Geoteric and SINTEF partner to build AI agent platform linking seismic interpretation with reservoir simulation
AI-madeGeoteric and SINTEF just announced they’re building a joint AI agent platform — one designed to finally connect two workflows that have spent decades ignoring each other: seismic interpretation and reservoir simulation. The platform runs on open standards, so specialized AI agents can move data and insights across software tools, disciplines, and vendors without getting stuck at proprietary walls. Geoteric’s AI-driven seismic tools plug directly into SINTEF’s reservoir simulators. Both organizations plan to show their first results at IMAGE 2026 in Houston this August.
Collaboration announced to integrate AI-driven subsurface workflows
The core idea: Geoteric and SINTEF are building a shared platform where AI agents handle the handoffs between seismic interpretation and reservoir simulation. Right now, those two worlds barely talk to each other in real time. Geoscientists interpret seismic data, then pass their conclusions downstream to reservoir engineers running entirely separate simulation models. The new platform is built to close that gap.
Open standards are a deliberate design choice. The platform isn’t locked to any single vendor or software environment—AI agents inside it can move data and insight across different tools, disciplines, and organizational boundaries. Interoperability is the default, not an afterthought.
Seismic data shows what rocks and structures look like underground; simulation describes how fluids—oil, gas, water, and CO₂—move through those structures over time.
The first public demo is set for IMAGE 2026, the international geoscience and energy conference held in Houston every August. Not a concept pitch. Both organizations plan to show the platform doing real work inside a live integrated workflow.
Why the two organizations decided to collaborate
The partnership makes sense once you look at what each side brings. Geoteric specializes in AI-based seismic interpretation, while SINTEF brings deep expertise in reservoir simulation, mathematical modeling, and research-grade software for complex physical systems. Seismic data shows what rocks and structures look like underground; simulation describes how fluids—oil, gas, water, and CO₂—move through those structures over time. The two capabilities fit together naturally.
For SINTEF, this is a chance to move research into practice. Knut-Andreas Lie, chief scientist at SINTEF, called it “an exciting opportunity to operationalize the research we are doing in SINTEF Agent Lab on the use of AI agents as part of expert systems.” The next step is layering agent technology on top of existing infrastructure and demonstrating how open tools can support more automated, verifiable workflows.
On the Geoteric side, Chair Jan Grimnes has a specific frame of reference — he was part of the team behind Petrel, the widely used subsurface modeling platform. That history shapes how he reads where the industry is heading. “I am convinced that open AI agent platforms will change the way geoscientists work,” Grimnes said. “I see this as an important next step for the industry—where specialized applications can collaborate seamlessly to provide better subsurface insight.”
Expected effects on subsurface decision-making and uncertainty management
The practical ambition here is shortening the path from geological interpretation to dynamic fluid-flow models. Today, that journey involves multiple handoffs, format conversions, and judgment calls that introduce delays and inconsistencies. Automated agent interaction is designed to reduce those friction points — and the difference in day-to-day workflow could be substantial.
One of the clearest benefits both organizations point to is uncertainty management. By automating how specialized agents interact, the platform is designed to produce more verifiable interpretations and clearer quantification of uncertainty. Uncertainty in subsurface work is unavoidable; the real question is whether it gets tracked systematically or quietly absorbed into someone’s assumptions.
A more connected workflow lets users assess alternative geological models side by side, compare scenarios, and identify which options provide the strongest basis for a decision. That kind of structured comparison is much harder to pull off when interpretation and simulation live in completely separate systems. The platform targets geophysicists, geologists, and reservoir engineers—giving all of them faster insight and a more consistent foundation throughout the subsurface workflow.
Background: The two organizations and their prior work
Geoteric has been building seismic analysis tools for more than 30 years. The company’s AI-enhanced software is used by energy companies worldwide to support exploration and production, helping operators with well placement, production planning, and subsurface understanding.
SINTEF is a Norwegian research organization with a broad portfolio in deep digital technology. Its Applied Computational Science group, part of SINTEF Digital, focuses on mathematical models, simulation, agentic AI, and research-based software for complex physical systems—work that spans geoenergy, reservoir simulation, CO₂ storage, and open computational tools for industrial decision support.
SINTEF’s connection to Petrel is worth noting. The organization’s earlier work contributed to that platform’s development, and Petrel became a standard tool across the oil and gas industry. Grimnes acknowledged that history directly: “SINTEF has been one of Norway’s most important research partners in technology for subsurface understanding and has contributed to a range of solutions that have shaped the oil and gas industry, including through the work that led to Petrel.” Much of SINTEF’s simulation code is open-source, built alongside major international energy companies over several decades—and that same openness runs through this new collaboration.
First demonstration at IMAGE 2026 in Houston
The Geoteric–SINTEF partnership is a concrete step toward integrating two workflows that have historically operated independently. The platform uses open standards and AI agents to connect seismic interpretation directly with reservoir simulation, cutting manual handoffs and making uncertainty more visible throughout the process. Target users are geophysicists, geologists, and reservoir engineers. Geoteric brings decades of AI-driven seismic analysis; SINTEF brings open-source reservoir and CO₂ storage simulation built over the same span of time. The first demonstration is planned for IMAGE 2026 in Houston this August.
Kelly is an experienced writer with 15 years of experience exploring the big stories that shape our world, from tech breakthroughs and space exploration to climate, energy, and the fascinating quirks of science. She has a talent for turning complex ideas into sharp, memorable insights that stay with readers long after they’ve finished reading.
