Aerial Interyear Comparison and Quantification of Methane Emissions Persistence in the Bakken Formation of North Dakota, USA

Temporal Variation and Persistence of Methane Emissions from Shallow Water Oil and Gas Production in the Gulf of Mexico

Methane emissions from the oil and gas supply chain can be intermittent, posing challenges for monitoring and mitigation efforts. This study examines shallow water facilities in the US Gulf of Mexico with repeat atmospheric observations to evaluate temporal variation in site-specific methane emissions. We combine new and previous observations to develop a longitudinal study, spanning from days to months to almost five years, evaluating the emissions behavior of sites over time. We also define and determine the chance of subsequent detection (CSD): the likelihood that an emitting site will be observed emitting again. The average emitting central hub in the Gulf has a 74% CSD at any time interval. Eight facilities contribute 50% of total emissions and are over 80% persistent with a 96% CSD above 100 kg/h and 46% persistent with a 42% CSD above 1000 kg/h, indicating that large emissions are persistent at certain sites. Forward-looking infrared (FLIR) footage shows many of these sites exhibiting cold venting. This suggests that for offshore, a low sampling frequency over large spatial coverage can capture typical site emissions behavior and identify targets for mitigation. We further demonstrate the preliminary use of space-based observations to monitor offshore emissions over time.

Large-Scale Controlled Experiment Demonstrates Effectiveness of Methane Leak Detection and Repair Programs at Oil and Gas Facilities

Most jurisdictions around the globe use leak detection and repair (LDAR) programs to find and fix methane leaks from oil and gas operations. In this work, we empirically evaluate the efficacy of LDAR programs using a large-scale, bottom-up, randomized controlled field experiment across ∼200 oil and gas sites in Red Deer, Canada. We find that tanks are the single largest source of emissions, contributing to nearly 60% of the total emissions. The average number of leaks at treatment sites that underwent repair reduced by ∼50% compared to the control sites. Although control sites did not see a reduction in the number of leaks, emissions reduced by approximately 36%, suggesting potential impact of routine maintenance activities to find and fix large leaks. By tracking tags on leaking equipment over time, we find a high degree of persistence; leaks that are repaired remain fixed in follow-up surveys, while non-repaired leaks remain emitting at a similar rate, suggesting that any increase in observed leak emissions following LDAR surveys are likely from new leaks. Our results show that a focus on equipment and sites that are prone to high emissions, such as tanks and oil sites, is key to cost-effective mitigation.

The Role of Emission Size Distribution on the Efficacy of New Technologies to Reduce Methane Emissions from the Oil and Gas Sector

Methane emissions from oil and gas operations exhibit skewed distributions. New technologies such as aerial-based leak detection surveys promise cost-effective detection of large emitters (greater than 10 kg/h). Recent policies such as the US Environmental Protection Agency (EPA) methane rule that allow the use of new technologies as part of leak detection and repair (LDAR) programs require a demonstration of equivalence with existing optical gas imaging (OGI) based LDAR programs. In this work, we illustrate the impact of emission size distribution on the equivalency condition between the OGI and site-wide survey technologies. Emission size distributions compiled from aerial measurements include significantly more emitters between 1 and 10 kg/h and lower average emission rates for large emitters compared to the emission distribution in the EPA rule. As a result, we find that equivalence may be achieved at lower site-wide survey frequencies when using technologies with detection thresholds below 10 kg/h, compared to the EPA rule. However, equivalence cannot be achieved with a detection threshold of 30 kg/h at any survey frequency, because most emitters across most US basins exhibit emission rates below 30 kg/h. We find that equivalence is a complex tradeoff among technology choice, design of LDAR programs, and survey frequency that can have more than one unique solution set.

Origins of Oil and Gas Sector Methane Emissions: On-Site Investigations of Aerial Measured Sources

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.

