Using 3D-printed fluidics to study the role of permeability heterogeneity on miscible density-driven convection in porous media

Abstract

Miscible density-driven convection in porous media has important implications to the long-term security of geological carbon sequestration. Laboratory investigations of miscible density-driven convection in heterogeneous porous media have been greatly limited due to the challenge in constructing well-controlled heterogeneous permeability fields. In this study, three-dimensional (3D) printing was used to solve the challenge. Particularly, elementary sediment blocks were 3D printed to construct heterogeneous permeability fields having the desired mean, standard deviation, and spatial correlation length of permeability. A methanol-ethylene-glycol (MEG) solution was placed at the top of the permeability field to trigger miscible density-driven downward convection. Results showed that permeability heterogeneity caused noticeable uncertainty in the total MEG mass transferred into the permeability field, and the uncertainty increased with increasing correlation length of the permeability field. In a heterogeneous permeability field with a larger spatial correlation length, a larger effective vertical permeability is in general favorable for solute mass transfer into the underlying porous medium. Conversely, in a heterogeneous permeability field with a shorter spatial correlation length, a larger effective vertical permeability does not necessarily lead to a higher mass transfer rate. This is because mass transfer across the top boundary through miscible density-driven convection depends on the flow recirculation near the interface. A large effective vertical permeability does not necessarily lead to fast flow recirculation because the former is measured in the vertical direction whereas the latter depends more on the internally-connected, high-permeability streaks within the domain. The 3D-printed elementary sediment blocks can be re-distributed to construct another permeability field easily, which greatly reduces the experimental time and thus significantly increases the total number of experiments that can be conducted, thereby approaching the ergodicity requirement when a large number of random permeability fields is needed.