Modelling Subsurface Systems for Safer Carbon Storage

Originally from Brazil, Carlos brings a background in fracture modelling and a growing expertise in the geophysical challenges tied to subsurface energy systems.

Carlos began his journey at DTU in 2020 as a PhD student working on fracture modelling in chalk reservoirs. His early research focused on how fractures influence fluid flow – an area crucial to geothermal and subsurface storage operations. That work now feeds into the EU-funded GO-Forward project, where the fundamentals of fracture flow developed during his PhD will be applied to geothermal reservoir analysis, enabling a more reliable characterisation of deep geothermal resources.

Today, he also works in the IFD-funded Cerberus project, where he develops models that predict how CO₂ injection affects subsurface monitoring signals. This work helps improve monitoring strategies and reduce the costs associated with long-term CO₂ storage. “If we can build reliable models of subsurface behaviour, we can design smarter, more efficient monitoring systems tailored to specific storage sites,” he explains.

Blending Disciplines, Broadening Impact

Carlos’s work sits at the crossroads of numerical simulation, rock physics, and artificial intelligence. He previously collaborated with Sandia National Laboratories on machine learning tools for CO₂ tracking and now builds on those efforts to support real-time monitoring in CCS.

“One of the biggest challenges is translating complex models into practical tools that operators can use with confidence,” he notes. “That’s what makes the work both challenging and meaningful.”

While his current focus is on carbon storage, Carlos sees broader applications for these tools, including environmental risk assessments in underground hydrogen storage and aquifer resilience under climate change.