Surveys a decade of AI work in subsurface imaging and proposes a benchmark covering fault segmentation, relative geologic time, geobody segmentation, and property modeling using synthetic and real data.
Machine learning for data-driven discovery in solid earth geoscience
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
PINNs for first-order plane-strain elastodynamics achieve higher accuracy with soft boundary enforcement over implicit geometries but require longer training than hard enforcement.
citing papers explorer
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CIG-Bench: A Comprehensive Survey and Benchmark for AI-Driven Subsurface Imaging Understanding
Surveys a decade of AI work in subsurface imaging and proposes a benchmark covering fault segmentation, relative geologic time, geobody segmentation, and property modeling using synthetic and real data.
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Exact Boundary Enforcement Along Implicit Geometries for Physics-Informed, Deep Learning Problems in Continuum Mechanics
PINNs for first-order plane-strain elastodynamics achieve higher accuracy with soft boundary enforcement over implicit geometries but require longer training than hard enforcement.