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Prediction of the interfacial tension between hydrocarbons and carbon dioxide

Suleymani, M ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1080/10916466.2017.1416629
  3. Publisher: Taylor and Francis Inc , 2018
  4. Abstract:
  5. In the recent years due to increasing demand for energy and declination of reservoir production, an impressive notice on enhancement of oil recovery has been found. The gas injection especially carbon dioxide injection due to low cost and friendly environmentally of this approach the special attention to CO2 injection increased. The miscibility is known as key factor which effects on enhancement of recovery. The miscibility is controlled by interfacial tension of hydrocarbons and carbon dioxide so the importance of investigation of the interfacial tension becomes highlighted.in this investigation by using radial basis function (RBF) artificial neural network (ANN) as a novel approach the interfacial tension of hydrocarbons and carbon dioxide in terms of pressure, temperature, liquid and gas densities and molecular weight of alkane. The graphical and statistical results illustrated the fact that RBF-ANN algorithm is applicable for estimation of interfacial tension between hydrocarbons and carbon dioxide with great accuracy. © 2018 Taylor & Francis Group, LLC
  6. Keywords:
  7. Artificial neural network ; EOR ; Interfacial tension ; Radial basis function ; Computer system recovery ; Functions ; Hydrocarbons ; Neural networks ; Oil well flooding ; Radial basis function networks ; Solubility ; Surface tension ; Well flooding ; ANN algorithm ; Carbon dioxide injection ; Gas density ; Key factors ; Low costs ; Oil recoveries ; Radial basis function(RBF) ; Radial basis functions ; Carbon dioxide
  8. Source: Petroleum Science and Technology ; Volume 36, Issue 3 , 1 February , 2018 , Pages 227-231 ; 10916466 (ISSN)
  9. URL: https://www.tandfonline.com/doi/abs/10.1080/10916466.2017.1416629