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Title: Uncertainty Quantification in CO 2 Sequestration Using Surrogate Models from Polynomial Chaos Expansion

Journal Article · · Industrial and Engineering Chemistry Research
DOI:https://doi.org/10.1021/ie300856p· OSTI ID:1123822

In this paper, surrogate models are iteratively built using polynomial chaos expansion (PCE) and detailed numerical simulations of a carbon sequestration system. Output variables from a numerical simulator are approximated as polynomial functions of uncertain parameters. Once generated, PCE representations can be used in place of the numerical simulator and often decrease simulation times by several orders of magnitude. However, PCE models are expensive to derive unless the number of terms in the expansion is moderate, which requires a relatively small number of uncertain variables and a low degree of expansion. To cope with this limitation, instead of using a classical full expansion at each step of an iterative PCE construction method, we introduce a mixed-integer programming (MIP) formulation to identify the best subset of basis terms in the expansion. This approach makes it possible to keep the number of terms small in the expansion. Monte Carlo (MC) simulation is then performed by substituting the values of the uncertain parameters into the closed-form polynomial functions. Based on the results of MC simulation, the uncertainties of injecting CO{sub 2} underground are quantified for a saline aquifer. Moreover, based on the PCE model, we formulate an optimization problem to determine the optimal CO{sub 2} injection rate so as to maximize the gas saturation (residual trapping) during injection, and thereby minimize the chance of leakage.

Research Organization:
National Energy Technology Lab. (NETL), Pittsburgh, PA, and Morgantown, WV (United States). In-house Research; National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV (United States)
Sponsoring Organization:
USDOE Office of Fossil Energy (FE)
DOE Contract Number:
DE-FE0004000
OSTI ID:
1123822
Report Number(s):
TPR-3856
Journal Information:
Industrial and Engineering Chemistry Research, Vol. 52, Issue 9; ISSN 0888-5885
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English