Abstract
Combined analysis of seismic P and S velocity information provides
a reasonable and efficient basis for the petrologic interpretation
of seismic cross sections. In this paper, a methodology is presented
which allows extraction of prominent features related to well-defined
P velocities and Poisson's ratios from a tomographic velocity model
using a classification approach. We used first-arrival travel time
data from a near-vertical seismic experiment and independently determined
P and S velocities by forward and inverse modeling. Resolution and
uncertainties were estimated from inverting synthetic data. The classification
procedure was carried out in two subsequent steps. First, prominent
classes were identified in the parameter space spanned by Poisson's
ratios and P wave velocities. For this purpose, a probability density
function was calculated from the tomograms. A function measuring
the topography of the probability density was then determined, and
a histogram analysis was carried out to detect significant classes.
In the second step, the results from principal component analysis
for the identified classes were used to map their distribution along
the seismic profile. We applied the method to the Messum intrusive
complex of Namibia and identified three prominent classes. On the
basis of the integration of petrophysical data and comparison with
surface geology, we conclude that quartz-syenite composition dominates
the upper 800 m of the crust under the complex. Outside of the intrusion
the upper crust has properties corresponding to felsic metasediments
and granites which are abundant in the local basement. This material
shows strong depth-dependent changes of seismic properties which
are ascribed to decreasing porosity and fluid saturation with depth.
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