Advanced Hydrocarbon Interpretation Using Modified Pixler Plots and Multivariate Statistics

James M. Fausnaugh

Recent drilling based on near surface hydrocarbon detection methods has led to the implementation of various statistical and interpretative approaches to test the validity of surface hydrocarbon anomalies. The techniques used are a combination of Factor Analysis, Discriminant Analysis, and a novel approach to the interpretation of Pixler Plots.

Factor Analysis and Discriminant Analysis are used to detect the structure of relationships between variables, classify variables, and to simplify the interpretation by reducing the number of variables. Variable classification is a function of hydrocarbon composition. The extraction of various compositional structures often shows the difference between productive and nonproductive hydrocarbon anomalies. The light hydrocarbons, methane through propene, often correlate very highly while the heavier hydrocarbons isobutane through pentane show a high correlation between each other, but a moderate correlation with the lighter ends.

Pixler plots show the relationship of methane to ethane, propane, butane, and pentane respectively. The location of the ratio values on the Pixler plot, determines whether these relationships, for any particular sample, may be representative of a producing or non-producing area or an oil bearing or gas bearing area. By determining the slope and intercept of the line drawn through the coordinates of these ratios for each sample, and plotting them in map view, productive areas versus non-productive areas can be defined.

AAPG Search and Discovery Article #91020©1995 AAPG Annual Convention, Houston, Texas, May 5-8, 1995