Statistics – Computation
Scientific paper
May 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011geoji.185..845b&link_type=abstract
Geophysical Journal International, Volume 185, Issue 2, pp. 845-870.
Statistics
Computation
2
Body Waves, Surface Waves And Free Oscillations, Seismic Tomography, Computational Seismology, Wave Propagation
Scientific paper
Resolution in seismic tomography intimately depends on data coverage, with different parts of seismograms sensitive to different parts of Earth's structure. In classical seismic tomography, the usable amount of data is often restricted because of approximations to the wave equation. 3-D numerical simulations of wave propagation provide new opportunities for increasing the amount of usable data in seismograms by choosing appropriate misfit functions which have direct control on Fréchet derivatives. We propose new misfit functions for full waveform tomography based on instantaneous phase differences and envelope ratios between observed and synthetic seismograms. The aim is to extract as much information as possible from a single seismogram. Using the properties of the Hilbert transform, we separate phase and amplitude information in the time domain. To gain insight in the advantages and disadvantages of chosen misfit functions, we make qualitative comparisons of the corresponding finite-frequency adjoint sensitivity kernels with those from commonly used misfit functions based on cross-correlation traveltime, amplitude and waveform differences. The major advantages of our misfit functions are: (1) working in the Hilbert domain reduces non-linear behaviour of waveforms due to interaction of phase and amplitude information, and (2) we show with noise-free synthetic seismograms that it is possible to use a complete seismogram without losing information from low-amplitude phases. Complementary to instantaneous phase measurements, envelope measurements provide a way of using amplitude information of waveforms, which may also easily be extended to constrain anelastic properties. The properties of the kernels allow us to simplify the tomography problem by separating elastic and anelastic inversions. First indications are that the kernels remain well behaved in the presence of noise.
Bozdağ Ebru
Trampert Jeannot
Tromp Jeroen
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