Journal of Mineralogical and Petrological Sciences
Online ISSN : 1349-3825
Print ISSN : 1345-6296
ISSN-L : 1345-6296
ORIGINAL ARTICLES
Bayesian probabilistic reconstruction of metamorphic PT paths using inclusion geothermobarometry
Tatsu KUWATANIKenji NAGATAKenta YOSHIDAMasato OKADAMitsuhiro TORIUMI
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2018 Volume 113 Issue 2 Pages 82-95

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Abstract

Geothermometry and geobarometry are used to study the equilibration of mineral inclusions and their zoned host minerals, which provide information on the PT conditions of inclusions at the time of their entrapment. However, reconstructing detailed PT paths remains difficult, owing to the sparsity of inclusions suitable for geothermometry and geobarometry. We developed a stochastic inversion method for reconstructing precise PT paths from chemically zoned structures and inclusions using the Markov random field (MRF) model, a type of Bayesian stochastic method often used in image restoration. As baseline information for PT path inversion, we introduce the concepts of pressure and temperature continuity during mineral growth into the MRF model. To evaluate the proposed model, it was applied to a PT inversion problem using the garnet–biotite geothermometer and the garnet–Al2SiO5–plagioclase–quartz geobarometer for mineral compositions from published datasets of host garnets and mineral inclusions in pelitic schist. Our method successfully reconstructed the PT path, even after removing a large part of the inclusion dataset. In addition, we found that by using a probability distribution of the most probable PT path, rather than a single solution, an objective discussion of the validity of the thermodynamic analysis is possible.

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© 2018 Japan Association of Mineralogical Sciences
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