The National Risk Assessment Partnership's integrated assessment model for carbon storage: A tool to support decision making amidst uncertainty. (September 2016)

• Record Type: Journal Article
• Authors: Pawar, Rajesh J.; Bromhal, Grant S.; Chu, Shaoping; Dilmore, Robert M.; Oldenburg, Curtis M.; Stauffer, Philip H.; Zhang, Yingqi; Guthrie, George D.
• Is Part Of: International journal of greenhouse gas control. Volume 52(2016:Sep.)
• Page Start: 175
• Page End: 189
• Publication Date: 2016-09
• Subjects: Risk assessment -- Risk quantification -- CO2 sequestration -- Risk profiles -- Integrated assessment model -- Reduced order models -- NRAP; Greenhouse gases -- Environmental aspects -- Periodicals; Air -- Purification -- Technological innovations -- Periodicals; Gaz à effet de serre -- Périodiques; Gaz à effet de serre -- Réduction -- Périodiques; Air -- Purification -- Technological innovations; Greenhouse gases -- Environmental aspects; Periodicals; 363.73874605
• DOI: 10.1016/j.ijggc.2016.06.015
• Languages: English
• ISSNs: 1750-5836

Abstract

Highlights: We provide an overview of NRAP's Integrated Assessment Model (NRAP-IAM-CS) for quantification of risks at geologic CO2 storage sites. Integrated assessment modeling approach can be effective in predicting long-term performance of an entire geologic CO2 storage system. NRAP-IAM-CS can be used to compute risk profiles as well as help inform decision making process. NRAP-IAM-CS can be used to perform multi-variate analysis taking into consideration uncertain variables in geologic CO2 storage system. Abstract: The US DOE-funded National Risk Assessment Partnership (NRAP) has developed an integrated assessment model (NRAP-IAM-CS) that can be used to simulate carbon dioxide (CO2 ) injection, migration, and associated impacts at a geologic carbon storage site. The model, NRAP-IAM-CS, incorporates a system-modeling-based approach while taking into account the full subsurface system from the storage reservoir to groundwater aquifers and the atmosphere. The approach utilizes reduced order models (ROMs) that allow fast computations of entire system performance even for periods of hundreds to thousands of years. The ROMs are run in Monte Carlo mode allowing estimation of uncertainties of the entire system without requiring long computational times. The NRAP-IAM-CS incorporates ROMs that realistically represent several key processes and properties of storage reservoirs, wells, seals, and groundwater aquifers. Results from the NRAP-IAM-CS model are used to quantify risk profiles for selected parameter distributions of reservoir properties, seal properties, numbers of wells, well properties, thief zones, and groundwater aquifer properties. A series of examples is used to illustrate how the risk under different storage conditions evolves over time, both during injection, in the near-term post injection period, and over the long term. It is also shown how results from NRAP-IAM-CS can be used to investigate the importance of different parameters on risk of leakage and risk of groundwater contamination under different storage conditions.