Bottom-up optimization approach and nonlinear model for oilfield output programming

In the process of oilfield development, it is unable to separate the marginal effect of each developing measure from the aggregate effect of all developing measures, so both marginal analysis method and Markowitz portfolio theory are helpless for the oilfield output programming. Function Simulation is proved to be a feasible tool to model the input-output relationship of oilfield development. By training with historical development data, it possesses extrapolation capability in some range, which forms the basis for the oilfield output programming. The purpose of this paper is to report on the use of bottom-up optimization mechanism which is embedded by Function Simulation to optimize the distribution of output in oilfield. Following presentation of the features of oilfield development, the top-down approach and the Function Simulation as a tool for oilfield output programming are reviewed. The process of designing the bottom-up optimization framework embedded with Function simulations, determining the embedding protocol and coordinating the corresponding relationship between the subentry outputs and the subentry costs is described. Subsequently, models and an example are given. Finally, the paper concludes that above optimization method is suitable to solve a class of programming problems.