Speakers: Sean Gregerson (AVEVA)

Abstract: 

Midstream operators generate vast amounts of operational, asset, maintenance, and integrity data across pipelines, compressor stations, terminals, control systems, and field operations. Bringing this data together and adding the right industrial context creates the intelligence needed to improve visibility, identify emerging risks earlier, prevent equipment failures, and support faster, better informed decisions.

This session explores how AI and data intelligence can help midstream organizations create a more connected and proactive approach to operations and reliability. By combining a unified view of operational performance with predictive insights, teams can detect developing equipment issues earlier, understand their potential impact, and act before availability, throughput, or operational performance are affected.

A trusted and contextualized industrial data foundation is central to this approach. Connecting real time and historical operational data with asset relationships, maintenance history, engineering information, and equipment context creates a more complete view of pipeline and asset performance. A shared operational view helps control room, operations, reliability, and maintenance teams identify what requires attention and collaborate around common priorities.