Automatic classification of carbonate rocks permeability from 1H NMR relaxation data
作者：
Highlights：
• This work investigates the effectiveness of data mining analysis on NMR data.
• The goal is to accurately predict the permeability class of carbonate rocks.
• Our approach outperforms the traditional NMR models Timur–Coates and Kenyon.
• Traditional models ignore the singular relationship between T2 bins and pore throat.
• Data mining models capture the influence of each T2 bin over the permeability class.
摘要
•This work investigates the effectiveness of data mining analysis on NMR data.•The goal is to accurately predict the permeability class of carbonate rocks.•Our approach outperforms the traditional NMR models Timur–Coates and Kenyon.•Traditional models ignore the singular relationship between T2 bins and pore throat.•Data mining models capture the influence of each T2 bin over the permeability class.
论文关键词：Nuclear magnetic resonance,Permeability,Classification,Data mining
论文评审过程：Available online 17 January 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.01.034
