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The energy industry has always grappled with the mysteries of the subsurface. From traditional wells to low-emission solutions like geothermal energy and Carbon Capture and Storage (CCS), these projects rely on incredibly complex mapping and long-term planning.
In these environments, engineers and geoscientists must make high-impact decisions based on incomplete data—often years before a project becomes operational.
The technology OMV is currently piloting in Norway isn’t generative AI; it is analytical, agent-based AI. Purpose-built for complex technical environments, the system was developed through OMV’s long-standing sponsorship of Stanford University and brought to life by TerraAI.
By leveraging advanced decision theory and geostatistics, the system explores millions of possible field development scenarios. It analyzes seismic data, geological models, and well information to recommend optimal strategies for drilling, $CO_2$ injection, and monitoring.
“I sometimes compare it to chess,” explains Torsten Clemens, Senior Reservoir Engineering Adviser at OMV. “In chess, you see the board. Underground, you don’t. The AI imagines all possible scenarios, tests different moves, and learns step-by-step which decisions reduce risk and create value.”
By running simulations up to 1,000 times faster than conventional tools, the system compresses months of analysis into hours. This allows teams to move with unprecedented speed without compromising quality or safety.
“Decisions that used to take months, we can now make in hours,” Clemens continues. “That doesn’t mean cutting corners; it means exploring significantly more options before we commit.”
The approach is already delivering tangible benefits. Early internal results from the Norwegian pilot indicate:
A 25%+ increase in total project value.
A 50% reduction in quantified subsurface risks.
Drastic acceleration of development timelines.
These results are particularly vital for CCS projects, where safety and regulatory confidence are paramount. The system integrates risk directly into the design phase, optimizing injection rates and well paths with strict safety limits in mind.
This is the ideal application of AI: enhancing human decision-making by managing complexity at an unparalleled scale. While currently focused on CCS in Norway, OMV sees massive potential to scale this technology across its low-carbon portfolio, including geothermal energy and other subsurface-dependent projects.
You can find the full case study and the official announcement on OMV’s blog here:
How AI is powering better decisions in the race to net zero | OMV.com
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