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Seequent, 400C Energy, and Cascade Institute Join Forces to Map Canada's Deep Geothermal Energy Potential

Beneath the Cold: How the Canadian Thermal Model Could Unlock a Geothermal Revolution

Calgary, Alberta – June 10, 2026 — The image of Canadian energy has long been defined by what we extract from the ground and burn: oil sands, natural gas, and coal. But two kilometers below the foothills of the Rockies, and three kilometers beneath the flat fields of Saskatchewan, a different kind of resource is simmering. It is silent, carbon-free, and inexhaustible. It is the heat of the Earth itself.

For decades, geothermal energy in Canada has been a tantalizing "what if." The country sits on some of the most significant deep heat reservoirs in the world—the product of ancient continental collisions, radioactive decay in granite batholiths, and the sheer thermal mass of the crust. Yet, compared to Iceland, the United States, or Kenya, Canada’s geothermal sector remains embryonic. The reason is not a lack of heat, but a lack of certainty.

On June 8, 2026, standing beneath the towering glass of the Calgary TELUS Convention Centre on the opening day of the World Geothermal Congress (WGC), a coalition of researchers, technology firms, and energy pioneers announced an ambitious plan to change that.

The Cascade Institute, in partnership with Seequent, 400C Energy, the Institut national de la recherche scientifique (INRS), and Simon Fraser University (SFU), has launched the Canadian Thermal Model (CTM) — a comprehensive, machine-learning-powered mapping of the nation’s deep geothermal resources. This isn't just another academic survey. It is an attempt to create a "Google Earth for the Canadian basement," a digital twin of the thermal frontier that could unlock billions in investment and position Canada as a surprise leader in next-generation renewable energy.

The Problem: The Blind Subsurface

To understand why the Canadian Thermal Model matters, one must first understand the fundamental challenge of geothermal energy. Wind and solar are visible; you can see the sun and feel the breeze. Geothermal energy, by contrast, is invisible, buried under kilometres of rock.

“The single greatest barrier to geothermal development is subsurface uncertainty,” explained Jeremy O’Brien, Energy Segment Director at Seequent, in an interview following the announcement. “You can model a wind turbine’s output with near-perfect accuracy based on above-ground weather data. But with geothermal, you are drilling a hole into the unknown. You don’t know the exact temperature, the porosity of the rock, or the fluid chemistry until you spend $10 million to $20 million on a well.”

This risk profile has kept Canadian institutional investors at bay. While the U.S. Department of Energy’s GeoVision analysis identified over 5,000 gigawatts of potential geothermal capacity across North America, Canada has historically lacked the high-resolution, national-scale data needed to de-risk first-mover projects.

Existing data is fragmented. Oil and gas companies have drilled hundreds of thousands of boreholes in the Western Canadian Sedimentary Basin (WCSB), but that temperature data is proprietary, scattered across corporate servers, or logged in inconsistent formats. Further east, in the crystalline shield of the Canadian Precambrian, there are vast holes in the data map—literally hundreds of thousands of square kilometers where bottom-hole temperatures have never been measured.

Dr. Thomas Homer-Dixon, Executive Director of the Cascade Institute, is blunt about the stakes. “Canada has world-class subsurface expertise and a growing opportunity to lead in geothermal,” he said from the conference floor. “But you cannot lead what you cannot measure. This project will provide a foundational resource to demonstrate the technical and economic viability of geothermal energy at scale.”

The Solution: InterPIGNN and Machine Learning

The Canadian Thermal Model is not your grandfather’s geologic survey. It abandons the old methodology of manual interpolation—drawing smooth temperature contours between sparse data points—in favor of a disruptive computational approach.

At the heart of the CTM is a novel machine learning algorithm called InterPIGNN (Physics-Informed Graph Neural Network for Interpolation). Developed by researchers at INRS and SFU, InterPIGNN is designed to do what classical physics cannot: predict deep underground temperatures in places where no wells exist, using the subtle relationships between different types of geophysical data.

Here is how it works. The team is feeding the algorithm three distinct layers of information:

1. Geologic Constraints: The known lithology (rock types), fault lines, and basin structures from surface mapping and seismic surveys.

2. Geophysical Signatures: Magnetic and gravitational field data, which reveal the depth of the basement and the location of radioactive heat-producing granites.

3. Thermal Calibration Points: Every available bottom-hole temperature from oil, gas, and mining exploration across the country, standardized and cleaned.

The graph neural network then learns the correlation between a rock’s magnetic signature and its thermal conductivity; between a gravity low and the presence of insulating sediments; between a fault line and a hydrothermal conduit. The result is a probabilistic three-dimensional model of the Canadian crust down to a depth of 5 to 7 kilometers.

“Traditional interpolation treats the Earth as a static, smooth surface,” notes a technical white paper released by the Cascade Institute on June 9. “InterPIGNN treats the Earth as a network of interacting systems. It learns the physics from the data itself, allowing it to predict high-resolution thermal gradients in complex, faulted terrains where traditional models fail.”

