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Real-Time Steam Allocation Optimization
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- Author / Creator
- Sibaweihi, Najmudeen
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Traditionally, reservoir model-based open-loop optimization is used to allocate an amount of steam to each injector well. In Steam-Assisted Gravity Drainage (SAGD) recovery, the optimal real-time steam allocation from a shared steam generator to physically connected multi-pads can significantly improve long-term performance goals. However, in real-time optimization (RTO), general-purpose optimization algorithms decide based on short-term responses, unlike long-term optimization processes. Using economic Key Performance Indicators (KPI) such as Net Present Value (NPV) in a single objective, the RTO determines the smallest amount of steam allocation that results in the highest economic returns. Injecting a small amount of steam reduces steam chamber heat loss, growth, and long-term ultimate bitumen recovery. Furthermore, when the oil price is volatile, maximizing steam allocation and non-condensable gas (NCG) at the wind-down stage is essential to ensuring a profit while reducing risk. This research addresses the SAGD RTO workflow limitations of handling oil price volatility and balancing steam chamber development and economics to achieve long-term goals.
An adaptive data-driven predictive model developed based on typical Athabasca oil reservoir properties is employed for real-time short-term forecasting of the KPI, reducing the computational cost. A modified version of Modigliani's risk-adjusted performance is proposed and integrated into the workflow as a tradeoff selector of expected returns and risk when handling oil price volatility. Additionally, the workflow is tested on multi-pad steam allocation using an Alternating Direction Method of Multipliers (ADMM) for single-, multi- and many-objective optimization problems. Finally, an alternating set of RTO objectives is proposed to ensure that both short- and long-term KPIs are achieved.
The performance of the RTO workflow introduced is tested on single and multi-pad field scale SAGD first principle models. In addition, the cases are designed to mimic SAGD operations steam availability, wind-down, single, multi, and many objective RTO. The impact of the developed workflow is the improved short-term strategies, improved long-term economics, and reduced carbon footprints
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- Graduation date
- Spring 2023
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- Type of Item
- Thesis
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- Degree
- Doctor of Philosophy
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- License
- This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.