Field-Scale Modelling of Hybrid Steam and Combustion In-Situ Recovery Process for Oil Sands using Dynamic Gridding

Yang, Min (University of Calgary) | Harding, Thomas G. (Nexen Energy ULC) | Chen, Zhangxin (University of Calgary)

OnePetro 

Abstract

Hybrid steam and in-situ combustion recovery processes have shown advantages over pure steam injection for recovery of oil sands resources, particularly with respect to reducing costs and lowering requirement for water and natural gas. However, it has been very challenging to predict 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 the steep temperature, saturation and fluid composition gradients in the vicinity of the combustion front. Using high resolution, fine grids to improve accuracy of simulation requires excessive computation time and, therefore, may be impractical for field scale modelling. 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 new reaction kinetics model derived from laboratory results was incorporated to represent the complex chemical reactions in the combustion process. The hybrid recovery process utilized oxygen enriched air co-injection after several years of SAGD operation. In the numerical model, safe limits were set on producing well temperature and oxygen content of produced fluids. The initial grid size in the numerical model was at the centimeter scale resulting in large run time, and thus, in order to improve the computational efficiency, a dynamic gridding feature was applied. Parameters for controlling the creation of a dynamic grid and subsequently reverting back to the coarse grid have been examined in order to properly trigger the dynamic gridding feature in the model. Once the optimized dynamic gridding parameters were determined, several different well configurations were investigated. Comparisons were made between SAGD and hybrid steam/combustion processes in terms of cumulative water (steam) injection, cumulative oil production, and a steam-oil ratio.

By comparing the simulation results from the fine grid model and the dynamic gridding model, it has been found that the temperature gradient is the best criterion to use for controlling dynamic gridding 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 fine grids in close proximity to the combustion front where the temperature and fluid saturation gradients are the steepest and it places the coarse grid blocks elsewhere in the model. Comparisons are made between the computation time and the accuracy of the simulation and these demonstrate that dynamic grid amalgamation reduces the computation time significantly while maintaining reasonable computation accuracy of simulation. Compared with SAGD, the hybrid steam/in-situ combustion process reduced cumulative water usage (steam injection) by 20% to 27%, while the cumulative oil production remained the same.

This paper provides a workflow for modelling of hybrid steam and combustion processes. Also, it is expected that this work will provide insights for field design of these hybrid thermal recovery processes.