| 摘要 |
Systems and methods which implement surrogate (e.g., approximation) models to systematically reduce the parameter space in an optimization problem are shown. In certain embodiments, rigorous (e.g., higher fidelity) models are implemented with respect to the reduced parameter space provided by use of surrogate models to efficiently and more rapidly arrive at an optimized solution. Accordingly, certain embodiments build surrogate models of an actual simulation, and systematically reduce the number of design parameters used in the actual simulation to solve optimization problems using the actual simulation. A multi-stage method that facilitates optimization of decisions related to development planning and reservoir management may be provided. Iterative processing may be implemented with respect to a multi-stage optimization method. There may be uncertainty in various parameters, such as in reservoir parameters, which is taken into account according to certain embodiments. |
