Bayesian inference

Approaching earth science problems in a “data-driven” philosophy can help glean new insights into our problem and quantify uncertainty.

Dr Ben Mather and Prof Louis Moresi from AuScope’s Simulation, Analysis and Modelling (SAM) program have recently developed a novel, speedy and data-driven way to model the temperature of Earth’s crust in southeastern Australia. Their work has since attracted a grant from the International Association of Mathematical Geosciences (IAMG) to refine the new method and investigate earth temperatures further afield in Alaska.

An efficient inversion framework that gives improved estimates of the thermal state of the crust in Victoria using heat flow measurements and Curie depth in a joint inversion using 3D geological models, and numerical models of thermal diffusion. The outcome of this work is an estimation of the basal heat flux, thermal properties and the heat production rates for the various domains in the model together with uncertainty information.