Time-reversal imaging techniques applied to tremor waveforms near Cholame, California to locate tectonic tremor

Frequently, the lack of distinctive phase arrivals makes locating tectonic tremor more challenging than locating earthquakes. Classic location algorithms based on travel times cannot be directly applied because impulsive phase arrivals are often difficult to recognize. Traditional location algorithms are often modified to use phase arrivals identified from stacks of recurring low-frequency events (LFEs) observed within tremor episodes, rather than single events. Stacking the LFE waveforms improves the signal-to-noise ratio for the otherwise non-distinct phase arrivals. In this study, we apply a different method to locate tectonic tremor: a modified time-reversal imaging approach that potentially exploits the information from the entire tremor waveform instead of phase arrivals from individual LFEs. Time reversal imaging uses the waveforms of a given seismic source recorded by multiple seismometers at discrete points on the surface and a 3D velocity model to rebroadcast the waveforms back into the medium to identify the seismic source location. In practice, the method works by reversing the seismograms recorded at each of the stations in time, and back-propagating them from the receiver location individually into the sub-surface as a new source time function. We use a staggered-grid, finite-difference code with 2.5 ms time steps and a grid node spacing of 50 m to compute the rebroadcast wavefield. We calculate the time-dependent curl field at each grid point of the model volume for each back-propagated seismogram. To locate the tremor, we assume that the source time function back-propagated from each individual station produces a similar curl field at the source position. We then cross-correlate the time dependent curl field functions and calculate a median cross-correlation coefficient at each grid point. The highest median cross-correlation coefficient in the model volume is expected to represent the source location. For our analysis, we use the velocity model of Thurber et al. (2006) interpolated to a grid spacing of 50 m. Such grid spacing corresponds to frequencies of up to 8 Hz, which is suitable to calculate the wave propagation of tremor. Our dataset contains continuous broadband data from 13 STS-2 seismometers deployed from May 2010 to July 2011 along the Cholame segment of the San Andreas Fault as well as data from the HRSN and PBO networks. Initial synthetic results from tests on a 2D plane using a line of 15 receivers suggest that we are able to recover accurate event locations to within 100 m horizontally and 300 m depth. We conduct additional synthetic tests to determine the influence of signal-to-noise ratio, number of stations used, and the uncertainty in the velocity model on the location result by adding noise to the seismograms and perturbations to the velocity model. Preliminary results show accurate show location results to within 400 m with a median signal-to-noise ratio of 3.5 and 5% perturbations in the velocity model. The next steps will entail performing the synthetic tests on the 3D velocity model, and applying the method to tremor waveforms. Furthermore, we will determine the spatial and temporal distribution of the source locations and compare our results to those by Sumy and others.