Volume IV-4 | Copyright
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4, 193-198, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Sep 2018

19 Sep 2018


S. Seraj1 and M. R. Delavar2 S. Seraj and M. R. Delavar
  • 1GIS Department, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran , Iran
  • 2Center of Excellence in Geomatic Engineering in Disaster Management, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Keywords: Evidential theory, GIS, Uncertainty, Risk, Play based Exploration (PBE)

Abstract. Hydrocarbon exploration is a process based on the prediction of existing hydrocarbon in the underground formations which is associated with uncertainties. A number of studies have been undertaken on the extent of these uncertainties in the risk maps concerned with hydrocarbon exploration. This paper has addressed this issue using a novel approach.

The differences of the proposed method are checked in a few cases. Firstly, the level of studying the hydrocarbon system is play which refers to an area with a potential for trapping hydrocarbon with a unique petroleum system. Second, the evidential theory was used to accurately examine the uncertainty in the maps of the hydrocarbon system. Finally, the model used to produce the final risk map is developed in a geospatial information system environment.

The results of the research show that the functions proposed in the model are accurately estimated the uncertainty in the prediction of the existence of hydrocarbon systems in the study area. The CCRS map outlines approximately 25.9% of the study area which is highly promising for the hydrocarbon potential reservation. According to the obtained results, around 61.2% of the prospects have low risk of hydrocarbon potential in the area having high belief and about 43.7% of the prospects are available with high risk of hydrocarbon potential in the regions with high uncertainty.

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