Scientific Studies on Gas Mapping LiDAR

Kunkel, William, Michael Thorpe, Asa Carre-Burritt, Grant Aivazian, Nicholas Snow, Jacob Harris, Tagert Mueller, and Peter Roos. 2023. “Extension of Methane Emission Rate Distribution for Permian Basin Oil and Gas Production Infrastructure by Aerial LiDAR.” Environmental Science & Technology, August 2023, https://pubs.acs.org/doi/10.1021/acs.est.3c00229

Abstract

Aerial LiDAR measurements at 7474 oil and gas production facilities in the Permian Basin yield a measured methane emission rate distribution extending to the detection sensitivity of the method, 2 kg/h at 90% probability of detection (POD). Emissions are found at 38.3% of facilities scanned, a significantly higher proportion than reported in lower-sensitivity campaigns. LiDAR measurements are analyzed in combination with measurements of the heavy tail portion of the distribution (>600 kg/h) obtained from an airborne solar infrared imaging spectrometry campaign by Carbon Mapper (CM). A joint distribution is found by fitting the aligned LiDAR and CM data. By comparing the aerial samples to the joint distribution, the practical detection sensitivity of the CM 2019 campaign is found to be 280 kg/h [256, 309] (95% confidence) at 50% POD for facility-sized emission sources. With respect to the joint model distribution and its confidence interval, the LiDAR campaign is found to have measured 103.6% [93.5, 114.2%] of the total emission rate predicted by the model for equipment-sized emission sources (∼2 m diameter) with emission rates above 3 kg/h, whereas the CM 2019 campaign is found to have measured 39.7% [34.6, 45.1%] of the same quantity for facility-sized sources (150 m diameter) above 10 kg/h. The analysis is repeated with data from CM 2020–21 campaigns with similar results. The combined distributions represent a more comprehensive view of the emission rate distribution in the survey area, revealing the significance of previously underreported emission sources at rates below the detection sensitivity of some emissions monitoring campaigns.

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Festa-Bianchet, S. A., Tyner, D. R., Seymour, S. P., & Johnson, M. R. (2023). Methane Venting at Cold Heavy Oil Production with Sand (CHOPS) Facilities Is Significantly Underreported and Led by High-Emitting Wells with Low or Negative Value. Environmental Science & Technology. https://doi.org/10.1021/acs.est.2c06255

‌Abstract

Cold Heavy Oil Production with or without Sand, CHOP(S), facilities produce a significant portion of Canada’s conventional oil. Methane venting from single-well CHOPS facilities in Saskatchewan, Canada was measured (i) using Bridger Photonics’ airborne Gas Mapping LiDAR (GML) at 962 sites and (ii) on-site using an optical mass flux meter (VentX), ultrasonic flow meter, and QOGI camera at 11 sites. The strong correlation between ground measurements and airborne GML supported subsequent detailed analysis of the aerial data and to our knowledge is the first study to directly test the ability of airplane surveys to accurately reproduce mean emission rates of unsteady sources. Actual methane venting was found to be nearly four times greater than the industry-reported levels used in emission inventories, with ∼80% of all emissions attributed to casing gas venting. Further analysis of site-total emissions revealed potential gaps in regulations, with 14% of sites appearing to exceed regulated limits while accounting for 61% of measured methane emissions. Finally, the concept of marginal wells was adapted to consider the inferred cost of methane emissions under current carbon pricing. Results suggest that almost a third of all methane is emitted from environmentally marginal wells, where the inferred methane cost negates the value of the oil produced. Overall, the present results illustrate the importance of independent monitoring, reporting, and verification (MRV) to ensure accuracy in reporting and regulatory compliance, and to ensure mitigation targets are not foiled by a collection of disproportionately high-emitting sites.

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Johnson, Matthew R., David R. Tyner, and Bradley M. Conrad. 2023. “Origins of Oil and Gas Sector Methane Emissions: On-Site Investigations of Aerial Measured Sources.” Environmental Science & Technology, January. https://doi.org/10.1021/acs.est.2c07318.

