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Proceedings Paper

Wavelet analysis for characterizing spatial heterogeneity in the subsurface
Author(s): Bai-Lian Li
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Paper Abstract

Wavelet analysis is a newly developed technique for separating and sorting structures on different time scales at different times, and different spatial scales at different locations. Mathematically, it is related to Fourier spectral analysis. It has been used extensively for image and signal processing, including the processing of seismic and turbulence data in geophysics. Characterizing spatial heterogeneity in the subsurface is an important issue for construction of facilities for waste containment and management, prediction of transport of pollutants through geologic media and remediation of contaminated sites. Localization processes in the subsurface and multiscale effect in geologic sampling data have to be addressed in the site characterization. Current methods can not solve these problems, however. The potential exists for using wavelet analysis as the multiscale spatial heterogeneity analysis method for characterizing detailed geologic structures. In particular, wavelet analysis overcomes significant limitations in standard geostatistics. We first present these limitations, then demonstrate how wavelet analysis overcomes them. We conclude with two demonstrations of geologic data analyses (the spatial variability of permeability in the alluvial fan deposits in DOE Nevada Test Site Pit 3. and cone penetrometer data interpretation) using wavelet analysis, compared to current geostatistical approaches.

Paper Details

Date Published: 1 September 1995
PDF: 11 pages
Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995); doi: 10.1117/12.217626
Show Author Affiliations
Bai-Lian Li, Texas A&M Univ. (United States)

Published in SPIE Proceedings Vol. 2569:
Wavelet Applications in Signal and Image Processing III
Andrew F. Laine; Michael A. Unser, Editor(s)

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