Advanced seismic velocity model inversion for crustal imaging using joint travel-time and waveform tomography

Project Abstract

This study presents a comprehensive methodology for advancing crustal imaging through an integrative seismic velocity model inversion that simultaneously utilizes travel-time data and full waveform information. By combining high-fidelity travel-time measurements with phase and amplitude content from seismic waveforms, the proposed framework aims to recover accurate 3D velocity models with improved resolution of structural features in complex crustal settings. The core innovation lies in a joint inversion scheme that leverages complementary sensitivities travel-time data constrain large-scale velocity variations and path-averaged properties, while waveform data constrain sharp discontinuities, anisotropy, and attenuation characteristics that are often underresolved in traditional traveltime inversions. We develop a robust Bayesian-regularized objective function that fuses misfit terms for travel times, waveform matching, and advanced priors informed by geological and geophysical constraints. The waveform component employs a composite objective that integrates full-waveform inversion principles with efficient adjoint-state techniques to compute gradients with respect to the velocity field, enabling scalable updates in high-dimensional models. To address nonlinearity and cycle-skipping challenges inherent in waveform inversion, the methodology integrates multiscale frequency progression, dynamic weighting of data contributions, and a hierarchical parameterization that transitions from smooth to heterogeneous representations guided by geological priors. The forward modeling engine combines accurate 3D elastic wave propagation with efficient ray-based traveltime calculations to exploit the strengths of both data types. A synthetic study demonstrates the method’s capacity to recover sharp crustal interfaces and anisotropic signatures under realistic noise levels, while a controlled field example from a tectonically active region illustrates improved delineation of fault zones, magma intrusions, and lithospheric boundaries compared with conventional travel-time or waveform inversions alone. Quantitative metrics including model resolution, misfit reduction, and trade-off analyses between velocity, density, and attenuation are presented to assess inversion stability and uncertainty. The research also explores sensitivity-to-parameters, such as regularization weights, initial model biases, and data sampling density, providing guidelines for field deployment. Uncertainty quantification is embedded through ensemble-based techniques and posterior sampling to deliver probabilistic velocity models with credible intervals, facilitating risk-informed interpretations for crustal processes. The study further examines the impact of incorporating ancillary datasets, such as gravity, magnetotelluric responses, and geological maps, on constraining inversion outcomes. Results indicate that joint travel-time and waveform tomography yields superior imaging of crustal architecture, with enhanced resolution of shallow structures and better recovery of deeper velocity contrasts than single-data-type approaches. This work contributes a scalable, robust framework for integrated seismic imaging, offering methodological advances and practical guidelines for researchers and exploration teams seeking higher-fidelity crustal velocity models in complex geologic settings.

Project Overview

What This Project Is About

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A beginner-friendly look at how scientists create a map of the underground by using two kinds of data: how long seismic waves take to travel and how the waves themselves look as they travel. The project combines these to build a clearer picture of how fast rocks shake waves, which helps us understand what the crust is made of and where features like faults lie.

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The Problem It Addresses

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Traditional methods can give rough pictures of the crust, but they may miss small features or variations in rock types. By combining travel-time information with the full wave shapes, we can reduce uncertainty and get a more accurate image of subsurface velocity changes, which is important for resource exploration, earthquake science, and geotechnical planning.

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Objectives of the Project

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1. Explain how seismic velocity models are built from data.
2. Demonstrate the benefits of combining travel-time and waveform information.
3. Develop a simple, teachable workflow that can be applied to small datasets.
4. Identify limitations and sources of error in the method.
5. Provide a visual demonstration of crustal imaging results.

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What You Will Do Step by Step

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1. Review basics of seismic waves and velocity concepts in the crust.
2. Collect or obtain a small seismic dataset appropriate for a classroom project.
3. Process data to extract travel times and waveform features.
4. Set up a basic joint inversion framework that uses both data types.
5. Run simple models to update the velocity structure and compare results.
6. Assess uncertainty and create clear visualizations of the crustal image.
7. Document the methods and discuss practical challenges.

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Expected Outcome

A practical, easy-to-follow workflow that shows how joint travel-time and waveform tomography improves crustal imaging, with a clear set of results and visuals suitable for teaching or initial research exploration.