Success Story
From Labeling Restart Patterns in Oil Well Data to Scalable Tolerance Corridor Generation for Brazil’s National Oil & Gas Company
Extensive sensor data history, but with sparsely labeled restart events.
Restarting a production process—whether an oil well, furnace, power plant, or any other complex asset —is a highly dynamic and risk-prone operation. In oil and gas, hydrate blockages during well restarts lead to significant delays for dissociation, and can cause significant costs and weeks of unplanned effort. Early detection of deviations is vital to prevent escalation and minimize losses.
Petrobras, Brazil’s national oil and gas company sought a way to define dynamic tolerance corridors for monitoring pressure and temperature measurements during restarts of more than 400 oil wells.
Challenges
The Solution
From a small dataset to a complex data-powered monitoring solution that enables:
How it works
The Results
Why It Matters for Any Industry
Data Scientists can:
Whether you’re managing oil wells, power plants, or process-intensive assets, accurate pattern monitoring can mean the difference between smooth production and unexpected downtime.
