Numerical Investigations of Water-Lubricated Core Annular Flow (CAF) for Heavy Oil Transportation
Year: 2025
Type: article
Abstract: This study examines the flow behavior of water-lubricated heavy oil transport utilizing the core annular flow (CAF) technique. The goal is to enhance efficiency and minimize risks in pipeline operations. The flow was numerically simulated in a horizontal pipe using a Large Eddy Simulation (LES) model within a commercial Computational Fluid Dynamics (CFD) framework. The Geo Reconstruct scheme is employed to accurately capture the oil–water interface, and both oil and water initialization methods were assessed against experimental data. Results show that the LES model accurately reproduces the main flow features observed experimentally, particularly for low-viscosity oil–water systems. This suggests that the model can be a reliable tool for predicting flow behaviour in similar fluid systems. Further validation with varying parameters could enhance its applicability across a broader range of conditions. In cases of heavy oil, the velocity profile remains nearly constant within the oil core, indicating rigid body-like motion surrounded by a turbulent water annulus. Turbulence intensity and oil volume fraction distributions were closely related, with higher turbulence in water and lower in oil. Although wall adhesion modelling limited fouling prediction, simulations confirmed that fouling can significantly increase pressure losses. This illustrates the value of considering both fluid dynamics and material interactions in such systems. Future studies could explore the impact of varying temperature and pressure conditions on fouling behaviour to further refine predictive models. Overall, the LES approach proved suitable for analysing turbulent CAF, offering insights for optimizing viscosity ratios, flow rates, and design parameters for safer and more efficient heavy oil transport.
Source: Computation
Authors: Salim Al Jadidi, Dadapeer Doddamani, Yahya Ubaid Al Shamsi, Ibrahim Nasser Al Siyabi, Siva Subramanian
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,172
OpenAlex ID: W4416916906