Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005. / This thesis describes techniques proposed for analysing images of borehole
cores. We address two problems: firstly, the automated stratigraphic classification
of cores based on texture and secondly, the location of thin chromitite
layers hidden in pyroxenite cores.
Texture features of different rock types are extracted using wavelets, the
theory of which provides an intuitive and powerful tool for this purpose. A
Bayesian classifier is trained and used to discriminate between different samples.
Thin, planar chromitite layers are located using a shortest path algorithm.
In order to estimate the physical orientation of any layer found, a sinusoidal
curve is fitted.
The proposed algorithms were implemented and tested on samples taken
from photographed cores. A high success rate was obtained in rock classification,
and thin planar layers were located and characterised.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/2045 |
Date | 03 1900 |
Creators | Van der Walt, Stefan Johann |
Contributors | Cloete, J. H., Herbst, B. M., University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. |
Publisher | Stellenbosch : University of Stellenbosch |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Thesis |
Format | 3775840 bytes, application/pdf |
Rights | University of Stellenbosch |
Page generated in 0.0014 seconds