Abstract

The article discusses concepts and computational tools to enable 'closed-loop' model-based reservoir management. Also known as 'real-time' reservoir management, this involves the use of (uncertain) reservoir and production system models in combination with production measurements and other data, such as time-lapse seismics, to continuously update the models. The key sources of inspiration for our work are measurement and control theory as used in the process industry and data assimilation techniques and, in particular, their integrated application in a reservoir management workflow. As an example the authors present early results that illustrate the scope for model-based optimal control of waterflooding using real-time production data under uncertain reservoir conditions.

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