Model parameter uncertainty updates to achieve optimal management of a reservoir

The objective of this work is to optimize oil production by managing the amount of water added to a reservoir. This management is accomplished by employing an optimal model-based control framework that includes uncertain parameter updating and a particular low-order model identified from a first-principles model. Two different methods are used to achieve continuous updates of the uncertain parameters, Markov chain Monte Carlo and an ensemble Kalman filter. A two-dimensional reservoir is introduced to demonstrate oil production performance when water addition is managed. The results are compared to a case when water management is absent.