Speaker
Description
Carbon capture and storage (CCS) is a proven technology to mitigate the impact of climate change by reducing anthropogenic CO2 emissions. However, to ensure the efficiency and safety of this storage, it is essential to understand the mechanisms that govern CO2 flow within the porous medium. The behavior of multiphase flow is strongly influenced by microscopic phenomena, such as relative permeability hysteresis and capillary pressure, which determine the phase distribution within the rock pores. Flow conditions, as well as the interaction between fluids in heterogeneous rocks, directly impact the storage efficiency and mobility of injected CO2. Numerical simulation offers a robust means to understand and predict CO2 behavior in porous media, allowing analyses at different scales.
This work aims to develop a methodology and numerical code to simulate supercritical CO2 flows in brine-saturated heterogeneous rocks, encompassing drainage and imbibition processes on two different scales the pore scale and the plug scale. On the pore scale the Navier Stokes equations are solved while on the plug scale the two-phase flow is resolved via Darcy equations. The two scales are connected through an upscaling process: 1) Several subsamples are taken from the CT imaged 3D plug with highly resolved pore geometry; 2) Drainage followed by imbibition processes are simulated to obtain the hysteretic capillary pressure and relative permeability functions; 3) The coarse grid on the plug scale is populated by the different saturation curves sets depending on their statistical proximity to the subsamples selected in step 1; 4) Simulations of drainage and imbibition processes on the plug scale are performed and are giving insight of the effect of heterogeneity of the saturation data on the trapped CO2 in place.
This proposed workflow allows for a deeper understanding of the capillary trapping phenomenon during CO2 flow in porous media, helping to characterize capillary hysteresis during drainage and imbibition processes, and enabling the identification of conditions under which storage is most efficient.
| Country | Brazil |
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