Fuzzy logic applied to value of information assessment in oil and gas projects

Abstract The concept of value of information (VOI) has been widely used in the oil industry when making decisions on the acquisition of new data sets for the development and operation of oil fields. The classical approach to VOI assumes that the outcome of the data acquisition process produces crisp...

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Autores principales:	Martin Vilela, Gbenga Oluyemi, Andrei Petrovski
Formato:	article
Lenguaje:	EN
Publicado:	KeAi Communications Co., Ltd. 2019
Materias:	Value of information Fuzzy logic Uncertainty and risk management Oil and gas industry Science Q Petrology QE420-499
Acceso en línea:	https://doaj.org/article/8fd3a675b29d4edf978774f7f991e665
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spelling	oai:doaj.org-article:8fd3a675b29d4edf978774f7f991e6652021-12-02T10:18:32ZFuzzy logic applied to value of information assessment in oil and gas projects10.1007/s12182-019-0348-01672-51071995-8226https://doaj.org/article/8fd3a675b29d4edf978774f7f991e6652019-07-01T00:00:00Zhttp://link.springer.com/article/10.1007/s12182-019-0348-0https://doaj.org/toc/1672-5107https://doaj.org/toc/1995-8226Abstract The concept of value of information (VOI) has been widely used in the oil industry when making decisions on the acquisition of new data sets for the development and operation of oil fields. The classical approach to VOI assumes that the outcome of the data acquisition process produces crisp values, which are uniquely mapped onto one of the deterministic reservoir models representing the subsurface variability. However, subsurface reservoir data are not always crisp; it can also be fuzzy and may correspond to various reservoir models to different degrees. The classical approach to VOI may not, therefore, lead to the best decision with regard to the need to acquire new data. Fuzzy logic, introduced in the 1960s as an alternative to the classical logic, is able to manage the uncertainty associated with the fuzziness of the data. In this paper, both classical and fuzzy theoretical formulations for VOI are developed and contrasted using inherently vague data. A case study, which is consistent with the future development of an oil reservoir, is used to compare the application of both approaches to the estimation of VOI. The results of the VOI process show that when the fuzzy nature of the data is included in the assessment, the value of the data decreases. In this case study, the results of the assessment using crisp data and fuzzy data change the decision from “acquire” the additional data (in the former) to “do not acquire” the additional data (in the latter). In general, different decisions are reached, depending on whether the fuzzy nature of the data is considered during the evaluation. The implications of these results are significant in a domain such as the oil and gas industry (where investments are huge). This work strongly suggests the need to define the data as crisp or fuzzy for use in VOI, prior to implementing the assessment to select and define the right approach.Martin VilelaGbenga OluyemiAndrei PetrovskiKeAi Communications Co., Ltd.articleValue of informationFuzzy logicUncertainty and risk managementOil and gas industryScienceQPetrologyQE420-499ENPetroleum Science, Vol 16, Iss 5, Pp 1208-1220 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Value of information Fuzzy logic Uncertainty and risk management Oil and gas industry Science Q Petrology QE420-499
spellingShingle	Value of information Fuzzy logic Uncertainty and risk management Oil and gas industry Science Q Petrology QE420-499 Martin Vilela Gbenga Oluyemi Andrei Petrovski Fuzzy logic applied to value of information assessment in oil and gas projects
description	Abstract The concept of value of information (VOI) has been widely used in the oil industry when making decisions on the acquisition of new data sets for the development and operation of oil fields. The classical approach to VOI assumes that the outcome of the data acquisition process produces crisp values, which are uniquely mapped onto one of the deterministic reservoir models representing the subsurface variability. However, subsurface reservoir data are not always crisp; it can also be fuzzy and may correspond to various reservoir models to different degrees. The classical approach to VOI may not, therefore, lead to the best decision with regard to the need to acquire new data. Fuzzy logic, introduced in the 1960s as an alternative to the classical logic, is able to manage the uncertainty associated with the fuzziness of the data. In this paper, both classical and fuzzy theoretical formulations for VOI are developed and contrasted using inherently vague data. A case study, which is consistent with the future development of an oil reservoir, is used to compare the application of both approaches to the estimation of VOI. The results of the VOI process show that when the fuzzy nature of the data is included in the assessment, the value of the data decreases. In this case study, the results of the assessment using crisp data and fuzzy data change the decision from “acquire” the additional data (in the former) to “do not acquire” the additional data (in the latter). In general, different decisions are reached, depending on whether the fuzzy nature of the data is considered during the evaluation. The implications of these results are significant in a domain such as the oil and gas industry (where investments are huge). This work strongly suggests the need to define the data as crisp or fuzzy for use in VOI, prior to implementing the assessment to select and define the right approach.
format	article
author	Martin Vilela Gbenga Oluyemi Andrei Petrovski
author_facet	Martin Vilela Gbenga Oluyemi Andrei Petrovski
author_sort	Martin Vilela
title	Fuzzy logic applied to value of information assessment in oil and gas projects
title_short	Fuzzy logic applied to value of information assessment in oil and gas projects
title_full	Fuzzy logic applied to value of information assessment in oil and gas projects
title_fullStr	Fuzzy logic applied to value of information assessment in oil and gas projects
title_full_unstemmed	Fuzzy logic applied to value of information assessment in oil and gas projects
title_sort	fuzzy logic applied to value of information assessment in oil and gas projects
publisher	KeAi Communications Co., Ltd.
publishDate	2019
url	https://doaj.org/article/8fd3a675b29d4edf978774f7f991e665
work_keys_str_mv	AT martinvilela fuzzylogicappliedtovalueofinformationassessmentinoilandgasprojects AT gbengaoluyemi fuzzylogicappliedtovalueofinformationassessmentinoilandgasprojects AT andreipetrovski fuzzylogicappliedtovalueofinformationassessmentinoilandgasprojects
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Fuzzy logic applied to value of information assessment in oil and gas projects

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