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Physical intelligence trader case study hub

Physical intelligence for traders:
market-moving signals identified early

Explore real-world examples of traders identifying disruptions and risks before the market does with proprietary sensor data.

See before the market

In energy trading, information arriving even minutes earlier could create a meaningful advantage. These case studies show how Wood Mackenzie's proprietary sensor network measures physical changes across oil, gas and power infrastructure before they appear in conventional market data, helping traders identify market-moving events earlier.

How traders gained an information advantage

Explore case studies showing how direct measurement of energy infrastructure provided earlier visibility into:

Infrastructure disruptions and flow changes
Production and supply shifts
Refinery and LNG facility operations
Generation outages, congestion events and demand changes
Emerging market imbalances

Oil

See how physical intelligence identified pipeline disruptions, refinery restarts and operational changes before they were reflected in traditional reporting channels. Featured examples include the Keystone pipeline leak and BP Whiting refinery restart.

4 hours ahead

A leak took ~600,000 b/d of Canadian crude offline, and PHMSA capped the restarted line at 80% pressure – a constraint that outlasted the outage. EMF sensors caught the flow drop within minutes, 4 hours before...

2–3 days ahead

Flooding shut the 440,000 b/d Whiting refinery during peak harvest season. Infrared caught the crude unit reheating 2-3 days before BP confirmed the restart – early enough for WoodMac subscribers to skip the panic buying and improve procurement economics by $0.20-$0.27/gal.

Gas

Explore how direct monitoring of gas infrastructure and LNG facilities provided earlier visibility into freeze-offs, supply disruptions and LNG outages. Featured examples include the Appalachia and Permian freeze-off and the Freeport LNG train shutdown.

~24 hrs ahead

A polar vortex froze off Appalachia and Permian gas production overnight. Pipeline sensors tracked the decline in real time, estimating a 2.5-3.5 Bcf/d loss by 6am ET – a full day before the market caught on, and 4 days before the EIA's weekly number confirmed it. WoodMac subscribers went long prompt gas and power ahead of the repricing. By the time public data caught up, Henry Hub had tripled, power prices had followed, and non-subscribers were buying at the top.

~5 hrs ahead

A Freeport LNG liquefaction train went dark in December 2025, with no public disclosure at the time. EMF sensors caught the drop – from ~31 to 20 milligauss – within 2 minutes, 5 hours before trade press picked up the story. WoodMac subscribers had that window to position as Henry Hub climbed from ~$3.20 to $4.40; anyone waiting on the pipeline EBB was already trading at the top by the time it confirmed the outage 30 hours later.

Power

Discover how real-time monitoring of generation, transmission and demand helped identify grid conditions, congestion risks and market-moving disruptions ahead of market repricing and broader awareness. Featured examples include the Comanche Peak generator trip and Tesla Gigafactory nodal basis event.

29 min ahead

One of ERCOT's largest generators lost half its output without warning. EMF sensors caught it within 60 seconds, 29 minutes before Hub North repriced ~24%. Overnight confirmation the unit remained offline opened a second window before next-day critical hours settled 63% above the prior peak.

$33/MWh loss avoided

A transmission line outage sent the node to ~$400/MWh while the hub remained near $40. Sensors identified the binding constraint 10 minutes before ERCOT's model. WoodMac subscribers captured $6/MWh on congestion products; desks relying on hub data lost $33/MWh.

How physical intelligence works

Wood Mackenzie's proprietary sensor network measures physical activity across energy infrastructure through technologies including infrared monitoring, electromagnetic sensors, satellite observation and vessel tracking. By measuring what is happening on the ground rather than relying solely on public reporting, traders gain earlier visibility into operational changes across interconnected energy markets. These sensors don't predict what's next. They reveal what's happening now, helping traders see before the market.

Learn more

Explore Wood Mackenzie Trading Analytics

Gain earlier visibility into price-moving events across oil, gas and power markets through the world's largest proprietary energy sensor network.

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