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Elucidating the complexity of metallogenic elements based on multifractal detrending moving average analysis

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  • Wan, Li
  • Zeng, Xiangjian
  • Lai, Jiajing

Abstract

Metallogenic element distributions generally present highly irregular spatial patterns and scale-dependent variations. In the present study, the multifractal detrending moving average (MFDMA) model is applied to describe the singularity spectrum of different metallogenic element distributions and study the heterogeneity of element concentrations in the Shangzhuang deposit, Jiaodong Province, China. The results show that six metallogenic elements exhibit multifractal scaling. The multifractal spectra of Au and Cu are left-deviated, while Ag, Pb, Zn, and Hg are close to symmetric. Hence, the shape of the multifractal spectrum may give directions to study the ore-forming potential. Notably, Au and Cu are unevenly distributed with stronger multifractal characteristics than other elements with significant difference, revealing that the distributions of orebodies are significantly inhomogeneous and that inflation and contraction phenomena are prominent. In contrast, Ag is a weak multifractal and nearly a single fractal, suggesting barely mineralized zones. When the sources of multifractality are quantified by two factors, long-range correlations, and broad fat-tail distributions, we find that the multifractal structure of Ag is because of the fat-tail probability density function, and the multifractal structure of the other elements is due to both factors.

Suggested Citation

  • Wan, Li & Zeng, Xiangjian & Lai, Jiajing, 2020. "Elucidating the complexity of metallogenic elements based on multifractal detrending moving average analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
  • Handle: RePEc:eee:phsmap:v:541:y:2020:i:c:s0378437119318473
    DOI: 10.1016/j.physa.2019.123296
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    References listed on IDEAS

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    1. Kaushik Matia & Yosef Ashkenazy & H. Eugene Stanley, 2003. "Multifractal Properties of Price Fluctuations of Stocks and Commodities," Papers cond-mat/0308012, arXiv.org.
    2. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    3. Gao-Feng Gu & Wei-Xing Zhou, 2010. "Detrending moving average algorithm for multifractals," Papers 1005.0877, arXiv.org, revised Jun 2010.
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