Improving salinity estimation from electromagnetic data using Bayesian Evidential Learning

Imaging the subsurface is of prime importance for many geological applications. Among geophysical
techniques, electromagnetic methods (EM) have become popular for rapidly covering large areas.
However, the solution of the inversion of EM data is not unique. In this research we are quantifying the
uncertainty of salinity estimation from EM data using a new framework called Bayesian evidential
learning.