Optimization Control Of Pump Station For Water Injection System In Oil-field Based On Hybrid Genetic Algorithm

Water-flooding is an important way to oil exploitation used by many oil-fields in our country. After analyzing the actuality of the water-flooding system in oil-fields,this paper proposed an optimization control scheme of water injection pumping station based on Hybrid Genetic Algorithm to solve the problem that the huge power consumption and serious pressure fluctuation in Wennan Oil-field water-flooding system. According to this scheme, the thesis designed the optimization solution algorithm and developed software on the basis of practical application.Combining the pump's characteristic and the project's real requirements, this thesis made research of the water-flooding efficiency optimization,targeting the water injection pumping station which is composed of centrifugal pumps and frequency converter driving reciprocating pumps, and aimed at its modeling, restricted terms establishment, solution algorithm choice and design, software development and result analysis. The efficiency of the pumping station is a complex and multi-variable function, involving many elements which lead to great difficulty in strategy research of efficiency optimization. In the thesis, the author used Least Squares Curve-fitting and BP Neural Network algorithm to get the pump's characteristics, and chose real-coded hybrid genetic algorithm to solve the optimization problem.In the end of the thesis, the author introduced the whole optimization system software, including its developing environment and main function blocks. In addition, to test the validity of the software and the optimization algorithm, the software was used to simulate with some practical test data. The results proved its validity.