Long-term stabilization of injected carbon dioxide (CO2) is an essential component of risk management for geological carbon sequestration operations. However, migration and trapping phenomena are inherently complex, involving processes that act over multiple spatial and temporal scales. One example involves centimeter-scale density instabilities in the dissolved CO2 region leading to large-scale convective mixing that can be a significant driver for CO2 dissolution. Another example is the potentially important effect of capillary forces, in addition to buoyancy and viscous forces, on the evolution of mobile CO2. Local capillary effects lead to a capillary transition zone, or capillary fringe, where both fluids are present in the mobile state. This small-scale effect may have a significant impact on large-scale plume migration as well as long-term residual and dissolution trapping. Computational models that can capture both large and small-scale effects are essential to predict the role of these processes on the long-term storage security of CO2 sequestration operations. Conventional modeling tools are unable to resolve sufficiently all of these relevant processes when modeling CO2 migration in large-scale geological systems. Herein, we present a vertically-integrated approach to CO2 modeling that employs upscaled representations of these subgrid processes. We apply the model to the Johansen formation, a prospective site for sequestration of Norwegian CO2 emissions, and explore the sensitivity of CO2 migration and trapping to subscale physics. Model results show the relative importance of different physical processes in large-scale simulations. The ability of models such as this to capture the relevant physical processes at large spatial and temporal scales is important for prediction and analysis of CO2 storage sites.
All Science Journal Classification (ASJC) codes
- Management, Monitoring, Policy and Law
- Industrial and Manufacturing Engineering
- Capillary trapping
- Long-term storage security
- Solubility trapping
- Vertically integrated models