Aberdeen, UK, 8 – 11 June
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.
High-quality subsurface imaging, especially of the shallow stratigraphic section, is critical to the success of CO₂ storage projects. In 2014-2018, Viridien began acquiring a regional broadband 3D seismic survey in the Northern Viking Graben (NVG). This regional dataset covers the Horda Platform in the north and Stord basin in the south, as seen in Figure 1 below. This dataset has been reimaged with Viridien’s latest proprietary technologies through continuous development, as industry demand for higher-quality data has grown. The newly reimaged NVG data (see map) reveals potential opportunities in semi-open aquifers with substantial storage capacity in the Stord Basin, where suitable reservoirs and seals may enable efficient injection and trapping of CO₂.
The Gulf of America is a vital part of US energy infrastructure, with its future increasingly dependent on new seismic technologies to tackle complex geology. As exploration advances into salt-dominated regions, operators are relying on advanced imaging and novel acquisition technologies to better map subsurface formations, improving visibility beneath salt layers and deepwater sediments that previously hid critical structures.
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