Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry.

Vilela, Martin; Oluyemi, Gbenga; Petrovski, Andrei

Abstract

To manage uncertainty in reservoir development projects, the Value of Information is one of the main factors on which the decision is based to determine whether it is necessary to acquire additional data. However, subsurface data is not always precise and is characterized by a certain level of fuzziness. In this paper, a model is formulated to assess the Value of Information in the oil and gas industry in cases where the data proposed to be acquired is imprecise. The methodology is based on the use of fuzzy data modelling and analysis aimed at providing decision support for oil field developers. An oilfield from North Africa is used as a case study to show how the methodology works. This work shows how the analysis can be utilized to reach financial decisions on the necessity of additional data acquisition.

Citation

VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2018. Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry. In Proceedings of the 2018 IEEE international conference on fuzzy systems (FUZZ-IEEE 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article ID 8491628. Available from: https://doi.org/10.1109/FUZZ-IEEE.2018.8491628

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2018 IEEE international conference on fuzzy systems (FUZZ-IEEE 2018)
• Start Date: Jul 8, 2018
• End Date: Jul 13, 2018
• Acceptance Date: Mar 15, 2018
• Online Publication Date: Jul 8, 2018
• Publication Date: Oct 15, 2018
• Deposit Date: May 4, 2018
• Publicly Available Date: Jul 8, 2018
• Print ISSN: 1063-6706
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• Article Number: 8491628
• Series ISSN: 1063-6706
• DOI: https://doi.org/10.1109/FUZZ-IEEE.2018.8491628
• Keywords: Fuzzy modelling; Value of information; Uncertainty and risks; Decision analysis and support; Oil and gas industry application
• Public URL: http://hdl.handle.net/10059/2902
• Contract Date: May 4, 2018