Looking at the Inside of the Earth with 3-D Wavelets: A Pair of New Glasses for Geoscientists

Abstract. Current seismic tomographical models produce databases with increasing size and higher spatial resolution. Consequently, direct visual inspection and interrogation of the seismic database are becoming more and more an arduous and time-consuming task. Recently, it has been shown that featur...

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Bibliographic Details
Main Authors: Stephen Y. Bergeron, David A. Yuen, Alain P. Vincent
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.63.5481
http://www.msi.umn.edu/general/Reports/rptfiles/UMSI99-185/UMSI_99-185.pdf
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Summary:Abstract. Current seismic tomographical models produce databases with increasing size and higher spatial resolution. Consequently, direct visual inspection and interrogation of the seismic database are becoming more and more an arduous and time-consuming task. Recently, it has been shown that feature extraction can be emphasized and simplified by the use local spectra extraction (LSE) obtained from Gaussian wavelet transform (Bergeron et al., 1999). For example, such a feature may be the subducting slab under Japan or a plume-like object beneath the transition zone under Iceland. A drawback of the LSE is that the physical space dimensionality is added by 1, thus increasing greatly the information content. Our approach is to assimilate and synthesize the set of local spectra by using two proxy quantities: the spatial distributions of the local maxima of the L2-norm, E-max, and the associated local wavenumber, k-max. We propose to test this new computer vision method with two types of noisy synthetic data in order to emphasize the basic strengths and features of this novel method. We show that even if the signal to noise ratio is very low (less than 1dB), the presence of a slab and a plume or columnar structure can be detected in the k-max spatial distribution. The E-max proxy detects background fluctuation modulated by the sharp peaks