A Classification of Metamorphic Grains in
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  • journal_title:Journal of Sedimentary Research
  • Contributor:Eduardo Garzanti ; Giovanni Vezzoli
  • Publisher:SEPM Society for Sedimentary Geology
  • Date:2003-
  • Format:text/html
  • Language:en
  • Identifier:10.1306/012203730830
  • journal_abbrev:Journal of Sedimentary Research
  • issn:1527-1404
  • volume:73
  • issue:5
  • firstpage:830
  • section:Research Methods
摘要

An operational classification of metamorphic grains in sands and sandstones is proposed with the aim of enhancing data reproducibility among operators and the potential of high-resolution bulk petrography in provenance studies. For each of four protolith compositions (metapelite, metapsammite/metafelsite, metacarbonate, metabasite), six archetype grains displaying increasing degree of recrystallization and foliation development are illustrated. Such a classification grid is specifically devised as a subsidiary tool for point counting with the Gazzi-Dickinson method. Traditional QFR parameters can also be easily recalculated from the data set obtained, thus meeting all possible needs (Decker and Helmold 1985; Suttner and Basu 1985). An experiment shows that usage of visual-comparison standards effectively minimizes operator variation and allows retrieval of crucial information during point counting in a reproducible way. A petrogenetic grid is presented as a subsidiary tool for classifying grains that include index minerals and to help correlation with dense-mineral data. The "metamorphic index" (MI) is introduced as an estimator of average metamorphic grade of source rocks. Our classification, an extension of concepts used first in the study of arc-continent collision in Taiwan (Dorsey 1988) and successfully expanded to interpret the evolution of continent-continent collision in the Himalayas (Najman and Garzanti 2000; White et al. 2002), proves to be fruitful in provenance analysis of foreland-basin sediments shed from Alpine-type, thick-skinned collision orogens, particularly when integrated with dense-mineral, geochemical, and geochronological data.

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