Abstract
Abstract To reduce the exploration costs for hydrocarbons during the reconnaissance stage of exploration, satellite images and available surface data could be used. This paper identified three significant surface patterns which are considered promising; surface temperature derived from satellite data, vegetation cover and gas geochemistry. These were integrated and their correlation to the presence of petroleum investigated. By employing GIS and fuzzy logic a dynamic model was developed which could be applied to any new petroleum exploration target using variable input data of that particular exploration target. A selected study area consisted of 53 existing petroleum-reach areas within 20 ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Granules. Each granule covers an area of 3600km2 (60 km x 60 km) of land in onshore Iran. 20 ASTER scenes over the study area were purchased from NASA and surface thermal data over these existing fields were retrieved from the satellite images. The direction of land surface temperature (thermal anomaly) was analyzed using variograms which correlated well with the direction of petroleum reservoir locations. Variograms were used to study the trend and direction of thermal anomaly behaviour over the reservoirs. Many contributing factors such as geological units, meteorological conditions, time and the seasons of ASTER data acquisition, thermal conductivity of stratigraphic units of the study area and other sources (hot springs, power stations, producing wells etc…) were considered and fuzzy membership values for corresponding pixels in the processed ASTER images were assigned accordingly. Spatial pre-processing and registrations of satellite data, together with spatial analyses consisting of Land Surface Temperature (LST) retrieval from ASTER data and removing the false thermal contributors to LST, were among the key processing procedures applied for the thermal data layer in the proposed GIS system.
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