Seismic Traveltime Inversion with Quantum Annealing

TL;DR

This paper explores using quantum annealing, a quantum computing technique, to perform seismic traveltime inversion, demonstrating its potential for high-precision geophysical imaging with synthetic data.

Contribution

It introduces a novel approach converting seismic inversion into a QUBO problem solvable by quantum annealing, showcasing its application on synthetic models.

Findings

Successful inversion on synthetic models

Quantum annealing handles noisy data environments

Potential for high-precision seismic imaging

Abstract

This study demonstrates the application of quantum computing based quantum annealing to seismic traveltime inversion, a critical approach for inverting highly accurate velocity models. The seismic inversion problem is first converted into a Quadratic Unconstrained Binary Optimization problem, which the quantum annealer is specifically designed to solve. We then solve the problem via quantum annealing method. The inversion is applied on a synthetic velocity model, presenting a carbon storage scenario at depths of 1000-1300 meters. As an application example, we also show the capacity of quantum computing to handle complex, noisy data environments. This work highlights the emerging potential of quantum computing in geophysical applications, providing a foundation for future developments in high-precision seismic imaging.