Monte Carlo and Sensitivity Analysis Methods for Kinetic Parameters Optimization: Application to Heavy Oil Slurry-Phase Hydrocracking

Abstract

A methodology to estimate kinetic parameters using the Monte Carlo algorithm and sensitivity analysis is described. The approach is applied to the experimental data reported in the literature for slurry-phase hydrocracking of heavy oil with ionic liquids. All experiments were carried out in a batch reactor at a reaction temperature of 430 ?C, H2 pressure of 12.3 MPa, and reaction times of 0.5-6 h. It is demonstrated that the reported values of kinetic parameters can be optimized so that the average absolute error is substantially reduced from 21.73 to 7.93%. Simulations with the Monte Carlo algorithm with various initial values of parameters help find the best initial guess for further optimization of parameters. The prediction of product yields was improved using the average absolute error as objective function since it was distributed equally for all products, being coke the lump with greater error reduction (from 57.39 to 7.60%). The sensitivity and statistical analyses performed on the optimized reaction rate coefficients confirmed that the obtained results are the optimal values that minimize the error between calculated and experimental data. The lowest value of average absolute error (7.93%) determined by sensitivity analysis was found for the optimized values; moreover, the slope and intercept of the parity plot are almost 1 and 0, respectively.