Factorial Analysis of Experimental Parameters Effecting Asphaltene Precipitation in Dead Crude Oils

The flow properties of crude oil often improve by rising the temperatures or diluting the oil with different lower molecular weight hydrocarbons. Nevertheless, operational changes like these often results in the asphaltene deposition problems. Therefore, to address this issue, in this study, two-level full factorial design was applied on two already published experimental dataset of Ashoori et al. and Hu and Guo for studying the effect of three experimental parameters which include the dilution ratio (R), molecular weight of precipitant (M), and temperature (T), on the yield of asphaltene weight percentage. According to the results of Ashoori dataset, all linear and 2-way interactions of input variables were found significant (P value < 0.05) except the interaction between M and T whereas, for Hu and Guo dataset, only linear interaction of variables was found significant (P-value < 0.05). These Pareto, normal, main effects plot and interaction plot charts confirmed that R has the significant positive effects while M and T has a moderate negative effect on response variable for both datasets. The analysis of Variance (ANOVA) technique evaluated the validity of the predictive models and produce satisfactory results (having R² value approximately 0.99). The results of contour plot and surface plot show that asphaltene precipitation increases at higher values of R and lower values of T and M. Finally, the full factorial technique was also applied on validation experimental dataset and results were found to be similar to Hu and Guo dataset. The study provides an effective methodology for the selection of optimum production parameters.