Source Rock Characterization Using Multivariate Analysis Of Log Data

Regional distribution of organic content and thermal maturity is an important aid in developing basin evolution and hydrocarbon generation models. We describe an approach to evaluate hydrocarbon source rocks using resistivity, sonic, density, neutron and natural gamma ray logs. 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 study we used logs and core data from wells in two separate oil provinces to test the methods of predicting total organic carbon content from log data. We followed two approaches. 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. The second method is based on single- and multi-variate regression analysis. For each log type (i. e. sonic, gamma, resistivity,…) log values are correlated with the laboratory measured total organic content. An equation based on linear combinations of individual correlation coefficients is obtained. This equation can be used to predict total organic carbon content using only log data, in different parts of an oil province.