Machine Learning for Characterization of Fluvial Architectural Elements

Main objectives: This project will develop machine learning algorithms to characterize architectural elements of modern fluvial depositional systems across a range of different climates and tectonic settings. The aim is to develop a database that will provide input for numerical models to study system behavior through time and the likely validity of modern systems to understand the preserved rock record.

Funding: AkerBP ASA

Project Period: 2021 – 2023

Project Coordinator: Björn Nyberg

People involved at UiB: Rob Gawthorpe

Project Partners: AkerBP ASA