Abstract
Holistic understanding of multiphase reactive flow mechanisms such as CO2 dissolution, multiphase displacement, and snap-off events is vital for optimisation of large-scale industrial operations like CO2 sequestration, enhanced oil recovery, and geothermal energy. Recent advances in three-dimensional (3D) printing allow for cheap and fast manufacturing of complex porosity models, which enable investigation of specific flow processes in a repeatable manner as well as sensitivity analysis for small geometry alterations. However, there are concerns regarding dimensional fidelity, shape conformity and surface quality, and therefore, the printing quality and printer limitations must be benchmarked. We present an experimental investigation into the ability of 3D printing to generate custom-designed micromodels accurately and repeatably down to a minimum pore-throat size of 140 μm, which is representative of the average pore-throat size in coarse sandstones. Homogeneous and heterogeneous micromodel geometries are designed, then the 3D printing process is optimised to achieve repeatable experiments with single-phase fluid flow. Finally, Particle Image Velocimetry is used to compare the velocity map obtained from flow experiments in 3D printed micromodels with the map generated with direct numerical simulation (OpenFOAM software) and an accurate match is obtained. This work indicates that 3D printed micromodels can be used to accurately investigate pore-scale processes present in CO2 sequestration, enhanced oil recovery and geothermal energy applications more cheaply than traditional micromodel methods.
Highlights
Sustainable low-carbon energy production is one of the major challenges society faces today
The error between the velocity map created by the Particle image velocimetry (PIV) analysis and the DNS was calculated by: Fig. 10 Computational domain generated with OpenFoam
We have investigated and showed that single-phase flow PIV works with our experimental setup
Summary
Sustainable low-carbon energy production is one of the major challenges society faces today. Improving engineering of the subsurface for oil and gas production, low-carbon energy storage, and CO2 trapping is a crucial aspect of lowering carbon emissions. The various mechanisms controlling the movement of fluids in the pore space (e.g. viscous displacement, capillary driven flow, and spontaneous imbibition) occur at the pore-scale and are poorly characterised (Blunt 2017). Multiphase fluid displacement is an important process during enhanced oil recovery (Szulczewski et al 2012) and C O2 sequestration (Blunt et al 2013; Orr Fm Jr 1984). There is still little understanding on how those structural and surface properties impact the dynamic multiphase fluid arrangements, which makes the optimization and upscaling of these processes for continuum-scale prediction challenging
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