Prediction of Surfactants' Properties using Multiscale Molecular Modeling Tools: A Review

Benoît Creton 1 Carlos Nieto-Draghi 1, 2 Nicolas Pannacci 1
1 IFPEN - IFP Energies nouvelles
2 DCPA - Direction Chimie et Physico-chimie appliquées
Abstract : During one of the existing Enhanced Oil Recovery (EOR) procedures, a mixture of Alkaline/Surfactant/Polymer (ASP) is injected into wells in order to move the trapped oil from the reservoir to the wellbores. The conception and/or the tuning of new ASP combinations, structures of surfactants and/or mixtures of surfactants is of primary interest to improve the efficiency of a such procedure. Molecular modeling tools can be used to understand microscopic effects, predict surfactants' properties and finally to optimize structures and mixtures of surfactants. We propose in this article a review of the literature on the ability of molecular simulation techniques such as Molecular Dynamics (MD),Monte Carlo (MC) simulations, Dissipative Particle Dynamics (DPD) and upper scale modeling methods such as Quantitative Structure-Property Relationship (QSPR) approaches to predict thermo-physical and structural properties of surfactants.
Document type :
Journal articles
Complete list of metadatas

Cited literature [43 references]  Display  Hide  Download
https://hal-ifp.archives-ouvertes.fr/hal-00815707
Contributor : Catherine Luttringer <>
Submitted on : Friday, April 19, 2013 - 11:26:08 AM
Last modification on : Thursday, February 7, 2019 - 4:30:53 PM
Long-term archiving on : Saturday, July 20, 2013 - 4:01:57 AM

File

ogst110174-Creton.pdf
Publisher files allowed on an open archive

Identifiers

Collections

IFP | OGST

Citation

Benoît Creton, Carlos Nieto-Draghi, Nicolas Pannacci. Prediction of Surfactants' Properties using Multiscale Molecular Modeling Tools: A Review. Oil & Gas Science and Technology - Revue d'IFP Energies nouvelles, Institut Français du Pétrole, 2012, 67 (6), pp.969-982. ⟨10.2516/ogst/2012040⟩. ⟨hal-00815707⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

222

Files downloads

1568

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD