AGU 2020: Zooming in on crystal mush | Scientific Talk
Channel: Michele Paulatto
Date: 2020-12-17

This is the recording of my presentation at the AGU Fall meeting 2020.
https://agu.confex.com/agu/fm20/meetingapp.cgi/Paper/783725

I present some early result from a study of the microscopic geometry of melt networks beneath active volcanoes. Understanding how the microgeometry affects the sound speed will help us make better use of field geophysical data and constrain the amount of magma stored in the magma reservoir. The work was funded be UKRI.

The code used is available from github:
https://github.com/acseai1419/Crius

Abstract
One of the most important observations supporting the mush paradigm is the lack of field seismological evidence for large molten magma chambers, with most seismological data instead being consistent with low melt fractions. The evidence is however not conclusive. Despite improvements in data quality and seismic techniques, imaging and quantifying in situ melt in the subsurface remains a challenging task. Melt fraction estimates suffer from extremely large uncertainties because of two limitations: inherent limits to resolution of seismic tomography and trade-offs in the constitutive relationships that tie melt fractions to seismic properties. Here we focus on the second limitation which is the result of the strong dependence of elastic properties on the microgeometry of the melt. Most published melt estimates rely on assuming that the melt pore space can be represented by simple geometrical shapes with a given aspect ratio. Since the aspect ratio is unknown and has to be guessed based on what petrological information is available, only a wide range of melt fractions can be determined. We tackle this limitation by developing a method for calculating the elastic properties of partially molten rocks starting from the microstructure determined by X-ray CT scanning. The microgeometry of the mush can be inferred from the study of glomerocrysts: crystal mush inclusions with quenched interstitial melt that are carried to the surface by erupted lava. After the sample is digitized, the average elastic properties are determined by numerical homogenisation which consists of numerically simulating the deformation of the sample under load. We developed a finite element solver of elastic deformation and applied it to CT-scan imagery of a basalt sample and a plutonic nodule. The results are compared to an open-source FFT-based homogenisation code and to a semi analytical approach that assumes ellipsoidal inclusions. This approach will allow rigorous testing of the Mush paradigm.