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1) AI and machine learning algorithms analyze data from electrical submersible pumps (ESPs) to predict failures and optimize production. 2) A proof-of-concept used historical data from 30 ESPs to train a machine learning model, which successfully differentiated normal and abnormal behaviors in advance of failures. 3) A pilot project then tested the machine learning model in real-time, using data streamed from the ESPs to predict anomalies and notify operators of potential issues hours to days before fai

Author

Ken Otoo

Language

EN