煤田地质与勘探Issue(4)：94-98,5.DOI:10.3969/j.issn.1001-1986.2015.04.020
煤层含气量测井解释方法参数选择及适用性
Parameter selection and applicability of gas content logging interpretation methodology in coal seam
唐颖 1李乐忠 2蒋时馨 3张滨海 3仲米虹 4孙玉红3
作者信息
- 1. 中国地质大学 北京 能源学院，北京 100083
- 2. 中海石油气电集团技术研发中心，北京 100027
- 3. 中海石油气电集团技术研发中心，北京 100027
- 4. 中海油研究总院，北京 100027
- 折叠
摘要
Abstract
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.关键词
煤层气/测井/煤层含气量/多元线性回归/BP 神经网络/参数选择/适用性Key words
CBM/well logging/gas content/multiple linear regression/BP neural network/parameter selection/applicability分类
天文与地球科学引用本文复制引用
唐颖,李乐忠,蒋时馨,张滨海,仲米虹,孙玉红..煤层含气量测井解释方法参数选择及适用性[J].煤田地质与勘探,2015,(4):94-98,5.
