Abstract
We present a skeletonized inversion method that inverts surface-wave data for the Q(s) quality factor. Similar to the inversion of dispersion curves for the S-wave velocity model, the complicated surface-wave arrivals are skeletonized as simpler data, namely the amplitude spectra of the windowed Rayleigh-wave arrivals. The optimal Q(s) model is the one that minimizes the difference in the peak frequencies of the predicted and observed Rayleigh wave arrivals using a gradient-basedwave-equation optimizationmethod. Solutions to the viscoelasticwaveequation are used to compute the predicted Rayleigh-wave arrivals and the misfit gradient at every iteration. This procedure, denoted as wave-equation Q(s) inversion WQ(s)), does not require the assumption of a layered model and tends to have fast and robust convergence compared to full waveform inversion FWI). Numerical examples with synthetic and field data demonstrate that theWQ(s) method can accurately invert for a smoothed approximation to the subsurface Q(s) distribution as long as the V-s model is known with sufficient accuracy.