Hybrid steam and in‐situ‐combustion (ISC) recovery processes have shown advantages over pure steam injection for recovery of oil‐sands resources, particularly with respect to reducing costs and lowering requirements for water and natural‐gas use. However, it has been very challenging to predict the field performance of hybrid steam-and-combustion processes with a reasonable degree of confidence. Usually, a combustion front has a thickness of only a few inches and high‐resolution grids are required to capture steep temperature, saturation, and fluid‐composition gradients in the vicinity of the combustion front. Using high‐resolution, fine grids (FGs) in an entire reservoir to improve the accuracy of simulation can involve excessive computation time and, therefore, might be impractical for field‐scale modeling. It is important to have a robust simulation tool to accurately predict reservoir performance without compromising the computational efficiency.
In this work, numerical modeling of a hybrid steam-and-combustion recovery process was performed in a typical Athabasca Oil Sands reservoir. A comprehensive reaction‐kinetics model derived from laboratory results was incorporated to represent the complex chemical reactions in the combustion process. This hybrid recovery process used oxygen‐enriched air coinjection after several years of a steam‐assisted‐gravity‐drainage (SAGD) operation. In the numerical model, safe limits were set on producing well temperature and oxygen content of the produced fluids. The initial grid size in the numerical model was at the centimeter scale, resulting in long run time, so to improve the computational efficiency a dynamic‐gridding (DG) feature was applied. Parameters for controlling the creation of a dynamic grid and subsequently reverting back to a coarse grid have been examined to properly trigger the DG feature in the model. Once the optimized DG parameters were determined, operating parameters were investigated, including well configuration, oxygen (O2) concentration, and steam concentration. Comparisons were made between SAGD and hybrid steam/combustion processes in terms of cumulative water (steam) injection, cumulative oil production, and a cumulative steam/oil ratio (cSOR).
By comparing the simulation results from an FG model and a DG model, we found that a temperature gradient is the best criterion to use for controlling DG compared to fluid‐saturation and/or composition criteria. The threshold value for the temperature criterion was determined to be 35°C. The model locates the FGs in close proximity to the combustion front where the temperature and fluid‐saturation gradients are the steepest and it places the coarse gridblocks elsewhere in the model. Comparisons are made between the computation time and the accuracy of simulation, and they demonstrate that dynamic grid amalgamation reduces the computation time significantly while maintaining reasonable computation accuracy of the simulation. Different well configurations affect O2‐injection timing, combustion‐front sweep efficiency and, therefore, the overall performance. The suggested O2 concentration in the hybrid process is between 10 and 20%. Steam can also be replaced with nitrogen (N2) to further improve the performance. For all simulation scenarios considered in this work, the cSOR in the hybrid process was improved, illustrating the main advantage of the hybrid approach over steam‐only injection as in SAGD.