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dc.contributor.advisorMcCarthy, William
dc.contributor.authorDixon, Oliver James
dc.coverage.spatial173en_US
dc.date.accessioned2023-10-30T14:51:56Z
dc.date.available2023-10-30T14:51:56Z
dc.date.issued2023-11-28
dc.identifier.urihttps://hdl.handle.net/10023/28590
dc.description.abstractPorphyry copper deposits form from upper crustal H₂O saturated magmatic systems, along ancient and active convergent margins. As the world’s major source of copper, gold and molybdenum, along with minor quantities of other base and precious metals, they are an increasingly important source of raw material, essential to the ongoing clean energy transition and in hitting key targets set by global societies today. Driven by the transition to renewable energy sources and electric vehicles, dependent on substantial quantities of iron ore, copper and aluminium, it has been estimated that the demand for copper alone will increase by over 20 times. With current reserves not expected to meet future demand, extensive additional exploration is anticipated. Furthermore, with the depletion of near-surface deposits in mature exploration terranes, there is a clear need for the development of new techniques to identify and unearth deeply buried reserves. Exploration programs rely on many techniques for the identification of the large, distal alteration systems associated with porphyry style mineralisation, which currently focus on pathfinding geochemical indicators. Alongside these techniques, infrared spectroscopy and magnetic susceptibility data is often collected but underutilised, despite providing a rapid and low-cost source of mineralogical information. Using samples collected form the Aktogay porphyry Cu deposit in the Central Asian Orogenic Belt, an extensive Palaeozoic subduction-accretion complex, the ability of magnetic and infrared spectroscopy to quantifiably define and characterise alteration, when used in conjunction with a specifically developed, unsupervised deep learning algorithm, has been examined. Our findings demonstrate that the resulting subdivision around porphyry mineralisation into twelve discrete domains, can uniquely identify otherwise hidden mineral assemblages. Through examining the consistency of key parameters within each domain such as ore grade and geochemical signatures, their statistical significance has been tested, indicating an increased consistency of between 60 and 70% when compared to traditional alteration zones classified by on-site mining geologists. In addition, detailed petrological and magnetic characterisation independently confirms the validity of the newly defined alteration domains, whilst also demonstrating the importance of magnetic characterisation as a new tool, which can improve our understanding and partial quantification of the magnetic effects during hydrothermal fluid-rock interactions throughout ore deposit formation. Quantifiably defining alteration domains provides a reproducible, rapid and non-destructive method that can be deployed in a wide variety of settings, leading to the consistent separation of domains which can be used as a superior proxy for ore distribution and grade.en_US
dc.description.sponsorship"This work was supported by the IAPETUS Doctoral Training Programme [NE/L002590/1]; and the St Leonard’s Postgraduate College scholarship."--Fundingen
dc.language.isoenen_US
dc.relationA Quantitative Classification Tool for Porphyry Cu Alteration Systems (thesis data). Dixon, O. J., University of St Andrews, 26 Oct 2033. DOI: 10.17630/0deb3aa1-e6c4-4cb2-8ce9-a7a945ce95bc
dc.relation.urihttps://doi.org/10.17630/0deb3aa1-e6c4-4cb2-8ce9-a7a945ce95bc
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMagnetic susceptibilityen_US
dc.subjectMachine learningen_US
dc.subjectMagnetic remanenceen_US
dc.subjectHyperspectral analysisen_US
dc.subjectAMSen_US
dc.subjectPorphyryen_US
dc.subjectHydrothermal alterationen_US
dc.subjectPorphyry copper depositsen_US
dc.subjectCopperen_US
dc.subjectClean energy transitionen_US
dc.subjectInfrared spectroscopyen_US
dc.subjectCentral Asian Orogenic Belten_US
dc.subjectAktogayen_US
dc.titleA quantitative classification tool for porphyry Cu alteration systemsen_US
dc.typeThesisen_US
dc.contributor.sponsorIAPETUS Doctoral Training Partnership (DTP)en_US
dc.contributor.sponsorUniversity of St Andrews. St Leonard's College Scholarshipen_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnamePhD Doctor of Philosophyen_US
dc.publisher.institutionThe University of St Andrewsen_US
dc.rights.embargodate2033-10-26
dc.rights.embargoreasonThesis restricted in accordance with University regulations. Restricted until 26th October 2033en
dc.identifier.doihttps://doi.org/10.17630/sta/641
dc.identifier.grantnumberNE/L002590/1en_US


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    Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
    Except where otherwise noted within the work, this item's licence for re-use is described as Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International