Pierre Arroucau

Transdimensional inversion of receiver functions and surface wave dispersion

[1] We present a novel method for joint inversion of receiver functions and surface wave dispersion data, using a transdimensional Bayesian formulation. This class of algorithm treats the number of model parameters (e.g. number of layers) as an unknown in the problem. The dimension of the model space is variable and a Markov chain Monte Carlo (McMC) scheme is used to provide a parsimonious solution that fully quantifies the degree of knowledge one has about seismic structure (i.e constraints on the model, resolution, and trade-offs). The level of data noise (i.e. the covariance matrix of data errors) effectively controls the information recoverable from the data and here it naturally determines the complexity of the model (i.e. the number of model parameters). However, it is often difficult to quantify the data noise appropriately, particularly in the case of seismic waveform inversion where data errors are correlated. Here we address the issue of noise estimation using an extended Hierarchical Bayesian formulation, which allows both the variance and covariance of data noise to be treated as unknowns in the inversion. In this way it is possible to let the data infer the appropriate level of data fit. In the context of joint inversions, assessment of uncertainty for different data types becomes crucial in the evaluation of the misfit function. We show that the Hierarchical Bayes procedure is a powerful tool in this situation, because it is able to evaluate the level of information brought by different data types in the misfit, thus removing the arbitrary choice of weighting factors. After illustrating the method with synthetic tests, a real data application is shown where teleseismic receiver functions and ambient noise surface wave dispersion measurements from the WOMBAT array (South-East Australia) are jointly inverted to provide a probabilistic 1D model of shear-wave velocity beneath a given station.

Crustal velocity structure associated with the eastern Tennessee seismic zone: Vp and Vs images based upon local earthquake tomography

We present three-dimensional P and S wave velocity models for the active eastern Tennessee seismic zone (ETSZ) using arrival time data from more than 1000 local earthquakes. A nonlinear tomography method is used that involves sequential inversion for model and hypocenter parameters. We image several velocity anomalies that persist through most of the inversion volume. Some anomalies support the presence of known features such as an ancient rift zone in northern Tennessee. Other anomalies reveal the presence of basement features that can be correlated with regional gravity and magnetic anomalies. We image a narrow, NE-SW trending, steeply dipping zone of low velocities that extends to a depth of at least 24 km and is associated with the vertical projection of the prominent New York-Alabama magnetic lineament. The low-velocity zone may have an apparent dip to the SE at depths exceeding 15 km. The low-velocity zone is interpreted as a major basement fault juxtaposing Granite-Rhyolite basement to the NW from Grenville southern Appalachian basement to the SE. Relocated hypocenters align in near-vertical segments suggesting reactivation of a distributed zone of deformation associated with a major strike-slip fault. We suggest that the ETSZ represents reactivation of an ancient shear zone established during formation of the super continent Rodinia.