X-ray computer tomography in clastic sedimentology

Abstract

Depositional environments composed of diverse sedimentary fades that represent the variability of
different physical, chemical and biological conditions which generate characteristic textures and fabrics
of clastic sedimentary rocks. X-ray attenuation of clastic sedimentary rocks generally depends on bulk
density, effective atomic number, fluid content, and the chemical composition of grains, cement and fluid content if present. Grain size is one of the most important characteristics of texture which affects bulk
density and consequently X-ray attenuation. The resolution of medical CT is suitable for detecting the
changes in X-ray attenuation which originate in grain size alteration above 0.1 mm. Numerical
identification of clastic sedimentary rocks, based on the observation that every type of texture could be
represented by different intervals of Hounsfield Units (HUs), takes age and depositional history into
consideration (even though some overlaps might occur). To avoid overlapping, an expected value should
be used if the distribution of data set is normal; if it is not the case a median or mean estimated by a
'Maximum-likelihood' method is recommended. Autocorrelation or rather a planar correlogram is
suitable for analyzing planar continuity in three-dimensions. The functional relationship between the
semivariogram (of at least the second order stationary regionalized variable) and its planar
autocorrelation allow the autocorrelogram surface to be used as a spatial continuity of the original data.
Thus the planar autocorrelogram gives the complete geostatistical system of the measured data. The
Laplacian operator is a mathematical tool used for determining the net recharge and discharge volume
for a physical quantity at a given point. Grid contours generated with the operator coincide with the
structural and heterogeneity characteristics of clastic sedimentary rocks and thus the method is suitable
for to indicating potential static flow surfaces or paths. Adoption of this method in coreflood experiments
improves — on a micro scale — the comprehension and predictability of fluid motions in reservoir beds.
This paper has two main goals: first, is to show that basic clastic sediments and sedimentary rocks are
numerically identifiable and clearly distinguishable from each other on the basis of CT derived data
analysis. The second goal to demonstrate that grid contours generated with the Laplacian operator
coincide with the structural characteristics and inner heterogeneity of sedimentary rocks; and the
method is suitable for indicating the potential flow surfaces or paths of clastic sedimentary rocks within
the range of resolution of medical CT.