Optimization of oil production may be performed on différent time horizons. Long-term optimization (which is typically performed over timescales of years) is usually conducted by reservoir engineers, whereas short-term optimization (which typically concerns days or weeks) is performed by production engineers. Long-term objectives focus on finding the best strategy to drain as much oil as possible from reservoirs. However, in reality it is often short-term goals such as maximizing daily oil rates that dictate the operational strategy. Unfortunately, these goals may be in conflict with each other. Therefore, incorporating long-term goals into short-term objectives is crucial. We present a novel approach to systematically combine long-term and short-term production optimization. The approach is based on a priori articulation of preferences, i.e., the decision maker is allowed to specify preferences that may be articulated in terms of goals or the relative importance of long-term and short-term objectives. The approach is adopted from multi-objective optimization method in which the solution is not a single point but rather a collection of points. To this end, we introduce the upper and lower bounds of the objective function such that the objective function can be written in a different form, whereas in reality, the short-term and long-term optimization are performed with the same objective but different methods. The idea is then to solve a bi-objective optimization problem using an adjoint-based method for the upper and lower objective functions and project the solution onto the original objective. The approach is tested on a simplified reservoir model of the south wing of the Voador field, which is located in the Campos Basin in Brazil. The results are presented as Pareto-like plots that can be used for decision support to balance long-term and short-term goals.

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