Comparing prospectivity modelling results and past exploration data: A case study of porphyry Cu–Au mineral systems in the Macquarie Arc, Lachlan Fold Belt, New South Wales

Kreuzer, Oliver P.; Miller, Alexandra; Peters, Katie J.; Payne, Constance E.; Wildman, Charlene; Partington, Gregor; Puccioni, Elisa; McMahon, Maureen E.; Etheridge, M. A.

doi:10.1016/j.oregeorev.2014.09.001

Cited by 43 publications

(4 citation statements)

References 57 publications

(74 reference statements)

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“…The unique conditions grid can be combined with other maps, for example of exploration expenditure, to simplify cost analysis of future exploration needs (e.g. Kreuzer et al, 2014).…”

Section: Weights Of Evidence Model Resultsmentioning

confidence: 99%

Chatham Rise nodular phosphate — Modelling the prospectivity of a lag deposit (off-shore New Zealand): A critical tool for use in resource development and deep sea mining

Nielsen¹,

McKenzie²,

Miller³

et al. 2015

Ore Geology Reviews

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“…The unique conditions grid can be combined with other maps, for example of exploration expenditure, to simplify cost analysis of future exploration needs (e.g. Kreuzer et al, 2014).…”

Section: Weights Of Evidence Model Resultsmentioning

confidence: 99%

Chatham Rise nodular phosphate — Modelling the prospectivity of a lag deposit (off-shore New Zealand): A critical tool for use in resource development and deep sea mining

Nielsen¹,

McKenzie²,

Miller³

et al. 2015

Ore Geology Reviews

Self Cite

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“…In order to extract reliable targeting criteria for the subsequent prospectivity modeling, a mineral systems approach is employed to transfer understandings of tungsten mineral system into a set of mappable spatial proxies representing critical ore-forming processes related to source, transport, physical trap and chemical deposition [32][33][34][35] (Figure 2). In many cases, a hydrothermal mineral system has a single source that provides not only the energy gradient, thus triggering mineralization events, but also the necessary components required for ore formation (e.g., metal, fluids and ligands) [34].…”

Section: Mineral Systemmentioning

confidence: 99%

Prospectivity Mapping of Tungsten Mineralization in Southern Jiangxi Province Using Few-Shot Learning

et al. 2023

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The development of mineral prospectivity mapping (MPM), which aims to outline and prioritize mineral exploration targets, has been spurred by advances in data-driven machine learning algorithms. Supervised data-driven MPM is a typical few-shot task, suffering from a scarcity of labeled data, the over-fitting of models and an uncertainty of predictions. The main objective of this contribution is to propose a robust framework of few-shot learning (FSL), combining data augmentation and transfer learning to enable the generation of prospectivity models with excellent predictive efficiency and low uncertainty. The mineral systems approach was used to transfer a conceptual mineral system into mappable exploration criteria. Synthetic minority over-sampling technique (SMOTE) was employed to augment and balance the labeled dataset, allowing for model pre-training with the large synthetic training dataset of a source domain. The knowledge derived from pre-trained models was then transferred to the target domain by fine-tuning, and the prospectivity model was generated in light of over-fitting and uncertainty assessments. The proposed FSL framework was applied to tungsten prospectivity mapping in southern Jiangxi Province. The results indicated that the SMOTE-ed balanced dataset boosted the classification accuracy in the training process. The FSL models yielded an arch-shaped prediction point pattern which was favorable for focusing potential targets with high probability and low uncertainty. The FSL models achieved a high predictive performance (test AUC = 0.9172) and the lowest quantitative over-fitting value compared to the models derived from the benchmark algorithms of random forest and support vector machine. Four levels of potential targeting zones, considering both predictive efficiency and uncertainty, were extracted from the resulting FSL prospectivity map. The final high-potential and low-risk exploration targets only cover 4.27% of the area, but capture 41.53% of known tungsten deposits, thus achieving a superior predictive performance. This study highlights the capability of FSL framework to control over-fitting and generate high-confidence exploration targets with low levels of uncertainty.

