TY - JOUR
T1 - A methodology to estimate maximum probable leakage along old wells in a geological sequestration operation
AU - Nogues, Juan P.
AU - Court, Benjamin
AU - Dobossy, Mark
AU - Nordbotten, Jan M.
AU - Celia, Michael Anthony
N1 - Funding Information:
This work was supported in part by the National Science Foundation under Grant EAR-0934722 ; the Environmental Protection Agency under Cooperative Agreement RD-83438501; the Department of Energy under Award No. DE-FE0001161, CFDA No. 81,089;the Princeton Environmental Institute Science, Technology and Environmental Policy (PEI-STEP) Fellowship ; and the Carbon Mitigation Initiative at Princeton University .
PY - 2012/3
Y1 - 2012/3
N2 - This study presents a computational methodology to estimate the maximum probable leakage of CO2 along old wells in a geological sequestration operation. The methodology quantifies the maximum probable CO2 leakage as a function of the statistical characterization of existing wells. We use a Monte Carlo approach based on a computationally efficient simulator to run many thousands of realizations. Results from the Monte Carlo simulations are used to determine maximum leakage rates at 95% confidence. Uncertainty in the analysis is due to leaky well parameters, which are known to be highly uncertain. We consider a wide range of parameter values, with our focus on assignment of effective well permeability values and the correlation of those values along individual wells. We use a specific location in Alberta, Canada, to demonstrate the methodology using a hypothetical injection and an assumed probability structure for the well permeabilities. We show that for a wide range of parameter values, the amount of leakage is within the bounds suggested as acceptable for climate change mitigation.
AB - This study presents a computational methodology to estimate the maximum probable leakage of CO2 along old wells in a geological sequestration operation. The methodology quantifies the maximum probable CO2 leakage as a function of the statistical characterization of existing wells. We use a Monte Carlo approach based on a computationally efficient simulator to run many thousands of realizations. Results from the Monte Carlo simulations are used to determine maximum leakage rates at 95% confidence. Uncertainty in the analysis is due to leaky well parameters, which are known to be highly uncertain. We consider a wide range of parameter values, with our focus on assignment of effective well permeability values and the correlation of those values along individual wells. We use a specific location in Alberta, Canada, to demonstrate the methodology using a hypothetical injection and an assumed probability structure for the well permeabilities. We show that for a wide range of parameter values, the amount of leakage is within the bounds suggested as acceptable for climate change mitigation.
KW - Carbon capture and storage
KW - Geological sequestration
KW - Risk assessment
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U2 - 10.1016/j.ijggc.2011.12.003
DO - 10.1016/j.ijggc.2011.12.003
M3 - Article
AN - SCOPUS:84858394434
SN - 1750-5836
VL - 7
SP - 39
EP - 47
JO - International Journal of Greenhouse Gas Control
JF - International Journal of Greenhouse Gas Control
ER -