A unified methodology for seismic waveform analysis and inversion

A central problem of seismology is the inversion of regional waveform data for models of earthquake sources and earth structure. In regions such as Southern California, preliminary 3D earth models are already available, and efficient numerical methods have been developed for solving the point-source forward problem. We describe a unified inversion procedure that utilizes these capabilities to improve 3D earth models and derive centroid moment tensor (CMT) or finite moment tensor (FMT) representations of earthquake ruptures. Our data are time- and frequency-localized measurements of the phase and amplitude anomalies relative to synthetic seismograms computed from reference seismic source and structure models. Our analysis on these phase and amplitude measurements shows that these preliminary 3D models provide substantially better fit to observed data than either laterally homogeneous or path-averaged 1D structure models that are commonly used in previous seismic studies for Southern California. And we found a small but statistically significant polarization anisotropy in the upper crust that might be associated with basin layering effect. Using the same type of phase and amplitude measurements, we resolved finite source properties for about 40 earthquakes in the Los Angeles basin area. Our results on a cluster of events in the Yorba Linda area show left-lateral faulting conjugate to the nearby right-lateral Whittier fault and are consistent with the "escaping-block" hypothesis about regional tectonics around Los Angeles basin. Our analysis on 16 events in a seismicity trend that extends southwest from Fotana to Puente Hills show right-lateral mechanism that is conjugate to the trend of the hypocenter distribution, suggesting a developing weak-zone that might be related to such "escaping" deformation. To set up the structural inverse problem, we computed 3D sensitivity kernels for our phase and amplitude measurements using the 3D SCEC CVM as the reference model and derived a preliminary 3D perturbation. Our results show that CVM is too slow on average and event slower in the basin area. To our knowledge, this is the first application of this "fully 3D" technique on a regional dataset.