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Generative inversion for early ranking of competing geologic interpretations

Rashid, Harun Ur et al.
arXiv (All) · Papers
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machine-learning
High-consequence subsurface decisions are often made under severe data scarcity. Experts may arrive at competing interpretations of the same subsurface system, yet early in a project there is rarely a practical way to determine which one is most realistic. This uncertainty can persist until several
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