Predictive modelling of seismic properties in single-foliated slates

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Authors

Marco Antonio Lopez-Sanchez , Víctor Cárdenes Van den Eynde, Fabrice Barou , Sergio Llana-Fúnez

Abstract

Slates play a key role in understanding the seismic anisotropy of the continental crust, a crucial aspect of geophysical interpretation. Using a comprehensive set of high-quality single-foliated chlorite-bearing roofing slates, we determined their typical seismic properties via mineral fractions and orientation distribution functions using the geometric mean averaging method. Our study focused on identifying an optimal transverse isotropy (polar) model, assess correlations between elastic constants, and explore the feasibility of predicting intrinsic maximum anisotropy from a single proxy. We demonstrate that maximum axial and polarization anisotropy in single-foliated slates can be accurately estimated with ~10% error using a single proxy, termed the S-norm, which integrates the ODF strength and volumetric fraction of phyllosilicates. Additionally, we found that a polar parameterization combining elastic tensor decomposition and the Anderson equations yields seismic anisotropy predictions similar to the Christoffel equation, with errors below 2.8% (<0.2% for Vp). Lastly, our findings suggest that it is feasible to estimate the seismic properties of transversely isotropic slates from only two measurements: a diagonal component and the non-diagonal C13 component. These models are applicable for investigating slate belts at various depths, enabling the calculation of the minimum expected seismic anisotropy from intrinsic properties.

DOI

https://doi.org/10.31223/X5RM4Z

Subjects

Earth Sciences, Geophysics and Seismology

Keywords

Slate, Crystallographic Preferred Orientation, Seismic Properties, Seismic anisotropy

Dates

Published: 2024-06-17 02:11

Last Updated: 2024-11-09 06:37

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License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
Please find sample data at https://github.com/marcoalopez/slates2024. All data will be available once the manuscript is formally accepted.