Digital Oil Field

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R&D/innovation

Seismos Opens Applied Acoustics Research Center To Advance Closed-Loop Stimulation Research

The Seismos full-scale research center opens to industry, universities, and national laboratories, advancing acoustic sensing across upstream energy, pipelines, critical infrastructure, and national security.

Fig. 1—Persistent high anomaly scores from installation to failure.

Artificial lift

Machine Learning Provides Reliable ESP-Condition Monitoring

This research focuses on combining physics-based expert rules with machine learning to improve the detection of failure-related events in electrical submersible pumps.

Fig. 1—Mean absolute normalized error across unseen wells. While most wells exhibit low prediction errors, some show greater deviations, highlighting variability in operating conditions and potential data limitations.

Artificial lift

Hybrid Physics/ML Framework for Virtual Flowmetering Optimizes Production

A combination of physics principles and machine-learning techniques is used in this work to develop a virtual flowmeter for oil-production optimization in electrical-submersible-pump-lifted oil wells, resulting in reliable generalization.