Potential CO2 and brine leakage through wellbore pathways for geologic CO2 sequestration using the National Risk Assessment Partnership tools: Application to the Big Sky Regional Partnership

• Published in: International journal of greenhouse gas control Vol. 81; no. C; pp. 44 - 65
• Main Authors: Onishi, Tsubasa, Nguyen, Minh C., Carey, J. William, Will, Bob, Zaluski, Wade, Bowen, David W., Devault, Bryan C., Duguid, Andrew, Zhou, Quanlin, Fairweather, Stacey H., Spangler, Lee H., Stauffer, Philip H.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01.02.2019; Elsevier
• Subjects: Design of experiment; Geologic CO2 sequestration; GEOSCIENCES; Reservoir simulation; Risk assessment; Uncertainty assessment; Geologic CO2 sequestration; Uncertainty assessment; Risk assessment; Reservoir simulation; Design of experiment
• ISSN: 1750-5836; 1878-0148
• DOI: 10.1016/j.ijggc.2018.12.002

•Application of National Risk Assessment Partnership (NRAP) tools to geologic CO2 sequestration in the Kevin Dome in Montana.•Sensitivity analysis of various reservoir properties and quality of legacy wells.•The developed risk assessment workflow using NRAP tools is shown to greatly reduce the computational burden.•The powerful stochastic framework is capable of risk assessment in field-scale applications. Geologic CO2 sequestration (GCS) has received high-level attention from the global scientific community as a response to climate change due to higher concentrations of CO2 in the atmosphere. However, GCS in saline aquifers poses certain risks including CO2/brine leakage through wells or non-sealing faults into groundwater or to the earth’s surface. Understanding crucial reservoir parameters and other geologic features affecting the likelihood of these leakage occurrences will aid the decision-making process regarding GCS operations. In this study, we develop a science-based methodology for quantifying risk profiles at geologic CO2 sequestration sites as part of US DOE’s National Risk Assessment Partnership (NRAP). We apply NRAP tools to a field scale project in a fractured saline aquifer located at Kevin Dome, Montana, which is part of DOE’s Big Sky Carbon Sequestration Partnership project. Risks associated with GCS injection and monitoring are difficult to quantify due to a dearth of data and uncertainties. One solution is running a large number of numerical simulations of the primary CO2 injection reservoir, shallow reservoirs/aquifers, faults, and wells to address leakage risks and uncertainties. However, a full-physics simulation is not computationally feasible because the model is too large and requires fine spatial and temporal discretization to accurately reproduce complex multiphase flow processes. We employ the NRAP Integrated Assessment Model (NRAP-IAM), a hybrid system model developed by the US-DOE for use in performance and quantitative risk assessment of CO2 sequestration. The IAM model requires reduced order models (ROMs) developed from numerical reservoir simulations of a primary CO2 injection reservoir. The ROMs are linked with discrete components of the NRAP-IAM including shallow reservoirs/aquifers and the atmosphere through potential leakage pathways. A powerful stochastic framework allows NRAP-IAM to be used to explore complex interactions among a large number of uncertain variables and to help evaluate the likely performance of potential sequestration sites. Using the NRAP-IAM, we find that the potential amount of CO2 leakage is most sensitive to values of permeability, end-point CO2 relative permeability, hysteresis of CO2 relative permeability, capillary pressure, and permeability of confining rocks. In addition to demonstrating the application of the NRAP risk assessment tools, this work shows that GCS in the Kevin Dome has a higher probability of encountering injectivity limitations during injection of CO2 into the Middle Duperow formation than previous studies have calculated. Finally, we estimate very low risk of CO2 leakage to the atmosphere unless the quality of the legacy well completions is extremely poor.