W-13: Modern Geophysical Inversion: Bridging Physics, AI, and Applications

Inversion of geophysical data is central to subsurface decision-making across energy, environmental, and resource sectors. This workshop focuses on the practical integration of modern inversion techniques, including physics-based modeling, advanced optimization, and machine learning, into workflows that drive value in industry. Covering a broad spectrum of methods (seismic, electromagnetic, gravity, and more), the workshop will explore how inversion is evolving to meet real-world challenges: imaging in complex geological settings, reducing exploration risk, improving reservoir characterization, and enabling emerging applications such as critical mineral discovery and geothermal exploration. Key themes include hybrid inversion frameworks that combine physical constraints with data-driven learning, uncertainty quantification for risk-aware decisions, and scalable computational strategies for large datasets. Participants will engage in technical talks, case studies, and open discussions aimed at bridging the gap between research innovation and operational deployment. This workshop offers a platform to share experiences, tools, and lessons from the field, while exploring what’s next in inversion for subsurface exploration and monitoring. We invite geoscientists, data scientist, and engineers to join in shaping the future of applied geophysical inversion.

Lead Organizer

Youzuo Lin, University of North Carolina

Co-Organizer(s)

Jiajia Sun, University of Houston