Steam Assisted Gravity Drainage (SAGD) is an enhanced oil recovery process whereby a long horizontal steam injection well is located above a long horizontal production well. Injected steam forms a steam chamber above the SAGD well pair, heating the reservoir rock and reservoir fluids. Heated oil (or bitumen) plus condensed steam flows down the sides of the steam chamber towards the production well. The condensed steam and bitumen are then lifted to surface with a downhole pump or by gas lift. Over the past decade, SAGD has become an increasingly popular method for extracting bitumen from Canadian oilsand leases that are too deep for surface mining, largely due to the high recovery factor from SAGD.
Nodal analysis for oil and gas wells enables the user to model well production or injection performance from the producing reservoir to the surface gathering system. Nodal analysis for well performance is based on the principle that reservoir inflow and wellbore outflow can be independently characterized as functions of flow rate. The single rate that balances the pressure losses in the inflow-outflow components with the pressure drop across the total system defines well flow. Nodal analysis is used to design new wells and optimize production or injection on existing wells. In addition, wellbore simulations are cheaper than instrumentation, meters or single well tests. Well evaluation software is the most popular package in Suncor's conventional production engineering toolkit because it is very accurate and easy to use.
Due to a rapidly increasing number of SAGD well pairs, Suncor required a tool that could accurately model these thermal wells. Over the past few years we worked with our software provider to develop nodal analysis for SAGD production wells, and we can now model SAGD producers with electric submersible pumps (ESP) with a high degree of confidence. The new SAGD nodal models quite closely match production rates, plus surface and downhole pressure and temperature data. Reliable and rigorous SAGD nodal models will enable improved decisions with respect to SAGD field development and production optimization.