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Identifying fugitive methane leaks can improve predictive maintenance of the extraction process, can extend gas extraction equipment lifetime, and eliminate hazardous work conditions. We demonstrate a wireless sensor network based on cost effective and robust chemi-resistive methane sensors combined with real time analytics to identify leaks from 2 scfh to 1000 scfh. The chemi-resistive sensors were validated to have a sensitivity better than 1 ppm in methane plume detection. The real time chemical sensor and wind data is integrated into an inversion models to identify the location and the magnitude of the methane leak. This integrated sensing and analytics solution can be deployed in outdoor environment for long term monitoring of accidental methane plume emissions, generate recommendations about fixing them, and ensure compliance with local government regulations.