Multiscale Methane Measurements at Oil and Gas Facilities Reveal Necessary Frameworks for Improved Emissions Accounting

Methane mitigation from the oil and gas (O&G) sector represents a key near-term global climate action opportunity. Recent legislation in the United States requires updating current methane reporting programs for oil and gas facilities with empirical data. While technological advances have led to improvements in methane emissions measurements and monitoring, the overall effectiveness of mitigation strategies rests on quantifying spatially and temporally varying methane emissions more accurately than the current approaches. In this work, we demonstrate a quantification, monitoring, reporting, and verification framework that pairs snapshot measurements with continuous emissions monitoring systems (CEMS) to reconcile measurements with inventory estimates and account for intermittent emission events. We find that site-level emissions exhibit significant intraday and daily emission variations. Snapshot measurements of methane can span over 3 orders of magnitude and may have limited application in developing annualized inventory estimates at the site level. Consequently, while official inventories underestimate methane emissions on average, emissions at individual facilities can be higher or lower than inventory estimates. Using CEMS, we characterize distributions of frequency and duration of intermittent emission events. Technologies that allow high sampling frequency such as CEMS, paired with a mechanistic understanding of facility-level events, are key to an accurate accounting of short-duration, episodic, and high-volume events that are often missed in snapshot surveys and to scale snapshot measurements to annualized emissions estimates.

Emission Quantification via Passive Infrared Optical Gas Imaging: A Review

Passive infrared optical gas imaging (IOGI) is sensitive to toxic or greenhouse gases of interest, offers non-invasive remote sensing, and provides the capability for spatially resolved measurements. It has been broadly applied to emission detection, localization, and visualization; however, emission quantification is a long-standing challenge for passive IOGI. In order to facilitate the development of quantitative IOGI, in this review, we summarize theoretical findings suggesting that a single pixel value does not provide sufficient information for quantification and then we proceed to collect, organize, and summarize effective and potential methods that can support IOGI to quantify column density, concentration, and emission rate. Along the way, we highlight the potential of the strong coupling of artificial intelligence (AI) with quantitative IOGI in all aspects, which substantially enhances the feasibility, performance, and agility of quantitative IOGI, and alleviates its heavy reliance on prior context-based knowledge. Despite progress in quantitative IOGI and the shift towards low-carbon/carbon-free fuels, which reduce the complexity of quantitative IOGI application scenarios, achieving accurate, robust, convenient, and cost-effective quantitative IOGI for engineering purposes, interdisciplinary efforts are still required to bring together the evolution of imaging equipment. Advanced AI algorithms, as well as the simultaneous development of diagnostics based on relevant physics and AI algorithms for the accurate and correct extraction of quantitative information from infrared images, have thus been introduced.

Closing the methane gap in US oil and natural gas production emissions inventories

Methane (CH4) emissions from oil and natural gas (O&NG) systems are an important contributor to greenhouse gas emissions. In the United States, recent synthesis studies of field measurements of CH4 emissions at different spatial scales are ~1.5-2× greater compared to official greenhouse gas inventory (GHGI) estimates, with the production-segment as the dominant contributor to this divergence. Based on an updated synthesis of measurements from component-level field studies, we develop a new inventory-based model for CH4 emissions, for the production-segment only, that agrees within error with recent syntheses of site-level field studies and allows for isolation of equipment-level contributions. We find that unintentional emissions from liquid storage tanks and other equipment leaks are the largest contributors to divergence with the GHGI. If our proposed method were adopted in the United States and other jurisdictions, inventory estimates could better guide CH4 mitigation policy priorities.

On the Long-Term Temporal Variations in Methane Emissions from an Unconventional Natural Gas Well Site

Understanding methane emissions from the natural gas supply chain continues to be of interest. Previous studies identified that measurements are skewed due to "super-emitters", and recently, researchers identified temporal variability as another contributor to discrepancies among studies. We focused on the latter by performing 17 methane audits at a single production site over 4 years, from 2016 to 2020. Source detection was similar to Method 21 but augmented with accurate methane mass rate quantification. Audit results varied from ∼78 g/h to over 43 kg/h with a mean emissions rate of 4.2 kg/h and a geometric mean of 821 g/h. Such high variability sheds light that even quarterly measurement programs will likely yield highly variable results. Total emissions were typically dominated by those from the produced water storage tank. Of 213 sources quantified, a single tank measurement represented 60% of the cumulative emission rate. Measurements were separated into four categories: wellheads (n = 78), tank (n = 17), enclosed gas process units (n = 31), and others (n = 97). Each subgroup of measurements was skewed and fat-tailed, with the skewness ranging from 2.4 to 5.7 and kurtosis values ranging from 6.5 to 33.7. Analyses found no significant correlations between methane emissions and temperature, whole gas production, or water production. Since measurement results were highly variable and daily production values were known, we completed a Monte Carlo analysis to estimate average throughput-normalized methane emissions which yielded an estimate of 0.093 ± 0.013%.

