Hundreds of thousands of unconventional natural gas wells recently constructed across North America have transformed the global energy landscape and generated widespread concern relating to fugitive methane leakage. To date, no studies have evaluated the integrity of unconventional wells post-abandonment. Here, we evaluated emissions at nine decommissioned unconventional wells within the Montney region of British Columbia, Canada and found two exhibited co-emission of CH₄ and CO₂ from surrounding soils indicating integrity failure, releasing up to ~2000 kg of CO₂-eq/yr into the atmosphere. A further three wells exhibited statistically significant anomalous CO₂ fluxes of ~500 kg/year from surficial soils around the well, likely associated with minor integrity failure and derived from near total soil-based aerobic oxidation of fugitive CH₄. These findings suggest that more than half of decommissioned unconventional wells may generate emissions, however only relatively small contributions to GHG emissions result that are significantly mitigated through natural soils-based CH₄ oxidation.

How to cite: Cahill, A.: Evaluating Methane Emissions From Decommissioned Unconventional Petroleum Wells in British Columbia, Canada, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22532, https://doi.org/10.5194/egusphere-egu24-22532, 2024.

Periodic comprehensive or screening leak detection and repair (LDAR) surveys are a central part of many current regulations, which are intended to reduce unintentional methane emissions caused by leaking infrastructure.  In principle, by swiftly identifying and repairing leaks, emissions of methane, a potent greenhouse gas, are reduced.  The primary tools used for comprehensive LDAR surveys are Optical Gas Imaging (OGI) cameras.  While OGI can be effective for detecting and visualizing methane leaks, its extension to quantitative measurement (QOGI) is notoriously imprecise.  Moreover, studies have shown considerable variation in the performance of OGI in practice, where successful use is heavily dependent on the skill of the operator. 

Manual OGI surveys are also time consuming and labour intensive.  Implementing and maintaining an effective LDAR program that involves multiple OGI surveys per facility can be costly, potentially disrupting routine operations while requiring the deployment of trained personnel to each site.  Although operators are obligated to address and verify the repair of identified leaks, there is also still potential that significant leaks may be allowed to persist if they are not initially detected.  Consequently, despite the substantial costs involved, the full potential of methane reduction benefits may not be realized.  By contrast, aerial surveys have the potential to overcome many of the negatives associated with OGI surveys. In particular, aerial surveys can permit large numbers of sites to be surveyed per day at significantly lower cost per site, reducing overall compliance costs, labour requirements, and improving safety through reduced risks.  However, there remains no objective way to assess the relative performance of aerial surveys in complementing or replacing LDAR surveys under different scenarios.  In the context of emerging regulations, this is an especially important topic.

This work seeks to directly compare the effectiveness of conventional OGI surveys and aerial measurement under real-world conditions.  At an identical set of approximately 500 operating oil and gas sites in British Columbia, Canada, we compare and contrast detected and quantified sources in regulated LDAR surveys with parallel aerial surveys completed using Bridger Photonics’ Gas Mapping LiDAR (GML) technology.  The publicly reported LDAR reports are parsed to analyze patterns in detected emissions on 1 and 3 times per year deployments which are contrasted with aerial measurements at the same set of sites.  This direct contrast under real world conditions gives one of the first large scale tests of LDAR and aerial performance in practice, helping to provide quantitative guidance for the design of potential alternative LDAR programs under emerging regulatory scenarios.

How to cite: Wilde, S., Tyner, D., Conrad, B., and Johnson, M.: A Comparison of the Effectiveness of Regulated OGI Leak Detection and Repair (LDAR) Surveys and Aerial Measurements in the Real-World, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6658, https://doi.org/10.5194/egusphere-egu24-6658, 2024.

