Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Localization and Quantification of Emission Rate

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...

Full description

Saved in:
Bibliographic Details
Published in:Atmosphere 2018-08, Vol.9 (9), p.333
Main Authors: Golston, Levi, Aubut, Nicholas, Frish, Michael, Yang, Shuting, Talbot, Robert, Gretencord, Christopher, McSpiritt, James, Zondlo, Mark
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Crosswinds
Detection
ENVIRONMENTAL SCIENCES
Flow rates
Flow velocity
Gases
Global positioning systems
GPS
inverse emissions
Lasers
LDAR
Leak detection
leak surveys
Localization
Locating
Methane
methane emissions
Methods
MONITOR
Monitoring systems
Natural gas
OTHER INSTRUMENTATION
Remote sensing
Sensors
source estimation
Surveys
UAV
Unmanned aerial vehicles
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2073-4433
2073-4433
DOI:10.3390/atmos9090333