The value of information (VOI) analysis has been recognized as a useful tool for measuring how much the expected monetary value can be increased as a result of an information-gathering activity. The VOI analysis is usually applied in the context of decision making under geological uncertainty, where only a relatively small number of decision alternatives are taken into account. In this paper we discuss possible applications of the VOI analysis in optimization of reservoir development under geological uncertainty. More precisely, by means of the VOI analysis, we evaluate how much an information-gathering activity provides an increase of the maximized expected monetary value, where the maximization is considered in a probabilistic sense to account for geological uncertainty. In this application we often need to deal with a quite large or even infinite number of candidate solutions within an optimization problem, which may cause trouble for an efficient implementation of the VOI analysis. After introducing a general methodology to estimate the VOI in our context, we validate our methodology through a toy problem, and moreover apply to a simple waterflooding problem. We find out that the VOI analysis can be conducted efficiently even in optimization under geological uncertainty by specializing our methodology properly.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations鈥揷itations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright 漏 2024 scite LLC. All rights reserved.
Made with 馃挋 for researchers
Part of the Research Solutions Family.