To operationalize this, Seequent is providing access to its Oasis montaj geophysics software. This is not a trivial donation of software licenses; Oasis montaj is the industry standard for integrating, processing, and visualizing large-scale geophysical datasets. Seequent’s tools support more than 60% of the world’s existing geothermal power generation, from the Imperial Valley in California to the Great Rift Valley in Kenya.

“Oasis montaj allows us to take raw magnetic vector data from the Geological Survey of Canada and fuse it with well-log temperature data in a unified coordinate system,” said a geophysicist working on the project. “Without that integration step, the machine learning model is just garbage in, garbage out. Seequent’s platform is the sieve that cleans the data.”

The Partners: A Coalition of Necessity

The Canadian Thermal Model is notable not just for its technology, but for its architecture of collaboration. It brings together four distinct pillars of the energy transition:

1. Research & Science (Cascade Institute, INRS, SFU)

Cascade provides the systems-level thinking and policy framework. Homer-Dixon’s institute specializes in solving “wicked problems”—complex global challenges like climate change and energy security. For them, geothermal is not just an electricity source; it is a strategic asset for grid resilience and northern economic development. INRS and SFU provide the algorithmic and geophysical horsepower.

2. Data & Technology (Seequent)

As a Bentley Systems company, Seequent brings the commercial rigor and software scalability. Their involvement signals that this is not an academic exercise. The goal is to produce a model that can be ingested by energy developers, engineering firms, and financial models. Seequent is essentially providing the digital twin framework.

3. Industry Application (400C Energy)

This is the most crucial piece. 400C Energy is a Canadian geothermal development company actively pursuing projects. They are not here for the science fair; they need drill targets. 400C will act as the "ground truth" validator. As the CTM identifies high-potential zones, 400C will cross-reference them with existing land holdings and seismic data to prioritize the first validation wells.

4. Government & Legacy Data (Geological Survey of Canada – Pacific Division)

While not a headline partner in the press release, the involvement of the GSC is the silent backbone of the project. Canada’s federal geoscience agency holds decades of aeromagnetic surveys, gravity data, and thermal conductivity measurements. Opening that vault to machine learning algorithms is a tacit acknowledgment that Canada needs a 21st-century energy atlas.

Why Now? The Global Geothermal Surge

The timing of the announcement—the opening day of the WGC in Calgary—was deliberate. The world is in the midst of a quiet geothermal renaissance.

For a decade, geothermal was the forgotten renewable. It was geographically constrained to volcanic hotspots and suffered from high upfront capital costs. But two trends have disrupted this narrative.

First, Enhanced Geothermal Systems (EGS) —popularized by companies like Fervo Energy—have matured. By using hydraulic fracturing techniques borrowed from the oil and gas industry, developers can now create artificial reservoirs in hot, dry rock where no natural water exists. Fervo’s Cape Station in Utah, which Seequent supported, is proving that EGS can deliver 24/7 clean power at utility scale.

Second, the energy crisis of the early 2020s taught a painful lesson about intermittency. As Germany shuttered nuclear plants and coal phased out, prices spiked when the wind stopped blowing. Geothermal offers a "baseload" renewable—a power plant that runs 95% of the time, regardless of weather.

“The need for reliable, always-on clean energy has never been greater,” O’Brien emphasized. “Realizing that potential starts with greater subsurface certainty.”

Canada is uniquely positioned to benefit from the EGS boom. The oil and gas sector in Alberta and British Columbia has spent 70 years perfecting the art of deep drilling, directional boring, and reservoir stimulation. Thousands of unemployed or transitioning petroleum geologists and engineers are now looking for a new frontier. Geothermal is the logical bridge.

However, EGS requires precise targeting. You need rock that is hot enough (above 150°C) but not too deep (ideally less than 5 km), with favorable stress regimes for fracturing. The Canadian Thermal Model is the treasure map for that specific geological sweet spot.

The Technical Challenges Ahead

Despite the optimism, the road to a national thermal model is fraught with technical and political hurdles. A 3000-word analysis would be incomplete without acknowledging the granite in the room.

The "No Data" Problem:

Machine learning is data-hungry. While the WCSB has decent coverage, Northern Canada—the Yukon, Northwest Territories, Nunavut, and vast swaths of Labrador—is a geophysical desert. There are no oil wells in the tundra. The InterPIGNN algorithm will have to extrapolate across massive distances, relying solely on satellite magnetic data. The uncertainty in those northern regions will be high, and communicating that uncertainty to investors (who hate ambiguity) is a core challenge for Cascade’s modeling team.

The Data Rights Maze:

Most bottom-hole temperature data in Alberta is owned by oil and gas producers. While the Alberta Energy Regulator collects logs, the proprietary periods can last years. Convincing producers to share raw temperature data—or allowing the model to use anonymized aggregates—requires a level of industry cooperation that is rare in the notoriously secretive extractive sector. The success of the CTM hinges on whether the partnership can negotiate data access agreements that protect corporate intellectual property while advancing the public good.

The Scale Problem:

Geothermal is local. A model that predicts a 200°C reservoir at 4 km depth is exciting, but to actually build a plant, you need a resolution of tens of meters, not kilometers. The CTM aims for a "national view"—a reconnaissance map. It will identify basins and heat highs. But the final 100 meters of resolution still requires conventional seismic surveys and exploration wells. The model de-risks the region; it does not eliminate the need for wildcat drilling.

