Discriminating Between Spatial and Temporal Variations in Seismic Anisotropy at Active Volcanoes

10.26686/wgtn.16992547 ◽

2021 ◽

Author(s):

◽

Jessica Helen Johnson

Keyword(s):

Shear Wave ◽

Seismic Anisotropy ◽

Shear Wave Splitting ◽

Temporal Variations ◽

Temporal Changes ◽

Stable Region ◽

Strong Anisotropy ◽

Wave Splitting ◽

Okmok Volcano ◽

Active Volcanoes

<p>This thesis addresses the measurement and interpretation of seismic anisotropy around active volcanoes via shear wave splitting analysis. An overpressured magma reservoir will exert a stress on the surrounding country rock that may or may not be manifest as observable strain. Shear wave splitting analysis can be a useful indicator of stress in the crust and hence, the pressure induced by magma movement. Changes in shear wave splitting have already been observed at Mt. Ruapehu following eruptions in 1995/1996 and are inferred to be caused by changes in local stress in response to magma pressure. One of the main problems with the interpretation of temporal changes in shear wave splitting is the possibility of spatial variations being sampled along differing raypaths and being interpreted as temporal changes. Using a dense observational network and an automated shear wave splitting analysis, we examine local earthquakes occurring in 2008 within 100 km of Mt. Ruapehu. We note a strong azimuthal dependence of the fast direction of anisotropy (phi) and so introduce a spatial averaging technique and a two-dimensional tomography of recorded delay times (dt), to observe the spatial variation in more detail. Using this new method of mapping shear wave splitting parameters, we have created a benchmark of spatial variations in shear wave anisotropy around Mt. Ruapehu, against which future temporal changes may be measured. The observed anisotropy is used to define regions in which phi agrees with stress estimations from focal mechanism inversions, suggesting stress-induced anisotropy, and those in which phi aligns with structural features such as fault strikes, suggesting structural anisotropy. Data from past deployments of three-component seismometers have been analysed in the same way as those recorded during the 2008 experiment and the results compared. We identify a stable region of strong anisotropy, interpreted to be caused by schistose mineral alignment, and a transient region of strong anisotropy centred on the volcano during the major magmatic eruption of 1995. We also introduce a method of analysing temporal variations in seismic anisotropy at active volcanoes by using tight clusters of earthquakes and highly correlated multiplets. At Mt. Ruapehu, changes in shear wave splitting parameters associated with the 2006 and 2007 phreatic eruptions are detected using a cluster of earthquakes to the west of the volcano. Similar analyses using another cluster and multiplets from the stable region of strong anisotropy do not reveal temporal changes, although examination of the waveform codas of the repeating earthquakes reveals systematic changes that we interpret as being caused by seismic scatterers associated with the 2006 and 2007 eruptions. These scatterers appear to contaminate the shear wave coda and so inhibit the detection of any subtle changes in shear wave splitting parameters. Finally, we apply some of these methods to data from the 2008 eruption of Okmok volcano, Alaska. Shear wave splitting analysis at Okmok reveals a change in anisotropy associated with the 2008 eruption. This change however, is attributed to a change in dominant hypocentre location. Multiplet analysis at Okmok volcano reveals a similar scatterer contamination of the shear wave arrival. This spurious phase is interpreted to be an S to P conversion from interaction with the magma reservoir.</p>

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Upper crust seismic anisotropy study and temporal variations of shear-wave splitting parameters in the western Gulf of Corinth (Greece) during 2013

Physics of The Earth and Planetary Interiors ◽

10.1016/j.pepi.2017.06.006 ◽

2017 ◽

Vol 269 ◽

pp. 148-164 ◽

Cited By ~ 15

Author(s):

George Kaviris ◽

Ioannis Spingos ◽

Vasileios Kapetanidis ◽

Panayotis Papadimitriou ◽

Nicholas Voulgaris ◽

...

Keyword(s):

Shear Wave ◽

Seismic Anisotropy ◽

Shear Wave Splitting ◽

Temporal Variations ◽

Upper Crust ◽

Gulf Of Corinth ◽

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

<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>

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