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  • 标题:Detecting hydrocarbon micro-seepage and related contamination, probable prospect areas, deduced from a comparative analysis of multispectral and hyperspectral satellite images
  • 本地全文:下载
  • 作者:Shaimaa M. El-Hadidy ; Fahad Alshehri ; Hossein Sahour
  • 期刊名称:Journal of King Saud University - Science
  • 印刷版ISSN:1018-3647
  • 出版年度:2022
  • 卷号:34
  • 期号:6
  • 页码:1-10
  • DOI:10.1016/j.jksus.2022.102192
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractDetecting mineralogical alteration by hydrocarbon micro-seepage from trap to surface across the deformed structure, through Comparative analysis study of hyperspectral image (EO-1, Hyperion), and multispectral (landsat7 and Advanced land imager (Ali) to map soil alteration by petroleum seepage with applying remote sensing techniques as (band ratios, supervised, SAM classification, and hydrocarbon detection and index (HD and HI) calculation to detect the potentiality of hydrocarbon seepage in the area. The type of spectral resolution accuracy available for each space imaging platform can be used to choose which is best in determining the target and whether exploration yields oil. Hyperspectral remote sensing data are integrated with a GIS framework Weighted Sum (Spatial Analyst) classified hydrocarbon seepage prospects into five potential zones very good, good, intermediate, poor, and very poor probable potentiality. The spatial lithologic carbonaceous alteration appears closely coincident along reactivated leaking faults that cause hydrocarbon micro-seepage and altered surface lithology and mineralogical cement. The hyperspectral images have proven their worth in identifying and studying hydrocarbon leaks and the resulting environmental pollution and mineral alteration, as well as use micro-seeps as a pathfinder to locations of new oil explorations discoveries that can use as a pre-drill prediction of hydrocarbon occurrence and detected a prospect area for hydrocarbon drill.
  • 关键词:KeywordsRemote sensingSoil alterationMicro-seepageHydrocarbon potentialityLeaking faultHyperspectral
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