Numerical inversion of 3D geodesic X-ray transform arising from traveltime tomography

TL;DR

This paper develops a localized, efficient numerical algorithm based on Neumann series and layer stripping to invert the 3D geodesic X-ray transform, crucial for traveltime tomography, with validation on test models including Marmousi.

Contribution

It introduces a novel localized numerical inversion method for the 3D geodesic X-ray transform using Neumann series and layer stripping, improving efficiency over global approaches.

Findings

Successful reconstruction on test cases including Marmousi model

Effective application to 3D traveltime tomography

Validation through numerical experiments

Abstract

In this paper, we consider the inverse problem of determining an unknown function defined in three space dimensions from its geodesic X-ray transform. The standard X-ray transform is defined on the Euclidean metric and is given by the integration of a function along straight lines. The geodesic X-ray transform is the generalization of the standard X-ray transform in Riemannian manifolds and is defined by integration of a function along geodesics. This paper is motivated by Uhlmann and Vasy's theoretical reconstruction algorithm for geodesic X-ray transform and mathematical formulation for traveltime tomography to develop a novel numerical algorithm for the stated goal. Our numerical scheme is based on a Neumann series approximation and a layer stripping approach. In particular, we will first reconstruct the unknown function by using a convergent Neumann series for each small neighborhood near the boundary. Once the solution is constructed on a layer near the boundary, we repeat the same procedure for the next layer, and continue this process until the unknown function is recovered on the whole domain. One main advantage of our approach is that the reconstruction is localized, and is therefore very efficient, compared with other global approaches for which the reconstructions are performed on the whole domain. We illustrate the performance of our method by showing some test cases including the Marmousi model. Finally, we apply this method to a travel time tomography in 3D, in which the inversion of the geodesic X-ray transform is one important step, and present several numerical results to validate the scheme.