Dynamic fugitive methane leaks monitoring on natural gas well pads

Wireless sensor network are ideally suited to measure permanent or intermittent leaks on natural gas wellpads and combined with advanced analytics it can localize the leaks and determine their emission rate. We developed a robust sensing solution combined with data management, analytics and cloud based computation for individual and multi well pad monitoring. Combination of this bottom up approach with contextual data extracted from geospatial information allows well pad layout identification, specifying the number of required sensors and the optimum sensor placement for best fugitive methane leak analytics outcome.

Methane sensors combined with local weather station can detect a leak in less than 1 hour. Two fields test results are presented where the technology was tested with known and "blind" methane release to quantify the benefits of point type measurement. Using back tracing algorithm, fugitive leaks can be localized with 1 m of their locations and using both physics based plume models and applying machine learning approaches the leak rates are quantified. The advantage of distributed point source solution is precise localization of leaks, the reduction of the mean time to detection of fugitive methane leaks and measurement of leaks within a range of 2 scfh up to 500 scfh that are hard to capture with other detection techniques.