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The AAPG/Datapages Combined Publications Database

Journal of Sedimentary Research (SEPM)

Abstract


Journal of Sedimentary Research
Vol. 73 (2003), No. 1. (January), Pages 47-57

Composition and Discrimination of Sandstones: A Statistical Evaluation of Different Analytical Methods

Hilmar von Eynatten, Carles Barcelo-Vidal, Vera Pawlowsky-Glahn

ABSTRACT

The discriminative power of four analytical approaches to sandstone composition is evaluated with respect to the separation of different formations and source areas. The case study is Cretaceous synorogenic sandstones (litharenites) from the Eastern Alps of Europe, which belong to four different formations and are derived from two source areas. Methods evaluated are light-mineral analysis (petrographic framework composition), heavy-mineral analysis, major-element XRF analysis, and trace-element XRF analysis. The statistical parameters calculated (percentages of well-classified samples, Mahalanobis distance) applying the logratio approach suggest that light-mineral analysis has a significantly lower discriminative power than the other three methods. Taking into account the analytical expenditure for data acquisition, trace-element analysis appears to be the most efficient method for discrimination of at least the sandstone units examined. Although based on a single case study, these results are interpreted to have a more general meaning with respect to sandstone discrimination based on composition. Concerning sandstone provenance, trace-element analysis provides a quick tool to estimate the discriminative potential of a sample suite, i.e., the potential to discriminate between contrasting source areas. If a provenance model already exists and discriminate functions between contrasting source areas are calculated, trace-element analysis is considered to be most efficient in correctly assigning an unknown sample to its source area. These results cannot be extended to all kinds of sands and sandstones, but they cast serious doubt on the belief that petrographic point-count methods are the best approach to discriminate between sandstones.


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