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TitleQuantifying geological uncertainty in metamorphic phase equilibria modelling; a Monte Carlo assessment and implications for tectonic interpretations
AuthorPalin, R M; Weller, O M; Waters, D J; Dyck, B
SourceGeoscience Frontiers vol. 7, issue 4, 2016 p. 591-607, https://doi.org/10.1016/j.gsf.2015.08.005
LinksSuplementary Data - Données supplémetaires
Year2016
Alt SeriesEarth Sciences Sector, Contribution Series 2015273
PublisherElsevier
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf; html; xls
Subjectstectonics; igneous and metamorphic petrology; modelling; metamorphic petrology; metamorphism; tectonic interpretations; tectonic evolution; thermal history; petrography; phase equilibria; bulk composition; pressure-temperature conditions; garnet; cordierite; staurolite; kyanite; mica; porphyroblasts; metamorphic rocks; schists; x-ray fluorescence analyses; whole rock analyses; major element analyses; point-count analyses; pseudosection modelling; granofels
Illustrationsbar graphs; sketches; schematic diagrams; photomicrographs; profiles; tables; phase diagrams; ternary diagrams
ProgramBaffin Bedrock Mapping, GEM2: Geo-mapping for Energy and Minerals
AbstractPseudosection modelling is rapidly becoming an essential part of a petrologist's toolkit and often forms the basis of interpreting the tectonothermal evolution of a rock sample, outcrop, or geological region. Of the several factors that can affect the accuracy and precision of such calculated phase diagrams, “geological” uncertainty related to natural petrographic variation at the hand sample- and/or thin section-scale is rarely considered. Such uncertainty influences the sample's bulk composition, which is the primary control on its equilibrium phase relationships and thus the interpreted pressure-temperature (P-T) conditions of formation. Two case study examples?a garnet-cordierite granofels and a garnet-staurolite-kyanite schist?are used to compare the relative importance that geological uncertainty has on bulk compositions determined via (1) X-ray fluorescence (XRF) or (2) point counting techniques. We show that only minor mineralogical variation at the thin-section scale propagates through the phase equilibria modelling procedure and affects the absolute P-T conditions at which key assemblages are stable. Absolute displacements of equilibria can approach \'011 kbar for only a moderate degree of modal proportion uncertainty, thus being essentially similar to the magnitudes reported for analytical uncertainties in conventional thermobarometry. Bulk compositions determined from multiple thin sections of an heterogeneous garnet-staurolite-kyanite schist show a wide range in major-element oxides, owing to notable variation in mineral proportions. Pseudosections constructed for individual point count-derived bulks accurately reproduce this variability on a case-by-case basis, though averaged proportions do not correlate with those calculated at equivalent peak P-T conditions for a whole-rock XRF-derived bulk composition. The main discrepancies relate to varying proportions of matrix phases (primarily mica) relative to porphyroblasts (primarily staurolite and kyanite), indicating that point counting preserves small-scale petrographic features that are otherwise averaged out in XRF analysis of a larger sample. Careful consideration of the size of the equilibration volume, the constituents that comprise the effective bulk composition, and the best technique to employ for its determination based on rock type and petrographic character, offer the best chance to produce trustworthy data from pseudosection analysis.
Summary(Plain Language Summary, not published)
Phase equilibria modelling is a common technique that geologists use to determine the pressure-temperature (P?T) history that a rock sample has experienced. The technique involves forward modelling a sample's bulk composition to produce phase diagram 'maps', which illustrate how mineral assemblages change as a function of changing P?T conditions. One of the key steps in this process is determining the bulk composition of a sample. This paper analyses the different methods used to calculate a bulk composition, and how this affects the topology of the maps and consequent P?T estimates. The results document that different methods are suitable for different rock types, and provide the first case study that explores random 'geological' errors associated with bulk composition calculation.
GEOSCAN ID297131