Multifidelity Framework for Uncertainty Quantification with Multiple Quantities of Interest

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Abstract/Contents

Abstract: A systematic framework, involving ﬂow simulation and model selection at many ﬁdelity (resolution) levels, is introduced to accurately quantify the impact of geological uncertainty on multiple output quantities of interest (QoIs). The methodology considers large numbers of realizations (O(1000) in the cases presented), though very few (O(10)) simulations are performed at the highest resolutions. We proceed from coarser to ﬁner resolution levels, and at each stage simulation results are used to select a subset of realizations to simulate at the next (higher) ﬁdelity level. Models are constructed at all resolution levels through upscaling of the underlying ﬁne-scale realizations. A global transmissibility upscaling procedure is applied for this purpose. Approximate cumulative distribution functions (CDFs) are constructed for all QoIs considered. The QoI values themselves are always computed at the ﬁnest scale, but corresponding percentile values are determined using results at a rank-preserving (coarser) ﬁdelity level. Detailed results are presented for oil-water ﬂow in two channelized system examples. Simulations at seven diﬀerent ﬁdelity levels are used, and eight QoIs are evaluated. Results for the examples considered demonstrate accurate reconstruction of ﬁne-scale CDFs for all QoIs, with a speedup factor of about 18 relative to performing all simulations on the ﬁne scale.

Type of resource	text
Date created	March 8, 2019

Subject	reservoir simulation
Subject	multilevel
Subject	multifidelity
Subject	uncertainty quantification
Subject	representative models
Genre	Thesis

Location	https://purl.stanford.edu/mh730wv9127

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Preferred Citation: Kostakis, Filippos. (2019). Multifidelity Framework for Uncertainty Quantification with Multiple Quantities of Interest. Stanford Digital Repository. Available at: https://purl.stanford.edu/mh730wv9127

Master's Theses, Doerr School of Sustainability

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