Paper No. 1
Presentation Time: 8:15 AM
MINERALOGICAL AND TEXTURAL CHARACTERIZATION OF METAMORPHIC ROCKS USING AN AUTOMATED MINERALOGY APPROACH
KELLY, Nigel1, APPLEBY, Sarah K.
1 and MAHAN, Kevin
2, (1)Department of Geology and Geological Engineering, Colorado School of Mines, 1516 Illinois Street, Golden, CO 80401, (2)Geological Sciences, University of Colorado, Campus Box 399, 2200 Colorado AVE, Boulder, CO 80309, nkelly@mines.edu
Petrographic analysis of rocks at the micro-scale remains the most fundamental step in many larger-scale studies of geologic processes. Conclusions made about processes in the continental crust and mantle, from micro- to mega-scales, are predicated on robust characterization and interpretation of mineral assemblage, modal abundance and textural data in rocks. Once limited to that fundamental of all petrographic devices, the optical microscope, petrographic analysis through the now commonplace use of micro-beam techniques such as Backscatter Electron (BSE) imaging have dramatically increased our ability to gain detailed information of what are commonly complex textures at resolutions not obtainable by optical means. When integrated with other techniques such as Cathodoluminescence and Electron Backscatter Diffraction imaging, and X-ray (element) mapping, we are able to combine more and more spatially constrained mineralogical, textural and geochemical information than ever before to gain greater insight into mineral and rock scale processes.
Automated mineralogical analysis uses an SEM-based platform where BSE data are coupled with X-ray data collected by Energy Dispersive Spectrometers to quickly identify, at a single point, a mineral or material in thin section, polished rock or grain mount. The ability to collect such data rapidly allows areas of a given material to be “mapped” not only for mineral type, but to calculate modal abundances, precisely estimate grain size distributions and generate textural data with significantly less effort and beam time than traditional micro-beam instruments. While this technique still requires a solid mineralogical understanding by the user and does not replace the more traditional petrographic means, it presents a powerful method by which we can characterize rocks and therefore form a more solid basis from which to make petrologic interpretations, in particular when integrated with other techniques.
This paper will present several applications of automated mineralogy that demonstrate the utility of the technique in petrologic studies ranging from partial melting in crustal rocks to the location and characterization of dateable accessory minerals for in situ geochronology.