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Memory efficient simulation of frequency dependent Q

Kyle B. Withers, Kim B. Olsen, & Steven M. Day

Published July 1, 2015, SCEC Contribution #6002

Memory-variable methods have been widely applied to approximate frequency-independent Q in numerical simulation of wave propagation. The frequency-independent model is often appropriate for frequencies up to about 1 Hz, but at higher frequencies is inconsistent with some regional studies of seismic attenuation. We apply the memory-variable approach to frequency-dependent Q models that are constant below, and power-law above, a chosen transition frequency. We present numerical results for the corresponding memory-variable relaxation times and weights, obtained by non-negative least squares fitting of the Q(f) function, for a range of exponent values; these times and weights can be scaled to arbitrary transition frequency and power-law prefactor, respectively. The resulting memory-variable formulation can be used with numerical wave-propagation solvers based on methods such as finite differences or spectral elements, and may be implemented in either conventional or coarse-grained form. In the coarse-grained approach, we fit ‘effective’ Q for low Q values (< 200) using a nonlinear inversion technique and use an interpolation formula to find the corresponding weighting coefficients for arbitrary Q. A 3D staggered-grid finite difference implementation closely approximates the frequency-wavenumber solution to both a half-space and layered model with a shallow dislocation source for Q as low as 20 over a bandwidth of two decades. We compare the effects of different power-law exponents using a finite-fault source model of the 2008 Mw 5.4 Chino Hills, CA, earthquake and find that Q(f) models generally better fit the strong motion data than constant Q models for frequencies above 1 Hz.

Citation
Withers, K. B., Olsen, K. B., & Day, S. M. (2015). Memory efficient simulation of frequency dependent Q. Bulletin of the Seismological Society of America, 105, 3129-3142.


Related Projects & Working Groups
CME, Ground-Motion Prediction