Multi-Million Cell SAGD Models - Opportunity For Detailed Field Analysis

Abstract Canada has the world’s largest deposits of ultraheavy oil and bitumen, estimated at 2.5 trillion barrels. Thermal recovery processes such as CHOPS (cold heavy-oil production with sand), SAGD (steam-assisted gravity drainage), and CSS (cyclic steam stimulation) have been successfully employed and promise good recovery for these oil sands. SAGD, however, is a relatively new technology and most of these projects are struggling to reach their expected production rates. SAGD recovery shortcomings are mostly related to geological aspects of the reservoirs that were not fully understood initially, and reservoir simulation studies are being conducted to improve the understanding of reservoir response to steam injection. As operators are gaining experience with the SAGD process, it is becoming clear that oil sands are anything but homogenous and have tremendous variations in key geological and reservoir properties. Building models for thermal simulation is significantly more complex than building them for conventional simulations, requiring more computing power, more iteration, and more memory. To capture the details of heterogeneity in a thermal reservoir simulation model, a very fine-scale grid is required. Also, a full-field model is required to appropriately understand the interplay of steam chambers for adjacent well pairs. The results gained by combining both full-field and thermal simulation results into a multimillion-cell model more accurately represent the geological heterogeneity and movement of steam along the wellbores. The methodology presented in this paper uses advanced simulator and computing technology for this purpose. The model preserves the extreme detail required for accurate interpretation and prediction, enabling testing of sensitivity for multiple operational parameters such as injection pressures and limiting flow pressures. A unique well-placement design is chosen that allows for greater sweep efficiency and flexibility in well placement. Advanced computing technology enables the large model to be run in a fraction of the time required by conventional techniques, enforcing greater accuracy in results and preserving the true behavior of the steam flow. To reduce the uncertainty of operational parameters, a sensitivity plot is provided to describe the parameters that have the most impact on the SAGD behavior. The methodology presented here allows for uncertainty and sensitivity analysis using a multimillion-cell model, bridging the gap between geology and engineering and instilling greater confidence in the results of the reservoir simulation study. The ultimate objective is to acquire more accurate results so that the expected SAGD production rates can be achieved through optimization of technology and processes.

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