Application of Neural Networks for Geophysical Interpretation - A case study of Basement delineation around a Detrital Iron Ore Deposit, Hammersley Province Western Australia

Tasman Gillfeather-Clark

Research output: ThesisDoctoral Thesis

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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.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • The University of Western Australia
Supervisors/Advisors
  • Holden, Eun-Jung, Supervisor
  • Horrocks, Tom, Supervisor
  • Wedge, Daniel, Supervisor
Thesis sponsors
Award date6 Nov 2023
DOIs
Publication statusUnpublished - 2023

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