DocumentCode
2713725
Title
The abnormal information extraction of the hydrocarbon micro-seepage based on the hyperspectral image
Author
Hou, Fang ; Wang, Daming ; Cai, Ying ; Li, Zhizhong ; Zhao, Wenji
Author_Institution
Coll. of Resource Environ. & Tourism, Capital Normal Univ., Beijing, China
fYear
2011
fDate
24-26 June 2011
Firstpage
1
Lastpage
4
Abstract
With the advantages of high spectrum resolution, the study on the accurate and effective extraction of the soil hydrocarbon micro-seepage information based on the hypercpectral data has an extremely extensive application prospect, such as be used as an important basis for carrying on the oil-gas prospect evaluation. Both of hydrocarbon index method and spectrum angle match (SAM) method are adopted in this paper, using the Hyperion data in Ordos Basin and according to the micro-seepage theory. It will determine the following alteration information: hydrocarbon, Fe, carbonate and clay mineral, and also determine the potential abnormal region. The HI method will be used to extract hydrocarbon information nearby 1730nm, and R index method in 2310nm; for the extraction of the Fe, carbonate and clay mineral, this paper applies the SAM method, compares the spectrum in the image with the standard spectrum in the USGS spectral library, charting to get the interpret results.
Keywords
geographic information systems; geophysical image processing; geophysical techniques; hydrocarbon reservoirs; minerals; HI method; Hyperion data; Ordos Basin; R index method; USGS spectral library; abnormal information extraction; carbonate extraction; clay mineral; hydrocarbon index method; hydrocarbon microseepage; hyperspectral image; iron extraction; oil-gas prospect evaluation; spectrum angle match method; Data mining; Hydrocarbons; Hyperspectral imaging; Indexes; Minerals; Hyperion; hydrocarbon index method; hydrocarbon micro-seepage; hyperspectral image; spectrum angle match (SAM);
fLanguage
English
Publisher
ieee
Conference_Titel
Geoinformatics, 2011 19th International Conference on
Conference_Location
Shanghai
ISSN
2161-024X
Print_ISBN
978-1-61284-849-5
Type
conf
DOI
10.1109/GeoInformatics.2011.5981133
Filename
5981133
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