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
Amirabbas Karbalaeiramezanali, Mohammad Parsa, David R. Lentz, Kathleen G. Thorne
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引用次数: 0
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.
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.