An Improved Particle Swarm Optimization algorithm for Optimal Control of ASP Flooding

Author:

Lang Meiling,Ge Liang

Abstract

Abstract An optimization for injection of alkali/surfactant/polymer (ASP) flooding in oil recovery is considered in this paper. This optimal control problem (OCP) is formulated as a parameter identification system, where the objective function is revenue maximization and the governing equation is multiphase flow in porous media. We use the ASP concentrations and slug size as the control and give the pointwise constraint for the control. An improved particle swarm optimization (IPSO) which is a particle swarm optimization (PSO) with second-order oscillatory in velocity, is applied to solve the OCP. Finally, an example of the OCP for ASP flooding is exposed and the results show that the IPSO method is effective and feasible.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference6 articles.

1. Optimal control of polymer fooding based on mixed-integer iterative dynamic programming;Lei;International Journal of Control,2011

2. An optimization methodology of alkaline-surfactant-polymer fooding processes using field scale numerical simulation and multiple surrogates;Zerpa;Journal of Petroleum Science and Engineering,2005

3. Particle swarm optimization;Kennedy,1995

4. A numerical computation approach for the optimal control of ASP flooding based on adaptive stategies;Li,2018

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