Gas Mapping LiDAR for large-area leak detection and emissions monitoring applications

Thorpe, Michael J.; Kreitinger, Aaron; Seger, Eric M.; Greenfield, Nathan; Wilson, Chris; Trey, Pierce; Kreitinger, Seth; Gordon, S. E.; Schmitt, R.L.; Roos, Pete

doi:10.1364/cleo_at.2017.af2b.1

Cited by 10 publications

(5 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During typical GML scans the plume height for detected releases is estimated using a technique that compares the LiDAR gas concentration measurements of the plume from multiple view angles described in Ref [17].…”

Section: Data Acquisitionmentioning

confidence: 99%

Deployment-invariant probability of detection characterization for aerial LiDAR methane detection

Thorpe,

Krietinger,

Altamura

et al. 2024

Preprint

View full text Add to dashboard Cite

Accurate detection sensitivity characterization of remote methane monitoring technologies is critical for designing, implementing, and auditing effective emissions monitoring and mitigation programs. Several research groups have developed test methods based on single/double-blind controlled release protocols and regression-based data analysis techniques to create probability of detection (PoD) models for characterizing remote sensor detection sensitivities. The previously created methods and models account for some of the important factors that affect detection sensitivity, such as wind speed, and in the case of Conrad et al. flight altitude. However, these models do not account for other important factors, such as terrain albedo, variation in individual sensor performance, or spatial density of the remote sensing measurements. In this paper, we build on the work of Conrad et al. by introducing a gas concentration noise (GCN) model for Gas Mapping LiDAR aerial methane detection technology that, when combined with wind speed at the emission location, accounts for all significant sensor and environmental parameters that affect detection sensitivity for scenarios involving an isolated emission source resulting in a single methane plume. We incorporate the GCN model into Conrad et al.’s PoD model and apply it to several sets of controlled release data acquired across widely varying deployment and environmental conditions to develop PoD models for Bridger Photonics Inc.’s first- and second-generation (GML 2.0) Gas Mapping LiDAR sensors. Finally, we compare controlled release data acquired by GML 2.0 in different geographic regions and terrain cover types, in different wind conditions, deployed on different aircraft types, and with different flight parameters. Results show that the GML 2.0 PoD model remains valid regardless of the location or conditions under which the sensors are deployed, and the aircraft and flight parameters used for deployment. Based on PoD measurements in 12 production basins across North America, the average 90% PoD emission rate for sites measured by GML 2.0 in 2023 was 1.27 kg/h.

show abstract

Section: Data Acquisitionmentioning

confidence: 99%

Deployment-invariant probability of detection characterization for aerial LiDAR methane detection

Thorpe,

Krietinger,

Altamura

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Hardware-based gas leak detection methods are used to detect gas leaks through certain special sensing devices, mainly including optical, acoustic, ultrasonic flow meter and cable methods. Thorpe et al [9] proposed a gas mapping LiDAR for large-area leak detection and emission monitoring applications by combining frequency-modulated continuouswave (FMCW) ranging and path-integrated gas concentration measurement techniques, which can display 3D highquality gas clouds for accurate gas leak monitoring, but the method is overly dependent on the reconstruction accuracy of 3D point clouds. It is worth noting that any leak occurs with anomalous temperature fluctuations around the leak point, and that distributed sensing systems enable gas leak detection using optical time-domain reflection [10].…”

Section: Introductionmentioning

confidence: 99%

Similarity evaluation method of single flow point energy consumption mapping based on Fréchet distance

Chen,

Lan,

Yan

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

Aiming at the problem of inaccurate measurement results caused by factors such as gas leakage during the calibration of the standard meter gas flow standard device of the same type and small diameter, this paper proposes a similarity assessment method of single flow point energy consumption mapping based on Fréchet distance (FD). First, through the statistical analysis of the historical energy consumption data of gas flow standard device, a discrete standard energy consumption mapping is formed. Next, the energy consumption mapping to be tested is standardized and the similarity of the energy consumption mapping is determined by the binary matrix accelerated search of the FD between the energy consumption mapping to be tested and the standard energy consumption mapping. Finally, the similarity threshold is calculated by combining the standard deviation of the FD and the reliability of the gas flowmeter calibration process is evaluated accordingly. The test shows that the method in this paper can effectively determine the reliability of the gas flowmeters calibration results.

show abstract

“…Therefore, the simultaneous measurement of the spectrum and the absolute distance can be realized in a single detection employing DCS. Such rich data measurement has the potential to be applied in air pollution monitoring [ 29 , 30 , 31 ] and remote sensing [ 32 ]. Our system provides a new standoff detection method to detect biological aerosols, explosives, and highly energetic materials [ 33 , 34 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

Achieving Precise Spectral Analysis and Imaging Simultaneously with a Mode-Resolved Dual-Comb Interferometer

Deng

Liu

Zhu

et al. 2021

Sensors

View full text Add to dashboard Cite

In this paper, we report a scheme providing precise spectral analysis and surface imaging, simultaneously, based on a high-coherence dual-comb interferometer. With two tightly phase-locking frequency combs, we demonstrate a high-coherence dual-comb interferometer (DCI) covering 188 to 195 THz (1538.5 to 1595.7 nm) with comb-tooth resolution and a max spectral signal-to-noise ratio (SNR) of 159.7. The combination of the high-coherence dual-comb spectrometer and a reference arm simultaneously enables gas absorption spectroscopy and for the absolute distance information to be obtained in one measurement. As a demonstration, we measure the spectrum of CO2 and CO. From the same interferograms, we demonstrate that distance measurement, by time-of-flight (TOF), can be resolved with an rms precision of 0.53 μm after averaging 140 images and a measurement time of 1 s. Finally, we demonstrate that non-contact surface imaging, using 2D mechanical scanning, reaches lateral resolution of 40 μm. The longitudinal precision is 0.68 μm with a measurement time of 0.5 s. It verifies that DCS has the potential to be applied in standoff detection, environmental pollution monitors, and remote sensing.

show abstract

Gas Mapping LiDAR for large-area leak detection and emissions monitoring applications

Cited by 10 publications

References 3 publications

Deployment-invariant probability of detection characterization for aerial LiDAR methane detection

Deployment-invariant probability of detection characterization for aerial LiDAR methane detection

Similarity evaluation method of single flow point energy consumption mapping based on Fréchet distance

Achieving Precise Spectral Analysis and Imaging Simultaneously with a Mode-Resolved Dual-Comb Interferometer

Contact Info

Product

Resources

About