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

Title: Probabilistic analysis of CO 2 storage mechanisms in a CO 2 -EOR field using polynomial chaos expansion

Authors:
ORCiD logo; ; ; ;
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1325349
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
International Journal of Greenhouse Gas Control
Additional Journal Information:
Journal Volume: 51; Journal Issue: C; Related Information: CHORUS Timestamp: 2017-10-03 15:44:47; Journal ID: ISSN 1750-5836
Publisher:
Elsevier
Country of Publication:
Netherlands
Language:
English

Citation Formats

Jia, Wei, McPherson, Brian J., Pan, Feng, Xiao, Ting, and Bromhal, Grant. Probabilistic analysis of CO 2 storage mechanisms in a CO 2 -EOR field using polynomial chaos expansion. Netherlands: N. p., 2016. Web. doi:10.1016/j.ijggc.2016.05.024.
Jia, Wei, McPherson, Brian J., Pan, Feng, Xiao, Ting, & Bromhal, Grant. Probabilistic analysis of CO 2 storage mechanisms in a CO 2 -EOR field using polynomial chaos expansion. Netherlands. doi:10.1016/j.ijggc.2016.05.024.
Jia, Wei, McPherson, Brian J., Pan, Feng, Xiao, Ting, and Bromhal, Grant. Mon . "Probabilistic analysis of CO 2 storage mechanisms in a CO 2 -EOR field using polynomial chaos expansion". Netherlands. doi:10.1016/j.ijggc.2016.05.024.
@article{osti_1325349,
title = {Probabilistic analysis of CO 2 storage mechanisms in a CO 2 -EOR field using polynomial chaos expansion},
author = {Jia, Wei and McPherson, Brian J. and Pan, Feng and Xiao, Ting and Bromhal, Grant},
abstractNote = {},
doi = {10.1016/j.ijggc.2016.05.024},
journal = {International Journal of Greenhouse Gas Control},
number = C,
volume = 51,
place = {Netherlands},
year = {Mon Aug 01 00:00:00 EDT 2016},
month = {Mon Aug 01 00:00:00 EDT 2016}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1016/j.ijggc.2016.05.024

Citation Metrics:
Cited by: 8works
Citation information provided by
Web of Science

Save / Share:
  • 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 amore » 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.« less
  • Extraction and treatment of in situ water can minimize risk for large-scale CO 2 injection in saline aquifers during carbon capture, utilization, and storage (CCUS), and for enhanced oil recovery (EOR). Additionally, treatment and reuse of oil and gas produced waters for hydraulic fracturing will conserve scarce fresh-water resources. Each treatment step, including transportation and waste disposal, generates economic and engineering challenges and risks; these steps should be factored into a comprehensive assessment. We expand the water treatment model (WTM) coupled within the sequestration system model CO 2-PENS and use chemistry data from seawater and proposed injection sites in Wyoming,more » to demonstrate the relative importance of different water types on costs, including little-studied effects of organic pretreatment and transportation. We compare the WTM with an engineering water treatment model, utilizing energy costs and transportation costs. Specific energy costs for treatment of Madison Formation brackish and saline base cases and for seawater compared closely between the two models, with moderate differences for scenarios incorporating energy recovery. Transportation costs corresponded for all but low flow scenarios (<5000 m 3/d). Some processes that have high costs (e.g., truck transportation) do not contribute the most variance to overall costs. Other factors, including feed-water temperature and water storage costs, are more significant contributors to variance. These results imply that the WTM can provide good estimates of treatment and related process costs (AACEI equivalent level 5, concept screening, or level 4, study or feasibility), and the complex relationships between processes when extracted waters are evaluated for use during CCUS and EOR site development.« less
  • Cited by 5
  • Cited by 9
  • Cited by 1