Machine Learning for Characterization of Fluvial Architectural Elements
Development of machine learning algorithms to characterize architectural elements of modern fluvial depositional systems
About the research project
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 Partners
Aker BP ASA
People
Project members
Bjørn Nyberg Project Coordinator (UiB-GEO)
Rob Gawthorpe Researcher (UiB-GEO)