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“…The mineral system concept (better considered as a mineralizing system concept) has been used for >20 years to conceptualize the overlap of necessary, i.e., "critical" [23], geological processes and elements to form and preserve mineral deposits [24] of various commodities [23,[25][26][27][28][29]. In this document, we use and recommend the term "mineral system critical components" instead of mineral system critical processes and elements, because REE-HFSE commodities are often termed critical elements in REE-HFSE research parlance.…”

Section: The Mineral System Concept For Mineral Deposit Formationmentioning

confidence: 99%

A Workflow to Define, Map and Name a Carbonatite- or Alkaline Igneous-Associated REE-HFSE Mineral System: A Case Study from SW Germany

et al. 2019

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Security of supply of "hi-tech" raw materials (including the rare earth elements (REE) and some high-field-strength elements (HFSEs)) is a concern for the European Union. Exploration and research projects mostly focus on deposit-to outcrop-scale description of carbonatite-and alkaline igneous-associated REE-HFSE mineralization. The REE-HFSE mineral system concept and approach are at a nascent stage, so developed further here. However, before applying the mineral system approach to a chosen REE-HFSE metallogenic province its mineral system extent first needs defining and mapping. This shifts a mineral system project's foundation from the mineral system concept to a province's mineral system extent. The mapped extent is required to investigate systematically the pathways and potential trap locations along which the REE-HFSE mass may be distributed. A workflow is presented to standardize the 4-D definition of a REE-HFSE mineral system at province-scale: (a) Identify and hierarchically organize a mineral system's genetically related sub-divisions and deposits, (b) map its known and possible maximum extents, (c) name it, (d) discern its size (known mineral endowment), and (e) assess the favorability of the critical components to prioritize further investigations. The workflow is designed to generate process-based perspective and improve predictive targeting effectiveness along under-evaluated plays of any mineral system, for the future risking, comparing and ranking of REE-HFSE provinces and plays.or geophysical pathfinder signatures [7]; or serendipitously, e.g., during uranium prospecting [7]. Knowledge of the location controls of these metals remains limited compared to knowledge about base and precious metal deposits [5]. Many of the >500 known carbonatite occurrences [8] remain under evaluated. The result is recent REE mining from only a few deposits related to carbonatite and alkaline igneous bodies [1,9], e.g., the Bayan Obo Fe-REE deposit in China [10,11]; the Mountain Pass carbonatite-hosted REE deposit in the USA [12]; the Mount Weld carbonatite-associated lateritic REE and Nb-Ta deposits in Australia (e.g., Reference [13]) and the Araxa carbonatite-associated, lateritic Nb deposit in Brazil [14]. Other REE mines are of ion-adsorption clay deposits and monazitexenotime-bearing placer deposits (e.g., Reference [9]). For details of REE and carbonatite-related data, uses, occurrences, and mines refer to References [1,5,[15][16][17][18][19]. Aims and AudienceAs most REE-HFSE-centric exploration and research projects tend to focus efforts on the depositto outcrop-scale they neglect to place occurrences within their wider context, where significant undiscovered potential may exist. To help address this knowledge gap we present a method and workflow for defining, mapping and naming any REE-HFSE mineral system associated with carbonatite and alkaline igneous rocks. The objective is to 4-D summarise the current knowledge status of the selected mineral system. It is designed so that geoscientists, economists, and stra...

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Comparing prospectivity modelling results and past exploration data: A case study of porphyry Cu–Au mineral systems in the Macquarie Arc, Lachlan Fold Belt, New South Wales

Cited by 43 publications

References 57 publications

Chatham Rise nodular phosphate — Modelling the prospectivity of a lag deposit (off-shore New Zealand): A critical tool for use in resource development and deep sea mining

Chatham Rise nodular phosphate — Modelling the prospectivity of a lag deposit (off-shore New Zealand): A critical tool for use in resource development and deep sea mining

Prospectivity Mapping of Tungsten Mineralization in Southern Jiangxi Province Using Few-Shot Learning

A Workflow to Define, Map and Name a Carbonatite- or Alkaline Igneous-Associated REE-HFSE Mineral System: A Case Study from SW Germany

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