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AI-Assisted Troubleshooting Is the Rare, Low-Hanging Fruit in Energy Production

📅 Date:

✍️ Author: Omar A. Talib

🔖 Topics: Funding Event

🏭 Vertical: Petroleum and Coal

🏢 Organizations: ControlRooms AI

Despite ample telemetry and robust alarm management in place, energy producers continue to experience unplanned trips, flaring and other surprises that result in significant downtime, emissions and costs. While, undoubtedly, many interruptions are unavoidable in the moment, a surprisingly large percentage of interruptions could have been avoided if operators were given a heads-up. What percentage is avoidable? Actual numbers will vary from case to case, but a liquified natural gas (LNG) operations executive put it this way “Last year, we lost $100 million due to trips, and 80 percent of those trips were avoidable.” That’s a lot of avoidable loss. leverages machine learning algorithms to analyze tens of thousands of tags (plant data) in real-time, and surfaces specific anomalies that could lead to unplanned trips or flaring events. Detecting hard-to-find, emerging issues is the first half of the battle. The second, equally important part is surfacing these issues in real-time, in an intuitive, actionable format that allows energy producers to take proactive measures to address them and nip them in the bud.

How much faster is troubleshooting with AI? Ten times faster. One plant manager, who used a troubleshooting platform for the first time said, “This would have taken me all day… staring at 60 trends… And even then I may have missed it…” reduces the hours-long task of triage to a single click.

Read more at Oilman Magazine