The goal of reducing anthropogenic methane emissions, in particular those arising from oil and gas operations, will require the implementation of routine and effective monitoring, both to detect repairable emissions and to reliably report emitted quantities. This will mean a transition from research investigations to more formal requirements for monitoring which will be the responsibility of industry. Methane emissions are particularly challenging to measure as the sources are highly inhomogeneous in terms of the ranges of their emission characteristics such as emission rate, temporal behaviour, and the wide variety of potential sources of emissions (ducted emissions, vents, fugitive leaks from components, storage tanks, flares, onshore and offshore facilities). To enable baselining and reliable reporting from across different parts of the oil and gas industry, and to address the different needs from detection to quantification, a range of different methods based on different measurement technologies are needed. This has resulted in a large number of available and developing approaches. Industry will need confidence in the emissions data they report as they will be used to guide emission reduction activities and to report into international frameworks such as the IMEO. In future there will be increasing regulatory pressure.   
To support these growing requirements, and to support the selection of appropriate methods, there is therefore a need for a metrology framework to ensure the quality, reliability, comparability and suitability of measurement methods. It is important that the measurement uncertainties associated with methods are well understood including key sources of uncertainties, and the impact of the use of methods in different conditions and locations. This will not only support the selection of appropriate methods, but also enable the interpretation and comparison of data between sources and over different scales (both temporal and spatial).
This talk will outline these issues, review the requirements for defining clear measurement objectives and performance requirements and provide an illustration of what such a metrology quality framework would look like.  The talk will discuss the issues around determining the uncertainties in methane emission measurements and in particular in derived data such as emission rates, and the use of validation studies and controlled releases will be discussed. It will also provide an overview of current activities to develop standardised methods for monitoring methane emissions and to develop the tools to support the evaluation of such methods.

How to cite: Robinson, R., Innocenti, F., and Helmore, J.: The requirements for standardisation and performance evaluation for methane emissions monitoring technologies – a metrology perspective., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10605, https://doi.org/10.5194/egusphere-egu24-10605, 2024.

Curbing methane emissions is a crucial aspect of achieving emissions reduction targets across the world. This is particularly important in Colombia, where it is estimated that 24% of anthropogenic methane emissions originate from the energy sector (IEA, 2023). However, the mitigation potential remains hampered by a lack of understanding of emission sources in the field and limited access to accurate official inventories.  The objective of this study is to develop a comprehensive inventory of methane emissions within the oil and gas industry in Colombia. The implemented framework consists of a hybrid inventory that integrates top-down, source-resolved aerial measurements with bottom-up measurements following the published methodology of Johnson et al., Comms. Earth & Environ, 2023. This approach not only facilitates a detailed attribution of emission sources but also quantifies the measurement and sample size uncertainties, employing the detection probability of the airborne sensor, Monte Carlo analysis, and bootstrap analysis.  For this study, around 3,400 facilities were included in the top-down campaign, complemented by a select sample of facilities in a parallel bottom-up campaign. The total facility sample covers six different production regions across five departments, including a wide range of oil and gas facilities and production types. This presentation will discuss the initial results of the field campaigns and progress towards the completion of a first-ever measurement-based methane inventory for Colombia that is intended to be used to support verified reporting under the International Oil and Gas Methane Partnership (OGMP 2.0).

How to cite: Calderon-Cangrejo, N., Festa-Bianchet, S. A., Conrad, B. M., Tyner, D. R., Wilde, S. E., and Johnson, M. R.: Combining Aerial and Ground Surveys to Quantify Oil and Gas Sector Methane Emissions in Colombia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20581, https://doi.org/10.5194/egusphere-egu24-20581, 2024.

Recent emphasis on decreasing methane emissions from oil and gas production and transport has stimulated the development of multiple regulatory and voluntary reporting programs.  These programs include monitoring and verification requirements, commonly known as MMRV (methane monitoring, reporting and verification).  An underlying assumption in these programs is the use of advanced methods to estimate emissions, including continuously installed sensors at facilities and aerial, satellite and driving survey methods. These methods provide emission estimates at the scale of major sources or entire facilities. Regulatory programs in the USA and EU are increasingly tying these estimates to substantial financial risks while encouraging anonymous 3^rd party measurements, raising the stakes for using these methods.  This abstract reviews recent studies of these methods, and reviews four areas of concern. 

