5:15 PM - 6:30 PM
[SSS28-P06] Development of trans-dimensional waveform inversion to estimate 1D layered underground structure model
Keywords:Trans-dimensional waveform inversion, Estimation of 1D structure model, Reversible jump MCMC method
The geometry of layers is described by a variable number of Voronoi nuclei (e.g. Bodin et al. 2012). For simplification, errors of the observation equation are assumed to follow a Gaussian distribution and be independent from each other. Unknown parameters are the number of layers, thickness of each layer, Vs of each layer, and hyper-parameter which represents the scale factor of the errors. Vp and density of each layer are calculated from Vs by the empirical relations of Brocher (2005). The attenuation characteristics (Qp, Qs) are calculated from Vs following the procedures of Kawabe and Kamae (2008) and Koketsu et al. (2009). Synthetic waveforms are calculated using the discrete wavenumber method (Bouchon 1981) and the reflection/transmission matrix method (Kennett and Kerry 1979). In the trans-dimensional sampling of structure models, we use the parallel tempering algorithm (e.g. Sambridge 2013) to improve the efficiency of the probabilistic sampling and the search range of parameter space.
In this presentation, we will show the results of the applications of the newly developed approach to synthetics and real data to show the validation and usefulness.