Research On Working Condition Diagnosis Method For Electrical Submersible Progressing Cavity Pump

The electrical submersible progressing cavity pump (ESPCP) has prevailed widely in the oil extraction industry. However, there is no proper working condition diagnosis procedure in practice, which has reduced production efficiency.Research on method of ESPCP working condition diagnosis is carried out in this paper. The main research work is as follows:The ESPCP system is introduced and running parameters are selected, as well as systematic design of ESPCP working condition diagnosis is proposed.Status recognition of the electrical parameters and speed identification of the electrical submersible motor are modeled and simulated by Matlab platform. The Support Vector Machine (SVM) based multi-class classification method is proposed. Moreover, training and test on different classifier are carried out considering different classification aims. Speed identification modeling based on the MRAS theory has been done by Simulink platform, and analysis method for ESPCP based on the identified speed is proposed.Estimation rule of typical working conditions based on logic relationship is proposed. After multi-angle analysis on typical working conditions, the logic discrimination rules are designed considering major parameter status.Working condition diagnosis system is designed and developed by Visual Basic platform, which includes some necessary modules, such as well management, personnel management, real-time curve draw, data storage, historical data query, working condition diagnosis, etc.Simulation results and experimental data analysis have shown that the proposed method for ESPCP diagnosis can monitor and detemine the working condition correctly, which makes it possible to apply in practice.