Image transforms for determining fit-for-purpose complexity of geostatistical models in flow modeling

DOI10.1007/S10596-013-9340-8zbMath1382.86017OpenAlexW2038257795MaRDI QIDQ1705881

Orhun Aydin, Jef Caers

Publication date: 19 March 2018

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-013-9340-8

zbMATH Keywords

complexityuncertaintygeostatisticsimage transformsdistance-based modeling

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Geostatistics (86A32) Computational methods for problems pertaining to geophysics (86-08)

Cites Work

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• A Mathematical Theory of Communication
• A distance-based prior model parameterization for constraining solutions of spatial inverse problems
• Representing spatial uncertainty using distances and kernels
• Generalizing the Hough transform to detect arbitrary shapes
• Modern multidimensional scaling: theory and applications
• Modeling Uncertainty in the Earth Sciences
• Bayesian Measures of Model Complexity and Fit

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