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.

Natural gas is an abundant resource across the United States, of which methane (CH4) is the main component. About 2% of extracted CH4 is lost through leaks. The Remote Methane Leak Detector (RMLD)-Unmanned Aerial Vehicle (UAV) system was developed to investigate natural gas fugitive leaks in this study. The system is composed of three major technologies: miniaturized RMLD (mini-RMLD) based on Backscatter Tunable Diode Laser Absorption Spectroscopy (TDLAS), an autonomous quadrotor UAV and simplified quantification and localization algorithms. With a miniaturized, downward-facing RMLD on a small UAV, the system measures the column-integrated CH4 mixing ratio and can semi-autonomously monitor CH4 leakage from sites associated with natural gas production, providing an advanced capability in detecting leaks at hard-to-access sites compared to traditional manual methods. Automated leak characterization algorithms combined with a wireless data link implement real-time leak quantification and reporting. This study placed particular emphasis on the RMLD-UAV system description and the quantification algorithm development based on a mass balance approach. Early data were gathered to test the prototype system and to evaluate the algorithm performance. The quantification algorithm derived in this study tended to underestimate the gas leak rates and yielded unreliable estimations in detecting leaks under 7 × 10 − 6 m3/s (~1 Standard Cubic Feet per Hour (SCFH)). Zero-leak cases can be ascertained via a skewness indicator, which is unique and promising. The influence of the systematic error was investigated by introducing simulated noises, of which Global Positioning System (GPS) noise presented the greatest impact on leak rate errors. The correlation between estimated leak rates and wind conditions were investigated, and steady winds with higher wind speeds were preferred to get better leak rate estimations, which was accurate to approximately 50% during several field trials. High precision coordinate information from the GPS, accurate wind measurements and preferred wind conditions, appropriate flight strategy and the relative steady survey height of the system are the crucial factors to optimize the leak rate estimations.

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The urgency to reduce methane emissions to the atmosphere is driving industry adoption of advanced technologies for methane measurement and monitoring. We present a suite of laser-based products for detecting, locating, and measuring methane sources.

There are 100,000’s of oil and gas storage tanks and tank batteries at upstream production sites. These sites have shown to be inadvertent, intermittent, generally unmonitored, high flow rate (flux) methane emitters; their emission rates are poorly quantified. Flux measurements are inhibited by the difficulty to directly access emission sources, instrument limitations and high-cost, and inability to distinguish between unintentional fugitive emission events (leaks) versus routine venting from pneumatic valves and compressors. Novel cost-effective and reliable continuous quantitative methane flux measurement technologies are needed to address these challenges. Methane is a potent greenhouse gas, and emissions from these sites need to be detected and prioritized for repairs based on emission rates. This paper describes a continuous methane emission monitor that combines our easily-installed high-speed laser-based long-open-path sensor, the Remote Emissions Monitor (REM), with a unique and novel fast laser beam scanning mechanism to create “flux planes” along site perimeters. This Enhanced REM (eREM) directly measures and reports emission rates (e.g. scfh) of methane plumes transported through the flux plane at about 1Hz without the need for plume modeling. The inherent temporal resolution enables novel statistical data processing that identifies routine vents and distinguishes them from unintended emissions. The simplicity of design, ease of installation, and minimal maintenance enable economically attractive fast and accurate detection and quantification of methane leakage.