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Paper No. 3
Presentation Time: 8:40 AM

ENHANCED PERFORMANCE ASSESSMENT TOOLS FOR CARBON SYSTEM MANAGEMENT


WANG, Yifeng, SUN, Amy Cha-Tien, HADGU, Teklu, DEWERS, Thomas, JOVE-COLON, Carlos and MCNEISH, Jerry, P. O. Box, MS 0779, Sandia National Laboratories, Albuquerque, NM 87185-0779, ywang@sandia.gov

Carbon capture and sequestration (CCS) is an option to mitigate impacts of atmospheric carbon emission. Initial studies indicate that for long-term carbon sequestration/storage (CS) to be effective the leakage rates must be less than 0.1 – 0.01%/yr. Recent efforts have been made to apply the existing probabilistic performance assessment (PA) methodology developed for deep nuclear waste geologic repositories to evaluate the effectiveness of subsurface carbon storage. However, to address the most pressing management, regulatory, and scientific concerns with CS, the existing PA methodology and tools must be enhanced and upgraded. For example, in the evaluation of a nuclear waste repository, a PA model is essentially a forward model that samples input parameters and runs multiple realizations to estimate future consequences and determine important parameters driving the system performance. In the CS evaluation, however, a PA model must be able to run both forward and inverse calculations to support real-time site monitoring as an integral part of the design and operational phases. The monitoring data must be continually fused into the PA model through model inversion and parameter estimation. Model calculations will in turn guide the design of optimal monitoring and carbon-injection strategies (e.g., in terms of monitoring techniques, locations, and time intervals). Under the support of Sandia National Laboratories LDRD funding, we have formulated the advanced PA concept for CS systems and established the related PA framework. The new PA framework includes a built-in optimization capability for model parameterization and monitoring system design. The capabilities of this framework have been demonstrated with a hypothetical CS system. The work presented here lays the foundation for the development of new generation PA tools for effective management of CS activities.

This work was performed at Sandia National Laboratories, which is a multiprogram laboratory operated by Sandia Corporation, a Lockheed-Martin Company, for the DOE under contract DE-AC04-94AL8500.

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