Analysis of tremor at the San Andreas Fault at Parkfield

Emergent phase arrivals, low amplitude waveforms, and variable event durations make detection and location of tectonic tremor a non-trivial task. In this work I employ a new method to identify tremor in large datasets using a semi-automated technique, which is comprised of an envelope cross-correlation and a Self-Organizing Map (SOM) algorithm to identify and classify event types. Furthermore, I present a new tremor localization method based on time-reversal imaging techniques.