Exploring for natural gas using reflectance spectra of surface soils Original Research Article

Reflectance spectra in the visible and near-infrared wavelengths provide a rapid and inexpensive means for determining the mineralogy of samples and obtaining information on chemical composition. Hydrocarbon microseepage theory establishes a cause-and-effect relation between oil and gas reservoirs and some special surface anomalies, which mainly include surface hydrocarbon microseepage and related alterations. Therefore, we can explore for oil, gas by determining reflectance spectra of surface anomalies. This idea has been applied to the R&D project of exploring for natural gas in Qinghai province of China using NASA EO-1 satellite with the Hyperion sensor (June 2005 to June 2006). In this project, in order to improve the accuracy of exploration targets of natural gas mapped in the field studied, an integrated practical system of exploration of oil and gas was built by the analysis of not only hyperspectral remote sensing data but also data provided from field work. In this paper, our efforts were focused on the analysis of the 799 reflectance spectra provided from the field work. In order to properly define the typical form of hydrocarbon microseepage with spectroscopy and fulfill the data analysis, it was necessary to build a spectral model. In this spectral model the most important features of hydrocarbon microseepage in the surface of our study area, i.e., diagnostic spectral macroscopic features and diagnostic spectral absorption features, were proposed and extracted, respectively. The distribution of coexisting anomalies, which results from both alteration minerals and hydrocarbons, is estimated by the diagnostic macroscopic features mainly using Spectral Angle Mapper (SAM) classifier. On the other hand, the diagnostic absorption features of two main absorption bands presented abundant local information, based on deep analysis of which, we are able to map the anomalies of alteration minerals and hydrocarbons, respectively. Additionally, a general framework of analysis and key classification algorithms applied to the Hyperion data have been introduced briefly. In our work, three exploration targets of natural gas were identified from the study area which covers 2100 km2. In the three exploration targets, three wildcats have been drilled by China National Petroleum Corporation (CNPC) since July 2006, and all the three wells have been proven some industrial reserves.