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- W4287282552 abstract "Holistic understanding of multiphase reactive flow mechanisms such as CO$_2$ dissolution, multiphase displacement, and snap-off events are vital for optimisation of large-scale industrial operations like CO$_2$ 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 micrometers, 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 CO$_2$ sequestration, enhanced oil recovery and geothermal energy applications more cheapely than traditional micromodel methods." @default.
- W4287282552 created "2022-07-25" @default.
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- W4287282552 date "2021-03-05" @default.
- W4287282552 modified "2023-09-30" @default.
- W4287282552 title "Benchmarking the viability of 3D printed micromodels for single phase flow using Particle Image Velocimetry and Direct Numerical Simulations" @default.
- W4287282552 doi "https://doi.org/10.48550/arxiv.2103.03597" @default.
- W4287282552 hasPublicationYear "2021" @default.
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