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Climate Tech

This AI for Geothermal Startup Just Announced Its Biggest Find Yet

Zanskar’s second geothermal discovery is its first on untapped ground.

A computer finding a reservoir.
Heatmap Illustration/Getty Images

For the past five years or so, talk of geothermal energy has largely centered on “next-generation” or “enhanced” technologies, which make it possible to develop geothermal systems in areas without naturally occurring hot water reservoirs. But one geothermal exploration and development company, Zanskar, is betting that the scope and potential of conventional geothermal resources has been vastly underestimated — and that artificial intelligence holds the key to unlocking it.

Last year, Zanskar acquired an underperforming geothermal power plant in New Mexico. By combining exclusive data on the subsurface of the region with AI-driven analysis, the company identified a promising new drilling site, striking what has now become the most productive pumped geothermal well in the U.S. Today, the company is announcing its second reservoir discovery, this one at an undeveloped site in northern Nevada, which Zanskar is preparing to turn into a full-scale, 20-megawatt power plant by 2028.

“This is probably one of the biggest confirmed resources in geothermal in the last 10 years,” Zanskar’s cofounder and CEO Carl Hoiland told me. When we first connected back in August, he explained that since founding the company in 2019, he’s become increasingly convinced that conventional geothermal — which taps into naturally occurring reservoirs of hot water and steam — will be the linchpin of the industry’s growth. “We think the estimates of conventional potential that are now decades old just all need to be rewritten,” Hoiland told me. “This is a much larger opportunity than has been previously appreciated.”

The past decade has seen a lull in geothermal development in the U.S. as developers have found exploration costs prohibitively high, especially as solar and wind fall drastically in price. Most new projects have involved either the expansion of existing facilities or tapping areas with established resources, spurring geothermal startups such as Fervo Energy and Sage Geosystems to use next-generation technologies to unlock new areas for development.

But Hoiland told me that in many cases, conventional geothermal plants will prove to be the simplest, most cost-effective path to growth.

Zanskar’s new site, dubbed Pumpernickel, has long drawn interest from potential geothermal developers given that it’s home to a cluster of hot springs. But while both oil and gas companies and the federal government have drilled exploratory wells here intermittently since the 1970s, none hit hot enough temperatures for the reservoirs to be deemed commercially viable.

But Zanksar’s AI models — trained on everything from decades old geological and geophysical data sets to newer satellite and remote sensing databases — indicated that Pumpernickel did indeed have adequately hot reservoirs, and showed where to drill for them. “We were able to take the prior data that was seen to be a failure, plug it into these models, and get not just the surface locations that we should drill from, but [the models] even helped us identify what angle and which direction to drill the well,” Hoiland told me.

That’s wildly different from the way geothermal exploration typically works, he explained. Traditionally, a geologist would arrive onsite with their own mental model of the subsurface and tell the team where to drill. “But there are millions of possible models, and there’s no way humans can model all of those fully and quantitatively,” Hoiland told me, hence the industry’s low success rate for exploratory wells. Zanskar can, though. By modeling all possible locations for geothermal reservoirs, the startup’s tools “create a probability distribution that allows you to make decisions with more confidence.”

To build these tools, Hoiland and his cofounder, Joel Edwards, both of whom have backgrounds in geology, tracked down and acquired long forgotten analog data sets mapping the subsurface of regions that were never developed. They digitized these records and fed them into their AI model, which is also trained on fresh inputs from Zanksar’s own data collection team, a group the company launched three years ago. After adding all this information, the team realized that test wells had been drilled in only about 5% of the “geothermally prospective areas of the western U.S.,” leaving the startup with no shortage of additional sites to explore.

“It’s been nine years since a greenfield geothermal plant has been built in the U.S.,” Edwards told me, meaning one constructed on land with no prior geothermal development. “So the intent here is to restart that flywheel of developing greenfield geothermal again.” And while Zanskar would not confirm, Axios reported earlier this month that the company is now seeking to raise a $100 million Series C round to help accomplish this goal.

In the future, Zanskar plans to test and develop sites where exploratory drilling has never even taken place, something the industry essentially stopped attempting decades ago. But these hitherto unknown sites, Edwards said, is where he anticipates “most of the gigawatts” are going to come from in the future.

Hoiland credits all this to advances in AI, which he believes will allow geothermal “to become the cheapest form of energy on the planet,” he told me. Because “if you knew exactly where to drill today, it already would be.”

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