Abstract

Success in reducing oil and gas sector methane emissions is contingent on understanding the sources driving emissions, associated options for mitigation, and the effectiveness of regulations in achieving intended outcomes. This study combines high-resolution, high-sensitivity aerial survey data with subsequent on-site investigations of detected sources to examine these points. Measurements were performed in British Columbia, Canada, an active oil- and gas-producing province with modern methane regulations featuring mandatory three times per year leak detection and repair (LDAR) surveys at most facilities. Derived emission factors enabled by source attribution show that significant methane emissions persist under this regulatory framework, dominated by (i) combustion slip (compressor exhaust and also catalytic heaters, which are not covered in current regulations), (ii) intentional venting (uncontrolled tanks, vent stacks or intentionally unlit flares, and uncontrolled compressors), and (iii) unintentional venting (controlled tanks, unintentionally unlit/blown out flares, and abnormally operating pneumatics). Although the detailed analysis shows mitigation options exist for all sources, the importance of combustion slip and the persistently large methane contributions from controlled tanks and unlit flares demonstrate the limits of current LDAR programs and the critical need for additional monitoring and verification if regulations are to have the intended impacts, and reduction targets of 75% and greater are to be met.

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Matthew R. Johnson, Bradley Conrad, David Tyner

Abstract

We present a new framework for incorporating aerial measurements into comprehensive oil and gas sector methane inventories that achieves robust, independent quantification of measurement and sample size uncertainties, while providing timely source-level insights beyond what is possible in current official inventories. This “hybrid” inventory combines top-down, multi-pass aerial measurements with bottom-up estimates of unmeasured sources leveraging continuous probability of detection and quantification models for a chosen aerial technology. Notably, the combined Monte Carlo and “mirror-match” bootstrapping technique explicitly considers skewed source distributions and finite facility populations that have not been previously addressed. The protocol is demonstrated to produce a comprehensive upstream oil and gas sector methane inventory for British Columbia, Canada, which while approximately 1.7 times higher than the most recent official bottom-up inventory, reveals a lower methane intensity of produced natural gas (< 0.5%) than comparable estimates for several other regions. Finally, the developed method and data are used to upper bound the potential influence of source variability/intermittency on the overall inventory, directly addressing an open question in the literature. Results demonstrate that even for an extreme case, variability/intermittency effects can be addressed by sample size and survey design and have a minor impact on overall inventory uncertainty.

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B.M. Conrad, D.R. Tyner, M.R. Johnson* (2023) Robust Probabilities of Detection and Quantification Uncertainty for Aerial Methane Detection: Examples for Three Airborne Technologies, Remote Sensing of Environment, 288:113499 (doi: 10.1016/j.rse.2023.113499)

Abstract

Thorough characterization of probabilities of detection (POD) and quantification uncertainties is fundamentally important to understand the place of aerial measurement technologies in alternative means of emission limitation (AMEL) or alternate fugitive emissions management programs (Alt-FEMP); monitoring, reporting, and verification (MRV) efforts; and surveys designed to support measurement-based emissions inventories and mitigation tracking. This paper presents a robust framework for deriving continuous probability of detection functions and quantification uncertainty models for example aerial measurement techniques based on controlled release data. Using extensive fully- and semi-blinded controlled release experiments to test Bridger Photonics Inc.’s Gas Mapping LiDAR (GML)TM, as well as available semi- and non-blinded controlled release data for Kairos LeakSurveyorTM 26 and NASA/JPL AVIRIS-NG technologies, robust POD functions are derived that enable calculation of detection probability for any given source rate, wind speed, and flight altitude. Uncertainty models are separately developed that independently address measurement bias, bias variability, and measurement precision, allowing for a distribution of the true source rate to be directly calculated from the source rate estimated by the technology. Derived results demonstrate the potential of all three technologies in methane detection and mitigation, and the developed methodology can be readily applied to characterize other techniques or update POD and uncertainty models following future controlled release experiments. Finally, the analyzed results also demonstrate the importance of using controlled release data from a range of sites and times to avoid underestimating measurement uncertainties

