Mn元素多重分形分析
Multifractal Analysis of Mn Element
DOI: 10.12677/AAM.2020.94067, PDF,  被引量    国家自然科学基金支持
作者: 马瑞华:中国地质大学(武汉),湖北 武汉
关键词: 非线性迁移多重分形谱非对称指数Nonlinear Migration Multifractal Spectrum Asymmetric Index
摘要: 地球化学元素分布规律的研究是揭示元素成矿及空间变化规律的重要途径之一。以新疆雅山荒漠地区为例,选取两类矿质,结合多重分形,利用多重分形矩估计法对荒漠两地区的土壤中元素进行全量分析,从奇异性和非对称指数方面,进一步探讨元素的非线性迁移,为以后荒漠区找矿提供一种新的方法和方向。从结果我们可以看出,成矿元素Mn在I区和II区的土壤中分布均具有连续的多重分形特征,随后通过对比两区域的奇异指数和非对称指数发现,奇异指数和非对称指数的值I区均大于II区,由此可以推断出I区迁移特征要高于II区,所以说元素的多重分形特征对于荒漠区找矿具有一定的指示意义。
Abstract: The study of the distribution law of geochemical elements is one of the important ways to reveal the law of element mineralization and spatial change. Taking the desert region of Yashan, Xinjiang as an example, two types of minerals are selected, combined with multiple fractals, and multiple fractal moment estimation methods are used to conduct a full analysis of the elements in the soil in the two desert regions. From the aspects of singularity and asymmetric index, the non-elements of the elements are further explored. Linear migration provides a new method and direction for prospecting in the desert areas in the future. From the results, we can see that the distribution of the ore-forming element Mn in the soils of regions I and II has continuous multifractal characteris-tics. Then, by comparing the singular and asymmetric indices of the two regions, we find that the singular and asymmetric indices for the values of area I are larger than area II. It can be inferred that the migration characteristics of area I are higher than area II. Therefore, the multifractal characteristics of the elements have certain significance for ore prospecting in desert areas.
文章引用:马瑞华. Mn元素多重分形分析[J]. 应用数学进展, 2020, 9(4): 560-564. https://doi.org/10.12677/AAM.2020.94067

参考文献

[1] 於崇文. 成矿动力系统在混沌边缘的分形生长——一种新的成矿理论与方法论[J]. 矿物岩石地球化学通报, 2002, 21(2): 103-113.
[2] 谢淑云, 焦杨, 燕敏, 信栋林, 徐德义, 成秋明. 白音诺尔矿区土壤地球化学纵向非主要成矿特征[J]. 地球科学(中国地质大学学报), 2012, 37(6): 1140-1148.
[3] 申维. 分形理论与矿产预测[M]. 北京: 地质出版社, 2002.
[4] 成秋明. 成矿过程奇异性与矿产预测定量化的新理论与新方法[J]. 地学前缘, 2007, 14(5): 42-53.
[5] 肖凡, 陈建国, 侯卫生, 王正海. 钦-杭结合带南段庞西垌地区Ag-Au致矿地球化学异常信息识别与提取[J]. 岩石学报, 2017, 33(3): 779-790.
[6] 成秋明. 非线性矿床模型与非常规矿产资源评价[J]. 地球科学, 2003, 28(4): 445-454.
[7] 成秋明. 非线性成矿预测理论: 多重分形奇异性-广义自相似性-分形谱系模型与方法[J]. 地球科学, 2006, 31(3): 337-348.
[8] 李伟, 何福国, 丁汝福, 李昌明, 游军, 邵帅. 内蒙古太平川钼铜矿床蚀变、地球化学异常特征及其找矿意义[J]. 矿产与地质, 2016, 30(6): 887-893.
[9] 李晓晖, 袁峰, 周涛发, 邓宇峰, 张达玉, 许超, 张若飞. 新疆塔尔巴哈台-萨吾尔地区多重分形地球化学异常提取及成矿预测[J]. 岩石学报, 2015, 31(2): 426-434.
[10] 刘舒飞. 广西右江盆地金异常分布分形特征与成矿预测[J]. 中国矿业, 2018, 27(S1): 143-146.
[11] 周杰, 袁峰, 李晓晖, 张明明, 胡训宇, 丁文祥, 胡迪, 李现锁. 皖东张八岭-管店地区Au地球化学异常信息识别与提取[J]. 矿物岩石地球化学通报, 2019, 38(1): 150-158.
[12] Manderbrot, D.B. (1982) The Fractal Geometry of Nature. Freeman and Company, San Francisco, 1-20.
[13] Manderbrot, D.B. (1989) Multifractal Measures, Especially for the Geophysicist. Pure and Applied Geophysics, 131, 5-42. [Google Scholar] [CrossRef
[14] Cheng, Q.M. (1999) Gliding Box Method and Multifractal Modelling. Computer & Geosciences, 25, 1073-1080. [Google Scholar] [CrossRef
[15] Cheng, Q.M. (1999) Markov Processes and Discrete Multifractals. Mathematical Geology, 31, 455-469. [Google Scholar] [CrossRef
[16] San, J.M., Martín, M.A. and Caniego, F.J. (2010) Multifractal Analysis of Discretized X-Ray CT Images for the Characterization of Soil Macropore Structures. Geoderma, 156, 32-42. [Google Scholar] [CrossRef
[17] Cheng, Q.M. (1999) Multifractality and Spatial Statistics. Computers and Geosciences, 25, 949-962. [Google Scholar] [CrossRef
[18] Tarquis, A.M. (2009) Pore Network Complexity and Thresholding of 3D Soil Images. Ecological Complexity, 6, 230-239. [Google Scholar] [CrossRef
[19] Cheng, Q.M. and Agterberg, F.P. (1995) Multifractal Modeling and Spatial Point Processes. Mathematical Geology, 27, 831-845. [Google Scholar] [CrossRef
[20] Xie, S.Y., Cheng, Q.M., Zhang, S.Y. and Huang, K. (2010) Assessing Microstructures of Pyrrhotites in Basalts by Multifractal Analysis. Nonlinear Processes in Geophysics, 17, 319-327. [Google Scholar] [CrossRef
[21] 谢淑云, 鲍征宇. 多重分形方法在金属成矿潜力评价中的应用[J]. 成都理工大学学报(自然科学版), 2004, 31(1): 28-33.