As demand for more accurate geological representations grows in fields such as resource exploration, geohazard assessment, and environmental geoscience, advances in modelling algorithms and inversion methods have become critical. Presentations will cover new approaches to the construction of detailed geological models, the use of machine learning and AI in model refinement, and the application of inversion techniques to improve the accuracy of subsurface property predictions.

Topics of interest include, but are not limited to:
- New methodologies for 3D structural modelling, including deterministic, stochastic, and hybrid approaches
- Case studies highlighting the application of model-based inversion for resource exploration, such as mineral, petroleum, and groundwater systems
- Integration of geophysical and geological data in model-based inversion for improved subsurface characterization
- Advances in computational efficiency and uncertainty quantification in inversion techniques
- Innovative use of machine learning and AI in enhancing both geological models and inversion results

This session brings together geoscientists, modellers, and computational experts to discuss the latest advancements and challenges, offering insights into the future direction of 3D structural geological modelling and inversion applications.