First, multiple commonly used methods display accuracy problems which are likely to be present in most methods. Recent studies study assessed methods at production and midstream facilities onshore in the USA.  Two methods deployed simultaneously at 14 midstream facilities disagreed by 2:1 averaged across all facilities and by more than 2:1 at 6 of the facilities.  Other studies in U.S.A production and European midstream have identified similar accuracy issues. 

Second, ‘measurement informed inventory’ methods, which use full-facility estimates to update emissions reporting, remain poorly developed and unevenly implemented.  While one study found that survey methods identified large emitters and operators corrected reporting, another study found that most aerial detections did not result in effective corrections to inventory estimates. 

Third, methods used to extrapolate facility-scale estimates to basin scale have unaddressed uncertainties.  Recent work indicates that 9-49% of plumes detected by aircraft methods are due to maintenance emissions, which are poorly characterized by anonymous aerial sampling.  Additionally, extrapolation methods poorly estimate short emission events, resulting in a significant potential to over-estimate of emissions.  Conversely, random non-detects of exhaust emissions likely under-estimates emissions from engines and combustors by a factor of 2 or more.  These errors both shift emission between sectors and may result in significant bias. Additional control inputs, better GIS data, and improved methods are required to better estimate regional emissions.  

Finally, recent studies of continuous emissions monitors in both controlled and field tests indicate poor quantification accuracy in controlled testing, and poorer accuracy in field conditions. 

While advanced methods show promise for improving emissions detection and mitigation, consumers of these data need to be aware of the performance of these methods and account for bias, uncertainty, and variability of emissions estimates when constructing programs that utilize these estimates.

How to cite: Zimmerle, D.: Impact of Emissions Estimation Uncertainty on Methane Monitoring Reporting and Verification (MMRV) Programs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14035, https://doi.org/10.5194/egusphere-egu24-14035, 2024.

Establishing a streamlined workflow within the Monitoring, Measuring, Reporting, and Verifying (MMRV) framework is crucial for effective methane emission management and accurate methane emission reconciliation in the oil and gas (O&G) industry. Despite existing MMRV standards such as the Oil & Gas Methane Partnership 2.0 (OGMP 2.0), Veritas 2.0, and MIQ providing valuable guidance, the O&G industry still faces obstacles in compliance with these standards. These obstacles include (1) The Bottom-Up (BU) inventory, constructed with generic activity and emission factors, underestimates emissions and poses gaps in closing uncertainties during the reconciliation process, (2) The decision to deploy one or multiple methane sensing technologies, relying on emission profiles derived from limited sample measurements, can not accurately represent all emissions due to their inherent limitations and the stochasticity and intermittency of emissions, (3) No standard has been employed to assimilate observations from sensing technologies with varying measurement scales and data from operational events, and (4) Addressing various uncertainties, including those arising from direct measurements, atmospheric inversion modeling, and population inference from sample emission events, proves challenging in the final stages of the reconciliation process.

In this study, we present a streamlined MMRV-focused workflow integrating established and novel methodologies for reconciling emissions. The workflow consists of five key steps: Firstly, using the Oil and Gas Production Greenhouse Gas Emissions Estimator (OPGEE) to construct more accurate BU inventories and emission profiles for each type of equipment; secondly, determining the technology deployment plan and work practice based on constructed emission profiles using the Leak Detection and Repair Simulator (LDAR-Sim); thirdly, assimilating real measurements from deployed technologies through an ISO/OGC standard-based integrated sensor web architecture; fourthly, leveraging assimilated measurements and operational data to resolve emission events and reconcile the emissions; and finally estimating uncertainties from emission quantifications, inaccuracies in establishing emission event duration, and missed emission events. We demonstrate this workflow using data from the upstream O&G sites provided by an anonymous company. At the end of the demonstration we reconcile and report emissions by following the OGMP 2.0 guidelines. 

How to cite: Gao, M. and Liang, S.: Toward developing a streamlined workflow for methane emission monitoring, reporting, and verification in the oil and gas industry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7156, https://doi.org/10.5194/egusphere-egu24-7156, 2024.

