Skip to main content

Research Repository

Advanced Search

A holistic approach to assessment of value of information (VOI) with fuzzy data and decision criteria.

Vilela, Martin; Oluyemi, Gbenga; Petrovski, Andrei


Martin Vilela

Andrei Petrovski


Classical decision and value of information theories have been applied in the oil and gas industry from the 1960s with partial success. In this research, we identify that the classical theory of value of information has weaknesses related with optimal data acquisition selection, data fuzziness and fuzzy decision criteria and we propose a modification in the theory to fill the gaps found. The research presented in this paper integrates theories and techniques from statistical analysis and artificial intelligence to develop a more coherent, robust and complete methodology for assessing the value of acquiring new information in the context of the oil and gas industry. The proposed methodology is applied to a case study describing a value of information assessment in an oil field where two alternatives for data acquisition are discussed. It is shown that: i) the technique of design of experiments provides a full identification of the input parameters affecting the value of the project and allows a proper selection of the data acquisition actions, ii) when the fuzziness of the data is included in the assessment, the value of the data decreases compared with the case where data are assumed to be crisp; this result means that the decision concerning the value of acquiring new data depends on whether the fuzzy nature of the data is included in the assessment and on the difference between the project value with and without data acquisition, iii) the fuzzy inference system developed for this case study successfully follows the logic of the decision-maker and results in a straightforward system to aggregate decision criteria.


VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2020. A holistic approach to assessment of value of information (VOI) with fuzzy data and decision criteria. Decision making: applications in management and engineering [online], 3(2), pages 97-118. Available from:

Journal Article Type Article
Acceptance Date Sep 28, 2020
Online Publication Date Sep 30, 2020
Publication Date Oct 11, 2020
Deposit Date Sep 28, 2020
Publicly Available Date Sep 28, 2020
Journal Decision Making: Applications in Management and Engineering
Print ISSN 2560-6018
Electronic ISSN 2620-0104
Peer Reviewed Peer Reviewed
Volume 3
Issue 2
Pages 97-118
Keywords Value of information; Fuzzy logic; Design of experiments; Uncertainty; Decision making
Public URL
Related Public URLs


Related Outputs

You might also like

Downloadable Citations