Sensors driven by machine learning sniff-out gas leaks fast

A new study confirms the success of a natural-gas leak-detection tool pioneered by Los Alamos National Laboratory scientists that uses sensors and machine learning to locate leak points at oil and gas fields, promising new automatic, affordable sampling across vast natural gas infrastructure.

The automated leak location system finds gas leaks fast, including small ones from failing infrastructure, and lowers cost as current methods to fix gas leaks are labor intensive, expensive and slow, said Manvendra Dubey, the lead Los Alamos National Laboratory scientist and coauthor of the new study.