In-situ combustion (ISC) is an effective thermal recovery method that provides an important alternative to steam injection, but it has yet to be widely applied due to the complexity of the process. The modeling of ISC requires an understanding of the behavior of different physical phenomena including phase change, heat and mass transfer, and chemical reactions. Properly conducted ramped temperature oxidation (RTO) tests on crude oil provide critical parameters for modeling. In this study, the focus is to model appropriate kinetics and improve reaction models for ISC.

Different chemical reactions occur during ISC in different temperature ranges. For heavy oils and oil sands low temperature oxidation (LTO) dominates below 260°C, yielding partially oxygenated compounds and increasing the viscosity of oil, and as a result, limiting the success of the ISC process. The so-called middle temperature oxidation (MTO) region is a combination of the negative temperature gradient region (NTGR) as well as the onset of thermal decomposition and pyrolysis/cracking of the hydrocarbon phase, some or all of which may have been previously oxidized. Above 350°C, high temperature oxidation (HTO) dominates, representing the more commonly known traditional combustion region. Most of the current reaction kinetics models for ISC only focus on specific conditions such as HTO and are not able to represent the wide range of reactions that occur over a larger temperature range.

The objective of this study was to develop reaction kinetic models that can be used to describe the reactions of hydrocarbon fractions at various temperature conditions during the ISC of Athabasca bitumen. In this work, a set of improved kinetic models including LTO, MTO, and HTO reactions based on Saturates, Aromatics, Resins, and Asphaltenes (SARA) fractions in the crude oil are established. These kinetic models are used to reproduce the RTO experimental results through numerical simulation. This research will contribute to the development of more reliable numerical models that can predict ISC performance in different temperature scenarios with greater accuracy and reliability.

You can access this article if you purchase or spend a download.