3D Seismic Wave Simulations of Mantle Heterogeneity and Shear Wave Splitting Phases

Mapping Intimacies ◽

10.5194/egusphere-egu21-12537 ◽

2021 ◽

Author(s):

Neala Creasy ◽

Ebru Bozdag

Keyword(s):

Shear Wave ◽

High Performance ◽

Seismic Anisotropy ◽

Body Wave ◽

Waveform Inversion ◽

Shear Wave Splitting ◽

Plate Motion ◽

Wave Splitting ◽

The Common ◽

Data Sensitivity

Constraining the pattern and properties of seismic anisotropy in the Earth can help reveal relationships between mineral physics, mantle convection, and seismology. Sources of anisotropy in the lithosphere as frozen-in anisotropy, transition zone, and D" complicate shear wave splitting measurements, resulting in shear wave splitting that can differ from plate motion. If we better understand seismic anisotropy sourced in the lithosphere, we could also better constrain D" anisotropy, which requires correcting for the upper mantle to some extent. The goal of this work is to investigate the effect of 3D mantle and crustal structure on waveforms based on 3D wave simulations and adjoint data sensitivity kernels. We will explore the common phases (SKS, SKKS, S, ScS, PKS, etc.) and the common distance ranges used for mantle shear wave splitting with a resolution down to 9 s by conducting numerical simulations via 3D global wave propagation solver SPECFEM3D_GLOBE. We show results for a 1D mantle model (i.e., PREM [Dziewonski and Anderson, 1981]) and at least three 3D mantle models (S20RTS [Ritsema et al., 2011], GLAD-M15 [Bozdag et al., 2015], GLAD-M25 [Lei et al., 2020]). We calculate a number of data sensitivity kernels for travel time, amplitude, and anisotropy for our phases of interest over a variety of event depths and distance ranges. This work will help improve the measurements of shear wave splitting. The long-running goal is to use shear wave splitting in global full waveform inversion by addressing appropriate parameterization to describe body-wave anisotropy in the mantle during the inversion process. All simulations were conducted on a Research Allocation on the high-performance computing environment of XSEDE resources (TACC Stampede2).

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Extracting robust splitting measurements for the AlpArray using the splitting intensity method

10.5194/egusphere-egu2020-16479 ◽

2020 ◽

Author(s):

Götz Bokelmann ◽

Gerrit Hein

Keyword(s):

Shear Wave ◽

Seismic Anisotropy ◽

Body Wave ◽

Wiener Filter ◽

Single Layer ◽

Shear Wave Splitting ◽

Wave Splitting ◽

Anisotropic Structures ◽

Geodynamic Processes ◽

Set Up

Seismic anisotropy is an important tool for studying geodynamic processes in the Earth, and a common way of constraining it is to analyse shear-wave splitting of seismological body-wave phases, i.p. SKS. Different techniques exist to quantify shear-wave splitting, but they do not always give the same result, raising the question of how stable they are, and whether there are systematic biases. Furthermore, the strength of the splitting ("splitting delay") has generally been more difficult to determine than the other (the "fast orientation"). A robust technique for determining shear-wave splitting can be set up based on the splitting intensity method. That technique can in particular also constrain the splitting delay well. Ambient noise can however lead to an underestimation of splitting delay, and it needs to be accounted for, e.g. by a least-squares Wiener filter. We apply that modified splitting intensity method to data from the AlpArray. We have processed 3 years of teleseismic earthquake data for 336 stations of the AlpArray deployment and additional 315 stations of the Italian network to get a potentially broad and more complete image of anisotropic structures in and outside the Alpine region. The technique makes restrictive assumptions, e.g. assuming single-layer anisotropy. Yet, the new constraints, especially the one of the splitting delay are rather useful for understanding the deformation under the mountain belt and around it.&#160;

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Upper Mantle Anisotropy beneath the Western Segment, NW Indian Himalaya, Using Shear Wave Splitting

Lithosphere ◽

10.2113/2020/8856812 ◽

2020 ◽

Vol 2020 (1) ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Shubhasmita Biswal ◽

Sushil Kumar ◽

Sunil K. Roy ◽

M. Ravi Kumar ◽

W. K. Mohanty ◽

...

