Regular Article
A review on polymer, gas, surfactant and nanoparticle adsorption modeling in porous media
College of Petroleum Engineering & Geosciences, King Fahd University of Petroleum & Minerals, Dhahran 31261, KSA
* Corresponding author: awotunde@kfupm.edu.sa
Received:
2
May
2020
Accepted:
7
August
2020
Adsorption is a rock surface phenomenon and has increasingly become popular, especially in particle-transport applications across many fields. This has drawn a remarkable number of publications from the industry and academia in the last decade, with many review articles focused on adsorption of polymers, surfactants, gas, and nanoparticles in porous media with main applications in Enhanced Oil Recovery (EOR). The discussions involved both experimental and modeling approaches to understanding and efficiently mimicking the particle transport in a bid to solve pertinent problems associated with particle retention on surfaces. The governing mechanisms of adsorption and desorption constitute an area under active research as many models have been proposed but the physics has not been fully honored. Thus, there is a need for continuous research effort in this field. Although adsorption/desorption process is a physical phenomenon and a reversible process resulting from inter-molecular and the intramolecular association between molecules and surfaces, modeling these phenomena requires molecular level understanding. For this reason, there is a wide acceptance of molecular simulation as a viable modeling tool among scientists in this area. This review focuses on existing knowledge of adsorption modeling as it relates to the petroleum industry cutting across flow through porous media and EOR mostly involving polymer and surfactant retention on reservoir rocks with the associated problems. The review also analyzes existing models to identify gaps in research and suggest some research directions to readers.
© I. Mohammed et al., published by IFP Energies nouvelles, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.