Chevron

Solution

Chevron describes an operational AI workflow built around field and equipment data rather than a consumer-facing assistant. Real-time sensor feeds from operating assets and facilities are ingested to monitor conditions continuously, while inspection imagery and observations from a Percepto system extend visibility into remote facilities. Chevron applies anomaly-detection methods to these inputs to identify leaks and other deviations from normal operations, then routes the resulting insights into crew workflows so teams can focus maintenance effort where problems are most likely. In parallel, Chevron uses AI to create a more accurate picture of the subsurface than traditional methods, improving decisions about hydrocarbon recovery and potential CO2 storage locations. The source does not name a storage platform, but it does show a production-style loop of sensing, AI analysis, remote inspection, and operational response, with Chevron expanding from a six-month pilot to a second Colorado deployment and evaluating broader rollout.

Data flow

Chevron ingests real-time sensor data from assets and inspection inputs gathered through the Percepto system, applies anomaly-detection methods to identify leaks and abnormal conditions, and sends the resulting insights to crews so they can prioritize inspection and maintenance work. Chevron also uses AI analysis of subsurface data to support reservoir and CO2 storage decisions.