Chapter 1 - Foundational Knowledge in Methane Management

01-01 - Part 1 Recap (17 min.) Sample Lesson Quiz: 01-01 - Part 1 Recap
01-02 - Methane Regulations Part 1 (9 min.)
01-03 - Methane Regulations Part 3 (15 min.) Quiz: 01-03 - Methane Regulations Part 3

Chapter 2 - Voluntary Initiatives

02-01 - The Emergence of Voluntary Initiatives (19 min.) Quiz: 02-01 - The Emergence of Voluntary Initiatives
02-02 - Introduction to OGMP 2.0 (8 min.) Quiz: 02-02 - Introduction to OGMP 2.0

Chapter 3 - Quantification of Methane Emissions

03-01 - Introduction To Methane Measurement Technology (21 min.) Quiz: 03-01 - Introduction To Methane Measurement Technology
03-02 - The Changing Landscape of GHG Inventories (14 min.) Quiz: 03-02 - The Changing Landscape of GHG Inventories

Chapter 4 - The Future of Methane Emissions

04-01 - Executive Summary (21 min.) Quiz: 04-01 - Executive Summary
04-02 - Future Trends (11 min.)

Executive Guide to Methane Management / Chapter 1 - Foundational Knowledge in Methane Management

Lesson 01-01 - Part 1 Recap

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Transcript

01. Lesson 1.01: Part 1 Recap 02. Methane is a Simple Molecule With Big Impact 03. Methane Comes from Diverse Human & Natural Sources 04. Methane in Oil and Gas 05. Methane Emissions From Oil & Gas are Complex 06. Methane Research & Practice are Actively Evolving 07. Estimating Methane Emissions 08. Bottom-up Inventories are Foundational for Quantification 09. Measurement & Reconciliation are Growing in Adoption

01. Lesson 1.01: Part 1 Recap

Introducing methane.

02. Methane is a Simple Molecule With Big Impact

So, methane is a simple molecule with a big impact. It's the most abundant molecule in natural gas. And combusting methane produces energy that's very valuable to society. This is why we produce natural gas. But emitting it directly to the atmosphere is harmful to the planet and to human health. And so, the challenge here is producing natural gas in a way that the gas is combusted and converted to energy, but not wasting the methane molecules in that natural gas by emitting them directly to the atmosphere. We talked about global warming potential in Part 1, and I'd invite you to revisit that if you forget what the term means. Methane's global warming potential is higher than carbon dioxide, which is why it's preferable to combust natural gas and turn the methane molecules into CO₂ rather than emitting it directly into the atmosphere. We know that methane's average residency in the atmosphere is only approximately 10 years, compared to 100s or, in some case, thousands of years for carbon dioxide. And we know that natural gas is a cleaner burning fuel than coal and oil, but we must limit methane emissions that are lost across the supply chain in order for it to be a clear improvement over these alternative energy sources. So, the figure on the left shows that the impact of methane emissions relative to carbon dioxide depends on the time horizon over which you assess the global warming potential. So, at approximately 100 years, the impact of methane is roughly 28x more than carbon dioxide. And at roughly 20 years, the impact is about 84x more than carbon dioxide per unit of mass. The reason for this is the residency time of methane in the atmosphere, which is lower than carbon dioxide. If you were to look at the kind of instantaneous, 0 to 5 year impact, it's closer to 120x the impact of carbon dioxide.

