Experimental Investigation of Solubility Trapping in 3D Printed Micromodels

Understanding interfacial mass transfer during dissolution of gas in a liquid is vital for optimizing large-scale carbon capture and storage operations. While the dissolution of CO₂ bubbles in reservoir brine is a crucial mechanism towards safe CO₂ storage, it is a process that occurs at the pore-scale and is not yet fully understood. Direct numerical simulation (DNS) models describing this type of dissolution exist and have been validated with semi-analytical models on simple cases like a rising bubble in a liquid column. However, DNS models have not been experimentally validated for more complicated scenarios such as dissolution of trapped CO₂ bubbles in pore geometries where there are few experimental datasets. In this work, we present an experimental and numerical study of trapping and dissolution of CO₂ bubbles in 3D printed micromodel geometries. We used 3D printing technology to generate three different geometries, a single cavity geometry, a triple cavity geometry, and a multiple channel geometry. To investigate the repeatability of the trapping and dissolution experimental results, each geometry was printed three times, and three identical experiments were performed for each geometry. The experiments were performed at a low capillary number (Ca = 3.33 x 10-6), representative of flow during CO₂ storage applications. The DNS simulations were then performed and compared with the experimental results. Our results show experimental reproducibility and consistency in terms of CO₂ trapping and the CO₂ dissolution process. At such a low capillary number, our numerical simulator cannot model the process accurately due to parasitic currents and the strong time-step constraints associated with capillary waves. However, we show that, for the single and triple cavity geometry, the interfacial transfer and resulting bubble dissolution can be reproduced by a numerical strategy where the interfacial tension is divided by 100 to relax the capillary time-step constraints. The full experimental dataset is provided and can be used to benchmark and improve future numerical models.