Anisotropy from full waveform inversion of multicomponent seismic data using a hybrid optimization method

Abstract

ABSTRACTSeismic waveforms contain valuable information about the media, but the waveform inversion is a non‐linear problem. We present a waveform inversion method that combines a local optimization method with a genetic algorithm to determine the anisotropic parameters of a horizontally stratified medium. Synthetic seismograms for a horizontally stratified anisotropic medium are calculated using the reflectivity technique. In the initial stage of the inversion, the global space‐sampling properties of the genetic algorithm are used to direct the search to the region close to the global solution. This solution is then further improved using a conjugate‐gradient method. The numerical experiments performed with noisy synthetic data show that our hybrid optimization method satisfactorily reconstructs the anisotropic parameters at a reasonable computing cost while the range of slowness is adequate. We found that (i) for small‐angle data neither single‐ nor multiple‐component data are sufficient to determine the anisotropic parameters uniquely; (ii) for medium‐angle data the multiple‐component data are sufficient to determine the anisotropic parameters exactly whereas the single‐component data are not sufficient; and (iii) for wide‐angle data, either single‐ or multiple‐component data are sufficient to determine the anisotropic parameters accurately.