Capabilities of 3-D wavelet transforms to detect plume-like structures from seismic tomography

Abstract

The wavelet transform methods have been applied to viewing 3-D seismic tomography by casting the transformed quantities into two proxy distributions, E-max, the maximum of the magnitude of the local spectra about a local point and the associated local wavenumber, k-max. Using a stochastic background noise, we test the capability of this procedure in picking up the coherent structures of upper-mantle plumes. Plumes with a Gaussian shape and a characteristic width up to 2250 km have been tested for various amounts of the signal-to-noise ratios (SNR). We have found that plumes can be picked out for SNR as low as 0.08 db and that the optimal plume width for detection is around 1500 km. For plume width ranging between 700 km and 2000 km, the SNR can be lower than 1 db. This length-scale falls within the range for plume-detection based on the signal-to-noise levels associated with the current global tomographical models.