Category: Cutting Edge

Investors may suffer if they do not consider the energy transition. But they may suffer more if they consider it, and get the answer wrong. We argue that the best way to drive the energy transition will be to maximise carbon-adjusted investment returns.

Our starting point is the chart below, which focuses on the power of compound interest, “the most powerful force in the universe” (the quote has been ascribed to Albert Einstein). This is not our usual tack — which focuses upon energy technologies, economics or quantifying CO2 — but purely mathematics…

The difference is enormous between compounding at, say, 4% and 12%. It may not sound material in any given year (“it’s just 8%”). But over a thirty year investment horizon, it makes the difference between a $100 initial investment rising to c$300 and $3,000 of value (i.e., a factor of 10x).

How this applies to the energy transition is that we currently observe institutional investors backing away from high-return (10-20% per year), industrial asset classes, which are feared to be high-carbon, towards low-returning asset classes (4-6% per year), which are perceived to be low-carbon.

For oil companies, the spread of opportunites is charted below (note here). Measured over any single year the difference may be imperceptible. But over 30-years it is vast.

By down-shifting from high-return assets to low-return assets, the costs of mitigating climate change end up falling upon the shoulders of institutional investors: endowments, foundations, hopeful retirees; as a hidden cost.

It is not for us to say whether this kind of hidden cost is morally right or wrong. But we can say that it is sub-optimal, in economic terms, because unlike a visible cost (e.g., a direct “carbon price”), it will not change behaviours in ways that actually drive decarbonisation.

No “incremental” energy transition occurs when investors divest from traditonal industrial sectors; and instead, outbid each other to finance the same renewable energy projects. A better alternative is needed.

Investment firms understand the challenge. This week, Blackrock’s CEO, Larry Fink, published a letter to CEOs, stating how climate change will “fundamentally re-shape finance”. What is not being reshaped, of course, is the maths of compound returns. Mr Fink’s letter begins by highlighting “we have a deep responsibility to institutions and individuals … to promote long-term value”. So how can this happen?

Three better alternatives for investors in the energy transition

In order to drive incremental energy transition, it is necessary to attract incremental capital. It must flow towards high-returning technologies and projects, which can drive decarbonization. This is our central tenet on investing for an energy transition. And it underpins the opportunities that excite us most in 2020 (chart below), which should all seek double-digit returns. Seen this way, climate change is not a cost to be passed on to investors, but a positive investment opportunity, to help meet a societal need.

A second alternative is to allocate more capital to companies that offer attractive returns and also have lower carbon contributions than their peers: such as lower-CO2 oil and gas producers, shale producers, refiners, midstream or chemicals companies. On any decarbonized energy model that we can construct, demand for gas will rise and demand for low carbon oil will not collapse. We have reams of data to help you with this screening. Often it is due to superior technologies.

A third alternative could be to offset CO2 directly, as you continue investing in high-returning, industrial companies. This still leaves investors paying for the cost of climate change out of their future returns. But the cost is much lower than if investment returns are sacrificed by divesting from industrial companies and funding renewables.

For example, we recently tabulated the costs of carbon credits, being offered by 15 separate offset schemes. Based on the data, we calculate that an investor could buy a SuperMajor oil company with an average distribution yield of 7%; offset their investment’s entire Scope 1&2 emissions for a drag of just 0.5pp; leaving their “zero carbon cash yield” at 6.5%. (It will be interesting which forward-thinking Super-Major is first to apply this logic and offer up such a “carbon-offset share class”).

The end point is that high carbon companies will see higher capital costs (and our survey work indicates this is already occurring, chart below). But how much higher? In an efficient carbon market, there is an easy answer: high enough so that the extra yield of Investment X (vs Investment Y) can be re-invested in carbon credits to offset the extra CO2 of Investment X (vs Investment Y).

These ‘carbon adjusted returns’ are directly comparable. The higher carbon- and risk- adjusted return equates to the better investment. The higher the carbon price, the higher the relative cost of capital for high-carbon companies; and the higher the relative incentive to lower emissions.

This system, we believe, will be much more sophisticated and effective in driving a full-scale energy transition that the blunt-force strategy of “divest from oil and buy renewables”. It will also not leave investors short-changed, by up to 90%, when they come to meet their budgeting or retirement needs in 2050.

Please do contact us if you have any observations, questions or comments; or would like to discuss some of the “long-term value” opportunities, which we think can help drive the energy transition…

Satellite-based analysis is gaining momentum, and features in three of our recent research reports. A step-change in resolution is helping to mitigate methane leaks and scale up low-carbon gas. It is possible to track Permian completion activity from space. We also suspect renewable growth may slow, as small-scale solar brings heartland markets closer to saturation. Satellite images should continue finding its way into commercial research, as data improves and costs deflate.

The Spy Who Loved Methane

If 3.5% of natural gas is “leaked” as it is commercialised, then it is debatable that natural gas may be a ‘dirtier’ fuel than coal, because methane causes 25-120x more radiative forcing than CO2. Hence it is crucial for the scale up of natural gas – and for the energy transition – that methane leaks are mitigated. Our recent note, ‘Catch Methane if you Can‘ outlined five breakthrough technologies to help, based on screening 34 companies and 150 patents (chart below).