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Clay Bell et al., “Single-Blind Determination of Methane Detection Limits and Quantification Accuracy Using Aircraft-Based LiDAR,” Elementa: Science of the Anthropocene 10, no. 1 (November 14, 2022): 00080, https://doi.org/10.1525/elementa.2022.00080.

Abstract

Methane detection limits, emission rate quantification accuracy, and potential cross-species interference are assessed for Bridger Photonics’ Gas Mapping LiDAR (GML) system utilizing data collected during laboratory testing and single-blind controlled release testing. Laboratory testing identified no significant interference in the path-integrated methane measurement from the gas species tested (ethylene, ethane, propane, n-butane, i-butane, and carbon dioxide). The controlled release study, comprised of 650 individual measurement passes, represents the largest dataset collected to date to characterize GML with respect to point-source emissions. Binomial regression is utilized to create detection curves illustrating the likelihood of detecting an emission of a given size under different wind conditions and for different flight altitudes. Wind-normalized methane detection limits (90% detection rate) of 0.25 (kg/h)/(m/s) and 0.41 (kg/h)/(m/s) are observed at a flight altitude of 500 feet and 675 feet above ground level, respectively. Quantification accuracy is also assessed for emissions ranging from 0.15 to 1,400 kg/h. When emission rate estimates were generated using wind from high-resolution rapid refresh (HRRR) model (the primary wind source that Bridger uses for their commercial operations), linear regression indicates bias of 8.1% (R2 = 0.89). For 95% of controlled releases above Bridger’s stated production-sector detection sensitivity (3 kg/h with 90% probability of detection), the accuracy of individual emission rate estimates produced using HRRR wind ranged from −64.1% to +87.0%. Across all controlled releases, 38.1% of estimates had error within ±20%, and 87.3% of measurements were within a factor of two (−50% to +100% error). At low wind speed (less than 2 m/s) and low emission rates (less than 3 kg/h), emission estimates are biased high, however when removed do not impact the regression significantly. The aggregate quantification error including all detected emission events was +8.2% using the HRRR wind source. The resulting detection curves and quantification accuracy illustrate important implications that must be considered when using measurements from GML or other remote emission measurement techniques to inform or validate inventory models or to audit reported emission levels from oil and gas systems.

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Collaboratory to Advance Methane Science, “Permian Basin Survey: An Array of Aerial Surveys in the Permian Basin to Acquire the Baseline Distribution of Methane Emission Rates and Sources,” Whitepaper, Scientific Insights, August 2021, https://methanecollaboratory.com/wp-content/uploads/2021/08/Scientific-Insights-Aerial-Survey-in-Permian-August2021_vFinal.pdf.

Background and Objectives

The Collaboratory to Advance Methane Science (CAMS) is an industry-led research collaboration administered by GTI and dedicated to improving the scientific understanding of methane emissions, including emissions detection, measurement, and quantification. As part of its mission, CAMS evaluates new tools and emerging technologies to improve the detection of methane leaks and characterization of emissions. In 2020, the CAMS group commissioned a project to assess the capabilities of an airborne Light Detection and Ranging (LiDAR) technology for methane leak detection, localization, and quantification.

For the work performed in this study, CAMS contracted with Bridger Photonics, Inc. (Bridger) to deploy their commercially available Gas Mapping LiDAR™ (GML) technology to scan a statistically significant number of 
production facilities within the Permian’s Delaware and Midland Basin to detect, locate, and quantify sources of methane emissions. This work was performed over a two-week period during which aerial images of methane 
plumes were captured for five targeted areas in the Permian Basin.

