Application of partial least squares regression for identifying multivariate geochemical anomalies in stream sediment data from Northwestern Hunan, China

Wang Kun, Xiao Keyan, Li Nan, Cong Yuan, Li Shengmiao

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

The Northwestern Hunan in China is a prospective area for Mississippi Valley-type (MVT) Pb-Zn mineralization similar to the large Huayuan Pb-Zn deposits, which contains tens of millions of tons of resources. Based on the characteristics of the host strata, geochemical data in the Qingxudong Formation were analysed and summarized using Pearson correlation coefficients, including both ore-forming oxides and trace elements. Significant correlation pairs related to Pb-Zn mineralization are extracted. Partial Least Squares Regression (PLSR) was applied separately to the rock-forming oxides and trace elements to extract integrated geochemical anomalies. Anomalies showing an association of rock-forming oxides extracted using PLSR largely coincide with mapped strata, faults, ore deposits and elemental correlations in ore-bearing stratum, indicating the superiority of PLSR; The trace element associations extracted by PLSR are similar to those extracted using the cluster method; we can directly map the former but not the latter. Therefore, the analyses of multivariate geochemical anomalies using PLSR can provide significant information relevant to exploration for mineral deposits.

Original languageEnglish
Pages (from-to)217-230
Number of pages14
JournalGeochemistry: Exploration, Environment, Analysis
Volume17
Issue number3
DOIs
Publication statusPublished - Aug 2017

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