The quantitative prediction of Coalbed Methane gas content based on super-low frequency electromagnetic technology

Author

Yanbing Bai ; Qiming Qin ; Li Chen ; Nan Wang ; Jianhua Wang ; Chao Chen

Author_Institution

Inst. of Remote Sensing & GIS, Peking Univ., Beijing, China

fYear

2013

fDate

21-26 July 2013

Firstpage

819

Lastpage

822

Abstract

Abundant field experiments have showed that the super low frequency (SLF) electromagnetic detector is sensitive to Coalbed Methane(CBM). The signal curves collected by the SLF electromagnetic detector show high amplitude anomalies in the CBM enrichment areas. Based on this finding, we choose the Qinshui basin as study area, and take advantage of the field SLF electromagnetic data to make quantitative prediction of CBM gas content.The results show that the average error between the estimated value and the measured value is 7.56%.

Keywords

hydrocarbon reservoirs; remote sensing; CBM enrichment; China; Coalbed Methane gas content; Qinshui basin; SLF electromagnetic detector; quantitative prediction; signal curves; superlow frequency electromagnetic technology; Coal; Electromagnetics; Geology; Measurement uncertainty; Neural networks; Predictive models; Training; SLF electromagnetic technology; coalbed methane; quantitative prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International

Conference_Location

Melbourne, VIC

ISSN

2153-6996

Print_ISBN

978-1-4799-1114-1

Type

conf

DOI

10.1109/IGARSS.2013.6721284

Filename

6721284