| Summary: | It is known that the static and dynamic behavior of
fluids in porous media depends to a large measure on porousmedia
geometry. In the past,. the ability to characterize
this geometry has been restricted to such average properties
as porosity and permeability. However, in recent years
attempts have been made to achieve a more precise charac-
terization based upon the fact that porous media is
statistically composed. In this thesis techniques from statistical 'communi-'
cation theory are adapted as possible methods for accomplish'
ing this classification process. In simplest form, a
dichotamous function is defined by passing a. line through a
porous medium, the function having one value when the' line
is in solid matrix, and another value when the line passes
through pore space. The function is then analyzed using
(1) Classical Fourier series harmonic analysis, and (2)
determination of the autocovariance estimate and power
spectrum. Comparisons are made between seyeral functions created from the same medium, and with functions created
from other media.
The results indicate that the autocovariance estimate *
and the power spectrum, as characterizing functions, can discriminate between different media. This success suggests
many more paths of investigation, possibly leading to the
complete characterization of porous media through statistical
analysis.
|
|---|
