Maria Araujo inspects a drone that uses midwave infrared cameras (MWIR) to autonomously detect methane leaks. SwRI’s Smart LEak Detection System (SLED) uses computer vision and machine learning to detect pipeline leaks from aerial drones. Credit: Courtesy of Southwest Research Institute
Drone technology has made functioning of almost all industry segments more efficient and in this recent application drones are assisting in automated inspections of oil and gas facilities.
A Southwest Research Institute methane leak detection system is taking flight as part of a U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) project in which SwRI researchers will adapt the Smart Leak Detection System/Methane (SLED/M) technology to detect methane leaks in real time, from aboard a drone. SwRI developed SLED/M and also SLED technology which uses cameras and artificial intelligence to detect liquid hydrocarbon leaks on pipelines and facilities, such as pump stations.
Methane the main component in natural gas absorbs heat more effectively making it more threatening greenhouse gas than carbon dioxide. The World Meteorological Organization reports indicate that methane levels are 2.5 times higher than pre-industrial times. The ability of detecting gas leaks critical to the air quality of the atmosphere.
By pairing passive optical sensing data with artificial intelligence algorithms the system enables identification of small methane leaks, or fugitive emissions. The latest funding will enable SwRI to collect data, test Mid Wave Infrared Cameras (MWIR) on drone flights and develop machine learning algorithms to detect methane leaks.
Maria Araujo, a manager in SwRI’s Critical Systems Department said, “After successfully developing SLED/M for stationary applications, such as fence line monitoring of midstream facilities, we are advancing the technology to perform autonomously from drones,” adding, “drones and camera configurations present unique challenges because they capture data at different heights, distances and speeds. This funding enables development and testing to adapt the technology for commercial aerial inspections.”
While Conventional detection systems, designed to locate larger leaks, suffer from false positives and missed detections, which hamper effectiveness and utilization by industry SwRI designed SLED/M to pinpoint these smaller methane leaks that usually go unnoticed along pipelines and storage facilities.
The project will also leverage SwRI’s ongoing research into unmanned aerial systems (UAS), drone automation, navigation, perception and data analytics. SwRI’s recent drone innovations include adapting technology to autonomously inspect damaged nuclear reactors and other hazardous facilities.
Reiterating that this effort will help address a significant challenge facing the world Dr. Steve Dellenback, vice president of SwRI’s Intelligent Systems Division said, “SwRI’s R&D investment in drone payloads and analytics aligns with our mission to advance science and technology that benefits government, industry and humankind”.
SwRI is addressing methane leaks from multiple disciplines. A team of fluids engineers participated in the Methane Detectors Challenge, developing a solar-powered system to identify fugitive emissions in the gas-producing sector besides pairing satellite data from space with algorithms to identify large methane leaks from midstream facilities and crude oil spills on the ocean surface.