V021-0014
Investigating the Causes of Unrest at Aluto Volcano, Central Main Ethiopian Rift, with Probabilistic Seismic Imaging
Abstract:
Here we address this current limitation for the seismic data by performing a fully nonlinearised joint inversion of local seismic P- and S-wave travel times, and surface wave dispersion data from empirical Green's functions, for the location of earthquakes and the velocity of the subsurface. The combination of data types helps reduce the range of permitted models. Investigation of the noise field between 2 Hz and 20 s reveals multiple sources and we observe a strong near-zero lag signal when cross-correlating pairs of recordings in some frequency bands.
We use a reversible-jump Markov chain Monte Carlo approach to incorporate prior information and, from our data, retrieve the posterior probability of earthquake parameters and seismic velocity in a Bayesian sense. This provides rigorous distributions of the covariance of the earthquake and velocity parameters. With these, we can test at an appropriate confidence level, amongst other things, whether the deep (>10 km) high-resistivity structure seen beneath Aluto in resistivity models is coincident with a low-seismic velocity body, such as would be expected for magma mush region where melt volumes are sufficiently low to preclude melt connectivity and keep resistivity high. Usefully, such an approach can also objectively tell us if the data do not give us sufficient information to distinguish between hypotheses, avoiding over-interpretation.