Anomaly identification in soil geochemistry using multifractal interpolation: A case study using the distribution of Cu and Au in soils from the Tongling mining district, Yangtze metallogenic belt, Anhui province, China

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• 作者：Feng Yuan^a ; ^b ; ^{yf_hfut@163.com} ; Xiaohui Li^a ; Simon M. Jowitt^b ; Mingming Zhang^a ; Cai Jia^a ; Xiaoyu Bai^a ; Taofa Zhou^a
• 关键词：Interpolation ; Multifractal Kriging ; Singularity index ; Anomaly threshold ; Soil geochemistry ; Tongling mining district
• 刊名：Journal of Geochemical Exploration
• 出版年：2012
• 期刊代码：44_03756742
• 类别：ear
• 出版时间：May-June, 2012
• 卷：116-117
• 期：Complete
• 页码：28-39
• 文件大小：2434 K

摘要

Interpolation between existing data points is necessary in order to construct contours and surfaces to determine spatial variations and anomalies within soil geochemical datasets. In this study we focus on the mature Cu and Au Tongling mining district, in Anhui province, eastern China. Copper and Au concentrations in both topsoil (A horizon) and deep soil (C horizon) were used to compare Kriging and multifractal Kriging interpolation methods. In order to separate anomalous samples from background concentrations, anomaly thresholds for Cu and Au soil concentrations were calculated for the Tongling mining district using a scattergram of contoured elemental concentrations versus number of mineral deposits contained in each contour. The anomaly threshold for Cu was 56.23 mg路kg^鈭?#xA0;1; a contour constructed for this value contains the majority of the known Cu deposits within the Tongling mining district while also indicating other potentially prospective areas. The calculated threshold value that distinguishes between background and anomalously high concentrations of Au was 2.22 渭g路kg^鈭?#xA0;1; however, this value is considered less robust than the Cu value due to the lower number of training points, i.e. known Au deposits, within the district. Geochemical anomalies associated with known mineralization are more consistently distinguished with multifractal approaches than when normal Kriging is used, and the deep soil geochemical data produced better results than the topsoil data. In terms of interpolation methods, singularity index and multifractal Krige interpolation approaches were more robust and produced better results than ordinary Kriging. The results indicate that an approach using deep soil sampling and multifractal Krige interpolation may be an effective tool for mineral exploration in areas where the topsoil may be contaminated by anthropogenic activities, such as mature mining districts.