Machine learning for subsurface geological feature identification from seismic data: Methods, datasets, challenges, and opportunities
Identification of geological features from seismic data such as faults, salt bodies, and
channels, is essential for studies of the shallow Earth, natural disaster forecasting and …
channels, is essential for studies of the shallow Earth, natural disaster forecasting and …
Implementation of denoising diffusion probability model for seismic interpretation
F Jiang, K Osypov, J Toms - SEG International Exposition and Annual …, 2023 - onepetro.org
In this abstract, we show a novel machine learning-based diffusion model for seismic
interpretation. In geophysics, reconstructing the subsurface structure from seismic data is an …
interpretation. In geophysics, reconstructing the subsurface structure from seismic data is an …
Perspectives of Quantifying Uncertainty in Seismic Inversion
K Osypov, M Gomes, M Belonosov, SR Singh… - 85th EAGE Annual …, 2024 - earthdoc.org
Uncertainty quantification in seismic inversion is challenged by the fact that there are
multiple perspectives on it. We discuss these perspectives, including parameterization …
multiple perspectives on it. We discuss these perspectives, including parameterization …