Prospectivity Modeling of Devonian Intrusion-Related W–Mo–Sb–Au Deposits in the Pokiok Plutonic Suite, West-Central New Brunswick, Canada, Using a Monte Carlo-Based Framework

IF 4.8 2区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Amirabbas Karbalaeiramezanali, Mohammad Parsa, David R. Lentz, Kathleen G. Thorne
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Abstract

The Pokiok Plutonic Suite (PPS) lies within the southern segment of New Brunswick's Central Plutonic Belt, Canada. The PPS exhibits significant Devonian intrusive events, including four main phases, namely the Hartfield Tonalite, the Hawkshaw Granite, the Skiff Lake Granite, and the Allandale Granite, hosting notable intrusion-related W–Mo–Sb–Au deposits. This study aimed to identify potential exploration targets for intrusion-related W–Mo–Sb–Au deposits using knowledge-driven mineral prospectivity mapping (MPM) techniques. Model- and judgment-related uncertainties undermine the reliability of knowledge-driven MPM. This study adopted a multifaceted approach, combining the mineral systems approach, parsimonious weighting methods, Monte Carlo simulation (MCS), and a risk–return analysis, to mitigate the effects of these uncertainties on MPM. We employed three multi-criteria decision-making systems, namely MCS-based Best Worst Method (BWM) with Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) (MCS–BWM–MARCOS), MCS-based Full Consistency Method (FUCOM) with MARCOS (MCS–FUCOM–MARCOS), and MCS-based Level Based Weight Assessment (LBWA) with MARCOS (MCS–LBWA–MARCOS), for MPM, with MCS–LBWA–MARCOS exhibiting the highest accuracy. The risk–return analysis was employed to interpret the results of our models. Low-risk, high-return cells reduced the search space for mineral exploration by ~ 15%, while predicting ~ 73% of the known intrusion-related W–Mo–Sb–Au occurrences. The methodology applied herein allows for a more confident selection of exploration targets using knowledge-driven MPM.

加拿大新不伦瑞克省中西部Pokiok深成套泥盆系侵入体相关W-Mo-Sb-Au矿床远景模拟——基于Monte carlo框架
Pokiok岩体套位于加拿大新不伦瑞克省中央岩体带的南段。PPS具有明显的泥盆系侵入事件,包括Hartfield Tonalite、Hawkshaw Granite、Skiff Lake Granite和Allandale Granite四个主要阶段,具有明显的侵入相关的W-Mo-Sb-Au矿床。本研究旨在利用知识驱动的矿产远景填图(MPM)技术,确定与侵入体相关的W-Mo-Sb-Au矿床的潜在勘探目标。模型和判断相关的不确定性破坏了知识驱动的MPM的可靠性。本研究采用了多方面的方法,结合矿物系统方法、简约加权方法、蒙特卡罗模拟(MCS)和风险回报分析,以减轻这些不确定性对MPM的影响。我们采用了三种多准则决策系统,即基于度量选项和折衷方案排序的基于MCS-BWM-MARCOS (MCS-BWM-MARCOS)的基于MCS-FUCOM-MARCOS的基于MCS-FUCOM-MARCOS的完全一致性方法(FUCOM)和基于MARCOS (MCS-LBWA-MARCOS)的基于层次的权重评估(LBWA)的MPM决策系统,其中MCS-LBWA-MARCOS的MPM决策精度最高。我们采用风险收益分析来解释模型的结果。低风险、高回报的单元减少了约15%的矿产勘探搜索空间,同时预测了约73%的已知侵入相关W-Mo-Sb-Au矿床。本文采用的方法允许使用知识驱动的MPM更有信心地选择勘探目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Natural Resources Research
Natural Resources Research Environmental Science-General Environmental Science
CiteScore
11.90
自引率
11.10%
发文量
151
期刊介绍: This journal publishes quantitative studies of natural (mainly but not limited to mineral) resources exploration, evaluation and exploitation, including environmental and risk-related aspects. Typical articles use geoscientific data or analyses to assess, test, or compare resource-related aspects. NRR covers a wide variety of resources including minerals, coal, hydrocarbon, geothermal, water, and vegetation. Case studies are welcome.
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