Compaction Localization in High Porosity Sandstones with Various Degrees of Heterogeneity: Insight from X-Ray Computed Tomography

- Organization:
- Canadian Institute of Mining, Metallurgy and Petroleum
- Pages:
- 2
- File Size:
- 44 KB
- Publication Date:
- May 1, 2009
Abstract
High resolution X-ray computed tomography imaging (with voxel size 48 µm) was conducted on various sandstone samples with different initial degrees of heterogeneity. All samples were imaged intact, and some after having developed localized compaction features in conventional triaxial experiments at high confining pressure, i.e. in the shear enhanced compaction domain (Wong et al., 1997). Our analysis of heterogeneity from X-ray CT data is based on the use of the coefficient of variation d =s /µ (s being the standard deviation and µ the average value). The coefficient of variation was shown by Otani et al. (2005) to be a convenient indicator of material heterogeneity in CT images of experimentally deformed sand piles. The authors reported differences in d before and after their experiments, and interpreted these differences as the effect of grain crushing resulting in more even material distribution within the voxels, hence in lower d values. The same concept was used by Louis et al. (2006) to image contrasts in d values throughout a volume of rock that had developed compaction bands in triaxial laboratory testing, knowing that the bands that had formed could be identified by visual inspection but not on the X-ray CT images. This study resulted in a radically enhanced image of the discrete compacted zones within the CT-scan series, whereby more deformed areas showed relatively low values of coefficient of variation due to grain crushing and pore collapse, as compared to nominally undeformed areas.
Citation
APA:
(2009) Compaction Localization in High Porosity Sandstones with Various Degrees of Heterogeneity: Insight from X-Ray Computed TomographyMLA: Compaction Localization in High Porosity Sandstones with Various Degrees of Heterogeneity: Insight from X-Ray Computed Tomography. Canadian Institute of Mining, Metallurgy and Petroleum, 2009.