An Object-Oriented Bayesian Gravity Inversion Scheme for Inferring Density Anomalies in Planetary Interiors

Abstract

Gravity inversions have contributed greatly to our knowledge of the interior of planetary bodies and the processes that shaped them. However, previous global gravity inversion methods neglect the inference of mantle density anomalies when using techniques to decrease the non-uniqueness of the inversion. In this work, we present a novel global gravity inversion algorithm, named THeBOOGIe, suited to inferring global-scale density anomalies within the crust and mantle of planetary bodies. The algorithm embraces the nonuniqueness inherent in gravity inversions by not prescribing at the outset a density interface or depth range of interest. Instead, the method combines a Bayesian approach with a flexible incorporation of prior geological or geophysical information to infer density anomalies at any depth. A validation test using synthetic lunar-like gravity data shows that THeBOOGIe can constrain the lateral location of crustal density anomalies but tends to overestimate their thicknesses. Importantly, THeBOOGIe can detect deep mantle density anomalies and quantify the level of confidence in the inferred density models. Our results show that THeBOOGIe can provide complementary information to one-dimensional seismic models of the interior of the terrestrial planets and the Moon by constraining density anomalies that are not spherically symmetric. Additionally, THeBOOGIe is specially suited to constraining the interior of partially differentiated bodies where these large-scale density anomalies are more likely to exist. Finally, thanks to the flexible use of priors, THeBOOGIe is an essential tool to understand the interior of planetary bodies lacking additional constraints.