Proposing a modified mechanism for determination of hydrocarbons dynamic viscosity, using artificial neural network

Shayan Ahmadi, Mohadeseh Motie, Ramin Soltanmohammadi

Research output: Contribution to journalArticleScientificpeer-review

Abstract

In this study, to have an accurate approximation of dynamic viscosity, radial basis function artificial neural network (RBF-ANN) is employed and developed for normal alkanes. This is done by considering the distinct number of carbons in n-alkanes, certain temperatures, and different pressures. Moreover, in order to train and test the predicting model, a databank of 228 experimental data is gathered from reliable sources in the literature. As a result, training and testing coefficient values are measured 0.99739 and 0.99051; consequently, the robustness and accuracy of RBF-ANN in providing an estimation of n-alkane viscosity is confirmed by graphical analysis and determined indexes.
Original languageEnglish
Pages (from-to)699-705
Number of pages7
JournalPetroleum Science and Technology
Volume38
Issue number10
DOIs
Publication statusPublished - 2020

Keywords

  • dynamic viscosity
  • normal alkane
  • predicting model
  • RBF-ANN
  • reservoir conditions

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