03. Methane Comes from Diverse Human & Natural Sources

We know that methane comes from diverse human and natural sources. The figure depicted here is data from the International Energy Agency, which shows, at a very high level, the primary sources of both natural and human-caused methane emissions globally. So, you can see that wetlands are by far the largest source, largest contributor globally to methane. The reason for this is that wetlands cover a significant proportion of Earth's surface, somewhere between 5 and 10%, and they create conditions where anaerobic decomposition of organic matter by methanotrophic bacteria or methanogenic bacteria leads to the production of methane. This is the same process that happens in the stomachs of cows and of termites, and also in landfills. So, bacteria as a whole are responsible for a significant proportion of the methane that's generated and emitted to the atmosphere. After wetlands, agriculture, which includes all sources of agriculture, is the most significant contributor of methane globally. The primary sources of methane within the agriculture category are livestock and the cultivation of rice. And so, livestock, in particular cattle, have methanogenic bacteria in their gut, and they do fart but primarily belch methane in quite significant quantities. And the manure management aspect of feedlots, not only for cattle but also for pigs, is also a contributor of methane emissions. Rice—the cultivation of rice or paddy, is another contributor of methane emissions. This is very similar to wetland emissions. It's effectively the same thing, except that humans intentionally cultivate rice and not natural wetlands. Energy as a whole is the third largest category globally of methane emissions that includes oil, natural gas, and coal, as well as bioenergy. And so, all of these sources combined are still less than agriculture and significantly less than wetlands. And you can see from this figure that if you break down methane emissions from energy that the majority of emissions come from oil and coal, and that natural gas is a smaller fraction of the total. Fourth in line is waste, and this is primarily landfills. Landfills also creates anaerobic conditions where bacteria produce methane by decomposing organic matter. And then, other sources of both natural and anthropogenic methane exist, but these four sources account for the vast majority of the total.

04. Methane in Oil and Gas

Methane in oil and gas.

05. Methane Emissions From Oil & Gas are Complex

So, the reason we have these courses is that methane emissions from oil and gas systems are extremely complex. Methane emission rates have quite extreme distributions, spanning at least 7 orders of magnitude, if not more. And so, for example, individual component leaks from a threaded connection or from a leaking valve are often less than 0.01 kg/h or much less. But large events that are captured by satellites are increasingly observed, and these often exceed 100 kg/h, or in some cases, 10 tonnes/h or more. And so, we know that most methane is from a small fraction of large sources, which creates both an opportunity to rapidly reduce methane emissions by focusing on a small number of sources but also introduces significant risks if those sources cannot be controlled. The other thing we know about methane emissions from the oil and gas industry is that source persistence is extremely variable. On one hand, you can have fugitive emissions or leaks that are more or less continuous and will emit at roughly the same rate until they're repaired. But you can also have highly intermittent sources such as pressure relief valves on tanks or unlit flares that may be intermittent and may be quite large in magnitude, but may only be emitting a small fraction of the time. And this makes detection and quantification more difficult. The figure on the right is from a recent paper out of Stanford University led by Evan Sherwin. And what they do in this study is they simulate emissions from bottom-up inventories and try to combine those emissions with empirical observations from primarily aircraft in order to characterize the distribution of methane emissions sources overall and understand really what proportion of emissions are accounted for by what fraction of sites. And so, the way to read this figure is you draw a line over from the Y-axis. And so in this case, we are at roughly 0.8, so 80% cumulative emissions are accounted for by sources greater than approximately; in this case, I think we're at around 50 kg/h in the Permian Basin. And the one thing I really want to illustrate in this figure is that the differences among basins are significant. And so, in the Denver Julesberg Basin, around 0.12% of sites account for about 20% of emissions, whereas in the Permian Basin, around 0.86 to 1.66% of sites account for nearly 80% of emissions. And so, this is a huge difference, and it means that this super-emitter phenomenon varies by basin, but it also varies by operator and other factors. So, the long story short is that large emission sources are rare but account for the majority of emissions. But how large these sources are and what proportion of total emissions they account for vary significantly by location.

06. Methane Research & Practice are Actively Evolving

We learned in Part 1 that methane research and practice are actively evolving. And so, rapid innovation is underway. We're seeing new satellites being built, and designed, and launched by NGOs. We're seeing significant advances in the capabilities of continuous monitoring, other screening technologies such as drones and aircraft, digital systems for managing data and analyzing data, and also mitigation technologies, which we'll talk a little bit about today. Global research campaigns exist that are attempting to determine how to build robust measurement-informed inventories. We talked a bit about measurement-informed inventories in Part 1 of the course. But effectively, this means combining or comparing different sources of information into a more robust estimate, typically by using company-specific methane measurement data. Researchers in a variety of institutions are also trying to figure out how to quantify supply chain methane intensity for natural gas and LNG cargo export. And are trying to figure out how to evaluate the performance of new technologies. One thing that's becoming increasingly clear is that the dozens, if not hundreds, of newly available methane detection and quantification technologies have vastly different performances. And testing them independently to evaluate their performances and really understand what their mitigation potential is a big challenge.

