9th EAGE Conference on Conjugate Margins
Newfoundland and Labrador, Canada, 27 – 31 July
Newfoundland and Labrador, Canada, 27 – 31 July
After the Aptian source lying on top of the early-drift oceanic crust, the second most important source rock in the South Atlantic is the Cenomanian-Turonian (CT) sequence, a pelagic organic-rich mud ubiquitously deposited in a global anoxic event. Seismic velocity inversion of 3D seismic data in the Pelotas Basin reveals a nuance to the CT-driven play, interpreted to be partly
reworked by contourites. The hunt for tools to chase this phenomenon is on…
Artificial intelligence is transforming geoscience, enabling unprecedented improvements in seismic interpretation, reservoir characterization, and multi-disciplinary data integration. Traditional subsurface workflows – often slow, siloed, and constrained by manual interpretation – are being reshaped by foundation models, multi-modal learning, physics-informed neural networks, and agent-driven automation.
Recent breakthroughs in seismic foundation models (SFMs), multi-modal geoscience transformers, and generative AI have demonstrated substantial gains in speed, accuracy, and generalization across surveys. These advances mark the beginning of a new era in earth modelling: One that promises holistic, continuously updating digital twins of the subsurface.
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