Mineralization-related geochemical anomalies derived from stream sediment geochemical data using multifractal analysis in Pangxidong area of Qinzhou-Hangzhou tectonic joint belt, Guangdong Province, China
来源期刊：中南大学学报(英文版)2013年第1期
论文作者：ZHANG Yan(张焱) ZHOU Yong-zhang(周永章) WANG Lin-feng(王林峰) WANG Zheng-hai(王正海) HE Jun-guo(何俊国) AN Yan-fei(安燕飞) LI Hong-zhong(李红中) ZENG Chang-yu(曾长育) LIANG Jin(梁锦) Lü Wen-chao(吕文超) GAO Le(高乐)
文章页码：184 - 192
Key words：geochemical anomalies; fractal modeling; principal component analysis; Qinzhou-Hangzhou joint tectonic belt; stream sediments
Abstract: Distinguishing geochemical anomalies from background is a basic task in exploratory geochemistry. The derivation of geochemical anomalies from stream sediment geochemical data and the decomposition of these anomalies into their component patterns were described. A set of stream sediment geochemical data was obtained for 1 880 km2 of the Pangxidong area, which is in the southern part of the recently recognized Qinzhou-Hangzhou joint tectonic belt. This belt crosses southern China and tends to the northwest (NE) direction. The total number of collected samples was 7 236, and the concentrations of Ag, Au, Cu, As, Pb and Zn were measured for each sample. The spatial combination distribution law of geochemical elements and principal component analysis (PCA) were used to construct combination models for the identification of combinations of geochemical anomalies. Spectrum-area (S-A) fractal modeling was used to strengthen weak anomalies and separate them from the background. Composite anomaly modeling was combined with fractal filtering techniques to process and analyze the geochemical data. The raster maps of Au, Ag, Cu, As, Pb and Zn were obtained by the multifractal inverse distance weighted (MIDW) method. PCA was used to combine the Au, Ag, Cu, As, Pb, and Zn concentration values. The S-A fractal method was used to decompose the first component pattern achieved by the PCA. The results show that combination anomalies from a combination of variables coincide with the known mineralization of the study area. Although the combination anomalies cannot reflect local anomalies closely enough, high-anomaly areas indicate good sites for further exploration for unknown deposits. On this basis, anomaly and background separation from combination anomalies using fractal filtering techniques can provide guidance for later work.
ZHANG Yan(张焱)1,2,3, ZHOU Yong-zhang(周永章)1,3, WANG Lin-feng(王林峰)1,3, WANG Zheng-hai(王正海)1,3, HE Jun-guo(何俊国)1,3, AN Yan-fei(安燕飞)1,3,LI Hong-zhong(李红中)1,3, ZENG Chang-yu(曾长育)1,3,LIANG Jin(梁锦)1,3, Lü Wen-chao(吕文超)1,3, GAO Le(高乐)1,3
(1. Department of Earth Sciences, Sun Yat-sen University, Guangzhou 510275, China;
2. Institute of Zhanjiang, China National Offshore Oil Corporation Ltd., Zhanjiang 524054, China;
3. Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration, Guangzhou 510275, China)
Abstract:Distinguishing geochemical anomalies from background is a basic task in exploratory geochemistry. The derivation of geochemical anomalies from stream sediment geochemical data and the decomposition of these anomalies into their component patterns were described. A set of stream sediment geochemical data was obtained for 1 880 km2 of the Pangxidong area, which is in the southern part of the recently recognized Qinzhou-Hangzhou joint tectonic belt. This belt crosses southern China and tends to the northwest (NE) direction. The total number of collected samples was 7 236, and the concentrations of Ag, Au, Cu, As, Pb and Zn were measured for each sample. The spatial combination distribution law of geochemical elements and principal component analysis (PCA) were used to construct combination models for the identification of combinations of geochemical anomalies. Spectrum-area (S-A) fractal modeling was used to strengthen weak anomalies and separate them from the background. Composite anomaly modeling was combined with fractal filtering techniques to process and analyze the geochemical data. The raster maps of Au, Ag, Cu, As, Pb and Zn were obtained by the multifractal inverse distance weighted (MIDW) method. PCA was used to combine the Au, Ag, Cu, As, Pb, and Zn concentration values. The S-A fractal method was used to decompose the first component pattern achieved by the PCA. The results show that combination anomalies from a combination of variables coincide with the known mineralization of the study area. Although the combination anomalies cannot reflect local anomalies closely enough, high-anomaly areas indicate good sites for further exploration for unknown deposits. On this basis, anomaly and background separation from combination anomalies using fractal filtering techniques can provide guidance for later work.
Key words:geochemical anomalies; fractal modeling; principal component analysis; Qinzhou-Hangzhou joint tectonic belt; stream sediments
