Velocity and anisotropy structure of the Icelandic crust - An ambient seismic noise analysis

Measuring the travel times of seismic waves is one of the most important tools for uncovering Earth’s structure and dynamics. In recent years, the discovery that surface wave dispersion could be estimated from ambient noise has introduced new possibilities into the field of seismic imaging, such as performing passive source tomography in regions where it was not previously possible with a dense azimuthal ray path coverage. In this work, I leverage the new possibilities introduced by this method to investigate the crust in Iceland in a number of ways, including tomographic imaging as well as azimuthal and radial anisotropy analyses in both the lower and upper crust. Understanding accretion and deformation processes at mid-ocean ridges is crucial because they control the resulting oceanic crustal structure, which covers two-thirds of the Earth’s surface. Iceland, which is uplifted by a convective mantle plume and has an active spreading ridge system exposed above sea level, offers a unique opportunity for studying this phenomenon. I first use a dataset of Love and Rayleigh wave dispersion measurements with dense azimuthal coverage to constrain seismic anisotropy in the Icelandic crust. I show that seismic anisotropy in the lower crust is controlled by crystal preferred orientation, providing a direct observation of lower crustal flow. Furthermore, since shear is needed to align the crystals, our result reveals that crustal flow cannot be a simple translation of mass and requires internal deformation. This finding has important implications for how thick, hot oceanic crust, as found in volcanic rifted margins and near plume-ridge interactions, can accrete and deform. Despite the growing use of ambient noise in measuring crustal properties, extensive comparisons between ambient noise results and those obtained from local earthquakes remain elusive. To address this, I measure Love and Rayleigh group velocity using ambient noise recorded around Askja, a large active volcano in central Iceland, explore its velocity structure and anisotropy and compare my findings to those from local earthquake studies. I show that crack properties estimated using surface wave anisotropy strongly correlate with local shear wave splitting and outcrop mapping, indicating the method is highly effective for such analyses. Next, I show that VSV models derived from Rayleigh waves can be significantly faster than VS extracted from body waves, which has important implications for viii jointly exploiting these two classes of data. Furthermore, 3D VSV and VSH models constrained by the data through a two-step inversion procedure resolve a shallow slow anomaly consistent with a magma chamber predicted by geodetic studies, but not imaged by local earthquake body wave tomography. I then measure Love and Rayleigh phase velocities from ambient noise in Iceland in the period range 7 - 16 s from more than 3000 station pairs. This involves the development and use of an automatic method for extracting phase velocities from noise cross-correlation functions (NCF). The phase travel times are then inverted for phase velocity maps. I present the first Love phase velocity maps of Iceland and show that like Rayleigh phase velocities, Love phase velocities display slow anomalies along the rift zones with the lowest velocities in the neighbourhood large volcanic centres, which I attribute to the presence of partial melt.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2020

Author dc:creator

• Volk, Omry

Advisors dc:contributor.advisor

• Rawlinson, Nicholas
• White, Robert

• Seismology
• Ambient Noise
• Iceland
• Tectonics

Licence

• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/e6fee01e-3e70-4f3c-9547-dd7f331dbc90/download
• https://www.rioxx.net/licenses/all-rights-reserved/

Language dc:language

eng

Author Identifier

0000-0002-6977-291X

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/322158