Estimating n-tetradecane/bitumen mixture viscosity in solvent-assisted oil recovery process using GEP and GMDH modeling approaches
Alireza Rostami, Abdolhossein Hemmati‐Sarapardeh, Amir H. Mohammadi · Petroleum Science and Technology · 2019
In this study, the methods of group method of data handling (GMDH) and gene expression programming (GEP) were used to develop symbolic correlations for truthful viscosity estimation of n-tetradecane/bitumen mixture. A number of graphical and statistical tools were utilized to make evident the omnipotence of the proposed models as compared to the published literature correlations. It is found that the GMDH model is the best acting approach with the lowest total error of 2.51% and the highest R2 of 0.9994. Sensitivity analysis verifies that concentration of the solvent is the most influencing input parameter on the viscosity estimation of n-tetradecane/bitumen mixture.