Quantitative prediction of residual wetting film generated in mobilizing a two-phase liquid in a capillary model

Harsh Joshi , Liming Dai

Petroleum ›› 2015, Vol. 1 ›› Issue (4) : 342 -348.

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Petroleum ›› 2015, Vol. 1 ›› Issue (4) :342 -348. DOI: 10.1016/j.petlm.2015.10.005
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Quantitative prediction of residual wetting film generated in mobilizing a two-phase liquid in a capillary model
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Abstract

This research studies the motion of immiscible two-phase liquid flow in a capillary tube through a numerical approach employing the volume of fluid method, for simulating the core-annular flow and water flooding in oil reservoirs of porous media. More specifically, the simulations are a representation of water flooding at a pore scale. A capillary tube model is established with ANSYS Fluent and verified. The numerical results matches well with the existing data available in the literature. Penetration of a less viscous liquid in a liquid of higher viscosity and the development of a residual wetting film of the higher viscosity liquid are thoroughly investigated. The effects of Capillary number, Reynolds Number and Viscosity ratio on the residual wetting film are studied in detail, as the thickness is directly related to the residual oil left in the porous media after water flooding. It should be noticed that the liquids considered in this research can be any liquids of different viscosity not necessarily oil and water. The results of this study can be used as guidance in the field of water flooding.

Keywords

Capillary model / Residual wetting film / Higher viscosity liquid / Water flooding / Numerical simulation / Immiscible flow / Oil slug mobilization

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Harsh Joshi, Liming Dai. Quantitative prediction of residual wetting film generated in mobilizing a two-phase liquid in a capillary model. Petroleum, 2015, 1(4): 342-348 DOI:10.1016/j.petlm.2015.10.005

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Acknowledgments

The Authors are grateful to International Performance Assessment Centre for Geologic Storage of Carbon Dioxide (IPAC-CO2) for allowing us to use that high performance cluster for the computations. We would also like to thank Patrick Mann of IPAC-CO2 for his help with the setup of Fluent on the cluster and for his continual help with the remote operation of Fluent.

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