Natural gas fugitive leak detection using an unmanned aerial vehicle: Localization and quantification of emission rate

Levi M. Golston, Nicholas F. Aubut, Michael B. Frish, Shuting Yang, Robert W. Talbot, Christopher Gretencord, James McSpiritt, Mark Andrew Zondlo

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

We describe a set of methods for locating and quantifying natural gas leaks using a small unmanned aerial system equipped with a path-integrated methane sensor. The algorithms are developed as part of a system to enable the continuous monitoring of methane, supported by a series of over 200 methane release trials covering 51 release location and flow rate combinations. The system was found throughout the trials to reliably distinguish between cases with and without a methane release down to 2 standard cubic feet per hour (0.011 g/s). Among several methods evaluated for horizontal localization, the location corresponding to the maximum path-integrated methane reading performed best with a mean absolute error of 1.2 m if the results from several flights are spatially averaged. Additionally, a method of rotating the data around the estimated leak location according to the wind is developed, with the leak magnitude calculated from the average crosswind integrated flux in the region near the source location. The system is initially applied at the well pad scale (100-1000 m2 area). Validation of these methods is presented including tests with unknown leak locations. Sources of error, including GPS uncertainty, meteorological variables, data averaging, and flight pattern coverage, are discussed. The techniques described here are important for surveys of small facilities where the scales for dispersion-based approaches are not readily applicable.

Original languageEnglish (US)
Article number333
JournalAtmosphere
Volume9
Issue number9
DOIs
StatePublished - Aug 23 2018

All Science Journal Classification (ASJC) codes

  • Environmental Science (miscellaneous)

Keywords

  • Inverse emissions
  • LDAR
  • Leak surveys
  • MONITOR
  • Methane emissions
  • Natural gas
  • Source estimation
  • UAV

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  • Cite this

    Golston, L. M., Aubut, N. F., Frish, M. B., Yang, S., Talbot, R. W., Gretencord, C., McSpiritt, J., & Zondlo, M. A. (2018). Natural gas fugitive leak detection using an unmanned aerial vehicle: Localization and quantification of emission rate. Atmosphere, 9(9), [333]. https://doi.org/10.3390/atmos9090333