Predicting the elastic response of organic‐rich shale using nanoscale measurements and homogenisation methods. (24th January 2017)

• Record Type: Journal Article
• Authors: Goodarzi, M.; Rouainia, M.; Aplin, A.C.; Cubillas, P.; de Block, M.
• Is Part Of: Geophysical prospecting. Volume 65:Number 6(2017)
• Page Start: 1597
• Page End: 1614
• Publication Date: 2017-01-24
• Subjects: Anisotropy -- Elastics -- Imaging -- Modelling -- Rock physics; Prospecting -- Geophysical methods -- Periodicals; 622.15
• DOI: 10.1111/1365-2478.12475
• Languages: English
• ISSNs: 0016-8025

Abstract

ABSTRACT: Determination of the mechanical response of shales through experimental procedures is a practical challenge due to their heterogeneity and the practical difficulties of retrieving good‐quality core samples. Here, we investigate the possibility of using multi‐scale homogenisation techniques to predict the macroscopic mechanical response of shales based on quantitative mineralogical descriptions. We use the novel PeakForce Quantitative Nanomechanical Mapping technique to generate high‐resolution mechanical images of shales, allowing the response of porous clay, organic matter, and mineral inclusions to be measured at the nanoscale. These observations support some of the assumptions previously made in the use of homogenisation methods to estimate the elastic properties of shale and also earlier estimates of the mechanical properties of organic matter. We evaluate the applicability of homogenisation techniques against measured elastic responses of organic‐rich shales, partly from published data and also from new indentation tests carried out in this work. Comparison of experimental values of the elastic constants of shale samples with those predicted by homogenisation methods showed that almost all predictions were within the standard deviation of experimental data. This suggests that the homogenisation approach is a useful way of estimating the elastic and mechanical properties of shales in situations where conventional rock mechanics test data cannot be measured.