scholarly journals Automatic measurement of shear wave splitting and applications to time varying anisotropy at Mount Ruapehu volcano, New Zealand

2010 ◽  
Vol 115 (B12) ◽  
Author(s):  
M. K. Savage ◽  
A. Wessel ◽  
N. A. Teanby ◽  
A. W. Hurst
Keyword(s):  
New Zealand ◽  
Shear Wave ◽  
Automatic Measurement ◽  
Shear Wave Splitting ◽  
Time Varying ◽  
Wave Splitting ◽  
Mount Ruapehu ◽  
Ruapehu Volcano

scholarly journals Automatic Shear Wave Splitting Measurements at Mt. Ruapehu Volcano, New Zealand

2021 ◽  
Author(s):  
◽  
Andreas Wessel
Keyword(s):  
New Zealand ◽  
Shear Wave ◽  
Automatic Measurement ◽  
Automatic Monitoring ◽  
Shear Wave Splitting ◽  
Measurement Tool ◽  
Data Set ◽  
The North ◽  
Wave Splitting ◽  
Ruapehu Volcano

<p>This thesis presents an automatic shear wave splitting measurement tool and the results from its application to data recorded in the vicinity of Mt. Ruapehu volcano on the North Island of New Zealand. The best methodology and parameters for routine automatic monitoring are determined and approximately 10,000 events are processed. About 50% of all S-phases lead to measurements of acceptable quality. Results obtained with this technique are reproducible and objective, but more scattered than results from manual measurements. The newly developed automatic measurement tool is used to measure shear wave splitting for previously analysed data and for new data recorded in 2003-2007. In contrast to previous studies at Mt. Ruapehu, we have a larger and continuous data set from numerous three-component seismic stations. No major temporal changes are found within the new data, but results vary for di erent station locations. I</p>

scholarly journals Automatic Shear Wave Splitting Measurements at Mt. Ruapehu Volcano, New Zealand

2021 ◽  
Author(s):  
◽  
Andreas Wessel
Keyword(s):  
New Zealand ◽  
Shear Wave ◽  
Automatic Measurement ◽  
Automatic Monitoring ◽  
Shear Wave Splitting ◽  
Measurement Tool ◽  
Data Set ◽  
The North ◽  
Wave Splitting ◽  
Ruapehu Volcano

<p>This thesis presents an automatic shear wave splitting measurement tool and the results from its application to data recorded in the vicinity of Mt. Ruapehu volcano on the North Island of New Zealand. The best methodology and parameters for routine automatic monitoring are determined and approximately 10,000 events are processed. About 50% of all S-phases lead to measurements of acceptable quality. Results obtained with this technique are reproducible and objective, but more scattered than results from manual measurements. The newly developed automatic measurement tool is used to measure shear wave splitting for previously analysed data and for new data recorded in 2003-2007. In contrast to previous studies at Mt. Ruapehu, we have a larger and continuous data set from numerous three-component seismic stations. No major temporal changes are found within the new data, but results vary for di erent station locations. I</p>

scholarly journals Measuring Crustal Seismic Anisotropy through Shear Wave Splitting

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

<p>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.</p>

scholarly journals Measuring Crustal Seismic Anisotropy through Shear Wave Splitting

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

<p>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.</p>

scholarly journals Modelling shear wave splitting observations from Wellington, New Zealand

2004 ◽  
Vol 157 (2) ◽  
pp. 853-864 ◽  
Author(s):  
Katrina Marson-Pidgeon ◽  
Martha K. Savage
Keyword(s):  
New Zealand ◽  
Shear Wave ◽  
Shear Wave Splitting ◽  
Wave Splitting

scholarly journals Crustal Cracks in Areas of Active  Deformation: Correlation of GPS and  Seismic Anisotropy

2021 ◽  
Author(s):  
◽  
Katharina Unglert
Keyword(s):  
New Zealand ◽  
Shear Wave ◽  
Seismic Anisotropy ◽  
Compressive Strain ◽  
Shear Wave Splitting ◽  
Slow Slip ◽  
Stress Changes ◽  
Wave Splitting ◽  
Aso Caldera ◽  
Strong Deformation

<p>Seismic anisotropy in the upper crust can be observed from shear-wave split- ting. It is closely related to crack distribution, orientation and density via the orientation of fast polarisation and the delay time between the two perpendic- ular components of the original shear-wave. Since stress variations can a ect crustal cracks, they should change shear-wave splitting. Another observable result of variations in stress can be deformation measured by GPS (Global Positioning System). Although there are as yet few publications linking these di erent methods, some have suggested an alignment of fast direction with maximum horizontal compressive stress and maximum horizontal compressive strain. We examine whether we can observe this or a di erent relation of seis- mic anisotropy to strain and stress changes in three di erent settings. We performed shear-wave splitting analyses of local earthquakes and baseline and strain calculations around Taupo caldera (New Zealand), Aso caldera (Japan), and around an area on the Raukumara peninsula (New Zealand) associated with slow slip on the Hikurangi subduction interface. Both anisotropy and deformation vary with time in all three regions, but the time variations do not strongly correlate with each other. We suggest that a strong deformation signal observed at Taupo caldera might have a regional, non-volcanic source, and small variations in shear-wave splitting cannot be linked to variations in GPS time series or baselines. At Aso caldera strong deformation seems to be directly related to volcanic activity. Seismic anisotropy also shows a change, but at a slightly di erent time than the GPS signal. On the Raukumara peninsula, the strong deformation associated with slow slip does not show up as a variation in seismic anisotropy, although variations in shear-wave splitting do exist in this area. Overall, we observe an alignment of fast direction with either maximum horizontal compressive strain or stress or both for a subset of time periods and stations. In addition, there is a contribution of structure to the observed anisotropy. We conclude that deformation and seismic anisotropy cannot always be linked in a straightforward way. Instead, shear-wave splitting may be connected to smaller scale processes than can be detected by the current densities of the GPS networks.</p>

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