ASEG FedEx - talk by Constanza Manassero: Including 3D Magnetotelluric Data into Joint Probabilistic Inversions for Imaging the Deep Earth

Date: 27/09/2022

Time: 1600 (Canberra)

Speaker: Constanza Manassero

Title: Including 3D Magnetotelluric Data into Joint Probabilistic Inversions for Imaging the Deep Earth

Registration: https://us02web.zoom.us/webinar/register/WN_h0re9idHQteBaeln9u3-eg

Abstract

Multi-observable inversions are gaining popularity for imaging the structure of the lithosphere (Afonso et al., 2016). Of particular interest is the joint inversion of magnetotelluric (MT) with seismic data as their complementary sensitivity to the thermal structure, hydrogen content and small volumes of fluid or melt offer a powerful means to detect fluid pathways in the lithosphere including the locus of partial melting, ore deposits and hydrated lithologies. This unique potential has given impetus to the acquisition of collocated MT and seismic data over large regions (e.g., AusLAMP/AusArray in Australia).

Probabilistic inversions provide complete information about the unknown parameters and their uncertainties conditioned on the data and modelling assumptions. Joint probabilistic inversions of MT and seismic data have been successfully implemented in the context of 1D MT data only. For the cases of 2D and 3D MT data, however, the large computational cost of the MT forward problem has been the main impediment for pursuing probabilistic inversions. To overcome this limitation, we have presented a novel strategy (Manassero et al., 2020, 2021) that reduces the computational cost of the 3D MT forward solver and allows us to perform full joint probabilistic inversions of MT and other datasets for the 3D imaging of deep thermochemical anomalies and fluid pathways.

In this webinar I will introduce our novel strategy and, as part of the Exploring for the Future program, I will present preliminary results of the first joint probabilistic inversion of 3D MT in southeast Australia using the AusLAMP data and a seismic velocity model derived from teleseismic tomography (Rawlinson et al.,2016). We also make interpretations of our conductivity models using the code MATE (Özaydın and Selway, 2020). These results demonstrate the capabilities of our conceptual and numerical framework for 3D joint probabilistic inversions of MT with other geophysical data sets and open up exciting opportunities for elucidating the Earth’s interior in other regions.

Bio

Dr. Manassero has graduated with a PhD in Geophysics at Macquarie University, Australia, in December 2019. Her project consisted of the development of new methodologies to help study the lithospheric structure and mapping the location of mineral deposits and energy sources within Australia. In particular, she has developed a new methodology for probabilistic inversion of 3D magnetotelluric (MT) data as part of an ARC-funded research program. She is currently working as a Post-doctoral Research fellow at Macquarie University in the same research field as part of an ARC Linkage Grant with UNSW, Geoscience Australia and several Australian Geological Surveys.