Publications & Presentations

Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Measurement System Description and Mass Balance Approach

Shuting Yang, RobertW. Talbot, Michael B. Frish, Levi M. Golston, Nicholas F. Aubut, Mark A. Zondlo, Christopher Gretencord, and James McSpiritt
Atmosphere 2018, 9(10), 383

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 x 10-66 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.

Monitoring fugitive methane emissions utilizing advanced small unmanned aerial sensor technology

Nicholas F. Aubut, Matthew C. Laderer, Shuting Yang, Robert W. Talbot, Levi M. Golston, Mark A. Zondlo, Paul D. Wehnert, and James Rutherford
27th World Gas Conference, June 25-29, 2018, Washington, DC

We integrated backscatter laser technology with a small Unmanned Aerial Vehicle to create a new platform for natural gas leak survey and quantification. Simulated flights with the sensor system

deployed on a rotating 10m diameter boom successfully located and quantified emission rates from a known methane source. Actual low-altitude flights conducting raster pattern surveys of wellhead
infrastructure located, visualized, and estimated flux from leaks smaller than 5 scfh.

Scanning, standoff laser-based leak imaging and quantification

Nicholas F. Aubut, Richard T. Wainner, Matthew C. Laderer, Paul D. Wehnert, and James Rutherford
27th World Gas Conference, June 25-29, 2018, Washington, DC

This paper reports a novel quantitative methane plume imaging tool, based on active near-infrared backscatter laser sensing technology. It integrates a laser sensor with a video camera in a future handheld

package to create a highly sensitive imager that also quantifies emission rate. It provides colorized quantified images of path-integrated methane concentration independent of background. The images depict methane plumes overlaid on a visible camera image of the background. This new tool addresses the need for reliable, robust, low-cost sensors to detect, image, and quantify fugitive methane emissions, enabling operators to prioritize repairs. We built a prototype platform that demonstrated quantitative performance in the laboratory and municipal field tests. Based on measured signal-to-noise ratios, it can quantify emissions as small as 0.25 scfh in seconds.

Development of the Virtual Source Training Toolkit for physically accurate simulation of the response of handheld radiation detectors

Development of the Virtual Source Training Toolkit for physically accurate simulation of the response of handheld radiation detectors
John Wright, Kirill Shokhirev, Eric Rappeport, Daniel Brown and Bogdan R. Cosofret
SPIE Defense and Commercial Sensing, Orlando, FL, 15 - 19 April 2018

Law enforcement officers and public safety personnel are a critical component of the Global Nuclear Detection Architecture, and would benefit from additional opportunities to train for this mission in realistic threat scenarios. Physical Sciences Inc.

(PSI) is developing a Virtual Source Training Toolkit (VSTT) system capable of reproducing the response of handheld radiation detectors to a virtual source in a complex occlusion and shielding environment. The toolkit will allow additional low-cost training opportunities for these officers inside operationally relevant public areas in order to reduce the time required to detect and localize a realistic radiological threat.

Active standoff chemical identification detector

Active standoff chemical identification detector
Jay P. Giblin*, Julia R. Dupuis, John P. Dixon, Joel M. Hensley, David J. Mansur, and William J. Marinelli
SPIE Defense and Commercial Sensing, Orlando, FL, 15 - 19 April 2018

An active, standoff, all-phase chemical detection capability has been developed under IARPA’s SILMARILS program. The detection platform utilizes reflectance spectroscopy in the longwave infrared coupled with an automated detection algorithm that implements physics-based reflectance models for planar chemical films, particulate in the solid and liquid phase, and vapors.

Target chemicals include chemical warfare agents, toxic industrial chemicals, and explosives. The platform employs broadband Fabry-Perot quantum cascade lasers with a spectrally selective detector to interrogate target surfaces at tens of meter standoff. A statistical F-test in a noise whitened space is used for detection and discrimination over a large target spectral library in high clutter environments. The capability is described with an emphasis on the physical reflectance models used to predict spectral reflectivity signatures as a function of surface contaminant presentation and loading. Developmental test results from a breadboard version of the detector platform are presented. Specifically, solid and liquid surface contaminants were detected and identified from a library of 325 compounds down to 30 μg/cm2 surface loading at a 5 m standoff. Vapor detection was demonstrated via topographic backscatter.