ABOUT THE WORKSHOP

In recent years, artificial intelligence—specifically machine learning—has emerged from abstraction and become of practical utility. AI/ML now offer powerful means to address one of humanity’s oldest and grandest challenges: understanding the hidden structure of the Earth. From delineating faults to tracing salt boundaries and refining image resolution, machine learning enables us not merely to compute, but to infer, to classify, and to quantify uncertainty in ways previously unattainable.

This workshop will bring together scholars and practitioners who have taken up this task. We aim to examine how machines may assist us in geoscientific inquiry, particularly in the context of subsurface exploration, characterisation, and recovery for oil, gas, and minerals. Participants will share their applications and insights, exploring the use of machine learning across the vast spectrum of geophysical data—from classification to interpretation, interpolation to inversion.

The central question is no longer whether machines can learn, but what we can—and cannot—teach them. And perhaps more profoundly, what they may teach us.

OBJECTIVES OF THE WORKSHOP

The workshop provides a platform to bridge the gap between human insight and algorithmic power, focusing on three core goals:

Intellectual Exchange: Uniting academia and industry to compare methods, results, and emerging institutional approaches.

Augmenting Physics: Exploring how AI can enhance, rather than replace, traditional Earth physics to extract signal from noise in seismic, gravity, and magnetic data.

Collaborative Innovation: Identifying the limitations of current methods and initiating cross-disciplinary partnerships to advance the science of the Earth and the science of learning simultaneously.