An open source algorithm to detect natural gas leaks from mobile methane survey data

• Published in: PloS one Vol. 14; no. 2; p. e0212287
• Main Authors: Weller, Zachary D., Yang, Duck Keun, von Fischer, Joseph C.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 13.02.2019; Public Library of Science (PLoS)
• Subjects: Air Pollutants - analysis; Air pollution; Algorithms; Black boxes; Census of Population; Chemical detectors; Cities and towns; Climate change; Computer and Information Sciences; Computer programs; Data analysis; Data processing; Data visualization; Earth Sciences; Ecology and Environmental Sciences; Engineering and Technology; Environmental aspects; Environmental Monitoring; Freeware; Gas leaks; Information management; Internet; Leaks; Measurement; Methane; Methane - analysis; Natural gas; Natural Gas - analysis; Natural gas distribution; Outdoor air quality; Physical Sciences; Pipelines; Polls & surveys; Quality Control; Research and Analysis Methods; Sensors; Software; Surveys; Surveys and Questionnaires; System effectiveness; United States; United States > US; Colorado
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0212287

The data collected by mobile methane (CH4) sensors can be used to find natural gas (NG) leaks in urban distribution systems. Extracting actionable insights from the large volumes of data collected by these sensors requires several data processing steps. While these survey platforms are commercially available, the associated data processing software largely constitute a black box due to their proprietary nature. In this paper we describe a step-by-step algorithm for developing leak indications using data from mobile CH4 surveys, providing an under-the-hood look at the choices and challenges associated with data analysis. We also describe how our algorithm has evolved over time, and the data-driven insights that have prompted these changes. Applying our algorithm to data collected in 15 cities produced more than 6100 leak indications and estimates of the leaks' size. We use these results to characterize the distribution of leak sizes in local NG distribution systems. Mobile surveys are already an effective and necessary tool for managing NG distribution systems, but improvements in the technology and software will continue to increase its value.