@phdthesis{042f5e816735413380f8e67c24c02bd0,
title = "Application of Neural Networks for Geophysical Interpretation - A case study of Basement delineation around a Detrital Iron Ore Deposit, Hammersley Province Western Australia",
abstract = "The interpretation of geophysical data is pivotal to characterising the subsurface. In mineral exploration, interpretations are often used to support or challenge a geological model. Application of machine learning to these tasks, need to contend with the growing overlap and volume of data, along with complex spatial relationships. This thesis presents the development and assessment of three neural network approaches to model the basement surface around the detrital iron ore deposits in the Fortescue valley of the Hamersley province, Western Australia. Culminating in the integration of two key geophysical datasets: a seismic dataset and an Airborne Electromagnetic (AEM) inversion. ",
keywords = "Geophysics, Machine Learning, Graph Neural Networks",
author = "Tasman Gillfeather-Clark",
year = "2023",
doi = "10.26182/tzan-hm89",
language = "English",
school = "The University of Western Australia",
}