Determining CO2-Brine Relative Permeability for CO2 Sequestration: A Pore Network Modelling Study

Seif Hemed, Thraiye
Predicting CO2 migration in the subsurface after its injection is crucial for successful long-term fluid storage. Relative permeability is one of the essential parameters that aid in accurately predicting injectivity, plume migration, and residual CO2 trapping. Despite the existing literature on CO2-brine relative permeability, there still needs to be more data to understand the behaviour of CO2 after being injected into the subsurface for future predictions. However, lab-based relative permeability experiments are usually expensive and time-consuming. This research focuses on conducting pore network modelling experiments using OpenPNM, an open-source Python package. It compares the results with lab-based experimental and other PNM-generated results to verify OpenPNM’s reliability as a cheaper, faster and easily accessible solution. Regardless of the lithology, homogeneous samples (Berea sandstone and a carbonate) exhibited a good match of results. However, a relatively heterogeneous sample (Mt Simon sandstone) did not have matching relative permeability curves. When altering the network parameters in OpenPNM, spacing impacted absolute permeability but had no effect on relative permeability, a larger shape value generated smoother curves but required higher computational power, and a larger connectivity value caused a shift of the relative permeability curves to the right.
Citation Formats
T. Seif Hemed, “Determining CO2-Brine Relative Permeability for CO2 Sequestration: A Pore Network Modelling Study,” M.S. - Master of Science, Middle East Technical University, 2023.