IDENTIFYING CLAYS IN SEDIMENTARY SEQUENCES UTILIZING A NEW CLAY MIXTURE SPECTRAL LIBRARY DEVELOPED WITH DIFFUSE SPECTRAL REFLECTANCE

The purpose of this study is to demonstrate the versatility of active electromagnetic sensing techniques, specifically diffuse spectral reflectance (DSR) as a complementary methodology to XRD and XRF when studying clay minerals in stratigraphic sequences. The Analytical Spectral Device (ASD) Labspec Pro FR UV/VIS/NIR spectrometer provides a cost effective, portable, quick and easy, nondestructive means, to analyze clays either in the lab or in the field. To test the applicability of the method, we evaluated two data sets: (1) sediment from core MNK3, a slack water Pleistocene lake near St. Louis. Stratigraphic changes in clay mineralogy occur down core, (2) and the Ordovician Millbrig K-bentonite (samples from AL, GA, KY, TN, and VA), an altered tephra in which the changes occur laterally in a single horizon. To support the interpretation of the DSR data, we have employed the Labspec Pro FR to generate a spectral library, which includes four primary clays and clay mixtures, readily available for use as a research reference tool. This library consist of over 231 two variable mixtures in 5% increments, by weighted percents and is augmented with spectra from the USGS spectral library. Clay mineral standards were obtained from the Clay Mineral Repository and Wards Natural Science. The aim is to close the gap that currently exists for an expanded spectral library of clay mixtures and explore the DSR variability of clay mixtures. PCA (Principal Component Analysis) was used to correlate the spectral data of the library with the two MNK3 and Millbrig samples. Stepwise Linear Regression analysis was used with the composite library as an identification tool. By combining PCA analysis of unknowns with stepwise linear regression against our clay mixture library, we identify our components in an objective, quantifiable way. The model predictors from the analysis gave highly significant R-squared values for the extracted PCA assemblages in the range of 0.8 to .99 depending on component. DSR has already demonstrated its ability to verify clay mineral content variability in both data sets in agreement with XRD data and supported by elemental trends based on XRF and ICM-AES.