Natural gas (NG) leakage from belowground pipelines is currently poorly understood, even though it is an area of safety, environmental, and economic concern. To date, there are limited studies on the transient behavior of NG, defined as the speed and maximum extent that gas travels belowground, and how this behavior changes with soil, environmental and leak characteristics. What is least identified is the interrelation between each controlling parameter, how to properly parameterize and characterize as well as the proper field application, specifically operator and first responder protocols. To address this gap, this work identifies key parameters influencing the transient behavior of leaked NG in the subsurface and opportunities to link this understanding to operator practice.  Though a three-year long series of over 150 controlled release experiments conducted at Colorado State University’s Methane Emission Technology Evaluation Center (METEC) and parallel numerical modeling we’ve investigated subsurface methane migration rates and extents and subsequent emission to the atmosphere. Experimental results were used to understand overall transient behavior both during and after terminating the leak. Numerical simulations were then used to extend experimental results to other conditions (e.g. additional soil types, surface conditions, and belowground infrastructure). Results demonstrate the impact of temporary rain and snow surface conditions on the extent and duration of leak transport, resulting in levels that pose heightened environmental and safety risks.  Furthermore, after leak termination, our findings demonstrate the isolated changes in the belowground migration time and the extent of leaked gas, driven by changes in surface and atmospheric conditions, a key point not consistently included in risk assessments or environmental emission rate calculations. While efforts to study a wider range of environmental conditions is underway, the findings of this study provide crucial insight to on identifying and prioritizing emissions from the perspective of both safety and the environment. 

How to cite: Smits, K., Jayarathne, N., Zimmerle, D., Riddick, S., and Kolodziej, R.: Unraveling Natural Gas Migration Rate and Extent from Leaking Underground Pipelines under Varying Environmental Conditions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4598, https://doi.org/10.5194/egusphere-egu24-4598, 2024.

Satellite observations are an important tool in large emission event detection and global monitoring of methane emissions from oil and gas facilities, but current satellite-based methods face significant uncertainty. One of the major sources of uncertainty is a high rate of false positives. Current methods to mitigate false positive rates typically involve manual inspection of plume imagery, a time-consuming process which introduces human error. The Sentinel-2 multispectral satellite is widely used in global methane observation, as methane enhancements can be identified by a signal in shortwave infrared bands 11 and 12.  However, physical, biological and other anthropogenic processes can have a similar spectral signature, leading to a high rate of false positives. We present an empirical False Discovery Rate approach for quantifying the false positive probability for a given candidate plume. Imagery data is divided into a near-to-well set (within 200m of oil and gas infrastructure) and a far-from-well control set (between 400m-1200m away from oil and gas infrastructure), which is conservatively assumed to consist entirely of false positives. With these datasets, we define the probability of a false positive given proximity to oil and gas infrastructure as a function of plume quality and distance to infrastructure.  The results from this approach are shown for a case study over the contiguous United States, where we found a strong relationship between the selected plume quality metrics, distance to infrastructure and the false positive probability. We also identified significant differences in plume characteristics between the near-to-well and far-from-well datasets.  This work presents a more efficient and data-driven false positive algorithm, which can significantly reduce the manual step in false positive identification, resulting in larger scale deployment and data processing of satellite-based methane emission monitoring.

How to cite: Rischard, M., Schissel, C., and Niazi, M.: Methane leak or false positive? An automated probabilistic treatment of detected emissions from oil and gas facilities in multi-spectral satellite imagery at continental scale., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16519, https://doi.org/10.5194/egusphere-egu24-16519, 2024.

Ambition on methane emissions reduction is growing, and open, reliable, measurement-based and actionable data is essential to track changes in emissions over time. The ability of countries and companies to meet their goals requires a thorough understanding of the magnitude and location of methane emissions, as well as being able to demonstrate progress towards these goals.  

