Model-Based Control and Optimization of Large Scale Physical Systems-Challenges in Reservoir Engineering
Due to urgent needs to increase efficiency in oil recovery from subsurface reservoirs new technology is developed that allows more detailed sensing and actuation of multiphase flow properties in oil reservoirs. One of the examples is the controlled injection of water through injection wells with the purpose to displace the oil in an appropriate direction. This technology enables the application of model-based optimization and control techniques to optimize production over the entire production period of a reservoir, which can be around 25 years. Large scale reservoir flow models are used for optimizing production settings, but suffer from high levels of uncertainty and limited validation options. One of the challenges is the development of reduced complexity models that deliver accurate long-term predictions, and at the same time are not more complex than can be warranted by the amount of data that is available. In this paper an overview will be given of the problems and opportunities for model-based control and optimization in this field aiming at the development of a closed-loop reservoir management system.
Oil reservoir production optimization optimal control parameter estimation dynamic optimization identifiability nonlinear observers
Paul M.J. Van den Hof Jan-Dirk Jansen Gijs van Essen Okko H. Bosgra
Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Department of Geotechnology, Delft University of Technology, The NetherlandsShell International Expl Department of Geotechnology, Delft University of Technology, The NetherlandsDelft Center for Systems
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
1-10
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）