An adaptive neuro-fuzzy approach for modeling of water-in-oil emulsion formation


Yetilmezsoy K. , Fingas M., Fieldhouse B.

COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS, vol.389, pp.50-62, 2011 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 389
  • Publication Date: 2011
  • Doi Number: 10.1016/j.colsurfa.2011.08.051
  • Journal Name: COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.50-62
  • Keywords: Water-in-oil emulsion, Stability, Adaptive neuro-fuzzy inference system, Regression model, CRUDE-OIL, PREDICTION, PERFORMANCE, NETWORK

Abstract

Oil composition and properties including density, viscosity, asphaltene, saturate, aromatics and resin contents are responsible factors for the formation of water-in-crude-oil emulsions. These factors can be used to develop an stability index which determines states of water-in-oil emulsion in terms of either an unstable, entrained, mesostable or stable conditions. It is important to note that most of the regression models cannot capture the non-linear relationships involved in the formation of these emulsions. This study deals with the prediction of water-in-oil emulsions stability by an adaptive neuro-fuzzy inference system (ANFIS) with basic compositional factors such as density, viscosity and percentages of SARA (saturates, aromatics, resins, and asphaltenes) components.