Digital rock physics: numerical prediction of pressure-dependent ultrasonic velocities using micro-CT imaging-Reference-Cited by-同舟云学术

Digital rock physics: numerical prediction of pressure-dependent ultrasonic velocities using micro-CT imaging

Published:2012-04-10 Issue:3 Volume:189 Page:1475-1482
ISSN:0956-540X
Container-title:Geophysical Journal International
language:en
Short-container-title:

Author:

Madonna Claudio,Almqvist Bjarne S.G.,Saenger Erik H.

Publisher

Oxford University Press (OUP)

Subject

Geochemistry and Petrology,Geophysics

Link

http://academic.oup.com/gji/article-pdf/189/3/1475/1677874/189-3-1475.pdf

Reference39 articles.

1. Modeling of grain boundary character reconstruction and predicting intergranular fracture susceptibility of textured and random polycrystalline materials;Arafin;Comput. Math. Appl.,2010

2. Accurate estimation of transport properties from microtomographic images;Arns;Geophys. Res. Lett.,2001

3. Computation of linear elastic properties from microtomographic images. Methodology and agreement between theory and experiment;Arns;Geophysics,2002

4. Inferential statistics of electron backscatter diffraction data from within individual crystalline grains;Bachmann;J. appl. Cryst.,2010

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