Coal reservior gas content evaluation using super-low frequency electromagnetic technology

Coalbed gas content of coal reservoir is one of the most important parameters. It is commonly monitored by experiment test, seismic and logging. But the exploration cost is huge. In this paper, Super-Low Frequency electromagnetic data are used to evaluate the gas content for the No. 3 coal seam in the Southern Qinshui Basin (Hudi coal zones). Coalbed gas content of drilling core samples from coal seams was obtained from the measured data. The results, together with the Super-Low Frequency electromagnetic data obtained from Super-Low Frequency electromagnetic technology, have been analyzed by using BP neural network modeling, permitting correlation of the coalbed gas content to the Super-Low Frequency electromagnetic responses. The correlation developed in this study provides better understanding of the coal reservoir for coalbed methane exploration in given coalfields by a new evaluation of the coalbed gas content. Copyright ? (2013) by the Asian Association on Remote Sensing.EI