Micro-CT sub-volume dataset for pore-scale rock property prediction using 3D CNNs

This dataset contains 9261 3D micro-CT image sub-volumes extracted from carbonate rock samples. The data were used to train and evaluate 3D convolutional neural network models for predicting pore-scale rock properties, including porosity, pore size, throat size, coordination number, and pore shape factor.

Keywords

micro-CT digital rock physics convolutional neural networks carbonate rocks pore-scale imaging

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

Found an issue? Give us feedback

0

Average