Abstract

ESPCP is a new way of well lifting. The speed optimization is the main way to improve economic index of ESPCP system. By analyzing the main factors of speed of ESPCP system and using the technology of artificial neural networks, established an artificial neural network model for output speed about oil viscosity, pressure difference of the pump two ends, magnitude of interference between stator and rotor as the input variables. Through the use of additional momentum and adaptive learning rate method to predict the learning samples, the results can fit experimental data. The results of recalling and forecasting are accurate. It is shown that the model is of high precision and reliability. It also provides a new calculation for ESPCP system speed prediction and optimization.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.