AI/machine learning

A credible custody-transfer record depends on far more than the accuracy of a single meter. It is the product of an integrated measurement chain. While meter performance supports measurement-system integrity, commercial confidence also depends on traceability, governance, and authorization.
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.
After years of market shocks, technological breakthroughs, and rising uncertainty, ATCE 2026 will provide new insights on how industry leaders and technical experts are preparing for the next era of the upstream business.

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