Dynamics of ion depletion in thin brine films

Embargo End Date
2023-08-26

Type
Article

Authors
Fang, Chao
Sun, Shuyu
Qiao, Rui

KAUST Department
Computational Transport Phenomena Lab
Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division

KAUST Grant Number
OSR-2019-CRG8-4074

Online Publication Date
2021-08-26

Print Publication Date
2021-12

Date
2021-08-26

Submitted Date
2021-04-25

Abstract
Low-salinity water flooding (LSW) effects are generated by the reduction of ionic concentration of environment electrolytes to which thin brine films confined between oil and rock are exposed. We study the dynamics of ion depletion from thin brine films upon a reduction of environment electrolyte concentration using the Poisson-Nernst-Planck (PNP) model. Interestingly, the model predicts that the timescale of ion depletion is not prolonged, but slightly shortened, by charged oil and rock surfaces in comparison with the absence of surface charges. This phenomenon is also reproduced quantitatively using a reduced ion depletion model inspired by the membrane science literature, in which salt diffusion and Donnan equilibrium between brine film and environment are considered. Furthermore, the self-diffusion of ions confined between n-decane and negatively charged quartz surface is investigated via atomistic simulations. It is found that, on average, the diffusion of ions in nanometer-thin brine films is slowed down up to ~8 times compared to that in bulk, although the slowdown relevant to ion depletion in event of a salinity reduction in the environment is most likely only about 2–3 times. These results provide new, pore-scale insights into LSW processes. The reduced salt depletion model and molecular simulation of ion diffusion demonstrated here help to develop a multiscale, bottom-up modeling framework for predicting LSW processes.

Citation
Fang, C., Sun, S., & Qiao, R. (2021). Dynamics of ion depletion in thin brine films. Fuel, 306, 121758. doi:10.1016/j.fuel.2021.121758

Acknowledgements
The authors thank the ARC at Virginia Tech for generous allocations of computer time and Professor Hassan Mahani and Professor Vahid Niasar for helpful discussions. This publication is based upon the work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award no. OSR-2019-CRG8-4074.

Publisher
Elsevier BV

Journal
Fuel

DOI
10.1016/j.fuel.2021.121758

Additional Links
https://linkinghub.elsevier.com/retrieve/pii/S0016236121016380

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