能源地球科学（英文）2026，Vol.7Issue(2)：121-132,12.DOI:10.1016/j.engeos.2026.100537
Porosity and permeability prediction from petrographic point-counting data using machine learning:Applications to Rotliegendes and Buntsandstein reservoirs
Porosity and permeability prediction from petrographic point-counting data using machine learning:Applications to Rotliegendes and Buntsandstein reservoirs
Sahar Sadrikhanloo 1Benjamin Busch 1Christoph Hilgers1
作者信息
- 1. Structural Geology and Tectonics,Institute of Applied Geosciences,Karlsruhe Institute of Technology,Adenauerring 20a,76131,Karlsruhe,Germany
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摘要
关键词
Machine learning/Petrography/Point-counting/Porosity/PermeabilityKey words
Machine learning/Petrography/Point-counting/Porosity/Permeability引用本文复制引用
Sahar Sadrikhanloo,Benjamin Busch,Christoph Hilgers..Porosity and permeability prediction from petrographic point-counting data using machine learning:Applications to Rotliegendes and Buntsandstein reservoirs[J].能源地球科学（英文）,2026,7(2):121-132,12.