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We present single-blind test results for quantification of very high emission rates using Bridger Photonics, Inc.’s (Bridger’s) airborne Gas Mapping LiDAR technology.  Flowmeter measurements from a controlled release are compared with emission rate quantification estimates from Gas Mapping LiDAR to determine Bridger’s measurement bias and uncertainty. 

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David R. Tyner and Matthew R. Johnson, “Where the Methane Is - Insights from Novel Airborne LiDAR Measurements Combined with Ground Survey Data,” Environmental Science and Technology 55, no. 14 (2021), https://doi.org/10.1021/acs.est.1c01572.

Abstract

Airborne LiDAR measurements, parallel controlled releases, and on-site optical gas imaging (OGI) survey and pneumatic device count data from 1 year prior, were combined to derive a new measurement-based methane inventory for oil and gas facilities in British Columbia, Canada. Results reveal a surprising distinction in the higher magnitudes, different types, and smaller number of sources seen by the plane versus OGI. Combined data suggest methane emissions are 1.6–2.2 times current federal inventory estimates. More importantly, analysis of high-resolution geo-located aerial imagery, facility schematics, and equipment counts allowed attribution to major source types revealing key drivers of this difference. More than half of emissions were attributed to three main sources: tanks (24%), reciprocating compressors (15%), and unlit flares (13%). These are the sources driving upstream oil and gas methane emissions, and specifically, where emerging regulations must focus to achieve meaningful reductions. Pneumatics accounted for 20%, but this contribution is lower than recent Canadian and U.S. inventory estimates, possibly reflecting a growing shift toward more low- and zero-emitting devices. The stark difference in the aerial and OGI results indicates key gaps in current inventories and suggests that policy and regulations relying on OGI surveys alone may risk missing a significant portion of emissions.

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Matthew R. Johnson, David R. Tyner, and Alexander J. Szekeres, “Blinded Evaluation of Airborne Methane Source Detection Using Bridger Photonics LiDAR,” Remote Sensing of Environment 259 (June 15, 2021): 112418, https://doi.org/10.1016/J.RSE.2021.112418.

Abstract
Controlled, fully-blinded methane releases and ancillary on-site wind measurements were performed during a separate airborne survey of active oil and gas facilities to quantitatively evaluate the capabilities and potential utility of the Bridger Photonics LiDAR-based airborne Gas Mapping LiDAR™ (GML) methane measurement technology under realistic field conditions. Importantly, although Bridger Photonics knew there was a ground team working in the area to deploy wind sensors as part of the broader survey of facilities, they had no knowledge whatsoever that controlled releases were taking place and were not informed of this until all data processing was complete. Thus, the presented data allow a true, fully-blinded assessment of the airborne technology's ability to both detect and locate unknown methane sources within active oil and gas facilities, as well as to quantify their release rates. Results were used to derive a lower-sensitivity limit threshold as a function of wind speed, which matches well with the broader field survey results. Comparison of measurement results with and without the benefit of on-site wind data reveal that uncertainty in the GML source quantification is a direct linear function of the uncertainty in the wind speed. Quantification uncertainties (1σ) of ±31–68% can be expected for sources near the sensitivity limit. The derived sensitivity limit function was incorporated into exploratory simulations using the Fugitive Emissions Abatement Simulation Toolkit (FEAST), which suggest that the Bridger GML technology has comparable performance to optical gas imaging (OGI) camera surveys both in terms of fraction of total emissions detected and anticipated net mitigation. The relative performance of the Bridger GML technology would be expected to improve or worsen as the assumed underlying distribution of source magnitudes becomes more or less positively skewed (i.e. more or less dominated by larger sources such as tank vents). Overall, the Bridger GML technology is shown to be capable of detecting, locating, and quantifying individual sources at or below the magnitudes of recent regulated venting limits. The presented detection sensitivity function will be useful for modelling potential alternate leak detection and repair strategies and interpreting future airborne measurement data.

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