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| The recognition and extraction of Au, Cu geochemical composite anomalies:A case study of the east of Laji Mountains |
| JIANG Xiao-Jia1, CHEN Xin1, ZHENG You-Ye1,2, 3, GAO Shun-Bao2, OUYANG-Song1, ZHANG Yong-Chao2, ZHENG Lei1, HUANG Jian2 |
1.The Faculty of Earth Resources, China University of Geosciences, Wuhan 430074, China;
2.Institute of Geological Survey, China University of Geosciences, Wuhan 430074,China;
3.State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Beijing 100083, China |
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Abstract In order to weaken the closure effect of the geochemical data which serve as typical component data, the authors analyzed the spatial distribution of geochemical elements in the Laji Mountains. The authors used the isometric log-ratio(ilr) transformation to "open" the geochemical data of the water sediments, built the combined model using robust principal component analysis (RPCA) to identify the combined geochemical anomalies and employed fractal filtering technique to strengthen weak anomalies and separate anomaly from background. In this way, the authors delineated geochemical anomaly so as to guide mineral exploration better. The result obtained by using RPCA displays two different compositional assemblages: (I) Au-As, probably representing tectonic-altered rock type gold deposit like the east ditch of Jinyuan, and (II) Cu-Ni, likely representing copper-nickel sulfide mineralization such as Lashuixia. The results from S-A filter technique can decompose anomalies further, strengthen weak anomaly and reduce the abnormal area in the strong background and, in combination with the geological survey of the study area and the anomaly map, can better search for tectonic-altered rock type Au-As deposits and Cu-Ni sulfide mineralization.
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Received: 25 July 2016
Published: 20 June 2017
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