Keyword(s):

Shear Wave ◽

Upper Mantle ◽

Seismic Anisotropy ◽

Western Himalaya ◽

Shear Wave Splitting ◽

Plate Motion ◽

Indian Plate ◽

Deformation Pattern ◽

Mantle Flow ◽

Wave Splitting

Abstract This study investigates the upper mantle deformation pattern beneath the Indo-Eurasia collision zone utilizing the core-refracted (S(K)KS) phases from 167 earthquakes recorded by 20 broadband seismic stations deployed in the Western Himalaya. The 76 new shear wave splitting measurements reveal that the fast polarization azimuths (FPAs) are mainly oriented in the ENE-WSW direction, with the delay times varying between 0.2 and 1.7 s. The FPAs at most of the stations tend to be orthogonal to the major geological boundaries in the Western Himalaya. The average trend of the FPAs at each station indicates that the seismic anisotropy is primarily caused due to strain-induced deformation in the top ~200 km of the upper mantle as a result of the ongoing Indo-Eurasian collision. A contribution from the mantle flow in the direction of the Indian plate motion is possible. The mantle strain revealed in the present study may be due to a combination of basal shear resulting from plate motion and ductile flow along the collision front due to compression.

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Combined plate motion and density-driven flow in the asthenosphere beneath Saudi Arabia: Evidence from shear-wave splitting and seismic anisotropy

Geology ◽

10.1130/g22713.1 ◽

2006 ◽

Vol 34 (10) ◽

pp. 869 ◽

Cited By ~ 62

Author(s):

Samantha Hansen ◽

Susan Schwartz ◽

Abdullah Al-Amri ◽

Arthur Rodgers

Keyword(s):

Saudi Arabia ◽

Shear Wave ◽

Seismic Anisotropy ◽

Shear Wave Splitting ◽

Plate Motion ◽

Density Driven Flow ◽

Wave Splitting

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Seismic anisotropy and mantle flow constrained by shear wave splitting in central Myanmar

Journal of Geophysical Research Solid Earth ◽

10.1029/2021jb022144 ◽

2021 ◽

Author(s):

Enbo Fan ◽

Yumei He ◽

Yinshuang Ai ◽

Stephen S. Gao ◽

Kelly H. Liu ◽

...

Keyword(s):

Shear Wave ◽

Seismic Anisotropy ◽

Shear Wave Splitting ◽

Mantle Flow ◽

Wave Splitting

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Seismic anisotropy of the crust and upper mantle beneath western Tibet revealed by shear wave splitting measurements

Geophysical Journal International ◽

10.1093/gji/ggy448 ◽

2018 ◽

Vol 216 (1) ◽

pp. 535-544 ◽

Cited By ~ 4

Author(s):

Changhui Ju ◽

Junmeng Zhao ◽

Ning Huang ◽

Qiang Xu ◽

Hongbing Liu

Keyword(s):

Shear Wave ◽

Upper Mantle ◽

Seismic Anisotropy ◽

Shear Wave Splitting ◽

Crust And Upper Mantle ◽

Wave Splitting

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Measuring Crustal Seismic Anisotropy through Shear Wave Splitting

10.26686/wgtn.17151191 ◽

2021 ◽

Author(s):

◽

Kenny Graham

Keyword(s):

