Rigid transformations for stabilized lower dimensional space to support subsurface uncertainty quantification and interpretation
AO Mabadeje, MJ Pyrcz - Computational Geosciences, 2024 - Springer
Subsurface datasets commonly are big data, ie, they meet big data criteria, such as large
data volume, significant feature variety, high sampling velocity, and limited data veracity …
data volume, significant feature variety, high sampling velocity, and limited data veracity …
Improved integration of information to reduce subsurface model bias
AO Mabadeje - 2024 - repositories.lib.utexas.edu
Subsurface modeling deals with data-related issues like cognitive and sampling biases, and
model-related challenges including statistical assumptions, misspecification, and algorithmic …
model-related challenges including statistical assumptions, misspecification, and algorithmic …