2020
DOI: 10.3844/ajeassp.2020.96.110
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New Approach in Application of the AHP–Fuzzy TOPSIS Method in Mineral Potential Mapping of the Natural Bitumen (Gilsonite): A Case Study from the Gilan-e-Gharb Block, the Kermanshah, West of Iran

Abstract: The Gilan-e-Gharb block is known as a prospective area for hydrocarbon resources in the form of oil, gas in deep potential and natural bitumen (Gilsonite) on the surface. Natural bitumen is not clearly detectable by geochemical or geophysical methods. Hereupon, identifying high potential areas for further exploration, attempted with the help of AHP-Fuzzy and TOPSIS methods. The comprehensive database of geological and geostructural records, satellite imagery analysis by remote sensing and mine indexes counted … Show more

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Cited by 11 publications
(4 citation statements)
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“…However, significant reserves are also concentrated in the United States, Mexico, Kuwait and Indonesia [33]. In the United States of America, the largest gilsonite reserves have been found in Utah and Colorado, estimated to have 45 million tons [38].…”
Section: Natural Asphalt In the Worldmentioning
confidence: 99%
“…However, significant reserves are also concentrated in the United States, Mexico, Kuwait and Indonesia [33]. In the United States of America, the largest gilsonite reserves have been found in Utah and Colorado, estimated to have 45 million tons [38].…”
Section: Natural Asphalt In the Worldmentioning
confidence: 99%
“…Mining is going to become more predictable through the Internet of Things and Big Data advanced analytics (Saroufim, 2016;Sharma et al, 2017a;Dong et al, 2017;Singh et al, 2018). A considerable number of generated information expected to be able to make decisions efficiently (Sun et al, 2012;Singh et al, 2018;Rahimi et al, 2020). This process requires cognitive computing to create automated mine planning (Sun et al, 2012;Mahdavinejad et al, 2018).…”
Section: Predictable Mining Operationmentioning
confidence: 99%
“…Innovative techniques in data processing and remote controlling are evolving all stages of mining from exploration to consumption patterns (Asgari et al, 2019;Rahimi et al, 2020). Artificial Intelligence (AI) is a reliable tool for data analysis and decision making in case of dealing with large or repeating sets of data (Russell and Norvig, 2002).…”
Section: Introductionmentioning
confidence: 99%
“…The many maintenance challenges force managers to explore innovative solutions that can facilitate these maintenance and repair processes. Innovative techniques in data processing and remote controlling are evolving in all stages of mining, from exploration to consumption patterns (Asgari et al ., 2019; Rahimi et al ., 2020). Even large companies know that they cannot ignore the digital revolution, as it makes them less competitive from an economic point of view (Canelón et al ., 2022).…”
Section: Introductionmentioning
confidence: 99%