Geochemical metallogenic potential based on cluster analysis: A new method to extract valuable information for mineral exploration from geochemical data

• Published in: Applied geochemistry Vol. 122; p. 104748
• Main Authors: Zhou, Shu-guang, Zhou, Ke-fa, Wang, Jin-lin
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2020
• Subjects: Cluster analysis; Compositional data; Geochemical anomaly; Metallogenic prediction; Mineral exploration; Cluster analysis; Metallogenic prediction; Mineral exploration; Geochemical anomaly; Compositional data
• ISSN: 0883-2927; 1872-9134
• DOI: 10.1016/j.apgeochem.2020.104748

Geochemical data are widely regarded as valuable for mineral exploration because they can be used to recognize ore-related geochemical anomalies. Many techniques have been used to identify geochemical anomalies within geochemical datasets, but most of these techniques focus on the concentration or fractal characteristics of one or a combination of indicator element(s). Indicator elements for a particular type of deposit are selected based on expert knowledge, but this approach is subjective and valuable information associated with the elements that are not selected is lost. This study describes a new method that maximize the extraction of valuable information from all elements available in a geochemical dataset. The technique involves geochemical metallogenic potential mapping based on cluster analysis (GMPM-CA), which enables the identification of prospective areas suitable for further mineral exploration. The results show that GMPM-CA can produce a map of mineralization potential with excellent predictive capacity. Furthermore, GMPM-CA is a practical method that does not require expert geological or geochemical knowledge, and can be integrated with existing geochemical anomaly identification methods. •A method based on cluster analysis (GMPM-CA) is proposed and a workflow is also developed for GMPM-CA in this study.•The GMPM-CA has the potential to extract more valuable information than some of the conventional methods.•The GMPM-CA method can produce relatively robust results for mineral exploration from geochemical data.