As a core implementing partner of the Global Methane Pledge, the UN Environment Programme’s International Methane Emissions Observatory (IMEO) has been tasked with creating a sound scientific basis for methane emissions estimates and is providing reliable, public, policy-relevant data to facilitate actions to reduce methane emissions. IMEO is collecting and integrating diverse methane emissions data streams, including satellite remote sensing data, science studies, national inventories, and measurement-based industry reporting to establish a global, centralized public record of empirically verified methane emissions. 

Here, we will show the progress of IMEO towards developing its global, public dataset of policy-relevant methane data, highlighting successful mitigation case studies for the oil and gas industry from the pilot phase of IMEO’s Methane Alert and Response System (MARS), and from IMEO’s Methane Science Studies. We demonstrate how empirical data can drive real, tangible mitigation action in countries around the world.  

How to cite: Zavala-Araiza, D., Hamburg, S. P., Calcan, A., Schwietzke, S., France, J. L., Randles, C., Baranski, M. R., Demeter, M., Kupers, R., Field, R., and Caltagirone, M.: Transparent Horizons: IMEO's Methane Data Empowering Global Climate Action , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20055, https://doi.org/10.5194/egusphere-egu24-20055, 2024.

This work will present a quantitative evaluation of the potential for measuring gas flare combustion efficiency using an aspirating sensor platform mounted under an uncrewed aerial vehicle (UAV).  The UAV sensor package contains lightweight commercial gas analyzers capable of precise measurements of atmospheric methane (CH₄), ethane (C₂H₆), carbon dioxide (CO₂), and carbon monoxide (CO).  By sampling the flare’s plume of combustion products with the help of a UAV, flare efficiency measurements can be safely and remotely completed without affecting the flare’s operation.  The relative mole fraction of the measured major carbon containing species can be used to close a carbon mass balance, which permits calculation of a local carbon conversion efficiency of the flare.  However, because the composition of the flare plume can be inhomogeneous as well as turbulent, it is not straightforward to determine whether the measured incomplete combustion products are representative of total inefficiencies.  Further uncertainty arises if the flared gas contains additional hydrocarbon species (e.g., C3+ hydrocarbons) that may not be directly measurable by the UAV platform.  To address these challenges, controlled experiments were completed on large scale (100-mm diameter) flares burning within Western University’s Boundary Layer Wind Tunnel.  With the wind tunnel running in an open circuit configuration, the UAV/sensor package was suspended within the wind tunnel test section downstream of the flare where it measured combustion efficiency while being moved in and out of the combustion plume.  Results were compared with known combustion efficiencies for identical operating conditions obtained following the established method of Burtt et al. (J. Energy Inst. 2022).  Further, combustion efficiency measurements from operating flares will be made using the developed sensor to validate the proposed measurement approach.  Ultimately, this tool could close a known gap in our ability to quantify carbon conversion efficiency and methane slip from flares under field conditions as required under emerging measurement, reporting, and verification (MRV) programs.  

How to cite: Festa-Bianchet, S., Mohammadi, M., Tanner, A., Kopp, G., and Johnson, M.: Evaluation of a UAV-Based Methodology for Measuring Flare Combustion Efficiency, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14031, https://doi.org/10.5194/egusphere-egu24-14031, 2024.

The recent global focus on anthropogenic methane emissions mitigation has accelerated the development and deployment of novel technologies to detect, quantify, locate and prioritize mitigation of fugitive and process emissions of methane, particularly within the oil and gas supply chain. The majority of emissions within this infrastructure result from large and intermittent sources. One study¹ showed that the largest 5% of emissions (i.e. super emitters) typically contribute over 50% of the total emission volumeand another study² found that most sources (66%) are intermittent, and account for most (48%) of the emissions. The largest impact on emissions mitigation therefore can be realized by deploying detection methods and technologies that are matched to how these two classes of emissions manifest in the infrastructure. Continuous monitoring solutions that can image and pinpoint emission sources are especially well-suited for use at sites that are expected to have intermittent process emissions.

