2 papers
physics.geo-ph2026
Pretrain-to-alignment learning paradigm to improve geophysical AI applicability under scarce field labels and synthetic-to-field gaps: A case study of relative geologic time estimation in global shelf-edge clinothems
Hui Gao, Xinming Wu, Jiarun Yang +2
Artificial intelligence (AI) has been increasingly applied to various geophysical scenarios, yet its practical deployment remains limited by scarce field labels, pronounced synthet…
physics.geo-ph2026
Massive-scale unlabeled field and labeled synthetic seismic datasets of global shelf-edge clinothems
Hui Gao, Xinming Wu, Jintao Li +2
Seismic stratigraphic interpretation of shelf-edge clinothems is essential for revealing tectonic evolution, paleoclimate change, depositional dynamic conditions, and hydrocarbon g…