Abstract
<jats:title>Abstract</jats:title> <jats:p>In situ combustion (ISC) modeling traditionally relies on coke combustion as the dominant reaction mechanism, often neglecting the role of vapor-phase reactions within porous media. This paper presents the modeling of a novel ISC experimental study using CMG STARS, incorporating an advanced kinetic framework that explicitly accounts for vapor-phase combustion of distillable hydrocarbon components. The primary objective is to demonstrate that inclusion of these reactions enables more accurate reproduction of experimental observations and provides a more realistic and predictive representation of ISC processes.</jats:p> <jats:p>A tailored ISC experimental setup was designed to isolate and observe vapor-phase combustion phenomena, and the results were simulated using a comprehensive kinetic model that extends beyond conventional coke-only approaches. The model includes detailed governing equations and reaction mechanisms, ensuring transparency and reproducibility. By capturing both solid-phase coke combustion and vapor-phase fuel oxidation, the proposed methodology represents a significant advancement in ISC simulation capabilities. Simulation results demonstrate that the enhanced kinetic model successfully reproduces key experimental behaviors that conventional models fail to capture. In particular, the model accurately predicts complex temperature distributions including the formation of reverse combustion fronts observed in specific zones of the experiments, gas composition trends, and fluid production behavior. These phenomena can only be replicated when vapor-phase combustion is included, revealing a fundamental limitation of traditional ISC modeling approaches. The findings provide strong evidence that vapor-phase combustion can occur in heavy oil systems, including reservoirs containing Athabasca bitumen. Incorporating vapor-phase reactions into ISC models significantly improves predictive accuracy and process understanding. This work introduces a novel and additive contribution to ISC literature and offers practicing engineers a more robust modeling framework for field-scale simulation, design optimization, and performance forecasting in challenging heavy oil reservoirs.</jats:p>