skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: The National Risk Assessment Partnership’s integrated assessment model for carbon storage: A tool to support decision making amidst uncertainty

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 (CO 2) 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. Finally, it is also shown how results from NRAP-IAM-CS can bemore » used to investigate the importance of different parameters on risk of leakage and risk of groundwater contamination under different storage conditions.« less

Authors:
 [1];  [2];  [1];  [2];  [3];  [1];  [3];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. National Energy Technology Lab. (NETL), Morgantown, WV (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); National Energy Technology Lab. (NETL), Morgantown, WV (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
OSTI Identifier:
1471021
Alternate Identifier(s):
OSTI ID: 1396563
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
International Journal of Greenhouse Gas Control
Additional Journal Information:
Journal Volume: 52; Journal ID: ISSN 1750-5836
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; risk assessment; risk quantification; CO2 sequestration; risk profiles; integrated assessment model; reduced order models; NRAP

Citation Formats

Pawar, Rajesh J., Bromhal, Grant S., Chu, Shaoping, Dilmore, Robert M., Oldenburg, Curtis M., Stauffer, Philip H., Zhang, Yingqi, and Guthrie, George D. The National Risk Assessment Partnership’s integrated assessment model for carbon storage: A tool to support decision making amidst uncertainty. United States: N. p., 2016. Web. doi:10.1016/j.ijggc.2016.06.015.
Pawar, Rajesh J., Bromhal, Grant S., Chu, Shaoping, Dilmore, Robert M., Oldenburg, Curtis M., Stauffer, Philip H., Zhang, Yingqi, & Guthrie, George D. The National Risk Assessment Partnership’s integrated assessment model for carbon storage: A tool to support decision making amidst uncertainty. United States. doi:10.1016/j.ijggc.2016.06.015.
Pawar, Rajesh J., Bromhal, Grant S., Chu, Shaoping, Dilmore, Robert M., Oldenburg, Curtis M., Stauffer, Philip H., Zhang, Yingqi, and Guthrie, George D. Mon . "The National Risk Assessment Partnership’s integrated assessment model for carbon storage: A tool to support decision making amidst uncertainty". United States. doi:10.1016/j.ijggc.2016.06.015. https://www.osti.gov/servlets/purl/1471021.
@article{osti_1471021,
title = {The National Risk Assessment Partnership’s integrated assessment model for carbon storage: A tool to support decision making amidst uncertainty},
author = {Pawar, Rajesh J. and Bromhal, Grant S. and Chu, Shaoping and Dilmore, Robert M. and Oldenburg, Curtis M. and Stauffer, Philip H. and Zhang, Yingqi and Guthrie, George D.},
abstractNote = {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. Finally, 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.},
doi = {10.1016/j.ijggc.2016.06.015},
journal = {International Journal of Greenhouse Gas Control},
number = ,
volume = 52,
place = {United States},
year = {Mon Jul 18 00:00:00 EDT 2016},
month = {Mon Jul 18 00:00:00 EDT 2016}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

Save / Share: