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A Wavelet and Neural Network based approach towards determination of Shale Volume using well logs of Indian Coalfields
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 79th EAGE Conference and Exhibition 2017, Jun 2017, Volume 2017, p.1 - 5
Abstract
Summary
Estimation of shale volume is very important in determining the quality of coal. Both shale and coal are deposited in a sedimentary environment, and more importantly both are deposited in low energy conditions. It often happens that coal is contaminated by the presence of shale and degrades its quality. In this study we have used artificial neural network (ANN) to determine the volume of shale and have compared it with traditional methods of shale volume estimation. Results suggest that ANN does a better job in estimating the shale volume and more importantly gives a confidence indicator of the purity of the coal. A wavelet based approach was also used in differentiating the different types of coal with respect to its purity levels. Results suggest that the wavelet approach too is a good method of qualitatively labelling the purity of coal. The study was conducted in the Mand Raigarh Coalfield, of India.
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