TY - JOUR
T1 - A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis
T2 - an application in hydrocarbon exploration
AU - Seraj, Sahand
AU - Delavar, Mahmoud Reza
AU - Rezaee, Reza
N1 - Publisher Copyright:
© 2019 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Dempster–Shafer theory
KW - fuzzy set
KW - Geospatial information system
KW - hydrocarbon exploration
KW - uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85068049034&partnerID=8YFLogxK
U2 - 10.1080/10106049.2019.1622602
DO - 10.1080/10106049.2019.1622602
M3 - Article
AN - SCOPUS:85068049034
SN - 1010-6049
VL - 36
SP - 820
EP - 838
JO - Geocarto International
JF - Geocarto International
IS - 7
ER -