Computational Geophysics

Program Introduction

This program provides a rigorous foundation in computational methods for geophysical modeling, simulation, and interpretation, with a strong emphasis on seismic imaging and subsurface characterization. The training is designed to bridge physical theory and modern numerical implementation.

Program Scope

The program focuses on numerical and algorithmic techniques used in contemporary geophysics, including forward modeling, inverse problems, and large-scale data analysis. Emphasis is placed on reproducible workflows, computational efficiency, and physical interpretability.

Program Topics

Numerical methods for geophysical modeling:

• •Forward and inverse problems
• •Computational seismic imaging
• •Optimization and regularization techniques
• •High-performance and large-scale computing concepts

Courses / Teaching Materials

Teaching materials associated with this program are structured to follow the program topics and support progressive learning from theoretical principles to applied computational workflows. The courses emphasize real geophysical datasets, numerical experimentation, and reproducible implementations.

All materials are intended for advanced undergraduate students, graduate students, and early-career researchers in geophysics, applied mathematics, and data science. Course resources include lecture notes, slides, and practical exercises that can be downloaded for independent study or classroom use.

Target Audience

This program is tailored for advanced undergraduate students, graduate researchers, computational geoscientists, and industry professionals seeking to build or enhance their skills in numerical modeling, seismic inverse problems, and high-performance geophysical computing.