A modified HLD-NAC equation of state to predict alkali/surfactant/oil/brine phase behavior

Soumyadeep Ghosh, Russell T. Johns

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Reservoir crudes often contain acidic components (primarily naphthenic acids), which undergo neutralization to form soaps in the presence of alkali. The generated soaps perform synergistically with injected synthetic surfactants to mobilize waterflood residual oil in what is termed alkali/surfactant/polymer (ASP) flooding. The two main advantages of using alkali in enhanced oil recovery (EOR) are to lower cost by injecting a lesser amount of expensive synthetic surfactant and to reduce adsorption of the surfactant on the mineral surfaces. The addition of alkali, however, complicates the measurement and prediction of the microemulsion phase behavior that forms with acidic crudes. For a robust chemical-flood design, a comprehensive understanding of the microemulsion phase behavior in such processes is critical. Chemical-flooding simulators currently use Hand's method to fit a limited amount of measured data, but that approach likely does not adequately predict the phase behavior outside the range of the measured data. In this paper, we present a novel and practical alternative. In this paper, we extend a dimensionless equation of state (EOS) (Ghosh and Johns 2016b) to model ASP phase behavior for potential use in reservoir simulators. We use an empirical equation to calculate the acid-distribution coefficient from the molecular structure of the soap. Key phase-behavior parameters such as optimum salinities and optimum solubilization ratios are calculated from soapmole- fraction-weighted equations. The model is tuned to data from phase-behavior experiments with real crudes to demonstrate the procedure. We also examine the ability of the new model to predict fish plots and activity charts that show the evolution of the three-phase region. The predictions of the model are in good agreement with measured data.

Original languageEnglish (US)
Pages (from-to)550-566
Number of pages17
JournalSPE Journal
Volume23
Issue number2
DOIs
StatePublished - Apr 2018

All Science Journal Classification (ASJC) codes

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

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