Uncertainty Quantification in Classifying Complex Geological Facies Using Bayesian Deep Learning

Uncertainty Quantification in Classifying Complex Geological Facies Using Bayesian Deep Learning

Understanding geological differences in a proved reservoir requires precise facies classification. Predicting facies from seismic data is frequently seen as an inverse uncertainty quantification problem in seismic reservoir characterization. Typically, the uncertainty in the model parameters that re...

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Bibliographic Details
Main Authors: Touhid Mohammad Hossain, Maman Hermana, Makky Sandra Jaya, Hiroshi Sakai, Said Jadid Abdulkadir
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Uncertainty quantification
Bayesian deep learning
facies classification
Online Access:https://ieeexplore.ieee.org/document/9933453/

Internet

https://ieeexplore.ieee.org/document/9933453/

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