TANG Ying, LI Lezhong, JIANG Shixin, ZHANG Binhai, ZHONG Mihong, SUN Yuhong. Parameter selection and applicability of gas content logging interpretation methodology in coal seam[J]. COAL GEOLOGY & EXPLORATION, 2015, 43(4): 94-98. DOI: 10.3969/j.issn.1001-1986.2015.04.020
Citation: TANG Ying, LI Lezhong, JIANG Shixin, ZHANG Binhai, ZHONG Mihong, SUN Yuhong. Parameter selection and applicability of gas content logging interpretation methodology in coal seam[J]. COAL GEOLOGY & EXPLORATION, 2015, 43(4): 94-98. DOI: 10.3969/j.issn.1001-1986.2015.04.020

Parameter selection and applicability of gas content logging interpretation methodology in coal seam

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  • Received Date: October 13, 2013
  • Available Online: October 21, 2021
  • Multiple linear regression and BP neural network are gas content logging interpretation methodologies commonly used in coal seam. Based on well logging data and measured gas content of CBM well in Galilee basin of Australia and Qinshui basin of China, this study screened the logging related parameters of gas content through correlation analysis and then established the relationship model between gas content and logging parameters. Based on BP neural network theory, this study not only established a nonlinear prediction model of CBM gas content and logging parameters through the network training and prediction, but also analyzed the error of the two methods and discussed their applicability.
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