Investigation of the Structure of Geological Process through Multivariate Statistical Analysis—The Creation of a Coal

• Published in: Mathematical geosciences Vol. 40; no. 7; pp. 789 - 811
• Main Authors: Drew, Lawrence J., Grunsky, Eric C., Schuenemeyer, John H.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01.10.2008; Springer Nature B.V
• Subjects: Chemistry and Earth Sciences; Coal; Computer Science; Earth and Environmental Science; Earth Sciences; Geochemistry; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology; Multivariate analysis; Physics; Statistical analysis; Statistics for Engineering; Multivariate analysis; Coal geochemistry; Identification of a coal-forming process; Centered logratio (clr) transformation; Compositional data
• DOI: 10.1007/s11004-008-9176-2
• ISSN: 1874-8961

The purpose of this study was to capture the structure of a geological process within a multivariate statistical framework by using geological data generated by that process and, where applicable, by associated processes. It is important to the practitioners of statistical analysis in geology to determine the degree to which the geological process can be captured and explained by multivariate analysis by using sample data (for example, chemical analyses) taken from the geological entity created by that process. The process chosen for study here is the creation of a coal deposit. In this study, the data are chemical analyses expressed in weight percentage and parts per million, and therefore are subject to the affects of the constant sum phenomenon. The data array is the chemical composition of the whole coal. This restriction on the data imposed by the constant sum phenomenon was removed by using the centered logratio (clr) transformation. The use of scatter plots and principal component biplots applied to the raw and centered logratio (clr) transformed data arrays affects the interpretation and comprehension of the geological process of coalification.