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R77V3
This work presents a model resolving data shortage problems when facing investment decisions in selecting drilling projects based on availability of equipments and drilling facilities. This is accomplished by enabling an environment for automatic information exchange using the technology of Radio Frequency Identification (RFID) integrated with assessments for projects net profit values. Incorporating the information technology tools facilitates the components selection and improves information retrieval efficiency for such missions especially during projects evaluation and drilling operation phase. Also, a fuzzy model is presented and convoyed with an optimization technique to take into consideration the risk of possible variation in oil prices and production cost. All these components are integrated by using information system design tools.
Dr. Maki K. Rashid. 2011. \u201cIntegrated Rfid Model For Optimal Selection of Drilling Projects\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 11 (GJRE Volume 11 Issue J7): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Total Score: 126
Country: Oman
Subject: Global Journal of Research in Engineering - J: General Engineering
Authors: Dr. Maki K. Rashid (PhD/Dr. count: 1)
View Count (all-time): 201
Total Views (Real + Logic): 5619
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Publish Date: 2011 12, Sat
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This work presents a model resolving data shortage problems when facing investment decisions in selecting drilling projects based on availability of equipments and drilling facilities. This is accomplished by enabling an environment for automatic information exchange using the technology of Radio Frequency Identification (RFID) integrated with assessments for projects net profit values. Incorporating the information technology tools facilitates the components selection and improves information retrieval efficiency for such missions especially during projects evaluation and drilling operation phase. Also, a fuzzy model is presented and convoyed with an optimization technique to take into consideration the risk of possible variation in oil prices and production cost. All these components are integrated by using information system design tools.
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