Search results for " earthquake tomography"
showing 3 items of 3 documents
Geophysical investigations along the Tyrrhenian shore of Calabria
2016
The Tyrrhenian Sea is a widely investigated basin developed in the Mediterranean area within the frame of Europe- Africa convergence and Ionian plate subduction process (Faccenna et al., 2014; Orecchio et al., 2014 and references therein). Since the Late Miocene, extension within the Tyrrhenian Sea was associated with coeval shortening in the Apennines-Maghrebide orogen and progressive southeastward rollback of the Ionian subducting plate. In this framework both extension and widespread volcanism well represented by the Vavilov and Marsili basins and the Aeolian volcanic arc, are typical features of the Tyrrhenian Sea region. Several authors (De Ritis et al., 2010; Loreto et al., 2015 and r…
Local earthquake tomography in the Southern Tyrrhenian region of Italy: Geophysical and petrological inferences on subducting litosphere
2009
We obtained a high-resolution seismic tomography of the Ionian lithosphere subduction using a new approach based on: (a) the Double-Difference technique for inversions and (b) the statistical post-processing of a great number of preliminary models (Weighted Average Model, WAM method); the latter was used to increase reliability and resolution. In the tomographic model, the high-velocity portion of the steeply dipping Ionian slab is well imaged, as is an underlying low-Vp (≈7.0 km/s) aseismic region. We propose that the low-velocity region can be assigned to a partially hydrated (serpentinized) mantle of the subducting Ionian slab, which progressively dehydrates with depth in dense high-pres…
Method to find the Minimum 1D Linear Gradient Model for Seismic Tomography
2016
The changes in the state of a geophysical medium before a strong earthquake can be found by studying of 3D seismic velocity images constructed for consecutive time windows. A preliminary step is to see changes with time in a minimum 1D model. In this paper we develop a method that finds the parameters of the minimum linear gradient model by applying a two-dimensional Taylor series of the observed data for the seismic ray and by performing least-square minimization for all seismic rays. This allows us to obtain the mean value of the discrete observed variable, close to zero value.