Paper Info
Title
Passive super-low frequency remote sensing technique for monitoring coal-bed methane reservoirs
Abstract
Coal-bed methane (CBM), as an increasingly promising resource for the energy supply, deserves further exploration and accurate reservoir evaluation. It is also required to dynamically monitor the reservoirs (>200 m). Remote sensing methods in regular wavebands may fail in the depth sounding, with only imaging geo-objects shallower than 100 m. In contrast, the Super-Low Frequency (SLF) remote sensing technique has outstanding traits over others, including lower attenuation, all-weather and deeper penetration. In this paper, we have developed a non-imaging remote sensor to acquire electromagnetic signals in the Super-Low Frequency bands (i.e. SLF signals), which also enables us to fast and efficiently pre-process signals in a real-time display. In order to accurately identify producing CBM reservoirs, we mainly extract electromagnetic radiation (EMR) anomalies from processed SLF signals, and then dynamic analysis can be achieved. This technique has been validated by field experiments in Qin shui Basin, China.
Year
DOI
Venue
2014
10.1109/IGARSS.2014.6946562
IGARSS
Keywords
Field
DocType
geophysical techniques,remote sensing,hydrocarbon reservoirs,reservoir evaluation,electromagnetic radiation,electromagnetic radiation anomalies,qin shui basin,reservoir identification,nonimaging remote sensor,china,super-low frequency,coal-bed methane reservoir monitoring,regular wavebands,electromagnetic signals,slf signals,dynamic monitoring,coal-bed methane,remote sensing methods,passive super-low frequency remote sensing technique,reservoirs,coal,noise,electromagnetics,production,super low frequency
Computer science,Remote sensing,Methane,Coal,Super low frequency
Conference
ISSN
Citations 
PageRank 
2153-6996
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Nan Wang101.69
Qi-ming Qin215849.12
Li Chen303.04
Yan-Bing Bai4132.64
Shanshan Zhao501.35
Cheng Ye Zhang634.09
Huazhong Ren77323.56