Numerical Simulation ◽

New Zealand ◽

Shear Wave ◽

Seismic Anisotropy ◽

Shear Wave Splitting ◽

Anisotropic Structure ◽

Crustal Anisotropy ◽

Physical Mechanisms ◽

Alpine Fault ◽

Wave Splitting

This thesis involves the study of crustal seismic anisotropy through shear wave splitting. For the past three decades, shear wave splitting (SWS) measurements from crustal earthquakes have been utilized as a technique to characterize seismic anisotropic structures and to infer in situ crustal properties such as the state of the stress and fracture geometry and density. However, the potential of this technique is yet to be realized in part because measurements on local earthquakes are often controlled and/or affected by physical mechanisms and processes which lead to variations in measurements and make interpretation difficult. Many studies have suggested a variety of physical mechanisms that control and/or affect SWS measurements, but few studies have quantitatively tested these suggestions. This thesis seeks to fill this gap by investigating what controls crustal shear-wave splitting (SWS) measurements using empirical and numerical simulation approaches, with the ultimate aim of improving SWS interpretation. For our empirical approach, we used two case studies to investigate what physical processes control seismic anisotropy in the crust at different scales and tectonic settings. In the numerical simulation test, we simulate the propagation of seismic waves in a variety of scenarios. We begin by measuring crustal anisotropy via SWS analysis around central New Zealand, where clusters of closely-spaced earthquakes have occurred. We used over 40,000 crustal earthquakes across 36 stations spanning close to 5.5 years between 2013 and 2018 to generate the largest catalog of high-quality SWS measurements (~102,000) around the Marlborough and Wellington region. The size of our SWS catalog allowed us to perform a detailed systematic analysis to investigate the processes that control crustal anisotropy and we also investigated the spatial and temporal variation of the anisotropic structure around the region. We observed a significant spatial variation of SWS measurements in Central New Zealand. We found that the crustal anisotropy around Central New Zealand is confined to the upper few kilometers of the crust, and is controlled by either one mechanism or a combination of more than one (such as structural, tectonic stresses, and gravitational stresses). The high correspondence between the orientation of the maximum horizontal compressive stress calculated from gravitational potential energy from topography and average fast polarization orientation around the Kaikōura region suggests that gravitationally induced stresses control the crustal anisotropy in the Kaikōura region. We suggest that examining the effect of gravitational stresses on crustal seismic anisotropy should not be neglected in future studies. We also observed no significant temporal changes in the state of anisotropy over the 5.5 year period despite the occurrence of significant seismicity. For the second empirical study, we characterized the anisotropic structure of a fault approaching failure (the Alpine Fault of New Zealand). We performed detailed SWS analysis on local earthquakes that were recorded on a dense array of 159 three-component seismometers with inter-station spacing about 30 m around the Whataroa Valley, New Zealand. The SWS analysis of data from this dense deployment enabled us to map the spatial characteristics of the anisotropic structure and also to investigate the mechanisms that control anisotropy in the Whataroa valley in the vicinity of the Alpine Fault. We observed that the orientation of the fast direction is parallel to the strike of the Alpine Fault trace and the orientations of the regional and borehole foliation planes. We also observed that there was no significant spatial variation of the anisotropic structure as we move across the Alpine Fault trace from the hanging wall to the footwall. We inferred that the geological structures, such as the Alpine Fault fabric and foliations within the valley, are the main mechanisms that control the anisotropic structure in the Whataroa valley. For our numerical simulation approach, we simulate waveforms propagating through an anisotropic media (using both 1-D and 3-D techniques). We simulate a variety of scenarios, to investigate how some of the suggested physical mechanisms affect SWS measurements. We considered (1) the effect on seismic waves caused by scatterers along the waves' propagation path, (2) the effect of the earthquake source mechanism, (3) the effect of incidence angle of the incoming shear wave. We observed that some of these mechanisms (such as the incidence angle of the incoming shear wave and scatterers) significantly affect SWS measurement while others such as earthquake source mechanisms have less effect on SWS measurements. We also observed that the effect of most of these physical mechanisms depends on the wavelength of the propagating shear wave relative to the size of the features. There is a significant effect on SWS measurements if the size of the physical mechanism (such as scatterers) is comparable to the wavelength of the incoming shear wave. With a larger wavelength, the wave treats the feature as a homogeneous medium.

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