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 met...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
TAYLOR & FRANCIS LTD
2021
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| Online Access: | http://hdl.handle.net/20.500.11937/89584 |
| _version_ | 1848765252268720128 |
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| author | Seraj, S. Delavar, M.R. Rezaee, Reza |
| author_facet | Seraj, S. Delavar, M.R. Rezaee, Reza |
| author_sort | Seraj, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:32:18Z |
| format | Journal Article |
| id | curtin-20.500.11937-89584 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:32:18Z |
| publishDate | 2021 |
| publisher | TAYLOR & FRANCIS LTD |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-895842022-11-18T07:14:26Z A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration Seraj, S. Delavar, M.R. Rezaee, Reza Science & Technology Life Sciences & Biomedicine Physical Sciences Technology Environmental Sciences Geosciences, Multidisciplinary Remote Sensing Imaging Science & Photographic Technology Environmental Sciences & Ecology Geology Geospatial information system uncertainty hydrocarbon exploration Dempster-Shafer theory fuzzy set BELIEF FUNCTIONS MINERAL PROSPECTIVITY LOGISTIC-REGRESSION EVOLUTION MODELS ZAGROS PROVINCE REGION 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. 2021 Journal Article http://hdl.handle.net/20.500.11937/89584 10.1080/10106049.2019.1622602 English TAYLOR & FRANCIS LTD restricted |
| spellingShingle | Science & Technology Life Sciences & Biomedicine Physical Sciences Technology Environmental Sciences Geosciences, Multidisciplinary Remote Sensing Imaging Science & Photographic Technology Environmental Sciences & Ecology Geology Geospatial information system uncertainty hydrocarbon exploration Dempster-Shafer theory fuzzy set BELIEF FUNCTIONS MINERAL PROSPECTIVITY LOGISTIC-REGRESSION EVOLUTION MODELS ZAGROS PROVINCE REGION Seraj, S. Delavar, M.R. Rezaee, Reza A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration |
| title | A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration |
| title_full | A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration |
| title_fullStr | A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration |
| title_full_unstemmed | A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration |
| title_short | A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration |
| title_sort | hybrid gis-assisted framework to integrate dempster–shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration |
| topic | Science & Technology Life Sciences & Biomedicine Physical Sciences Technology Environmental Sciences Geosciences, Multidisciplinary Remote Sensing Imaging Science & Photographic Technology Environmental Sciences & Ecology Geology Geospatial information system uncertainty hydrocarbon exploration Dempster-Shafer theory fuzzy set BELIEF FUNCTIONS MINERAL PROSPECTIVITY LOGISTIC-REGRESSION EVOLUTION MODELS ZAGROS PROVINCE REGION |
| url | http://hdl.handle.net/20.500.11937/89584 |