How Computer Vision Streamlines Risk Avoidance Workflows in Oil & Gas
See how operators use aerial imagery and vision AI to find risks across pipeline networks.
Roboflow reads the fixed cameras, thermal and OGI cameras, drones, and aerial imagery you already have, watches the flares, the gauges, the tanks, the rights-of-way, and the people, and turns the field into data, in real time and at remote-site scale.
Wellsites, Flares, and Emissions:
Pipelines, Tanks, and Integrity:
Safety, People, and Systems Integration:
Bring intelligence to every site today.
What is computer vision in oil and gas?
Computer vision in oil and gas uses the cameras the industry already deploys, fixed site cameras, thermal and optical gas imaging cameras, drones, and aerial and satellite imagery, with deep-learning models trained for field conditions to monitor what operators care about: flare state and combustion quality, analog gauges and valve positions at unmanned sites, spills and leaks, right-of-way encroachment, tank and containment condition, corrosion and integrity indicators, and people and PPE around hazardous work. Detections flow into SCADA, historians, and control room alarm systems, so vision becomes another instrument on the site rather than another screen to watch. Learn more about corrosion detection for integrity findings, PPE detection and safety zone monitoring for people around hazards, and predictive maintenance for equipment condition.
Does this work at remote, unmanned sites with poor connectivity?
Yes. Inference runs at the edge on a small industrial computer at the site, on solar-and-battery power budgets where needed, so detection does not depend on a backhaul: the model watches locally, and only events, readings, and their images travel over the satellite, cellular, or radio link the site has. A gauge reading is a few bytes; a flare alert carries one frame. Cameras and enclosures are chosen for the environment, Class I Division 2 rated where classification requires it, heated housings for winter, and models are trained on your sites' actual footage, so heat shimmer over a pad in August and a snow-covered wellhead in January are training data rather than false alarms. When the link is down, events queue and sync when it returns.
Can it integrate with our SCADA, historians, and control room?
Yes. Roboflow Inference runs at the edge on site and exposes a standard API and the protocols operations already use, so vision events land in the systems operators already watch: SCADA platforms from Emerson, Honeywell, ABB, and AVEVA, historians like AVEVA PI, alarm management and control room displays, CMMS and integrity systems like SAP PM and IBM Maximo, pipeline control and leak detection systems, and field data capture tools, through REST, MQTT, OPC UA, Modbus, discrete I/O, and direct database writes. A smoking flare becomes an alarm with a frame attached, a gauge reading becomes a historian tag, an encroachment becomes a one-call ticket with coordinates, and every event carries site, asset, timestamp, class, reading or measurement, and imagery, with a full record behind every alarm and every report.
