Abstract

Abstract As the most commonly used process for the secondary development of oilfields, waterflooding plays a significant role in maintaining reservoir pressure, enhancing oil recovery and achieving high and stable oil production. The previous waterflooding optimization studies usually worked out the optimal injection/production rates but didn't take into account the energy consumed by the surface waterflooding pipeline network system which transfers water from the waterflooding stations to the waterflooding wells. Taking the maximum waterflooding development profit as the objective function, this paper proposes an integrated methodology for the unified optimization of injection/production rates and the operation control of surface waterflooding pipeline network system. The objective function is defined as the oil production income minus the operation cost of the pipeline network. With a given set of injection rates of waterflooding wells, the reservoir numerical simulation is employed to obtain the oil production rates and a mixed integer nonlinear programming (MINLP) model is established for the optimal operation control of the surface waterflooding pipeline network, including the pump schedule of waterflooding stations, flowrate of pipe segments and pressure at each node. A hybrid solving strategy incorporating particle swarm optimization (PSO), linear approximation method, and branch-and-bound algorithm, is proposed for solving the results. The PSO algorithm is adopted to search for the optimal injection rates of waterflooding wells, while the linear approximation method and branch-and-bound algorithm are used for the MINLP model solving. In this study, we took the Daqing waterflooding Oilfield in China as an example. The applicability of the methodology and the stability of the solving strategy are illustrated in detail. It is proved that the proposed methodology could provide the engineers with significant guidelines for the unified optimization of waterflooding process incorporating the reservoir and surface pipeline network.

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