy Logic over coal seams of Mand Raigarh coalfield.J. Indian Geolog. Congress.9, 95–99https://researchgate.net/publication/320407496
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