| dc.description.abstract | Regional distributions of organic content are an important aid in developing basin
evolution and hydrocarbon generation models. An approach to evaluate hydrocarbon
source rocks using resistivity, sonic, density, neutron and natural gamma ray logs is
developed. Organic matter, as a constituent in sedimentary rocks, has a relatively
low density, slow velocity, and is high in hydrogen content. Source rocks generally
have low water content, and often exhibit abnormally high concentrations of uranium.
These effects combine to make an in-situ estimation of organic content plausible.
Evolution of kerogen to bitumen, oil, and gas systematically affects the above
properties and it is possible to obtain a qualitative assessment of the state of
maturation of a known source bed.
In this thesis logs and core data from wells in two separate oil provinces are
used to test the methods of predicting total organic carbon content from log data.
Two approaches are followed. The first method treats the organic matter as a rock
constituent and calculates the log responses as a function of organic content. Two
(rock and organic matter) and three (rock matrix, water and organic matter)
component models are tested. This approach suffers because of the uncertainties of
the physical properties of the organic matter. For each log type (I.e. sonic, gamma,
resistivity, ...) log values are correlated with the laboratory measured total organic
content. Bivariate regression helps to illustrate the efficacy of the models. In the
second method, multivariate equations based on linear combinations of individual
correlation coefficients are obtained. The importance cf combining several logs which
are organic content predictors is demonstrated. These equations can be used to
predict total organic carbon content using only log data, in different parts of an oil
province. | en_US |
