An optimization algorithm for evaluation of kinetic parameters for crude oil combustion

Abstract The design of enhanced oil recovery processes that employ in-situ combustion requires high-fidelity simulation models that accurately describe the physics and chemistry of reactive, exothermic multiphase fluid flow. Therefore, a detailed description of oil combustion kinetics is required. The goal of this work is to present and apply a workflow to define and match pseudo-kinetic reaction models based on Arrhenius kinetics. These models are meant to be used at the laboratory scale with high-resolution, fully-resolved simulation models as a tool to generate high density data required by upscaled models at reservoir scale. The workflow starts by performing ramped temperature oxidation (RTO) experiments for a wide range of heating rates. New experimental equipment has allowed us to obtain data for large heating rates ( > 15 ° C m i n ) that were not achievable in the past. A subset of the experiments are selected to match the oxygen consumption curves by tuning kinetic parameters of several global reaction models using pattern search optimization. Those models that obtain a match are validated by predicting a second subset of the data that was not considered during the optimization. The workflow is tested using a heavy oil and two satisfactory matches with two different global reaction models are obtained.