Potential Hotspots: Where Will the Model Look?

Based on preliminary data discussed at the WGC, the Canadian Thermal Model is likely to highlight three major archetypes of geothermal potential:

1. The Deep Basin (Alberta & BC)

The Western Canadian Sedimentary Basin is the low-hanging fruit. With sediment thicknesses exceeding 6 km in the Deep Basin, geothermal gradients are highly variable. The model is expected to confirm zones near the Rocky Mountain deformation front where deep circulation along faults brings heat closer to the surface. Existing abandoned oil wells could be converted to geothermal heat for nearby towns (like the Swan Hills project).

2. The Basement Heat (Saskatchewan & Manitoba)

Hidden under the flat prairies is the Precambrian basement. In places where the sedimentary cover is thin (1-2 km), the heat flowing from the radioactive granites of the Canadian Shield can be tapped via EGS. The CTM will likely identify the "Lloydminster Dome" and the "Sweetgrass Arch" as prime targets.

3. The Cordilleran Faults (BC & Yukon)

British Columbia is Canada's "Iceland." The interaction of the Pacific and North American plates creates high heat flow, hot springs (Liard River, Meager Creek), and active volcanism (Mount Garibaldi). The CTM will help map the deep roots of these geothermal systems, moving beyond obvious surface hot springs to find blind geothermal systems hidden beneath valley floors.

Implications  for Policy and Investment

The most profound impact of the Canadian Thermal Model may be outside the geology lab—in the boardrooms of pension funds and the committee rooms of Parliament.

For Investors:

Institutional capital requires standard metrics. You cannot get a "Proven" geothermal reserve classification without a well. But you can get a "Prospective Resource" classification with a robust, peer-reviewed national model. The CTM will allow the Canada Infrastructure Bank and private equity firms to screen opportunities nationally, comparing the Levelized Cost of Energy (LCOE) of a geothermal project in BC versus a solar farm in Alberta. It brings geothermal into the same financial planning tools as every other asset class.

For Policymakers:

The federal government's Clean Electricity Regulations require a net-zero grid by 2035. Provinces like Alberta, which have no large-scale hydro, are struggling to balance solar/wind intermittency. A national thermal model would allow Natural Resources Canada to designate "Geothermal Development Zones" with streamlined permitting, similar to the Geothermal Steam Act in the US. It provides the evidence base for subsidies, tax credits, and strategic land allocation.

For Indigenous Communities:

Perhaps the most exciting application is for remote, diesel-dependent Indigenous nations in BC, Yukon, and the Territories. Many of these communities sit on thermal anomalies but lack the millions of dollars required for exploration. The CTM will de-risk small-scale, district heating projects (direct use of heat) and binary-cycle power plants. When combined with federal funding like the Indigenous Off-Diesel Initiative, the model could catalyze a wave of energy sovereignty.

The Seequent Factor: From Maps to Reality

One cannot discuss the Canadian Thermal Model without acknowledging the quiet revolution at Seequent. Historically a geoscience software company, Seequent has increasingly positioned itself as the connective tissue between subsurface data and energy transition infrastructure.

Their support of the CTM goes beyond corporate social responsibility. Seequent has a direct commercial interest in proving that robust geophysics reduces project risk. If the CTM successfully accelerates Canadian geothermal, every subsequent developer will need Seequent’s Leapfrog geothermal software to build their site-specific models, and Oasis montaj to process their magnetic surveys.

“This is not charity; it is ecosystem building,” a Seequent product manager noted during a breakout session at WGC. “When the industry grows, we grow. But right now, the bottleneck is the data. We have the tools to unblock it.”

The Verdict: A Necessary Pivot

As the World Geothermal Congress continues in Calgary through June 11, the mood is electric—literally. For a city built on fossil fuels, hosting a geothermal conference feels like a homecoming. The skills are the same. The rigs are the same. Only the target has changed.

The Canadian Thermal Model will not be finished by the end of the WGC. The partnership estimates a first-phase national map in 12 to 18 months, with iterative updates as new data arrives. It is a long-term play.

But Thomas Homer-Dixon is thinking in decades. “We solve global problems,” the Cascade Institute’s motto reads.

“Canada has an opportunity to turn a geological liability—a cold climate and deep crust—into an energy asset,” he said. “But we must start with knowledge. The Canadian Thermal Model is that start.”

For the first time, Canada is no longer guessing where the heat is. It is measuring. And in the high-stakes game of energy transition, measurement is the first step to domination.

About the partners: The Cascade Institute is a research hub focused on global systemic risks and solutions. Seequent develops earth modeling, data management, and team collaboration software. 400C Energy is a Canadian geothermal developer. INRS is a Quebec university specializing in engineering and geoscience. Simon Fraser University is a public research university in British Columbia.

World Geothermal Congress 2026 continues in Calgary until June 11, featuring technical sessions on EGS, direct use, and policy frameworks.

See also: Data-Driven Site Selection in Nevada Pushes SLB and Ormat's EGS Development Forward

Source: Seequent , Cascade Institute 

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