How observation data is upending our understanding of methane emissions

The world is focused on reducing methane emissions right now, and the oil and gas sector is at the heart of those efforts. Companies, regulators and investors agree that methane leakage, outside of safety measures, rarely benefits anyone. At the same time, finding leaks can be painstaking and costly. Moreover, oil- and gas-producing assets exhibit significant variations in emissions rates due to operational practices, equipment configuration, infrastructure access and other variables.

Given rising climate change concerns, the potency of methane's warming potential -- 28 times carbon dioxide on a 100-year basis and 84 times on a 20-year basis -- have made it the priority target for mitigation in the oil and gas sector, which has concentrated sources and viable monetization pathways.

Over the past decade, oil and gas companies have made significant strides in addressing methane emissions. They have set goals, such as the Global Methane Pledge, built teams of experts and piloted an array of technologies to monitor this invisible substance. Importantly, they began systematically estimating and reporting greenhouse gas emissions to various authorities.

Methane emissions reported to the US Environmental Protection Agency since 2012 form the most important record available, especially as US gas supply and LNG exports have surged. When promulgated, EPA sought to create a straightforward system that all companies could implement with available information. A proscriptive and rigid system was necessary to assure comparable results and feasible calculations. Unfortunately, unlike CO2, methane emissions result from sporadic operations or unintentional releases due to malfunction. No formula can reliably predict the rate or volume of these releases.

Producers have since honed internal processes to report annually, but even this simplified method requires significant resources. Furthermore, the public record it generated has had little value to companies beyond mere compliance.

Alongside this regulatory time series, technologies to directly detect methane have rapidly matured. Companies have migrated from generic factors toward observation, exploring internal datasets and providing new, relevant information. Appearing more frequently in company sustainability reports, studies and third-party releases -- including S&P Global Commodity Insights benchmarks -- these data paint a different picture of emissions levels. Critically (and controversially), the observation data almost always exceed corresponding figures from the mandated, static calculations. This begs the question, "Who is 'right'?"

The nearly universal truth is that no one knows the exact reality of methane emissions outside of laboratory settings. Assumptions, calculation and judgement still retain a significant role in even the best "observed" figures. For any sizable oil and gas asset over any notable period, it is not cost-efficient to obtain precision. If confronted with five estimates of emissions for a given facility for a given time, it is helpful to posit the existence of a sixth -- the actual number.

At Commodity Insights, the Center for Emissions Excellence partners with data scientists and domain experts to evaluate data from external sources and proprietary estimates derived from our core energy databases. Strengths and weaknesses are assessed in every quantification approach, including remote sensing using satellites and overflights.

A number of factors make error bars for remote sensing remain wide (+/- 50%) for any individual leak estimate. However, regular calibration of remote sensing against known releases at test facilities has allowed improvement that provides meaningful certainty. When interpreted properly and placed in the right context, Commodity Insights finds that emissions derived from observation are consistently and significantly more credible than the methane emissions historically calculated for regulatory purposes. They are in the ballpark of actual emissions.

Reconciling regulatory and observed estimates

The Permian Basin offers an illuminating case study to contrast Commodity Insights methane benchmarks, built with in partnership with Insight M, based on remote sensing data versus regulatory data submitted to the EPA. Before starting, it is critical to note that basin-level aggregates do not apply to individual companies. A handful of operators even have actual emissions below the figure reported to the EPA. Most companies have the reverse, of course, but as in any system as diverse as the Permian, performance ranges widely. Distributions matter.

Turning to the numbers, the sum of methane emissions (grossed up to account for the small portion of assets not reporting) submitted to EPA for 2022 in the Permian production segment was 8.3 Bcf. Expressed as a percentage of the total barrels of oil equivalent energy that the basin produced yields an intensity of 0.06%. In 2023, the EPA figure increased to 0.07%, a sharp rise of 26%. In the big picture, both years registered an intensity below 0.2% of output, a level suggesting relatively low -- if deteriorating -- methane emission operations in the world's biggest oilfield.

Meanwhile, observed data tells a different story. The Commodity Insights benchmark for upstream Permian methane emissions intensity is 0.92% of boe for 2022 and 0.63% for 2023, an impressive 32% improvement. While the continuing emissions remain quite large, the absolute decrease in 2023 Permian Basin upstream methane emissions -- 34 Bcf -- is huge. And because methane is such a potent GHG, the equivalent amount of CO2 avoided -- 18.5 MMt -- is also outsized. In fact, the decrease in CO2 equivalent was more than the total 2023 driving emissions avoided by every electric vehicle ever sold in the US, even if fully powered with zero-carbon electricity.

