| Document Date: 2015-03-24 06:34:14
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City Perth / Reading / London / Geoscience / / Company Continental / / Continent South America / / Country Australia / Peru / / Currency IDR / / / Facility Geosciences The University of Sydney / Geosciences The University / / IndustryTerm machine learning algorithms / spatio-temporal data mining approach / mining / porphyry systems / spatio-temporal data-mining / / NaturalFeature Andes / / Organization University of Sydney / Geological Society of America Bulletin / Science Industry Endowment Fund / Geological Society / Australian Research Council / / Person R. Dietmar Müller / Simon Williams Stephen Hardy Andrew Merdith / Nathaniel Butterworth Daniel Steinberg / Sydney Stephen / / Position will aide / representative / controller / / PublishedMedium Nature Geoscience / Machine Learning / / Region Antarctic / south china / south america / central america / east asia / / Technology Geophysics / remote sensing / five machine learning algorithms / data mining / machine learning / / URL www.gplates.org / /
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For several decades single-component seismic reflection methods have provided the primary geophysical tool for hydrocarbon exploration and development