Satellite-based survey of extreme methane emissions in the Permian basin

Industrial emissions play a major role in the global methane budget. The Permian basin is thought to be responsible for almost half of the methane emissions from all U.S. oil- and gas-producing regions, but little is known about individual contributors, a prerequisite for mitigation. We use a new class of satellite measurements acquired during several days in 2019 and 2020 to perform the first regional-scale and high-resolution survey of methane sources in the Permian. We find an unexpectedly large number of extreme point sources (37 plumes with emission rates >500 kg hour^-1), which account for a range between 31 and 53% of the estimated emissions in the sampled area. Our analysis reveals that new facilities are major emitters in the area, often due to inefficient flaring operations (20% of detections). These results put current practices into question and are relevant to guide emission reduction efforts.

Projecting the Temporal Evolution of Methane Emissions from Oil and Gas Production Sites

Many recent studies have reported methane emissions from oil and gas production regions, often reporting results as a methane emission intensity (methane emitted as a percentage of natural gas produced or methane produced). Almost all of these studies have been instantaneous snapshots of methane emissions; however, total methane emissions from a production site and the methane emission intensity would be expected to evolve over time. A detailed site-level methane emission estimation model is used to estimate the temporal evolution of methane emissions and the methane emission intensity for a variety of well configurations with and without emission mitigation measures in place. The general pattern predicted is that total emissions decrease over time as production declines. Methane emission intensity shows complex behavior because production-dependent emissions decline at different rates and some emissions do not decline over time. Prototypical uncontrolled wet gas wells can have approximately half of their emissions over a 10 year period occur in the first year; instantaneous wellsite methane emission intensities range over a factor of 3 (0.62-2.00%) in the same period, with a 10 year production weighted-average lifecycle methane emission intensity of 0.79%. Including emission control in the form of a flare can decrease the average lifecycle methane emission intensity to 0.23%. Emissions from liquid unloadings, which are observed in subsets of wells, can increase the lifecycle methane emission intensity by up to a factor of 2-3, between 1.2 and 2.3%, depending on the characteristics of the unloadings. Emissions from well completion flowbacks raise the average lifecycle methane emission intensity from 0.79 to 0.81% for flowbacks with emission controls; for flowbacks with uncontrolled emissions, lifecycle methane emissions increase to 1.26%. Dry gas and oil wells show qualitatively similar temporal behavior but different absolute emission rates.

California's methane super-emitters

Methane is a powerful greenhouse gas and is targeted for emissions mitigation by the US state of California and other jurisdictions worldwide^1,2. Unique opportunities for mitigation are presented by point-source emitters-surface features or infrastructure components that are typically less than 10 metres in diameter and emit plumes of highly concentrated methane³. However, data on point-source emissions are sparse and typically lack sufficient spatial and temporal resolution to guide their mitigation and to accurately assess their magnitude⁴. Here we survey more than 272,000 infrastructure elements in California using an airborne imaging spectrometer that can rapidly map methane plumes^5-7. We conduct five campaigns over several months from 2016 to 2018, spanning the oil and gas, manure-management and waste-management sectors, resulting in the detection, geolocation and quantification of emissions from 564 strong methane point sources. Our remote sensing approach enables the rapid and repeated assessment of large areas at high spatial resolution for a poorly characterized population of methane emitters that often appear intermittently and stochastically. We estimate net methane point-source emissions in California to be 0.618 teragrams per year (95 per cent confidence interval 0.523-0.725), equivalent to 34-46 per cent of the state's methane inventory⁸ for 2016. Methane 'super-emitter' activity occurs in every sector surveyed, with 10 per cent of point sources contributing roughly 60 per cent of point-source emissions-consistent with a study of the US Four Corners region that had a different sectoral mix⁹. The largest methane emitters in California are a subset of landfills, which exhibit persistent anomalous activity. Methane point-source emissions in California are dominated by landfills (41 per cent), followed by dairies (26 per cent) and the oil and gas sector (26 per cent). Our data have enabled the identification of the 0.2 per cent of California's infrastructure that is responsible for these emissions. Sharing these data with collaborating infrastructure operators has led to the mitigation of anomalous methane-emission activity¹⁰.