Finite-frequency sensitivity of seismic waves in three-dimensional fault zone models

Tuesday, 16 December 2014: 8:45 AM
Amir A Allam1, Yehuda Ben-Zion2 and Carl Tape1, (1)University of Alaska Fairbanks, Fairbanks, AK, United States, (2)University of Southern California, Los Angeles, CA, United States
We analyze the volumetric sensitivity of fault zone seismic head and trapped waves by constructing finite-frequency Fréchet kernels for these phases using idealized and tomographically-derived seismic velocity models of fault zones. We first validate numerical calculations by waveform comparisons with analytical results for two idealized fault zone models: a vertical bimaterial interface separating two solids of differing elastic properties, and a ‘vertical sandwich’ in which a vertical low velocity zone is surrounded on either side by higher velocity media. After establishing numerical accuracy up to 10 Hz, we construct models of the San Jacinto Fault Zone (SJFZ) using previous detailed tomographic results, including versions with explicit fault zone boundary interfaces. We compare numerical waveform calculations with observed data for the Southern California Seismic Network and the Anza seismic network. We construct P and S velocity sensitivity kernels for different seismic phases observed in the SJFZ and idealized models. In contrast to P body waves, which have little or no sensitivity to fault zone structure, the sensitivity kernels for head waves have sharp peaks with high values near the fault in the faster medium. Surface wave kernels show the broadest spatial distribution of sensitivity, while trapped wave kernels are extremely narrow with sensitivity focused entirely inside the low-velocity fault zone layer. Taken together, these phases contain complementary information about fault zone and regional velocity structure. These results indicate that adjoint tomography using high-frequency head and trapped waves kernels, combined with traditional body and surface wave kernels, can constrain fault zone structure across a larger range of scales than has previously been possible.