Multi-observable probabilistic inversions are gaining popularity for imaging the Earth's interior and elucidating the physicochemical structure of the lithosphere. Of particular interest is the joint inversion of magnetotelluric (MT) with seismic data, as they are inherently sensitive to different physical properties, viz. electrical conductivity and seismic velocity and they, therefore, provide complementary information on the thermal structure, fluid pathways and water content. This complementary information is critical for understanding the complex fluid-rock interactions responsible for mineralization events and water-assisted tectonism.

Joint probabilistic inversions of MT and seismic data have been successfully implemented in the context of 1D MT data only. In the case of 2D and 3D MT data, however, joint probabilistic approaches have, up until now, been impractical due to the large computational cost of the full MT forward solutions. In this seminar, I will introduce our strategy (RB+MCMC) that allows us to reduce the computational cost of the 3D MT forward solver and makes it possible to perform full probabilistic 3D MT inversions. I will present the structure of the code and show results of joint probabilistic inversions of 3D MT and seismic data for the 3D imaging of the lithosphere.

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