Anisotropic Elastic Modelling for Organic Shales

Wu, Xiaomin; Chapman, Mark; Li, X. Y.; Dai, Hengchang

doi:10.3997/2214-4609.20148651

Cited by 15 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In some studies (e.g., Wu et al . ; Zu et al . ), multiple microstructural features such as the amount of pores and their aspect ratios in both clay and kerogen, kerogen particle aspect ratio, and cracks were considered numerically.…”

Section: Introductionmentioning

confidence: 94%

Predicting the elastic response of organic‐rich shale using nanoscale measurements and homogenisation methods

Goodarzi

Rouainia

Aplin

et al. 2017

Geophysical Prospecting

View full text Add to dashboard Cite

Block, M. (2017) 'Predicting the elastic response of organic-rich shale using nanoscale measurements and homogenisation methods.', Geophysical prospecting., 65 (6). pp. 1597-1614. Further information on publisher's website:https://doi.org/10.1111/ 1365-2478.12475 Publisher's copyright statement: This is the accepted version of the following article: Goodarzi, M., Rouainia, M., Aplin, A.C., Cubillas, P. and de Block, M. (2017), Predicting the elastic response of organic-rich shale using nanoscale measurements and homogenisation methods. Geophysical Prospecting., which has been published in nal form at https://doi.org/10.1111/1365-2478.12475. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving. Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractDetermination 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 (QNM ) 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.

show abstract

Section: Introductionmentioning

confidence: 94%

Predicting the elastic response of organic‐rich shale using nanoscale measurements and homogenisation methods

Goodarzi

Rouainia

Aplin

et al. 2017

Geophysical Prospecting

View full text Add to dashboard Cite

show abstract

“…This model can be used to estimate the elastic stiffness of laminated shales with vertical fractures. Xiaoyang Wu introduced a general rock physics modelling process to estimate the elastic properties from mineralogy and rock texture by combination of different rock physics models [3].…”

Section: Anisotropic Rock Physics Theorymentioning

confidence: 99%

Anisotropic Rock Physics Model Based Statistical Inversion

Wu¹

2017

PPEJ

View full text Add to dashboard Cite

“…Bayuk et al (2008) develop a rock physics model of organic-rich shale, in which the kerogen is treated as the background load-bearing matrix, and the other minerals and pore/cracks are then added. Wu et al (2012) develop an organic-rich shale anisotropic rock physics model, who mix the kerogen with the other minerals to calculate the effective rock properties. Zhu et al (2012) place the organic matter as a part of inclusion space to calculate the elastic properties, which is in accordance with the well log data.…”

Section: Introductionmentioning

confidence: 99%

The construction of shale rock physics model and brittleness prediction for high-porosity shale gas-bearing reservoir

2020

View full text Add to dashboard Cite

Due to the huge differences between the unconventional shale and conventional sand reservoirs in many aspects such as the types and the characteristics of minerals, matrix pores and fluids, the construction of shale rock physics model is significant for the exploration and development of shale reservoirs. To make a better characterization of shale gas-bearing reservoirs, we first propose a new but more suitable rock physics model to characterize the reservoirs. We then use a well A to demonstrate the feasibility and reliability of the proposed rock physics model of shale gas-bearing reservoirs. Moreover, we propose a new brittleness indicator for the high-porosity and organic-rich shale gas-bearing reservoirs. Based on the parameter analysis using the constructed rock physics model, we finally compare the new brittleness indicator with the commonly used Young's modulus in the content of quartz and organic matter, the matrix porosity, and the types of filled fluids. We also propose a new shale brittleness index by integrating the proposed new brittleness indicator and the Poisson's ratio. Tests on real data sets demonstrate that the new brittleness indicator and index are more sensitive than the commonly used Young's modulus and brittleness index for the high-porosity and high-brittleness shale gas-bearing reservoirs.

show abstract

Anisotropic Elastic Modelling for Organic Shales

Cited by 15 publications

References 8 publications

Predicting the elastic response of organic‐rich shale using nanoscale measurements and homogenisation methods

Predicting the elastic response of organic‐rich shale using nanoscale measurements and homogenisation methods

Anisotropic Rock Physics Model Based Statistical Inversion

The construction of shale rock physics model and brittleness prediction for high-porosity shale gas-bearing reservoir

Contact Info

Product

Resources

About