A hybrid GIS-assisted framework to integrate Dempster-Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration

One of the most important reasons for the existence of geologic risk during the hydrocarbon exploration process is related to uncertainties in geospatial data and models employed for data fusion. This study proposes a geospatial information system-assisted approach integrated with soft computing methods to manage spatial uncertainties during the hydrocarbon exploration process. A framework was designed to illustrate the process of calculating the geologic risk interval of each hydrocarbon structure and its estimation of uncertainties. The model enhances the geologic risk analysis of a Dempster-Shafer data-driven method by a fuzzy logic approach. The resultant hybrid method showed high predictive power with the area under the success and predictive curves being 82.2 and 75.9%, respectively. According to the results, the proposed hybrid method has improved the quality of risk analysis.

Automated summary

This study proposes a method to manage spatial uncertainties during the hydrocarbon exploration process using a geospatial information system and soft computing methods, calculating the geologic risk interval through uncertainty estimation to improve the quality of risk analysis.