As argued above, the EPA's proscribed methodology underestimates actual emissions for many companies. Indeed, the EPA's proposed changes to its methodology will mostly work to close the gap with observed volumes. But for historical purposes, the observed data were roughly 16x the level of submissions to the US government in 2022 and 8x in 2023.

Thus, observation data is resetting the baseline much higher than the regulatory record, but it also shows the industry making significant progress as it ramps up spending and deploys technology.

How does measurement improve accuracy? There are many technologies in various stages of deployment and development in the service of methane emissions quantification. But for now and the foreseeable future, no single technology can provide a practical, perfect quantification of methane emissions, and most companies ascribe to a layered approach that features multiple technologies. Companies gauge performance in six desired dimensions:

• Resolution: High spatial resolution allows for accurate pinpointing of leaks to specific equipment at specific sites.
• Frequency: Higher frequency (or even continuous monitoring) allows companies to take action sooner, reducing the total volumes emitted.
• Coverage: Technologies that can cover large areas provide more completeness and certainty.
• Threshold: Ideally, companies would wish to know every emission, no matter how small.
• Reliability: Technologies that can accurately assess the rate of leaks help operators to calculate total emission volume and prioritize remediation. Also, avoiding false positive and false negatives is critical.
• Affordability: The imperative to manage and optimize costs runs through every methane detection program as budgets are limited and competition for capital is high.

Looking at four of the most common technologies in use today, we find that companies must inevitably trade off some of the parameters, making gains in some while accepting the inevitable shortcomings. The S&P Global methane benchmark powered by Insight M observations offers a good combination of these metrics.

In the context of the public debate about methane emissions, adopting observation-informed measures would seem to be a large setback for the oil and gas producers in communicating their current emissions levels and achieving the methane mitigation goals most have set. Indeed, some companies see the situation that way.

There are payoffs, however, for companies that leverage these new technologies and utilize observed estimates sooner rather than later.

First, unlike static calculations, direct observation provides companies critical data they can use to take concrete action to reduce methane and to carry out root-cause analysis. It is difficult to fix a leak you do not know exists.

Companies also face mounting reputational risk as the proliferation of third-party detection, including by environmental groups, provides a new level of public transparency into methane emissions. It may be more prudent to recalibrate sooner and proactively control that shift rather than accept the risk of involuntary, third-party exposure later.

Finally, the gain in data credibility from adopting observation-based numbers can offer a critical counterbalance to acknowledging higher emissions levels. The global methane discussion today simplistically ranks performance using data of vastly different qualities. Insightful analysis should consider the spectrum of high versus low intensity tied to an assessment of the data quality.

To this end, Commodity Insights has developed and publicized a transparent scheme that scores the reliability of emissions data. The figure below tells this story for the Permian.

Moving from the reported to observation-informed data dramatically increases the level of emissions intensity. However, it also catapults the reliability score from a very low confidence level to a much higher level.

The regulatory data makes the basin look quite clean but is inherently unreliable. In other words, we just do not know if the estimate can be trusted.

In contrast, the observation-informed estimates show worse performance but are more trustworthy. This has benefits as publicized third-party estimates are likely to corroborate and bolster -- rather than contradict -- the estimates of the operator. In addition, by including data quality, companies can provide a means to distinguish true performance over time and across companies and jurisdictions.

Investors in particular can choose. Which do they prefer: a cleaner but doubtful number or a higher intensity, certain performance that they can track. In our conversations, most investors evince a preference for the latter.

One finding from our review of observation-informed estimates supports the notion that corporate goals, operational improvements, and investor pressure are having an  influence on reducing methane emissions. An analysis of 93 Permian basin operators shows that the publicly traded operators had a median methane intensity of 0.38%, versus 0.69% for the privately owned companies, in 2023. This measure of intensity represents the amount of methane emitted per barrel of oil equivalent as a percentage of barrel of oil equivalent produced,

This notion, however, is not universally true, again emphasizing the need to be specific: in fact, the four lowest intensity producers are all private, and three public companies are in the bottom quartile. But by and large it appears that the public firms, who usually have greater detection and mitigation resources as well as more investor pressure, have lower emissions per unit of oil and gas produced.

Further reading: The reckoning: How observation data is changing our understanding of methane emissions