We present recent work utilizing novel Quantum Gas Lidar for continuous methane emissions monitoring in sludge treatment works where methane-rich biogas is produced from the anaerobic digestion of sewage sludge. Some of the biogas is consumed on site and the rest is cleaned, upgraded and fed into the natural gas distribution network. Monitoring campaigns are ongoing at three such plants in the UK, owned and operated by Severn Trent, two of which have full gas to grid infrastructure. The third site uses combined heat and power engines to convert the biogas into electricity for use on site. Specific elements of the infrastructure are targeted for continuous, automated measurement by the lidar system (especially the digesters, gas storage, combined heat and power engines and gas to grid plants) and any detected methane emission plumes are imaged, their origins are pinpointed, and their emission rates are quantified. This results in a methane emission rate dataset having both high spatial and temporal resolution which can be used for both component and site-level emissions reporting within, for example, the OGMP 2.0 level 4 and level 5 framework, and IPCC Tier 3 (facility level) reporting. ³ The individual emission sources are intermittent and can have emission rates that vary in time depending on various process variables (i.e. varying pressures within the equipment) so that an accurate accounting of the overall emissions over time is reliant on the high-accuracy quantification and high temporal resolution that the lidar system provides. The continuous measurements have so far identified some previously unknown emission sources and have allowed the actual emissions of those sources to be accurately quantified for the first time, offering a high-confidence, measurement-based accounting of the methane emissions at these sites.

How to cite: Van Pelt, A., Srinamasivayam, B., Harrison, A., Millington-Smith, D., and Lindsay, G.: Using Quantum Gas Lidar for Continuous Methane Emissions Quantification of Gas to Grid Plants in Water Sewage Treatment Works., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2391, https://doi.org/10.5194/egusphere-egu24-2391, 2024.

To develop methods based on integrating the two-phase (liquid and gas) flow and free flow in the porous media to optimize the operation of subsurface gas venting, we developed a two-dimension soil aeration model based on the coupling of two-phase flow (liquid and gas) in the porous media with the single-phase flow (methane, CH₄) in the free-flow domain under homogeneous, isotropic, and isothermal conditions. The dissolution, bioreaction, and thermal diffusion of CH₄ are not included in the model. Numerical experiments were conducted with diverse near-surface meteorological conditions, soil properties (e.g., porosity, soil layering, air permeability, and soil moisture), and the deployment of venting bar holes to study the effects of environmental conditions and venting system designs on the gas flow in the subsurface. Simulation results not only demonstrated the capability of the soil aeration model on the prediction of the migration of the residual CH₄ concentration in the subsurface due to the venting but also highlighted the influence of soil permeability, deployment of venting bar holes, and the venting pressure on the change in residual gas concentration in the unsaturated zone. During the soil aeration, the low soil permeability impacted the migration of advective air flow by venting in the soil and prolonged the operation time of the soil aeration. Furthermore, the Peclet number of the gas migration significantly decreased from the center of the venting bar hole with the decrease in soil permeability and venting pressure. The variation of venting pressure is more sensitive to the development of venting flow rates than that of the number of venting bar holes. The proposed 2D soil aeration model and approaches of evaluation of soil aeration in this study provide insights to investigate the multiphase flow in the subsurface due to soil aeration operation under various environmental conditions and venting strategies.

How to cite: Lo, J.-H., Smits, K., and Zimmerle, D.: A Two-dimensional Model for the Gas Transport in the Unsaturated Zone with the Soil Aeration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4195, https://doi.org/10.5194/egusphere-egu24-4195, 2024.

