Optimization of reaction temperature and Ni-W-Mo catalyst soaking time in oil upgrading: application to kinetic modeling of in-situ upgrading

Decreasing the conventional sources of oil reservoirs attracts researchers' attention to the tertiary recovery of oil reservoirs, such as in-situ catalytic upgrading. In this contribution, the response surface methodology (RSM) approach and multi-objective optimization were utilized to investigate the effect of reaction temperature and catalysts soaking time on the concentration distribution of upgraded oil samples. To this end, 22 sets of experimental oil upgrading over Ni-W-Mo catalyst were utilized for the statistical modeling. Then, optimization based on the minimum reaction temperature, catalysts soaking time, gas, and residue wt.% was performed. Also, correlations for the prediction of concentration of different fractions (residue, vacuum gas oil (VGO), distillate, naphtha, and gases) as a function of independent factors were developed. Statistical results revealed that RSM model is in good agreement with experimental data and high coefficients of determination (R-2 = 0.96, 0.945, 0.97, 0.996, 0.89) are the witness for this claim. Finally, based on multi-objective optimization, 378.81 degrees C and 17.31 h were obtained as the optimum upgrading condition. In this condition, the composition of residue, VGO, distillate, naphtha, and gases are 6.798%, 39.23%, 32.93%, 16.865%, and 2.896%, respectively, and the optimum condition is worthwhile for the pilot and industrial application of catalyst injection during in-situ oil upgrading.

Automated summary

In this study, the effect of reaction temperature and catalysts soaking time on the concentration distribution of upgraded oil samples was investigated using the response surface methodology (RSM) approach and multi-objective optimization. Statistical modeling was performed using experimental data, and correlations for predicting the concentration of different fractions were developed. The results showed good agreement between the RSM model and experimental data, with high coefficients of determination. The optimum upgrading condition, obtained through multi-objective optimization, was found to be 378.81 degrees C and 17.31 hours, with specific compositions for each fraction.