Multifractal modeling and spatial point processes

The multifractal model can be applied to spatial point processes. It provides new, approximately power-law type, expressions for their second-order intensity and K (r) functions. The box-counting and cluster dimensions are different but mutually interrelated according to multifractal theory. This approach is used to describe the underlying spatial structure of gold mineral occurrences in the Iskut River area, northwestern British Columbia. The box-counting and cluster dimensions for the example are estimated to be 1.335±0.077 and 1.219±0.037, respectively. The relatively strong clustering of the gold deposits is reflected by the fact that both values are considerably less than the corresponding Euclidean dimension (=2).     

Characterization of Geochemical Distributions Using Multifractal Models

The use of multifractals in the applied sciences has proven useful in the characterization and modeling of complex phenomena. Multifractal theory has also been recently applied to the study and characterization of geochemical distributions, and its relation to spatial statistics clearly stated. The present paper proposes a two-dimensional multifractal model based on a trinomial multiplicative cascade as a proxy to some geochemical distribution. The equations for the generalized dimensions, mass exponent, coarse Lipschitz–Hölder exponent, and multifractal spectrum are derived. This model was tested with an example data set used for geochemical exploration of gold deposits in Northwest Portugal. The element used was arsenic because a large number of sample assays were below detection limit for gold. Arsenic, however, has a positive correlation with gold, and the two generations of arsenopyrite identified in the gold quartz veins are consistent with different mineralizing events, which gave rise to different gold grades. Performing the multifractal analysis has shown problems arising in the subdivision of the area with boxes of constant side length and in the uncertainty the edge effects produce in the experimental estimation of the mass exponent. However, it was possible to closely fit a multifractal spectrum to the data with enrichment factors in the range 2.4–2.6 and constant K₁ = 1.3. Such parameters may give some information on the magnitude of the concentration efficiency and heterogeneity of the distribution of arsenic in the mineralized structures. In a simple test with estimated points using ordinary lognormal kriging, the fitted multifractal model showed the magnitude of smoothing in estimated data. Therefore, it is concluded that multifractal models may be useful in the stochastic simulation of geochemical distributions.     

空间模式的广义自相似性分析与矿产资源评价

尺度不变性(scale invariance)包括自相似性(各向同性)、自仿射性(成层结构)、广义自相似性(各向异性标度不变性),是由各种地质过程和地质事件所产生的地质特征和模式的本质属性．尺度不变性可用分形和多重分形模型来表征．这些尺度特征的定量化可为刻画地质空问模式和模式识别提供有力的工具．例如。热液矿床的群聚现象可以用局部分形特征(局部奇异性)来刻画．通过在特征空问中(如频率空问)识别空问模式的广义自相似性．可以将空间混合模式进行分解或异常的识别．介绍了几种相关的分形模型和方法。包括度量空问模式广义尺度独立性(GSI)的线性模型;基于广义尺度独立性的异常分解S—A方法;度量空问模式的局部奇异性方法;以及如何利用分形特征预测未发现矿床的2种方法．有些方法已应用于许多矿产资源评价实例中．给出了对加拿大Nova Scotia省西南部湖泊沉积物样品中的4种元素As、Pb、Zn和Cu的地球化学数据处理分析结果。证明了局部奇异性分析和S—A异常分解方法对地球化学异常的增强和分离的有效性．研究表明：由S—A方法分解的异常往往具有多重分形的特点,而且普遍具有局部奇异性．研究区内具有明显奇异性的地区(元素含量富集区)是金矿异常区域。它们与金矿成矿作用和已知矿床的赋存密切相关．     

Discrete multifractals

The concept of multifractal modeling has been used intensively in various fields of science for characterizing measures with self- similarity. It has been shown that multifractal modeling provides powerful tools for characterizing patterns in the spatial distribution of geological quantities and objects. Existing multifractal models were proposed for the purpose of handling spatially intertwined fractals with continuous fractal spectrum f(α) (or continuous codimension function C(γ)). In this paper, these conventional multifractals are termed “continuous multifractals” whereas multifractals with discrete fractal dimensions are termed “discrete multifractals.” The properties of discrete multifractals are investigated. It is shown by various artificial examples and a case study of stratigraphy of Ocean Drilling Program (ODP) site 645 that spatially intertwined fractals/multifractals indeed can have discrete fractal dimensions. Histogram-and moment-based techniques are proposed for discrete multifractal modeling and illustrated using the artificial examples. The new concept of discrete multifractals and associated multifractal modeling yields not only techniques for characterizing multifractals with discrete fractal dimensions but it also provides insight into the relationships between fractals, bifractals, and multifractals.     

