Matthew Smith — Natural Gas: The Next Bottleneck

**Patrick O'Shaughnessy** (0:00)
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Hello and welcome everyone. I'm Patrick O'Shaughnessy and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus along with all of our podcasts at colossus.com.

**SPEAKER_2** (0:58)
Patrick O'Shaughnessy is the CEO of PositiveSum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of PositiveSum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of PositiveSum may maintain positions in the securities discussed in this podcast. To learn more, visit PSUMVC.

**Patrick O'Shaughnessy** (1:26)
Our guest today is Matthew Smith. He's been on the show before many years ago, and I always love talking to him about energy markets where he's worked for 20 years. He's the founder and CIO of Chronometer Partners, which invests in energy, industrials, materials, power, and utilities and related infrastructure. He and his team have modeled nearly every natural gas well pipeline and processing asset in the United States. He's reached a conclusion that most of the market does not share. Starting in 2028, AI data centers and LNG exports will need more gas than the country can produce and deliver. By his math, the US could exhaust its working natural gas storage by 2030 and could lead to a true energy crisis. In his words, the upside risk to prices becomes unbounded and convex. We talk about why this was set in motion long before AI arrived, why the US can't just turn off exports, who wins and loses among producers, nuclear, solar and hyperscalers, and what he sees as the only long term solution.
Please enjoy my Great Conversation with Matthew Smith.
So Matt, the last time we did this was, I think during COVID, kind of crazy that it's been six years. I've always loved talking to you about energy markets. You've been working in this space for 20 years. You're about as encyclopedic on this stuff as anyone I've ever met. But you've also been acutely studying the current energy situation in the US.,
rebuilding in a way that you'll describe from the well level up a picture of what's happening, especially as AI is creating all this new demand through data centers, et cetera, of what is going on over the last 18 months of concerted effort. You've reached a fascinating and somewhat scary conclusion.
I'd love you to just start with the conclusion, and then we're going to talk through how you came to this conclusion, who the winners might be, the losers might be, what's to be done about it. But before we get deep into all the component parts, just tell us what you found after 18 months of study.

**Matthew Smith** (3:14)
We are headed into a place where we see an historic deficit in natural gas supply available in the United States, which does pretend some pretty serious consequences. Natural gas, which is over 40% of US power generation, is imminently going to become the most important fuel in the country. It's overtaking petroleum, given the amount that we use now for generation.
Our work suggests that 26, 27 natural gas is appropriately supplied. But as we get into 28, and you plug in this compute, and you assign gas to very specific assets as they're plugged in as well, and you continue to export LNG as we're planning to do with known projects, we start to eat into our work in gas storage, which is the nexus of supply and demand in the country. I think we will come to the conclusion that the upside risk of compressing natural gas is both unbounded and convex. And so where you will feel at the most acutely will be electricity prices in 28, 29, 20, 30, based on our work.

**Patrick O'Shaughnessy** (4:19)
How much of this is just attributable to data centers? Like just purely we're building a lot more data centers. That's just for AI. Is it that simple or is there something else going on as well?