Abstract
Abstract Recent exploration has identified a series of Cu-Mo skarn deposits within the Xuancheng-Magushan orefield. The orefield forms part of the Nanling-Xuancheng mining district, which is located within the Middle-Lower Yangtze River Metallogenic Belt (MLYRMB) of central-eastern China. However, this area contains thick and widespread unprospective sedimentary cover sequences that have impeded traditional approaches to mineral exploration. This study presents the results of 3D numerical simulation modeling that identifies possible mineral exploration targets within the entire Xuancheng-Magushan orefield. This modeling enables the identification of unexplored areas with significant exploration potential that are covered by thick sedimentary sequences that cannot be easily explored using traditional exploration approaches. This study outlines the practical value of 3D numerical simulation-based targeting in areas with thick sedimentary cover sequences and uses the Flac3D software package to couple processes involved in ore formation such as stress, pressure, and heat transfer. Here, we use volumetric strain increments calculated during numerical modeling as the thermodynamic representation of the generation of space during prograde skarn formation, with this space filed by sulfides either penecontemporaneously or soon after magmatism. This process occurred during retrograde hydrothermal ore formation and the genesis of the skarn-type mineralization in this area. The results of the volumetric strain increment calculated during this numerical modeling study matches the distribution of known mineralization as well as delineating eight potential targets that have not yet been explored but represent areas of significant exploration potential within the Xuancheng-Magushan orefield, indicating these targets should be considered prospective for future mineral exploration. One of these targets was also identified during our previous Comsol-based numerical modeling of the formation of the Magushan Cu-Mo skarn deposit. The fact that this area has been identified as prospective using two different numerical modeling methods indicates that this area should be prioritized for future exploration and also validates the numerical modeling approaches used here and in our previous research that more specifically focused on the Magushan skarn deposit. Overall, our study indicates that prospectivity modeling using 3D numerical simulation-based approaches can be both effective and economical and should be considered an additional tool for future mineral exploration to reduce exploration risks when targeting mineralization in areas with thick and unprospective sedimentary cover sequences.
Highlights
Skarn deposits are widely distributed in both space and time (e.g., [1]) and are important sources of copper, lead, zinc, molybdenum, and other metals [2,3,4]
We address the following questions using numerical simulations, namely, (1) Can numerical simulations enable the identification or verification of existing geological data? and (2) Can numerical simulations be used to identify prospective areas for exploration targeting in areas with thick and unprospective sedimentary cover sequences, such as the XuanchengMagushan orefield, as well as providing guides for future mineral exploration? Both of these points are assessed during this study, demonstrating that numerical simulation can be used in both fundamental geological and economic geology research as well as in exploration targeting in regions of orefield scale with thick and unprospective cover sequences
The simulation undertaken during this study provides an additional approach to identifying areas prospective for deep-seated exploration purely based on 3D numerical simulation, supplementing more traditional exploration approaches and removing some of the risks conditional dependence-related risks associated with other types of prospectivity modeling
Summary
Skarn deposits are widely distributed in both space and time (e.g., [1]) and are important sources of copper, lead, zinc, molybdenum, and other metals [2,3,4]. Traditional three-dimensional prospectivity modeling approaches (e.g., weights-of-evidence) frequently encounter issues related to conditional independence, where datasets are biased by relationships where given exploration criteria can generate responses in different datasets, particular mineralizing processes can generate more than one exploration criteria, or responses present within one dataset can be conditioned by responses in another dataset [15] This can be overcome by using the numerical simulation approaches utilized in this study, providing another approach for the identification of areas that are prospective for deeper exploration in regions with thick sedimentary cover sequences. This means that even though this software is not designed for geological research, it allows the coupling of multiple physical fields (e.g., temperature and pressure) that enables the easier formulation of coupled simulation models This approach allows the numerical simulation of the hydrothermal and mineralizing processes that generated the skarn deposits in the study area (as well as other types of mineralization). This type of modeling and simulation can highlight unexplored areas where hydrothermal and mineralizing processes are likely to have occurred but where mineralization has not yet been identified or exploration has not as yet taken place, yielding targets for future exploration
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