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    Stress-induced anisotropy model for triaxially stressed rocks

    Access Status
    Fulltext not available
    Authors
    Collet, Olivia
    Gurevich, Boris
    Madadi, Mahyar
    Pervukhina, Marina
    Date
    2012
    Type
    Conference Paper
    
    Metadata
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    Citation
    Collet, Olivia and Gurevich, Boris and Madadi, Mahyar and Pervukhina, Marina. 2012. Stress-induced anisotropy model for triaxially stressed rocks, in Proceedings of the Annual Meeting of the Society of Exploration Geophysicists (SEG), Nov 4-9 2012. Las Vegas: SEG.
    Source Title
    SEG Technical Program Expanded Abstracts
    Source Conference
    SEG/Las Vegas 2012
    DOI
    10.1190/segam2012-0919.1
    ISSN
    1052-3812
    URI
    http://hdl.handle.net/20.500.11937/6936
    Collection
    • Curtin Research Publications
    Abstract

    Elastic wave velocities in rocks vary with stress due to the presence of discontinuities and microcracks within the rock. In this paper, we analytically derive a model for seismic anisotropy caused by small triaxial stresses. We first consider a linearly isotropic elastic medium permeated by a distribution of cracks with random orientations. The geometry of cracks is not specified; instead, their behavior is defined by a ratio B of their normal to tangential excess compliances. When this isotropic rock is subjected to small triaxial stresses, crack closure occurs perpendicular to the applied stresses. This effect is modeled using Sayers and Kachanaov (1995) non-interactive approximation. The model predicts ellipsoidal anisotropy and also expresses the ratios of Thomsen’s parameters ε/γ as a function of the compliance and Poisson’s ratios in the three orthogonal planes of symmetry. A reasonable agreement was obtained when comparing the model predictions to laboratory measurements for small stresses (up to 20 MPa). These results could be used to differentiate stress-induced anisotropy from that caused by aligned fractures. Besides, if the cause of anisotropy is known, then this model could enable one to fully estimate the elasticity tensor from log data.

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