07. Estimating Methane Emissions

Estimating methane emissions.

08. Bottom-up Inventories are Foundational for Quantification

In Part 1 of the course, we introduced bottom-up inventories, which are foundational for quantification. These are the tools that have existed for regulatory reporting for quite a few years now. And the way bottom-up inventories work is that they use activity factors and emissions factors. Very simply, they multiply them together in order to estimate emissions, typically for a given source category. So, emissions factors are an estimate of loss rate by unit of activity. And so, an example could be an average emission rate for a leak. And activity factors can be equipment, throughput, events, or accounts, so it's some activity that is associated with emissions. And so, by multiplying the activity factor by the emissions factor, we can estimate overall emissions. We are seeing a world where bottom-up inventories are relying increasingly on measurement data because generic estimates for emissions factors and activity factors have proven to be unreliable in a large number of academic studies and industry studies for understanding the company-specific emissions that may occur. And the reason for this is that companies are so variable in what their emissions are. And so, because these generic assumptions have been shown to be inaccurate, we're actually moving towards leveraging different types of measurement data, both at the source level, also at the site level, and weaving this data together into measurement-informed inventories so that we can get more accurate reporting. The table on the left is a very, very simple hypothetical example of a bottom-up inventory where you have 5 source categories in this- inventory heater-treaters, fugitives, pneumatic devices/pumps, compressors, and storage tanks. And you can see for each of these source categories for a given company and for a given year what the emissions are, what the relative percentage or materiality of those emissions are by source category, and how many sites those source categories exist at. The materiality is a concept that's increasingly important, and it's leveraged involuntary initiatives like OGMP and others because it helps direct operators towards the source categories that are the largest contributors of emissions and therefore should get the most attention when it comes to making decisions around mitigation. And we'll talk a little bit more about materiality later in the course.

09. Measurement & Reconciliation are Growing in Adoption

We're also seeing that measurement and reconciliation are growing in adoption. Site-level measurement data is often compared now to bottom-up inventories in order to understand areas of discrepancies. And so, because methane estimation is so difficult, not only to the individual measurements that are performed but extrapolating those measurements across space and time to get an annualized estimate for an individual company, we start to look for ways to estimate in different ways and then compare those different estimates. If the estimates match, it suggest that we're doing a relatively good job of estimating emissions, and that we understand the system. But if the estimates don't match and there are large discrepancies, which is often the case, it indicates that something is wrong with one of the estimates and that a further investigation is needed in order to explain those discrepancies. And so, the figure on the left here shows a simple example from a series of measurements in 3 different basins by Bridger, which is an Aerial LiDAR technology, and SeekOps, which is a drone-based technology. And so, in this chart, we have inventory emissions on the X-axis and measured emissions on the Y-axis. And so, if you see a correspondence or a lack of discrepancy between the 2 estimates, then the scatter plot should align with the horizontal or diagonal line that crosses from the bottom left of the chart to the top right of the chart. And so, we can see here that for basins A and B for both Bridger and SeekOps, there's a relatively good correspondence, although far from perfect. Whereas for basin C, there's a systematic bias and large discrepancy between what the technologies are measuring and what the inventory is estimating. And in this situation, the measurements that are performed, and I'm gonna just draw a circle around them here—these measurements exceed what you would expect from the bottom-up inventory by several orders of magnitude. And so, this is an area of concern. And this is somewhere that an operator may choose to perform investigations to determine what elements or source categories within the bottom-up inventory are contributing to this discrepancy. Is the compressor exhaust is higher than calculated? Are there more fugitive emissions or unlit flares than were expected? Or is it something else? Thank you for joining me in Lesson 1.01. We'll see you in Lesson 1.02, which is all about methane regulations.
Sherwin, Evan D., "US oil and gas system emissions from nearly one million aerial site measurements." Nature 627, no. 8003 (2024): 328-334.Wang, Jiayang Lyra, "Multiscale methane measurements at oil and gas facilities reveal necessary frameworks for improved emissions accounting." Environmental science & technology 56, no. 20 (2022): 14743-14752.