Oil-gas information extraction and prospective area prediction based on hydrocarbon microseepage theory: A case study of Salamat Basin in Central Africa
1. Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China 2. China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083,China 3. College of Resources and Environment, Chengdu University of Information Technology,Chengdu 610225, China 4. China Geological Survey, Beijing 100037, China
Anomaly information caused by hydrocarbon seepage in oil-gas fields can be detected by remote sensing technology. Compared with traditional oil and gas exploration methods,remote sensing technology has many advantages in getting information from long range, large-area mapping, high efficiency and low cost, especially in areas with complex terrain and geomorphological environment. Based on the hydrocarbon microseepage theory, the mineral alteration information such as clays, carbonates, ferrous ion and brightness temperature were respectively extracted by methods of crosstalk correction, atmospheric correction, band ratio, principal component analysis and mono-window algorithm with the ASTER data in Salamat Basin of Central Africa. The results show that the above-mentioned several types of strong mineral alteration information and high temperature anomaly information are mainly distributed in the central and southern part of the study area, namely, the central uplift zone and the southern depression zone are highly likely to contain hydrocarbons. Combined with existing geological, seismic, geophysical and geochemical data, five oil-gas prospecting areas were delineated, which can provide theoretical direction for the further oil-gas exploration.
肖晨超, 吴小娟, 汪大明, 褚永彬. 基于烃类微渗漏的油气异常信息提取及远景区预测——以中非Salamat盆地为例[J]. 国土资源遥感, 2019, 31(4): 120-127.
Chenchao XIAO, Xiaojuan WU, Daming WANG, Yongbin CHU. Oil-gas information extraction and prospective area prediction based on hydrocarbon microseepage theory: A case study of Salamat Basin in Central Africa. Remote Sensing for Land & Resources, 2019, 31(4): 120-127.
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