Increasingly, AI is changing the way industries find and develop new resources. AI has changed the way people use and understand big data in many fields, right from predictive maintenance in manufacturing to algorithmic trading in finance. The same data-driven approach is now starting to change the manner in which energy is explored.
MAX Power Mining developed MAXX LEMI, an AI-assisted geological modeling platform, to speed up the quest for naturally occurring hydrogen systems. At the 2026 Canadian Hydrogen Convention in Edmonton, which will be held between April 21 and 23, this platform could win the “Digital Innovator” award for MAX Power.
Deep inside the Earth’s crust, natural hydrogen, also known as white hydrogen, forms through geological reactions. Natural hydrogen is already underground and ready to use, unlike manufactured hydrogen, which usually needs electricity or fossil fuels to produce. If it is possible to find large-scale viable reservoirs, natural hydrogen could as well become a major part of the world’s clean energy mix. MAX Power has reported the first-ever discovery of a subsurface natural hydrogen system in Canada. It is currently being evaluated for commercial use.
Finding natural hydrogen is challenging, which makes MAX Power’s discovery so important.
Natural hydrogen systems are complicated geological settings that include a number of different things –Â source rocks that can make hydrogen, migration pathways that let gas move through the ground, reservoirs where it can build up, and seals and traps that keep it in place. To find these conditions over large geological areas, you need to combine a lot of data, such as seismic surveys, historical well records, and geophysical maps, as well as geochemical datasets.
This is where MAXX LEMI comes into the picture.
Large Earth Model Integration, the platform name, means that it can combine large geological and geophysical datasets into a single model that can find good places to explore. The system lets geoscientists look at the chance of hydrogen systems forming in certain geological settings by combining regional data with modern analytical tools.
The model is changing in stages. The first versions of this AI-assisted geological modeling platform were mostly about putting together regional datasets and making play-based exploration maps to help find possible hydrogen zones. Future versions are looking to add machine learning algorithms that can look at complicated geological relationships between many variables, all at once. In real life, this means that MAXX LEMI will be able to figure out patterns that would take traditional exploration teams months or even years to figure out.
The technology is already helping with exploration on MAX Power’s large land holdings in Saskatchewan, where the company has one of the world’s largest permitted natural hydrogen exploration packages. Data from drilling activities, such as the Lawson Discovery from the company, which confirmed Canada’s first subsurface natural hydrogen system, continues to be fed back into the model, which helps it make better predictions.
The goal for MAXX LEMI goes beyond just one project over time. The system is being built as a platform that can grow and be used to look for hydrogen exploration possibilities in other parts of the world. Using what one learned about Saskatchewan’s geology on global datasets, the platform could greatly speed up the process of finding natural hydrogen systems that work.
The method is similar to how digital tools have changed other resource sectors in many ways. Advanced modeling and data analytics are becoming steadily important for finding subsurface reservoirs in oil and gas exploration. Similar tools are used by mining companies in order to understand mineral systems across large geological belts. Natural hydrogen exploration is starting to use the same set of tools as other fields.
The bigger picture is how AI can lower the risk of exploration. Models such as MAXX LEMI may help companies focus their drilling efforts where the chances of finding something are highest by making it easier to find good geological environments. That efficiency is important in new industries, where each drill hole gives useful information that helps people learn more about the resource itself.
As the world’s energy system looks for new ways to get cheap, low-carbon energy, technologies that combine data science with subsurface exploration could as well go on to become increasingly crucial. MAXX LEMI is one of the first examples of how AI could help one find natural hydrogen as a new type of energy source. This type of hydrogen has been underground for millions of years but is only now getting thoroughly explored.