Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/3979
Authors: Quarta, T.* 
Fedi, M.* 
De Santis, A.* 
Title: Source ambiguity from an estimation of the scaling exponent of potential field power spectra
Journal: Geophysical Journal International 
Series/Report no.: 2 / 140 (2000)
Publisher: Blackwell Science Ltd
Issue Date: 2000
Keywords: fractals
potential field
spectral analysis
Subject Classification04. Solid Earth::04.02. Exploration geophysics::04.02.04. Magnetic and electrical methods 
05. General::05.01. Computational geophysics::05.01.03. Inverse methods 
05. General::05.05. Mathematical geophysics::05.05.99. General or miscellaneous 
Abstract: An analysis of the field scaling power spectrum yields useful information about the source distribution, but it is uncertain whether deterministic, random, fractal or mixed approaches have to be used for the interpretation. To this end, the scaling properties of potential field spectra are analysed for a number of different source models of geological interest. Besides the models of Naidu (purely random sources) and Spector and Grant (gross block statistical ensembles) we consider other types of density and magnetization distributions with spectral exponents in the fractal range, such as a single homogeneous body with a random white source distribution. Spectral slopes in the fractal range are obtained. We also study the effects of important natural sources, such as salt domes and sedimentary basins, representing them with simple Gaussians or combinations of Gaussian signals. The same spectral slopes as for gravity signals generated by 3-D fractal source distributions are found for them. Hence the power law decay of the field is not a characteristic only of fractal source models. If a 3-D fractal source distribution is assumed a priori, a way of verifying the goodness of the model is to examine the whitened field at source level. The probability that the whitened field derives from a random white population is estimated for synthetic and real anomalies by applying the usual statistical tests.
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