Using Forward Modeling of Geophysical Fields to Link Magma Dynamics Modeling to Observations

Abstract:

The Laguna del Maule volcanic field in Chile has been a continuously active rhyolitic field since the last deglaciation (Hildreth et al., 2010). Its size, silicic compositions, and current high deformation rate have attracted the attention of the volcanological community. Large silicic magmatic centers assemble over many time and length scales and exchange mass and energy with the crust. These systems can be simulated using multiscale numerical models, but it can be challenging to compare the results of simulations in a detailed way with geological and geophysical observations.

Investigating the full 3D structure of a magmatic system is difficult, but the presence of melt, crystals, and various phase equilibria modify the density and resistivity structure of the crust, which in turn impart changes to the local gravitational and geoelectromagnetic fields. These fields can be measured at the surface and used to infer conditions at depth. Conversely, if the conditions at depth are known (such as through simulation), these conditions can be used to estimate the surface fields.

We forward model the surficial geophysical fields, namely gravity and magnetotellurics, of simulated Laguna del Maule systems over a range of magmatic fluxes consistent with a range of observations. These numerous simulations are full 3D multiphase models of the evolution and long-term history of magma in the crust, including melt residence and spatio-temporal relationship of melt in the crust (Dufek et al., this conference). From the final state of these simulations, the physical parameters (density, resistivity, etc.) of 3D blocks including the magma bodies and surrounding crust are calculated and then transformed into gravimetric and magnetotelluric signals at the simulation surface, which is coincident with the ground surface. These modeled surface signals are then compared to survey maps of gravity anomaly and electrical resistivity for Laguna del Maule (Singer et al., 2014; Miller et al., 2017).