Since the proof-of-concept field testing at AOSTRA's Underground Test Facility (UTF) in late 1980's, the SAGD (Steam-Assisted Gravity Drainage) process has been applied for many bitumen recovery projects in Alberta. According to public-domain data, these projects have shown a wide range of recovery performance - ranging from very good to very poor - on basis of actual Oil Rate & Volume, Steam-Oil Ratio (SOR) versus expected and/or nameplate design. SAGD recovery performance in these projects is mainly affected by geological deposits, reservoir quality and operational experience. Numerical modeling has been an important tool in SAGD commercialization development, including being used for production forecasting, evaluation of process operations and enhancements.
This paper first reviews and analyzes actual field production and injection data for 28 Athabasca Oil Sands Deposit SAGD well pairs (WPs). These WPs are from 4 different pads, in close proximity to one another, producing from reservoir of different qualities from Jackfish 1 SAGD project; they have more than 1700 days of history (from first steam to end of July 2013). It is seen that reservoir quality has a considerable (bigger than commonly believed) impact on recovery performance, particularly in terms of thermal efficiency (as measured by SOR) and steam chamber dynamics. Discussion is provided in view of observed field performance vis-à-vis current/common industry practice of field production forecasting and project development planning.
Another important finding from the production data analysis is revealed in the reported gas production behavior, including cumulative volume and trend. It is seen that in many of these 28 WPs, there was considerable ‘extra’ gas (commonly attributed to aquathermolysis) production - up to 20% of total gas produced at the end of approximately 6 years of steam injection. The analysis helps providing some answers to oft-asked questions from field operators about too much production of (sour) gas; it should also help future studies model more closely SAGD gas production, in addition to liquids production.
Based on the analysis of field production data, a numerical model was built and calibrated against production data from 2 of the poorer-performing WPs among the 28 studied. Agreement between simulated and actual Cumulative Oil and SOR was within 10%, after 6 years of operations, on a first-iteration basis. The model was also successful in modeling the gas production behavior.