V31E-4801:
Predicting Equilibrium Mineral Assemblages in Contact Metamorphism By Integrating Thermodynamic and Numerical Models of Magma Chamber Cooling

Wednesday, 17 December 2014
Madison Douglas, Massachusetts Institute of Technology, Cambridge, MA, United States, Antonio Álvarez-Valero, Universidad de Salamanca, Department of Geology, Salamanca, Spain and Adelina Geyer, Consejo Superior de Investigaciones Científicas, Institut de Ciéncies de la Terra Jaume Almera, Barcelona, Spain
Abstract:
Extensive field studies indicate that exposed crustal-level magma chambers generate contact metamorphic aureoles in a variety of widths, from a few centimeters to upwards of a kilometer. To examine the large variation in metamorphic signatures, we modeled an instantaneously emplaced magma chamber at various depths in dry, compositionally representative carbonate and silicic crusts. The chamber contained magmas of rhyolitic, andesitic, dacitic, and basaltic composition, and cooling was modeled in prolate, spherical, and sill-like geometries. This combination created a time series of crustal temperature (T) and pressure (P) conditions driven by conductive cooling of the magma chamber. The spatial P-T relations were overlain with representative metapelitic and calcareous P-T pseudosections. Our results indicate that magma chambers will exhibit thinner aureoles with increasing depth of emplacement, due to the higher initial crustal temperature from the geothermal gradient. In addition, sill-like and prolate magma chambers exhibit significant variation in aureole thickness, with contacts on their outermost ends generating thin aureoles while contacts closer to their centers generate very thick aureoles. These results indicate that magma intrusion geometry plays a dominant role in controlling the local impacts of contact metamorphism. While future models will investigate the more complex thermodynamic effects of hydrated crusts, current results demonstrate that the combination of relatively simple geothermal models with petrologic datasets can generate predictions for the maximum metamorphic grade and geometry of magma chamber aureoles.