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

Vilela Ibarra, Martin Jose

Abstract

The research presented in this thesis 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 classical methodology for value of information assessment has been used in the oil and gas industry since the 1960s, even though it is only recently that more applications have been published. It is commonly acknowledged that, due to the large number of data acquisition actions and the capital investment associated with it, the oil and gas industry is an ideal domain for developing and applying value of information assessments. In this research, three main gaps in the classical methodology for value of information are identified and addressed by integrating three existing techniques from other domains. Firstly, the research identifies that the technique design of experiments can be used in value of information for providing a holistic assessment of the complete set of uncertain parameters, selecting the ones that have the most impact on the value of the project and supporting the selection of the data acquisition actions for evaluation. Secondly, the fuzziness of the data is captured through membership functions and the expected utility value of each financial parameter is estimated using the probability of the states conditioned to the membership functions - in the classical methodology, this is conditioned to crisp values of the data. Thirdly, a fuzzy inference system is developed for making the value of information assessment, capturing the decision-making human logic into the assessment process and integrating several financial parameters into one. 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. The case study shows how the three techniques can be integrated within the previous methodology, resulting in a more complete theory. It is observed that the technique or 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. In the case study, it is concluded that, when the fuzziness of the data is included in the assessment, the value of the data decreases in comparison 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. 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. Sensitivity analysis of the parameters of two different membership functions is made, reaching consistent results in both cases.

Citation

VILELA IBARRA, M.J. 2019. A holistic approach to assessment of value of information (VOI) with fuzzy data and decision criteria. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

• Thesis Type: Thesis
• Deposit Date: Jan 28, 2020
• Publicly Available Date: Jan 28, 2020
• Keywords: Value of information; Information value; Fuzzy logic; Fuzzy inference systems; Oil and gas industry
• Public URL: https://rgu-repository.worktribe.com/output/842164
• Related Public URLs: https://rgu-repository.worktribe.com/output/970515
• Award Date: Nov 30, 2019