Statistical Approaches to Quantifying Uncertainty of Monitoring and Performance at Geologic CO2 Storage Sites

<p>Geologic carbon dioxide (CO2) storage is one approach for mitigating concentrations of CO2 in the atmosphere that are caused by stationary anthropogenic inputs. Injecting CO2 into the subsurface for long-term storage is an “engineered-natural system”. This engineered-natural system is complex, with potential interactions during CO2 injection between CO2 and other reservoir fluids and various components of the geologic system. The National Risk Assessment Partnership (NRAP) is an initiative within DOE’s Office of Fossil Energy that is improving the fundamental understanding of the complex science behind engineered-natural systems and is developing the risk assessment tools that are needed for safe, permanent geologic CO2 storage. The NRAP technical approach entails an iterative modeling process that integrates component models into a system model which may then be used to provide quantitative assessments of potential risks and to design monitoring protocols that will effectively monitor risks at a geologic CO2 storage project. A theme throughout all phases of the NRAP approach is quantifying uncertainty and variability. The focus of this dissertation is to contribute statistical methods and/or approaches for quantifying uncertainty and variability with respect to both monitoring and performance at geologic CO2 storage sites. These methods are intended for future use by NRAP or other geologic CO2 storage practitioners and may be incorporated into broader modeling approaches. However, the results and contributions from this work extend beyond geologic CO2 storage and apply to other subsurface engineered-natural systems.