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Title: Applicability of aquifer impact models to support decisions at CO2 sequestration sites

Abstract

The National Risk Assessment Partnership has developed a suite of tools to assess and manage risk at CO 2 sequestration sites. This capability includes polynomial or look-up table based reduced-order models (ROMs) that predict the impact of CO 2 and brine leaks on overlying aquifers. The development of these computationally-efficient models and the underlying reactive transport simulations they emulate has been documented elsewhere (Carroll et al., 2014a,b; Dai et al., 2014; Keating et al., 2016). In this paper, we seek to demonstrate applicability of ROM-based analysis by considering what types of decisions and aquifer types would benefit from the ROM analysis. We present four hypothetical examples where applying ROMs, in ensemble mode, could support decisions during a geologic CO 2 sequestration project. These decisions pertain to site selection, site characterization, monitoring network evaluation, and health impacts. In all cases, we consider potential brine/CO 2 leak rates at the base of the aquifer to be uncertain. We show that derived probabilities provide information relevant to the decision at hand. Although the ROMs were developed using site-specific data from two aquifers (High Plains and Edwards), the models accept aquifer characteristics as variable inputs and so they may have more broad applicability. Wemore » conclude that pH and TDS predictions are the most transferable to other aquifers based on the analysis of the nine water quality metrics (pH, TDS, 4 trace metals, 3 organic compounds). Guidelines are presented for determining the aquifer types for which the ROMs should be applicable.« less

Authors:
 [1];  [2];  [3];  [3];  [3];  [4];  [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
OSTI Identifier:
1394966
Alternate Identifier(s):
OSTI ID: 1396565; OSTI ID: 1454486; OSTI ID: 1463023
Report Number(s):
LA-UR-15-28985; PNNL-SA-114632; LLNL-JRNL-737443
Journal ID: ISSN 1750-5836
Grant/Contract Number:  
AC52-06NA25396; AC05-76RL01830; AC02-05CH11231; AC52-07NA27344
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
International Journal of Greenhouse Gas Control
Additional Journal Information:
Journal Volume: 52; Journal Issue: C; Journal ID: ISSN 1750-5836
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Earth Sciences; Carbon sequestration; Groundwater impacts; Risk assessment; Reduced-order modeling; 58 GEOSCIENCES

Citation Formats

Keating, Elizabeth, Bacon, Diana, Carroll, Susan, Mansoor, Kayyum, Sun, Yunwei, Zheng, Liange, Harp, Dylan, and Dai, Zhenxue. Applicability of aquifer impact models to support decisions at CO2 sequestration sites. United States: N. p., 2016. Web. doi:10.1016/j.ijggc.2016.07.001.
Keating, Elizabeth, Bacon, Diana, Carroll, Susan, Mansoor, Kayyum, Sun, Yunwei, Zheng, Liange, Harp, Dylan, & Dai, Zhenxue. Applicability of aquifer impact models to support decisions at CO2 sequestration sites. United States. https://doi.org/10.1016/j.ijggc.2016.07.001
Keating, Elizabeth, Bacon, Diana, Carroll, Susan, Mansoor, Kayyum, Sun, Yunwei, Zheng, Liange, Harp, Dylan, and Dai, Zhenxue. 2016. "Applicability of aquifer impact models to support decisions at CO2 sequestration sites". United States. https://doi.org/10.1016/j.ijggc.2016.07.001. https://www.osti.gov/servlets/purl/1394966.
@article{osti_1394966,
title = {Applicability of aquifer impact models to support decisions at CO2 sequestration sites},
author = {Keating, Elizabeth and Bacon, Diana and Carroll, Susan and Mansoor, Kayyum and Sun, Yunwei and Zheng, Liange and Harp, Dylan and Dai, Zhenxue},
abstractNote = {The National Risk Assessment Partnership has developed a suite of tools to assess and manage risk at CO 2 sequestration sites. This capability includes polynomial or look-up table based reduced-order models (ROMs) that predict the impact of CO 2 and brine leaks on overlying aquifers. The development of these computationally-efficient models and the underlying reactive transport simulations they emulate has been documented elsewhere (Carroll et al., 2014a,b; Dai et al., 2014; Keating et al., 2016). In this paper, we seek to demonstrate applicability of ROM-based analysis by considering what types of decisions and aquifer types would benefit from the ROM analysis. We present four hypothetical examples where applying ROMs, in ensemble mode, could support decisions during a geologic CO 2 sequestration project. These decisions pertain to site selection, site characterization, monitoring network evaluation, and health impacts. In all cases, we consider potential brine/CO 2 leak rates at the base of the aquifer to be uncertain. We show that derived probabilities provide information relevant to the decision at hand. Although the ROMs were developed using site-specific data from two aquifers (High Plains and Edwards), the models accept aquifer characteristics as variable inputs and so they may have more broad applicability. We conclude that pH and TDS predictions are the most transferable to other aquifers based on the analysis of the nine water quality metrics (pH, TDS, 4 trace metals, 3 organic compounds). Guidelines are presented for determining the aquifer types for which the ROMs should be applicable.},
doi = {10.1016/j.ijggc.2016.07.001},
url = {https://www.osti.gov/biblio/1394966}, journal = {International Journal of Greenhouse Gas Control},
issn = {1750-5836},
number = C,
volume = 52,
place = {United States},
year = {Mon Jul 25 00:00:00 EDT 2016},
month = {Mon Jul 25 00:00:00 EDT 2016}
}

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Cited by: 23 works
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