Satellites were among the breakthrough technologies, with the capability to find methane leaks from space. This matters as c5% of super-emitting leaks comprise c50% of leaked methane volumes. But pinpointing these leaks – and who is reponsible for them – has not previously been possible. The current satellites in orbit have had spatial resolutions of 50-100 sq km and detection thresholds of 4-7Tons/hour. By 2022, this will improve to <1sq km spatial resolutions and c100kg/hour. Full details are contained in the note and data-file.

Tracking Shale Completions from Space?

Another debate in 2020 is whether the shale industry is slowing down, in activity terms, in productivity terms, or whether it is staring to re-accelerate. Based on reviewing 650 recent technical papers, we know the best companies are continuing to improve underlying productivity; while they can also re-attract capital and growth by touting low carbon credentials, with some ever potentially becoming “carbon neutral” .

Satellite imagery shows how the industry is consolidating. Below, using data from Terrabotics, we can count the number of completions in the Permian, by operator and by county, in 3Q19. The ‘Top 10’ companies now comprise half of all completion activity. For an introduction to Terrabotics, and their data, please contact us.

Renewables slow-down: Could it be soooner?

Another theme for 2020 is whether renewables growth will slow down, as heartland markets reach grid saturation. This was the precedent when Spain and Portugal reached 25% penetration of renewables in their grids. The UK, Germany and California could follow suit this year, as explored in detail here.

What is not quantified in our data-set of large-scale utility plants is small scale renewable penetration, such as rooftop solar. However, satellite are also starting to unearth these smaller-scale systems, finding them to be more extensive than expected. For example, Stanford’s “Deep Solar” project, has used machine learning to identify over 1.5M solar installations from 1bn satellite images. 5% of houses in California are found to have rooftop solar systems, suggesting renewables are even closer to their threshold.

How do you use satellites in your process?

We are incorporating satellite imagery into more of our research, as evidenced by the three examples above. We write about technologies in the energy space, but these technologies are also changing the commercial research space. We would be very interested to hear from you, if you have observations on the topic, or would like to discuss useful data sources.

Over 100 attacks on global energy assets made major news headlines in the past decade. The majority were small-scale, targeting pipelines in conflict-regions, because this was the infrastructure most accessible to aggressors. However, a new and devastating wave of drone technologies could place the world’s largest and most vulnerable facilities into the firing line, threatening multiple millions of barrels per day. This short note outlines the latest in drone technologies and why they concern us.

Historical attacks on energy assets

Supply disruptions have been a feature of oil markets over the past ten years. For example, in the chart below, we have counted 100 violent attacks on energy infrastructure from major news stories. However, the majority were small-scale and located in active conflict-zones. Most oil infrastructure has heretofore been safe.

Here are the numbers: 90% of the prior attacks in our sample were low impact, when we assessed their severity. c60% were concentrated on pipeline infrastructure, which is relatively easy to repair. 70% of the upstream attacks were on wells or small processing units. 80% were localised within active war-zones such as Libya, Nigeria, Iraq, Yemen and the Sudans, rather than in stable countries. These attacks were nevertheless numerous. They shuttered 1Mbpd of Nigerian output between 2006 and 2016, 1Mbpd of Libyan output in 2011 and c0.5Mbpd of output in Yemen and Syria.

The more dangerous and worrying attacks have been full-scale assaults on large industrial assets. The worst example, many will remember, was Al Qaeda’s January-2013 attack on Algeria’s 9bcm pa In Amenas gas facility. 39 hostages were killed, as well as 29 terrorists. In addition, it took until June-2016 to bring production back to full capacity. The impacts of such incidents are hard-felt and long-lasting. Another legacy is that security measures have been escalated in high-risk regions.

On 14th September 2019, another industry-changing attack took place, on Saudi Arabia’s Abqaiq and Khurais oilfields. 5.7Mbpd of oil production was curtailed, constituting the largest supply-disruption on record. Repairing the damage will cost hundreds of millions of dollars. The latest suggestion is that the damage was inflicted by 20 drones, plus additional cruise missiles, which may have been guided to their targets by the drones. Unfortunately, this attack raises the spectre of further incidents, owing to the rise of drone swarm technology.

Ten Characteristics of Drone Swarms

Drone swarms could emerge as the most devastating weapon of 21st century warfare, outflanking large, high-speed, high-cost military vehicles of the past (Hambling, 2015; chart below, data here). They pose much greater risk to high-value infrastructure than prior weaponry that was available to aggressors. To understand why, it is necessary to review ten properties of drone swarms.

(1) Easy to access. Most military equipment is not openly available for purchase on the internet or in consumer electronic stores. However, hundreds of models of drones are now available in the consumer sector. They can be modified and retro-fitted to inflict violence or damage. Similarly, in the military sphere, one expects large super-powers such as the US, Russia and China to develop leading military technologies, but advanced drones are also being developed in smaller countries such as Israel, Iran, Turkey, Korea. The technology is not always closely contained. In particular, Iran has been found to donate its Ababil drones and Quds missiles to allies such as the Houthis; and Islamic State was able to use drones to drop grenades in Northern Iraq in 2016-17.

