Sammendrag
In the secondary phase of oil recovery, water
flooding is the most common way to sweep remaining oil in
the reservoirs. The process can be regarded as a nonlinear
optimization problem. This paper focuses on how to handle
state constraints in an adjoint optimization framework for
such systems. The state constraints are cast as nonlinear
inequality constraints. In the presence of state constraints,
adjoint-based gradient optimization methods can loose their
efficiency. Moreover, using existing optimization packages one
needs to supply Jacobians of the inequality constraints. We
propose a Lagrangian-barrier function based method which
adds the state constraints as a term to the objective function.Furthermore, we present a numerical case demonstrating that the feasibility and efficiency of the proposed method
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