DGS Café welcomed Dr. Miguel Corrales and Dr. Harpeet Sethi, both Solutions Architects for Energy at NVIDIA, for a session on physics-informed machine learning in the geosciences. The speakers explained how pairing data-driven models with physical laws and domain knowledge can capture complex subsurface behaviour more effectively than either approach alone.
Examples ranged from waveform inversion to CO2 plume migration, showing how physics-ML can shorten simulation times, make predictions more dependable and support uncertainty analysis. More than 30 attendees joined the discussion on how these tools can work alongside conventional physics-based modelling in exploration. The session was organised by DGS Vice President of Technical Exchange Rayan Kanfar and Technical Meeting Officer Fahad Alhussaini.
Event enablers: Rayan Kanfar, Fahad Alhussaini, Dalia Almaghlouth, Tanya Alauddin, Kawthar Alelg
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