(2) Easy to fund. These drones have price points in the thousands of dollars, rather than the millions, which makes them accessible to small groups of aggressors rather than just to nation-states. Out of 15 high-spec consumer drones that we reviewed recently, the median cost was $10,000 (chart below, data here). Half-a-dozen priced below $2,500. This not only makes them accessible, compared to cruise missiles costing $150k to $1.5M; but also expendable, compared to fighter jets costing $30-150M.

(3) Easy to launch. There is no need for runways, special hangers or refuelling facilities. Drones can launch from any terrain and travel tens or hundreds of miles. The fact that drones can be launched and travel to their targets brings a much wider array of assets into the firing line. This will include facilities deep within protected territory, such as Abqaiq and Khurais; or offshore assets, which have repeatedly been considered as targets by Nigerian militants, but have been protected by their offshore locations.

(4) Increasingly large swarms. In 2015, the largest drone swarms being flown numbered 30-50. However, China’s CETC flew drone swarms numbering 100-200 in 2018 (chart below). Israel is developing technologies where a single operator could fly an entire swarm of drones, in a single, controllable formation. This matters because the larger the swarm, the harder it is to neutralize. Using a swarm of 20 drones may be one reason why the latest attack on Saudi infrastructure succeeded, while dozens of prior attacks from 2017-18 were thwarted.

(5) Increasingly autonomous swarms. The most effective counter-measure against military drones in the past has been to “jam” the controllers used for steering them. This tactic was used, for example, against Islamic State, in Northern Iraq. But now, some of the leading commercial drones use neural network algorithms to auto-navigate. Thus they cannot be “jammed”. For example, the Skydio R1 uses a NVIDIA Jetson processor with 192 processing cores, which is less power hungry than prior chips. Qualcomm is also making ‘simultaneous location and mapping’ hardware the size of a credit card, allowing drones to navigate by sight alone.

(6) Potency. A large drone may carry a warhead or missile; smaller drones can carry grenades, IEDs or firearms and small drones may illuminate targets (e.g., with lasers) in order to direct larger incoming missiles. Any of these could do very significant damage to facilities that contain live hydrocarbons.

(7) Precision. Autonomous drones can attack very specific targets. This level of precision was seen in the recent Saudi attacks, where individual missiles hit each spheroid tank at Abqaiq, in almost the same identical location (US satellite images below). Another example in the civilian sector is being used at beaches in Australia, where ‘SharkSpotter’ deep learning software is used to identify sharks with 90% accuracy, compared with 30% for human operators. Training a drone to identify sharks versus dolphins is computationally similar to identifying vulnerable versus non-vulnerable processing units at energy infrastructure.

(8) Hard to predict. Because swarms of drones are created with standard electronics equipment, much of it available in the civilian sector, “manufacture [of drone swarms] would be relatively hard to spot—compared to the production of traditional military hardware such as manned aircraft, ships or ballistic missiles—as it would resemble any other consumer electronics assembly” (Hambling, 2018).

(9) Hard to stop. The challenge of stopping a large swarm of drones is that there may simply be too many units to neutralize, especially when they are moving quickly. Laser cannons may stop a few units. A battery of missiles may stop many more. However “shooting down a $1,000 drone with a $5,000 missile is not a winning strategy” (Hambling, 2015). Assuming similar budgets, the drone attackers may outnumber the missile defenders. Acknowledging this challenge, the US has budgeted $1.5bn over the next year, to investigate potential solutions. But outside the military, and back in the realm of energy assets, we doubt that any of today’s onshore or offshore processing facilities have the capacity to stop drone attacks.

(10). Hard to retaliate. Drone attacks are very different from prior cases where armed insurgents attacked oil infrastructure, risking their own lives in the melee. Drones are by their nature remotely operated. Furthermore, reading through the history of recent drone attacks (e.g., in Yemen and Syria), it has often been impossible even to identify the culprit. In some cases, their identity still remains disputed. Failure to pinpoint the perpetrator makes it difficult to strike back. In turn, this removes the usual deterrent to attacking an enemy.

Implications for Oil Markets and Companies

Our latest oil market forecasts point to 1-2Mbpd of over-supply each year in the 2020s, assuming steady demand growth of 1.3Mbpd per annum. However, these base case forecasts do not incorporate any impact of supply disruptions from further attacks, which could sway the balance, and cause significant price spikes.

For energy companies, we think it will be crucial to mitigate against the risk of drone strikes, to the best extent possible. This may include diversification, counter-measures, and a growing preference to operate in lower-risk countries. We would be very happy to introduce clients of Thunder Said Energy to our contacts in the military drone space, who may be able to provide further observations.

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References

Hambling, D. (2018). Change in the air: Disruptive Developments in Armed UAV Technology.

Hambling, D. (2015). Swarm Troopers. How Small Drones will Conquer the World.

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