There are many challenges in making rigorous economic decisions for capital intensive SAGD projects. Among those challenges is the need for reliable production forecasts. The traditional forecasting techniques of analogy, numerical simulation, and analytical methods are each burdened with their own drawbacks. The resulting production forecasts can vary to such a degree that the validity of the results obtained from each approach is questionable. When used in isolation, the individual forecasting techniques yield a significantly different result from each other, making economic decisions an imposing task.
This paper presents an integrated ternary approach which draws on the strengths of each methodology. A database of 70 SAGD well pairs from Suncor's MacKay River property is used to obtain analogs. It captures the variations in reservoir quality, reservoir thickness, and well design. In addition, an internally developed Monte-Carlo analytical tool, based on fundamental physics (i.e. material/energy balance, gravity drainage theory), is used to generate a probabilistic range of oil and SOR forecasts. This tool utilizes statistical distributions of static and time- dependent variables. Finally, numerical simulation models are also generated in conjunction with Suncor's geostatistical modeling process. The simulation input parameters are obtained through validation of multi-well simulation models against a long period of historical field data in MacKay River project area. The integration of these methodologies is presented in detail in this paper.
This integrated approach provides a basis for comparing relevant SAGD performance indicators, such as oil rate and SOR. The results generated from the integrated approach have served to increase confidence in the robustness of the associated business decisions.