Optimal control for an alkali/surfactant/polymer flooding system

The alkali/surfactant/polymer (ASP) flooding is an important enhanced oil recovery technology which is widely concerned in recent years. In this paper, a novel one-dimensional optimization model for ASP flooding is developed, in which the performance index is economic profit, the state equations are oil/water seepage continuity equations and adsorption diffusion equations of displacing agents, and some other constraint equations. To optimize the injection strategy, an improved spiral optimization algorithm (ISOA) is proposed. In ISOA, an adjustment strategy is introduced to change the contraction coefficient, a new adaptive Cauchy mutation which contains the global population information and individual information is developed to jump the local extremum. Then three benchmark functions are adopted to test the performance of ISOA. After the constraints handled by non-stationary multi-stage assignment penalty function, the ISOA is applied to optimize the one-dimensional optimization model of ASP flooding to get the optimal injection strategy.

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