Fuzzy MCDM-based GIS model for subsea oil pipeline route optimization: An integrated approach |
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Authors: | Abdul-Lateef Balogun Abdul-Nasir Matori Adekunle Isa Hamid-Mosaku Dano Umar Lawal Imtiaz Ahmed Chandio |
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Affiliation: | 1. Department of Civil &2. Environmental Engineering, Geomatic Research Group, Universiti Teknologi PETRONAS, Seri Iskandar, Perak Darul Ridzuan, Malaysia;3. Department of Geomatic Engineering Technology, Yanbu Industrial College, Yanbu Al-Sinaiyah, Kingdom of Saudi Arabiageospatial63@gmail.com;5. Department of Surveying and Geoinformatics, University of Lagos, Lagos, Nigeria;6. Depatment of Urban Planning, University of Dammam, Dammam, Kingdom of Saudi Arabia;7. Department of City and Regional Planning, Mehran University of Engineering and Technology, Jamshoro, Pakistan |
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Abstract: | Proper pipeline route selection is an integral component of a typical oil exploration and transportation project. Improperly selected routes could have severe consequences including pipe failures, oil spillage, and environmental disasters. Consequently, technologies like geographic information systems (GIS) are increasingly being used to facilitate the oil pipeline route selection procedure—especially for onshore routing projects. Surprisingly, not much has been documented on the application of GIS to offshore pipeline routing. With recent discoveries on the merits of offshore oil exploration, it is necessary to extend the analytical capabilities of GIS to the unique offshore domain. However, concerns have been raised regarding the limitations of GIS in accurately prioritizing diverse selection criteria in typical multi-criteria decision-making (MCDM) problems like route selection. Consequently, this paper addresses the offshore/subsea pipeline routing constraint using a hybrid decision support system (DSS), which integrates a GIS and fuzzy logic-based approximate reasoning (AR) models for optimal performance. The resultant spatial decision support system (SDSS) was successfully applied to a case study in Malaysia. The AR algorithm calculated the significance level of the multiple criteria using various fuzzy linguistic variables and membership functions. The aggregated priority ranking from different pipeline routing experts showed that the overall influence of the environmental criteria (61.4%) significantly exceeded that of other equally important criteria in the study area. These rankings were inputted into the SDSS to simulate various probable routes. Final results accurately highlighted an optimal route, which places a premium on the protection of environmental features in the subsea study area—in alignment with the preferences of majority of the experts. |
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Keywords: | AR fuzzy logic GIS MCDM pipeline routing SDSS subsea |
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