Simulation of surfactant/polymer floods with a predictive and robust microemulsion flash calculation

Saeid Khorsandi, Changhe Qiao, Russell Taylor Johns

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

A compositional reservoir simulator that uses a predictive micro-emulsion phase-behavior model is essential for accurate estimation of oil recovery from surfactant/polymer (SP) floods. Current chemical-flooding simulators, however, use Hand's model (Hand 1939) for phase-behavior calculation. Hand's model can reasonably fit a limited set of experimental data, such as those of a salinity scan, but because it is empirical, it cannot predict phase behavior outside the matched data set. Hydrophyllic/lypophyllic difference (HLD) and net-average-curvature (NAC) equation of state (EOS) (Acosta et al. 2003) has shown great performance for tuning and prediction of experimental data. In this paper, the EOS model with the extension to two-phase regions has been incorporated for the first time into UTCHEM (2000) and our in-house general-purpose compositional simulator, PennSim (2013). All Winsor regions (Type II -, II+, III, and IV) are modeled by use of a consistent physics-based EOS model without the need for Hand's approach. The new simulator is therefore able to account correctly for gridblock properties, which can vary temporally and spatially, and significantly improve the modeling of phase behavior and oil recovery. The results show excellent agreement between UTCHEM and PennSim both in composition space and for composition/saturation profiles for the 1D simulation. The effects of varying pressure, temperature, equivalent alkane carbon number (EACN), and salinity on recoveries are demonstrated also in 1D simulations.

Original languageEnglish (US)
Pages (from-to)470-479
Number of pages10
JournalSPE Journal
Volume22
Issue number2
DOIs
StatePublished - Apr 1 2017

Fingerprint

Microemulsions
surfactant
Phase behavior
Surface active agents
polymer
simulator
Simulators
Equations of state
equation of state
Polymers
simulation
Recovery
salinity
oil
emulsion
Chemical analysis
alkane
Paraffins
curvature
Emulsions

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Geotechnical Engineering and Engineering Geology

Cite this

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abstract = "A compositional reservoir simulator that uses a predictive micro-emulsion phase-behavior model is essential for accurate estimation of oil recovery from surfactant/polymer (SP) floods. Current chemical-flooding simulators, however, use Hand's model (Hand 1939) for phase-behavior calculation. Hand's model can reasonably fit a limited set of experimental data, such as those of a salinity scan, but because it is empirical, it cannot predict phase behavior outside the matched data set. Hydrophyllic/lypophyllic difference (HLD) and net-average-curvature (NAC) equation of state (EOS) (Acosta et al. 2003) has shown great performance for tuning and prediction of experimental data. In this paper, the EOS model with the extension to two-phase regions has been incorporated for the first time into UTCHEM (2000) and our in-house general-purpose compositional simulator, PennSim (2013). All Winsor regions (Type II -, II+, III, and IV) are modeled by use of a consistent physics-based EOS model without the need for Hand's approach. The new simulator is therefore able to account correctly for gridblock properties, which can vary temporally and spatially, and significantly improve the modeling of phase behavior and oil recovery. The results show excellent agreement between UTCHEM and PennSim both in composition space and for composition/saturation profiles for the 1D simulation. The effects of varying pressure, temperature, equivalent alkane carbon number (EACN), and salinity on recoveries are demonstrated also in 1D simulations.",
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Simulation of surfactant/polymer floods with a predictive and robust microemulsion flash calculation. / Khorsandi, Saeid; Qiao, Changhe; Johns, Russell Taylor.

In: SPE Journal, Vol. 22, No. 2, 01.04.2017, p. 470-479.

Research output: Contribution to journalArticle

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