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	COAL-BED METHANE RESERVOIR IDENTIFICATION USING THE NATURAL SOURCE SUPER-LOW FREQUENCY REMOTE SENSING
	Wang, Nan ; Qin, Qi Ming ; Xie, Chao ; Chen, Li ; Bai, Yan Bing
	2013
关键词	Super-Low Frequency (SLF) Independent Component Analysis (ICA) Lifting Wavelet Transform Coal-bed Methane (CBM) Reservoir identification BLIND SEPARATION PROPAGATION EXPLORATION
英文摘要	The goal of this paper is to develop and analyze the natural source Super-Low Frequency (SLF) remote sensing using the BD-6 detector and its data processing and interpretation system to help with Coal-bed Methane (CBM) reservoir information extraction. We delineated the diagram of the SLF remote sensing technique, and especially illustrated the integrated method of the Independent Component Analysis (ICA) and Wavelet-Lifting Wavelet Transform to suppress time-varying 150Hz and 250Hz power frequency electromagnetic interference (EMI). In the application of interpreting enrichment layers of (CBM), we obtained the SLF interpretation signs to identify CBM reservoirs and features. The result demonstrates that the SLF remote sensing provides a prosperous perspective on the detection and demarcation of underground geo-objects.; Engineering, Electrical & Electronic; Geosciences, Multidisciplinary; Remote Sensing; EI; CPCI-S(ISTP); 0
语种	英语
DOI标识	10.1109/IGARSS.2013.6723715
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/405864]
专题	地球与空间科学学院
推荐引用方式 GB/T 7714	Wang, Nan,Qin, Qi Ming,Xie, Chao,et al. COAL-BED METHANE RESERVOIR IDENTIFICATION USING THE NATURAL SOURCE SUPER-LOW FREQUENCY REMOTE SENSING. 2013-01-01.

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