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Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers

Journal Article · · International Journal of Greenhouse Gas Control
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  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. National Energy Technology Lab. (NETL), Pittsburgh, PA (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
+ Show Author Affiliations
Here, we evaluated and compared the effectiveness of four surface-based geophysical monitoring methods to downhole pressure and chemical methods to detect brine and CO2 leakage in underground sources of drinking water overlying a CO2 storage reservoir. This assessment uses synthetic monitoring data generated from 400 simulated aquifer impact data sets. Here, the six monitoring techniques can detect impacted groundwater once 20,000 tonnes of CO2 have leaked into the drinking water resource. Geophysical methods are most effective at detecting shallow plumes. Although downhole monitoring methods outperform geophysical methods in detecting deep plumes, geophysical methods may help reduce the false negative during the post injection site care because they detect impacted groundwater where downhole sensors may be absent.
Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States); National Energy Technology Lab. (NETL), Pittsburgh, PA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Fossil Energy (FE); USDOE Office of Fossil Energy and Carbon Management (FECM)
Grant/Contract Number:
89233218CNA000001; AC52-07NA27344
OSTI ID:
1572327
Alternate ID(s):
OSTI ID: 1607758
OSTI ID: 1780315
OSTI ID: 1591622
OSTI ID: 1591620
OSTI ID: 1591621
OSTI ID: 1591623
OSTI ID: 1597614
Report Number(s):
LA-UR--19-21588; LLNL-JRNL--759257
Journal Information:
International Journal of Greenhouse Gas Control, Journal Name: International Journal of Greenhouse Gas Control Journal Issue: C Vol. 90; ISSN 1750-5836
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (2)

Kimberlina 1.2 Velocity Models and Seismic Data dataset January 2021
Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets dataset January 2022

Figures / Tables (19)

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Related Subjects

58 GEOSCIENCES
Drinking water aquifers
Earth Sciences
Electrical resistivity tomography (ERT)
Gravity
Leak detection
Magnetotellurics (MT)
Pressure monitoring
Reflection
Seismic
Total dissolved solids (TDS)
Wellbore leakage