Self-Organizing Maps for identification of zeolitic diagenesis patterns in closed hydrologic systems on the Earth and its implications for Mars

Abstract

We have conducted a survey of zeolite occurrences in saline-alkaline paleolake deposits on Earth to identify the most prominent zeolite alteration patterns and to characterize the most common authigenic minerals and their paragenetic relationships. We collected the bulk mineral assemblages (from previous and our studies) as identified by X-ray diffraction from zeolitic tuff beds and associated sedimentary beds from thirteen paleolake deposits from the USA, Mexico, Greece, and Tanzania. We applied the Kohonen Self-Organizing Maps (SOM) to look for interesting patterns in the tuff bed mineral assemblages without prescribing any specific interpretation, and for information reduction and classification. Decision Tree (DT) method was applied to characterize these clusters. We were able to define clear class boundaries between fresh glass, non-analcime zeolites, analcime, and K feldspar. The non-analcime zeolites were further grouped into several classes based on mineral type. We also discuss the potential implications for Mars, showing that the mineral assemblages of diagenetic facies identified by SOM and DT can be used to test or validate the orbital, in situ, or modeling results, while the trained SOM provides a robust generalized ability to classify the new mineral assemblage data into the most common diagenetic facies identified in saline-alkaline paleoenvironments that contain zeolites. The study concludes that generalizing the complex geochemical behaviors using unsupervised statistical learning methods can help to identify the most prominent geochemical behaviors.