anisotropic seismic tomography: potentials and pitfalls mark panning university of florida cider...
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![Page 1: Anisotropic seismic tomography: Potentials and pitfalls Mark Panning University of Florida CIDER Research Talk 7/5/2010](https://reader035.vdocuments.net/reader035/viewer/2022062518/56649d215503460f949f6fb9/html5/thumbnails/1.jpg)
Anisotropic seismic tomography: Potentials and
pitfallsMark Panning
University of Florida
CIDER Research Talk 7/5/2010
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Cartoon land motivation: tomography of scientists
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What is seismic anisotropy?
?
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Origins of mantle anisotropy
Single crystal has anisotropic elastic properties
But large regions of the Earth appear nearly isotropic to seismic waves!
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Origins of mantle anisotropy
A random mix of orientations makes seismic waves see an isotropic average
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Origins of mantle anisotropy
Deformation can lead to preferential orientation (LPO) and seismic anisotropy
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Complications
• Anisotropy depends on deformation mechanism– Varies by stress state and grain size– Varies by volatile content
• Depends on integrated strain history
• Requires many model parameters to describe
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Fabric development
from Karato et al, 2008
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Not all gloom and doom• Natural samples (e.g. Montagner and
Anderson, 1989) and numerical modeling (e.g. Becker et al, 2006) suggest hexagonal symmetry is dominant
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Why we like hexagonal symmetry
• Reduces number of elastic coefficients from 21 to 5 (2 isotropic properties, 3 anisotropic ones) plus 2 orientation angles
• With scaling, we can reduce the number of parameters even further (scale Vp to Vs, and the various anisotropic parameters to each other)
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Why we like finite strain ellipses
from Becker et al, 2003
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“Vectorial tomography”
• Arbitrarily oriented hexagonal medium
• Can be linearized – with assumptions to reduce number of parameters
• Also can invert directly for anisotropic strength and orientation angles
symmetry axis
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Nonlinearity
Sensitivity to strength and orientation of anisotropy depends on the starting model
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Potential?
Chevrot and Monteiller, 2009 synthetic tests with non-linear inversion of body wave splitting data
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Matching models
from Gaboret et al, 2003
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Matching models
from Becker, 2008
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12% 7%
4% 4%
Upper mantle anisotropy
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Correlation with ridges
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Inconsistency of radial anisotropy models
From Becker et al., 2008
Correlation of VS models above 350 km
Correlation of ξ models above 350
km
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Poor crustal corrections - source of some inconsistency?
• Inversions of synthetic data using Crust2.0 but no mantle anisotropy show anisotropy
From Bozdağ and Trampert, 2008
From Lekic et al, 2010
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The crust and anisotropic models
• All seismic data is influenced by crustal structure
• Varying crustal models has similar effect on data fit as mantle radial anisotropy (Ferreira et al, 2010)
• Corrections based on linear perturbations from 1D crustal models are inadequate for long-period data
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Testing the impact of crustal corrections
• SAW642AN (as well as S362WMANI) incorporated non-linear crustal corrections based on regionalized mode calculations
• Other methods of non-linear crustal corrections exist
• We can compare models using different corrections and look at stability of model parameters.
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VS modelSAW642AN SAW642ANb
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Changing ξ model
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What remains
General pattern of radial anisotropy beneath oceanic and continental lithosphere remains. Ridge signature also remains.
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Troublesome details – D” structure
SAW642AN
New corrections – more regularization
Same dataset with linear corrections and longer wavelengths
New corrections – less regularization
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Takeaway message
• Anisotropic modeling has great potential for constraining flow patterns (and therefore mantle rheology, etc.)
• Inverse approach and crustal correction matter and can strongly affect anisotropic models
• In order to resolve anisotropic structure (and other secondary effects like attenuation), we need to figure out the crust!