1. Methane emissions – what does the peer-reviewed literature say? A scoping review to document the state of knowledge on measurements from the oil and gas sector
Authors: Coleman Vollrath, Chris Hugenholtz, Thomas Barchyn, Tyler Gough, Mozhou Gao, Michelle Clements
Methane is a major focus of international efforts to mitigate climate change and has fueled recent growth in research activity, technology start-ups, and emissions management consultancy. Synthesizing the state of knowledge on methane emissions from the cascade of information is difficult. To address this challenge, we performed a scoping review of the peer-reviewed literature with a standardized methodology and documented the state of research knowledge on methane emissions measurements from the oil and gas (O&G) sector. Here, we highlight five key findings from this review:
· First, we found that the research subject area is nascent, growing, and primarily based on studies completed in the last decade. As a result, the research-based understanding of emissions is still evolving, which creates uncertainty about the challenges and solutions.
· Second, research has relied heavily and increasingly on stand-off or screening methods to measure emissions, which may be influencing our understanding of the problem.
· Third, the majority (73%) of research published to date has targeted the U.S. O&G industry – mostly the upstream supply chain segment – while other major O&G-producing countries like Saudi Arabia, Russia, and China are under-represented. Are the U.S. findings representative of Canada’s emissions characteristics, or are there differences?
· Fourth, research indicates that top-down (TD) measurements of emissions are larger than bottom-up (BU) estimates. This suggests that there are missing sources in BU inventories, inaccurate emissions estimates, or incorrect activity factors.
· Finally, there is little empirical evidence in the literature directly connecting site-level screening measurements to emissions reductions. Screening may support reductions in practice, but it is not well-demonstrated in the peer-reviewed literature.
Based on these findings, we recommend the following actions to support Canada’s knowledge base: (1) test the conclusions from U.S. measurement studies in a Canadian context and identify the unique emissions characteristics of our diverse production types; (2) investigate the TD/BU discrepancy with targeted research; (3) build uncertainty into near-term policies to account for the evolving understanding of the problems and solutions needed to meet reduction targets; and (4) collect appropriate data to evaluate the reductions and efficacy of screening programs.
2. Satellite-based methane emissions from five oil and gas fields in Algeria, Turkmenistan, the U.S., and Canada
Authors: Zhenyu Xing*, Mozhou Gao, Coleman Vollrath, Thomas Barchyn, Chris Hugenholtz - Department of Geography, University of Calgary,
*: Corresponding author.
How do methane emissions from Alberta’s oil and gas (O&G) sector compare to other O&G fields in the world? Satellite observations from TROPOMI may help answer this question. Using TROPOMI observations and mass balance emissions quantification modeling, we estimated annual methane emissions in 2021 from five global regions with intensive production activities: the CHOPS area near Lloydminster, Canada; the Hassi R’Mel gas field in Algeria; the Dovletabat gas field and fields along the west coast of Turkmenistan; and the Permian basin in the U.S. We found that all five regions had significant enhancements of methane dry-air mole fractions (XCH4) compared to surrounding regions. Based on the mass balance method, regional emission rates were 0.2±0.1 Mt/yr from the CHOPS area in Canada, 0.5±0.4 Mt/yr from Hassi R’Mel gas field in Algeria, 0.9±0.6 and 0.2±0.1 Mt/yr from Dovletabat gas field and west coast of Turkmenistan, and 1.9±0.9 Mt/yr from the Permian basin in United States. These rates are 11.8, 2.0, 20.1, 2.3 and 1.6 times greater, respectively, than bottom-up estimates from the latest version of the Emissions Database for Global Atmospheric Research (EDGARv7.0). These discrepancies may be related to missing and/or poorly characterized anthropogenic sources in the EDGAR dataset, including O&G emissions. TROPOMI-based estimates indicate that the highest emission flux is from the two regions in Turkmenistan (54.9±36.4 t/yr/km2 from the west coast fields and 76.3±20.1 t/yr/km2 from Dovletabat field), followed by the Hassi R’Mel gas field in Algeria (22.3±16.4 t/yr/km2) and the CHOPS region in Canada (22.2±8.6 t/yr/km2). The lowest emission flux estimate was from the Permian basin (14.8±6.8 t/yr/km2). Our analysis highlights the need to apply more granular and targeted investigations to determine why differences occur between satellite estimates of methane emissions and bottom-up inventories.
3. How reliable are satellites for monitoring methane emissions from the oil and gas sector?
Authors: Mozhou Gao*, Zhenyu Xing, Coleman Vollrath, Chris Hugenholtz, Thomas Barchyn, Tyler Gough, Chandler Billinghurst, Marshall Staples, Clay Wearmouth, Michelle Clements - Department of Geography, University of Calgary
Satellite observations are providing important insights about methane emissions from the oil and gas (O&G) industry, particularly by revealing previously undocumented occurrences of very large (ultra) emissions events. They are expected to play a growing role in global methane monitoring. However, most satellite systems use passive remote sensing to retrieve methane mixing ratios, which is sensitive to sunlight, surface properties, and atmospheric conditions. Accordingly, the reliability of satellites for routine monitoring varies across the globe.
