Bayesian Ambient-Noise Inversion

Invited paper

Stan Dosso

University of Victoria

Tuesday 2 june, 2015, 15:40 - 16:00

0.8 Rome (118)

While ambient noise in the environment has generally been considered detrimental to traditional controlled-source ocean acoustic or seismic inversions for geophysical profiles, in recent years it has been recognized that noise itself can provide an extremely useful passive source for geoacoustic/seismic remote sensing. Potential advantages to ambient-noise inversion over active acoustic and direct (coring) methods include simpler instrumentation and deployment procedures, the ability to carry out unobtrusive surveys or long-term/large-area measurements with low cost and power requirements, and reduced environmental impact (e.g., minimal disruption to marine mammals). This talk presents several approaches to estimate seabed and terrestrial geophysical profiles based on ambient-noise inversion. These approaches include estimating seabed reflection-coefficient data from beamformed ambient noise due to wind-blown sea-surface waves, estimating seabed Scholte-wave dispersion data from ambient-noise measurements at seafloor hydrophones, and estimating Rayleigh-wave dispersion data on land using seismometer arrays at both small scales (10s of metres penetration depth for site assessment of earthquake hazards) and large scales (10s of kilometres depth for geologic/tectonic crustal mapping). In all cases nonlinear Bayesian (probabilistic) inference methods are applied in inversion to quantify the information content of the ambient-noise data to resolve geophysical profile structure and provide rigorous uncertainty estimates. An important component of this involves model selection methods to determine appropriate geophysical model parameterizations consistent with the resolving power of the data, with both the Bayesian information criterion and trans-dimensional sampling considered for various ambient-noise data sets.

ICS file for iCal / Outlook

[ Close ]