Optimal well placement is a complex problem that requires detailed models of the reservoir structure/geometry and the petrophysical properties such as facies, porosity, permeability, and fluid saturation. The reservoir development team attempts to integrate all of these aspects when devising a well plan for optimal reservoir exploitation. Ideally the well locations would be selected with the assistance of a flow simulator; however, this is impractical due to time and CPU requirements. This paper presents a technique for selecting optimal well locations for fine-tuning with a flow simulator. The technique constructs the well placement problem as an optimization problem to be solved with simulated annealing. The global objective function consists of multiple component objective functions. Each component represents a desirable feature or constraint in the problem. Optimality is defined as the best balance among the component objectives. The format of the technique is flexible and can incorporate 3-D geostatistical models of uncertainty and multiple constraints. The proposed method iteratively refines initial well locations and trajectories until the global objective is maximized. Several examples are shown. Optimal well placement in a steam assisted gravity drainage context is illustrated.

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