Tectonic earthquake swarms in the Northern Volcanic Zone, Iceland
Microseismicity offers an opportunity to image subsurface deformation at exceptionally high spatial and temporal resolution. This may be related to a diverse range of processes, including fore- and aftershocks to destructive earthquakes on large faults, magma movement at volcanoes, or the gradual ad...
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| Format: | Doctoral or Postdoctoral Thesis |
| Language: | English |
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University of Cambridge
2022
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| Online Access: | https://www.repository.cam.ac.uk/handle/1810/335065 https://doi.org/10.17863/CAM.82505 |
| Summary: | Microseismicity offers an opportunity to image subsurface deformation at exceptionally high spatial and temporal resolution. This may be related to a diverse range of processes, including fore- and aftershocks to destructive earthquakes on large faults, magma movement at volcanoes, or the gradual advance of glaciers. Microearthquakes at faults might also signal more exotic behaviour, including due to transient events such as fluid injections or pulses of aseismic fault creep. The study of small earthquakes has advanced significantly over the past decades, as seismology has entered the digital age. Denser networks, with larger numbers of more sensitive seismometers allow ever smaller seismic events to be detected and analysed. The study of larger numbers of earthquakes brings a raft of benefits, including more robust statistical analyses, higher temporal resolution, and the opportunity to achieve significantly greater spatial resolution by harnessing the power of relative relocation algorithms. However, the fundamental task has remained the challenge of extracting an earthquake catalogue from continuous waveform recordings. I present new software that offers a powerful, efficient, and highly automatable method to produce exceptionally complete and robust earthquake catalogues from continuous seismic data. Instead of reducing the information contained in waveforms to “picks” – discrete timestamps marking candidate phase arrival times – within QuakeMigrate the seismic data is transformed to continuous functions which are then combined across the network by migration. Retaining as much information as possible until the point of comparing the recordings from across the entire array allows phase arrivals at or below the signal-to-noise ratio to be successfully associated with events, improving both detection capability and location resolution. I use QuakeMigrate to detect and locate microseismicity in the Northern Volcanic Zone, Iceland, from 13 years of continuous seismic data recorded on a dense local network. ... |
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