We present an overview of aerial Gas Mapping LiDAR (GML) technology and its application to methane emissions monitoring and informatics for oil and gas infrastructure. The GML sensor combines spatially scanned and coaligned topographic and path-integrated methane concentration LiDAR measurements with navigation data and aerial photography to provide episodic detection, localization, emission rate quantification, and emission source attribution of methane plumes within scanned infrastructure. Aerial deployment enables rapid and efficient coverage of large and dispersed infrastructure. High sensitivity LiDAR measurements allow detection of methane emissions at rates below 1.5 kg/h with greater than 90% probability of detection in most deployment conditions, resulting in the detection of more than 90% of emissions from typical oil and gas production basins. The high spatial resolution of the LiDAR scans provides geo-location of emission sources, typically to within 2 m, for targeted LDAR response and reliable emission source attribution. Well characterized emission rate estimates, produced by combining LiDAR methane concentration measurements with gas flow speed information, allow source-level prioritization of LDAR response and enable accurate source-resolved methane emissions inventories.  Real-world examples of Gas Mapping LiDAR use cases will be presented and requirements for producing large-scale methane emission inventories including sample planning, facility and equipment identification, emission rate quantification accuracy, detection sensitivity, and statistical analysis methods will be covered. Specific applications of the GML technology include leak detection and repair (LDAR); measurement, monitoring, reporting, and verification (MMRV) programs; measurement-based methane emissions inventory and intensity benchmarking and reductions tracking; and differentiated gas certification programs. © 2024 The Author(s)

How to cite: Thorpe, M., Kreitinger, A., Roos, P., Brasseur, J., Losby, B., Greenfield, N., Carre-Burritt, A., Kunkel, W., Altamura, D., Dudiak, C., Donahue, C., and Moscona, B.: Aerial Gas Mapping LiDAR for Methane Emissions Management at Oil and Gas Infrastructure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13335, https://doi.org/10.5194/egusphere-egu24-13335, 2024.

The Heath Discover – Advanced Mobile Leak Detection (AMLD) is an ultra-sensitive advanced technology capable of detecting natural gas leaks or emissions from a remote distance while driving on a street or right of way. It allows the user to cover large areas for compliance or emission surveys and provides reports and GIS data with breadcrumb trail on a Windows-based tablet app.

The Discover AMLD employs a mid-IR open path version of the proven TDLAS technology which has been used in other Heath Products such as RMLD-CS. It uses two Mid-Infrared Lasers, one each for Methane and Ethane, that pass through the air in front of the vehicle. As the lasers pass through a gas plume, the methane and ethane absorb a portion of the light, which the instrument detects. Based on the local meteorological conditions, a given amount of gas escaping from the ground will produce a plume that varies in size and uniformity of concentration levels. The plume, by nature is variable and dependent on the soil type, moisture, temperature, wind, venting and leak rate.

The Discover AMLD technology is already employed at 4 major gas utilities 2 domestic and 2 international and is being used to find real world leaks and disaster-based surveys. It is helping to distinguish between sewer/Biogas leak and pipeline leaks and is able to localize and quantify the methane emissions. The technology was demonstrated in real world conditions at more than 50 domestic and international gas utilities with excellent results. METEC facility at Colorado State University has done extensive testing and confirmed the efficacy and accuracy of the technology in its ability to find, localize & quantify emissions. This is helping utilities rapidly find leaks and reduce methane emissions to keep communities safe and reduce greenhouse gas emissions.

The technology was developed and commercialized by Heath Products division by connecting with research scientists at Physical Sciences Incorporation a premier research organization based in Massachusetts and utilizing their most innovative ideas and bring them to life. By using their TDLAS technology and adopting it to an open path vehicle mountable system that can be very versatile and completely wireless without the need to modify the vehicle, Heath engineers and technicians were able make it into a manufacturable product and make it available commercially in the last quarter of 2022. Since then, the product has been demonstrated and has impressed the technology evaluation laboratories of gas utilities and academia with its real-world prowess in rapidly discovering methane emissions and improving productivity of surveys by a multiplier of 4 or more. We believe that this will be a game changing technology that will help utilities in making their operations safer, build trust with communities and make environmentally friendly energy available to hundreds of millions of people.

How to cite: Wehnert, P. and Six, E.: Discover Advanced Mobile Leak Detection (AMLD) - Natural Gas Leak Surveys Utilitzing Mid-IR Open Path TDLAS , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1698, https://doi.org/10.5194/egusphere-egu24-1698, 2024.