Unsupervised machine learning and depth clusters of Euler deconvolution of magnetic data: a new approach to imaging geological structures

Chibuzo Chukwua School of Earth, Atmosphere and Environment, Monash University, Clayton, Australia;b Department of Earth Sciences, Indian Institute of Technology Bombay, Mumbai, India;c IITB-Monash Research Academy, Indian Institute of Technology Bombay, Mumbai, IndiaCorrespondence[email protected]
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Peter Bettsa School of Earth, Atmosphere and Environment, Monash University, Clayton, AustraliaView further author information

David Moorea School of Earth, Atmosphere and Environment, Monash University, Clayton, AustraliaView further author information

Radhakrishna Munukutlab Department of Earth Sciences, Indian Institute of Technology Bombay, Mumbai, IndiaView further author information

Robin Armita School of Earth, Atmosphere and Environment, Monash University, Clayton, AustraliaView further author information

Mark McLeand Geological Survey of Victoria, Melbourne, Australia;e Department of Applied Geophysics, Earth and Atmospheric Sciences, University of Melbourne, Melbourne, AustraliaView further author information

Lachlan Grosea School of Earth, Atmosphere and Environment, Monash University, Clayton, AustraliaView further author information

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Unsupervised machine learning and depth clusters of Euler deconvolution of magnetic data: a new approach to imaging geological structures

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Unsupervised machine learning and depth clusters of Euler deconvolution of magnetic data: a new approach to imaging geological structures

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