Curvature-Based Equation of State for Microemulsion-Phase Behavior

Victor A. Torrealba, Russell T. Johns, Hussein Hoteit

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

An accurate description of the microemulsion-phase behavior is critical for many industrial applications, including surfactant flooding in enhanced oil recovery (EOR). Recent phase-behavior models have assumed constant-shaped micelles, typically spherical, using netaverage curvature (NAC), which is not consistent with scattering and microscopy experiments that suggest changes in shapes of the continuous and discontinuous domains. On the basis of the strong evidence of varying micellar shape, principal micellar curves were used recently to model interfacial tensions (IFTs). Huh’s scaling equation (Huh 1979) also was coupled to this IFT model to generate phase-behavior estimates, but without accounting for the micellar shape. \nIn this paper, we present a novel microemulsion-phase-behavior equation of state (EoS) that accounts for changing micellar curvatures under the assumption of a general-prolate spheroidal geometry, instead of through Huh’s equation. This new EoS improves phase-behavior-modeling capabilities and eliminates the use of NAC in favor of a more-physical definition of characteristic length. Our new EoS can be used to fit and predict microemulsion-phase behavior irrespective of IFT-data availability. For the cases considered, the new EoS agrees well with experimental data for scans in both salinity and composition. The model also predicts phase-behavior data for a wide range of temperature and pressure, and it is validated against dynamic scattering experiments to show the physical significance of the approach.
Original languageEnglish (US)
Pages (from-to)647-659
Number of pages13
JournalSPE Journal
Volume24
Issue number02
DOIs
StatePublished - Apr 11 2019

Fingerprint

Dive into the research topics of 'Curvature-Based Equation of State for Microemulsion-Phase Behavior'. Together they form a unique fingerprint.

Cite this