To better understand the opportunities and limitations of satellite-based methane emissions monitoring, we investigated the global observational coverage of the TROPOMI instrument onboard the Sentinel-5P satellite – the only satellite system with daily global coverage. Based on the recommended measurement retrieval quality-assurance threshold of ≥0.5, we created a global map showing the percentage of days in a year with valid observations from 2019 to 2021. The highest observational coverage (58.6%) occurred over dry continental regions and the lowest (0%) over tropical regions and at high latitudes. Cloud cover and solar zenith angle were the primary impeding factors at high latitudes, while aerosol optical thickness was the primary impeding factor in dry regions.
We extracted TROPOMI observational coverage of global O&G sector for the top 10 producing countries. In order of O&G production volumes, the median average annual observational coverages were: USA (9.5%), Saudi Arabia (20.8%), Russia (3.6%), Canada (4.1%), China (4.6%), Iraq (22.3%), UAE (8.7%), Brazil (2.1%), Iran (6.3%), and Kuwait (36.7%). Low observational coverage limits the ability to identify and quantify large emissions events and to derive regional emissions estimates using inverse modelling.
We also assessed the impact of TROPOMI observational coverage on using atmospheric inversion modelling to quantify regional methane emissions from the global O&G sector. We found that atmospheric inversion modelling may only maintain high performance in countries located in dry or mid-latitude regions, such as Algeria, Turkmenistan, and Iraq, where conditions are conducive for regular monitoring with TROPOMI. Therefore, O&G-producing countries in tropical and high-latitude regions, like Brazil, Russia, and Canada, should consider other methods for routine emissions monitoring.
4. Finding a needle in a sewing shop: a review of challenges and research directions within multi-source localization
Authors: Marshall Staples, Chris Hugenholtz, Thomas Barchyn, Mozhou Gao, Zhenyu Xing, Coleman Vollrath, Tyler Gough, Chandler Billinghurst, Michelle Clements - Department of Mechanical Engineering, University of Calgary
Scanning-based leak detection and localization methodologies offer the potential to reduce the cost of LDAR due to their ability to rapidly screen facility emissions. Drone and truck-based platforms have been used to detect, localize, and quantify methane emissions for research and applied purposes with varying levels of precision and accuracy. Currently, scanning methods are used to flag equipment with potential fugitive emissions to be further investigated by OGI crews. One of the primary criticisms of scanning-based methods is their inability to localize and quantify fugitive emissions that are within the plumes of other methane emissions on site. In order to account for these potential ‘hidden’ emissions some scanning methodologies flag for follow-up all equipment in the downwind plume to ensure all fugitive emissions are found. Some methodologies may naively assume that either fugitive emissions can’t or are very unlikely to be within the plume of another emission and just flag the area of the upwind emission source. In this case fugitive emission sources may be missed and not identified until the next scan. Missing emission sources can affect emission quantification depending on the quantification method used. To further increase the performance/cost savings of scanning-based methods, the size of the flagged areas needs to decrease. There are many existing algorithms intended to for use when there are multiple sources, but their performance is lacking. They were either designed with the assumption that plumes are static, and their concentration distribution does not change with time, or they identify large areas in which the plume could be coming from to ensure not a single fugitive emission sources is missed.
Here we use several examples to outline the problem and characteristics that make increasing localization accuracy and precision difficult in practice. We review work to date on the problem and chart future directions to improve localization accuracy, with direct translation to improved efficiency in scan-based surveys.
5. When a Drone and an Old Map Collide: Challenges of Methane Emissions Screening with the Alberta Township System
Authors: Tyler Gough*, Thomas Barchyn, Chris Hugenholtz, Coleman Vollrath, Mozhou Gao, Michelle Clements - Department of Geography, University of Calgary
Innovative methane emissions monitoring technologies that can guide us to a net-zero future are at the forefront of this conference. This work explores an underappreciated limitation to some of these technologies’ capacity to help achieve that future: the absence of precise locations for all potentially emitting infrastructure caused by an ongoing commitment to a nineteenth-century geospatial system. No emissions can be mitigated if they cannot be attributed to their source.
We seek engagement from all stakeholders on how they address and understand issues presented by the current status quo of using the Alberta Township System’s (ATS) legal subdivisions (LSDs) as the primary location identifier of wells and facilities. Some universal issues LSDs create are simple to understand. Most are familiar with the often-frustrating process of finding an unfamiliar oil and gas well: receive an LSD, drive to the area, and then try to find the correct access road – in forested areas or regions of dense production this process can be particularly frustrating and cause significant lost time. A new, related problem is emerging. Mobile emissions monitoring technologies require high-precision prior geospatial information to reliably locate a site for methane emissions attribution and measurement. In many cases, the only location data available are a facility’s LSD. In practice, this means that potentially emitting infrastructure could be present anywhere in an area the size of thirty football fields. This lack of precision presents a fundamental challenge for new screening technologies to automatically attribute emissions to a specific source location and can be solved only by labour-intensive ground validation and verification. Mobile technologies are promising next-generation emissions monitoring tools, but the level of sophistication, accuracy, and efficiency of these technologies’ outputs are currently limited by accurate location information. Precise prior location data is currently the ‘weak link’ in the emissions attribution chain for remote platforms. We suggest a simple solution: geospatial data practices for the purpose of emissions monitoring must be updated as part of regulatory reporting and separated from those used for leasing and drilling.