High-resolution eikonal imaging and uncertainty quantification of the Kilauea caldera

TL;DR

This paper introduces a high-resolution 3D imaging method for Kilauea's magmatic system using stochastic eikonal tomography, providing detailed images and uncertainty estimates without relying on strong priors.

Contribution

It develops a novel stochastic eikonal tomography approach with uncertainty quantification, improving imaging resolution and reliability of volcanic interior models.

Findings

Enhanced resolution of Kilauea's magmatic system

Quantified uncertainties in seismic velocity estimates

Revealed detailed structure and melt distribution

Abstract

Images of the Earth's interior can provide us with insight into the underlying properties of the Earth, such as how seismic activity might emerge and the interplay between seismic and volcanic activity. Understanding these systems requires reliable high-resolution images to understand mechanisms and estimate physical quantities. However, reliable images are often difficult to obtain due to the non-linear nature of seismic wave propagation and the ill-posedness of the related inverse problem. Reconstructions rely on good initial estimates as well as hand-crafted priors, which can ultimately bias solutions. In our work, we present a 3D reconstruction of Kilauea's magmatic system at a previously unattained resolution. Our eikonal tomography procedure improves upon prior imaging results of Kilauea through increased resolution and per-pixel uncertainties estimated through variational inference. In particular, solving eikonal imaging using variational inference with stochastic gradient descent enables stable inversion and uncertainty quantification in the absence of strong prior knowledge of the velocity structure. Our work makes two key contributions: developing a stochastic eikonal tomography scheme with uncertainty quantification and illuminating the structure and melt quantity of the magmatic system that underlies Kilauea.