Investigating Residual Trapping Mechanism in CO2 Storage in the Brine through Analytical and Numerical Simulation Methods

Abstract

Abstract Injecting CO2 in subsurface formations bearing brine creates different storage mechanisms. Firstly, CO2 will have an upward movement due to the buoyancy and it will be trapped below a geological barrier. During this stage of flow brine starts to imbibe into the pore spaces already occupied by CO2. Because of the wetting behavior of the system and CO2-brine capillary pressure, fractions of CO2 remain as residual saturation in the pore spaces. This is an important phenomenon that affects the storage capability and security. Later, and in a long term process, CO2 starts to dissolute into the brine and its density will be increased; and as a result convection mixing phenomena will starts. To clarify the trapping mechanism, two different issues are discussed. One is the one dimensional, two phase behavior during CO2 injection and the second is the water imbibition process that includes the trapping mechanism. By arranging the flow equations and normalizing them by dimensionless parameters, main scaling parameters that define the physics in each problem are obtained. These parameters are CO2-brine mobility ratio and special gravity and capillary dimensionless numbers for each problem. In the water imbibition problem, hysteresis in relative permeability results in modifications to the dimensionless scaling parameters. These parameters are key factors in design and scaling of the experimental measurements to the simulation and analytical results. To verify the analytical analysis, a numerical simulation model is constructed for the problems. Reservoir parameters of the Sleipner CO2 storage reservoir and the Viking formation (Bennion et. al. 2008) are used in this study in order to construct the model. This time, dimensionless parameters are defined according to the reservoir parameters. Analytical models are established based on simplifying assumptions, while simulation results are dependent on key scaling parameters obtained from analytical clarification. This means that they are good representatives of phenomena at reservoir conditions and can be used as a conceptual model before performing a fine scale, time consuming reservoir simulation study.