Optimization Design of Production Parameters of Rod pump Lifting System of Pumping Unit based on Mechanism Simulation
The design method of rod pump lifting system based on traditional experience method and prediction model method is either too simple or too complicated in practical application,and the reliability of the design scheme needs to be improved.The application of big data driven technology to explore the law of mass pumping well lifting system design scheme,and recommend the optimal swabbing parameter optimization design scheme with the goal of increasing production and reducing energy consumption,will effectively improve the scientific and operational design method of pumping well lifting system.This article analyzes the main control factors of pumping well production,and combines the software simulation and on-site collection of pumping well lifting system design samples for cluster analysis to obtain a new sample library.A deep learning model for pumping well lifting system design scheme is established,and a scheme similarity model based on matching algorithm is studied.A parameter design recommendation system for pumping well lifting system is developed.The calcula-tion example verified that this system can match and find the lifting design scheme with high similarity of geolog-ical reservoir conditions and good operation effect from a large number of samples for recommendation,according to the physical properties and development characteristics of the geological reservoir to be designed.The analysis shows that the lifting parameters and lifting effect of the recommended lifting system design have been greatly im-proved in the original scheme.The feasibility of this algorithm is proved,which provides a new idea and method for the design of lifting system of pumping unit.
NETL
NSTL
万方数据
维普
