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date: 22 July 2019

Abstract and Keywords

This article discusses the results of a Bayes linear uncertainty analysis for oil reservoirs based on multiscale computer experiments. Using the Gullfaks oil and gas reservoir located in the North Sea as a case study, the article demonstrates the applicability of Bayes linear methods to address highly complex problems for which the full Bayesian analysis may be computationally intractable. A reservoir simulation model, run at two different levels of complexity, is used, and a simulator of a hydrocarbon reservoir represents properties of the reservoir on a three-dimensional grid. The article also describes a general formulation for the approach to uncertainty analysis for complex physical systems given a computer model for that system. Finally, it presents the results of simulations and forecasting for the Gullfaks reservoir.

Keywords: uncertainty analysis, oil reservoirs, linear methods, simulations, multiscale computer experiments, forecasting

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