The fractal properties of geochemical landscapes as an indicator of weathering and transport processes within the Eastern Alps

Variations in surface morphology and lithology provide an opportunity to study lithologic and morphologic influences on the spatial pattern of stream-sediment geochemistry within two contrasting environments of the Eastern Alps (Hohe Tauern Range and Gurktaler Alpen Range). The fractal dimension, a measure of surface roughness over a variety of scales, is used to model the dissipation of erosive products due to climatic controlled denudation and fluvial mass transport. Based on a spatial correlation analysis, specific elemental concentrations are used as indicators for a dominant lithotype. Fractal geometry of these elements has been estimated by sequential Gaussian simulation of the area/perimeter relationship (Dal) and by the estimation of multifractal spectra. It is shown that within a 510–780 km² survey area the spatial variations of Al, Ga, Ni and Ca can be approximated by single fractals but for those of Ag and Sn multifractal models must be used. Fractal properties derived from simulated surfaces are explainable by the process controlling the spatial structure of the data. Climatic and tectonic parameters apparently influences Dal at large scales. At smaller scales rock-type variation exert an additional influence on Dal.     

Discrete multifractals

The concept of multifractal modeling has been used intensively in various fields of science for characterizing measures with self- similarity. It has been shown that multifractal modeling provides powerful tools for characterizing patterns in the spatial distribution of geological quantities and objects. Existing multifractal models were proposed for the purpose of handling spatially intertwined fractals with continuous fractal spectrum f(α) (or continuous codimension function C(γ)). In this paper, these conventional multifractals are termed “continuous multifractals” whereas multifractals with discrete fractal dimensions are termed “discrete multifractals.” The properties of discrete multifractals are investigated. It is shown by various artificial examples and a case study of stratigraphy of Ocean Drilling Program (ODP) site 645 that spatially intertwined fractals/multifractals indeed can have discrete fractal dimensions. Histogram-and moment-based techniques are proposed for discrete multifractal modeling and illustrated using the artificial examples. The new concept of discrete multifractals and associated multifractal modeling yields not only techniques for characterizing multifractals with discrete fractal dimensions but it also provides insight into the relationships between fractals, bifractals, and multifractals.     

新疆阿尔泰地区断裂控矿的多重分形机理

新疆阿尔泰地区断裂构造非常发育并对热液成矿有重要控制作用。分形分析表明该区断裂和矿床的空间分布均为多重分形分布,断裂的奇异指数为1.597～2.403,多重分维谱值为0.551～1.706;矿床的奇异指数为0.925～2.287,分维谱值为0.138～1.363。断裂的高的奇异指数和分维谱值表明该区断裂构造具有较高的成熟度和连通性,有利于提高岩石渗透性、促进流体流动和热液矿床的形成。断裂构造的多重分形分布导致该区热液成矿作用的多重分形分布。断裂体系演化过程中不同断裂部位变形和渗透性存在明显差异,数值模拟表明断裂与岩性和流体之间存在强烈的耦合作用并导致不同岩性的断裂具有明显不同的断裂渗透率。断裂-脉体系演化是一个自组织过程,元胞自动机模拟表明只有在分形渗透临界以上连通性较好的脊骨断裂部位是最有利于流体流动和成矿作用的。因此只有在部分有利的断裂部位才能形成矿床,并导致了断裂构造的奇异指数和多重分维谱值明显高于矿床。     

Correlation Fractal and Multifractal Characteristics of Seismic Activity in the Taiwan Area, China

Based on the analysis of newly collected data of plate tectonics, distribution of active faults and crustal deformation, the Taiwan area is divided into two seismic regions and six seismic belts. Then, correlation fractal dimensions of all the regions and belts are calculated, and the fractal characteristics of hypocenteral distribution can be quantitatively analyzed. Finally, multifractal dimensions Dq and f(α) are calculated by using the earthquake catalog of the past 11 years in the Taiwan area. This study indicates that (1) there exists a favorable corresponding relationship between spatial images of seismic activity described with correlation fractal dimension analysis and tectonic settings; (2) the temporal structure of earthquakes is not single but multifractal fractal, and the pattern of Dq variation with time is a good indicator for predicting strong earthquake events.     

Markov Processes and Discrete Multifractals

Fractals and multifractals are a natural consequence of self-similarity resulting from scale-independent processes. Multifractals are spatially intertwined fractals which can be further grouped into two classes according to the characteristics of their fractal dimension spectra: continuous and discrete multifractals. The concept of multifractals emphasizes spatial associations between fractals and fractal spectra. Distinguishing discrete multifractals from continuous multifractals makes it possible to describe discrete physical processes from a multifractal point of view. It is shown that multiplicative cascade processes can generate continuous multifractals and that Markov processes result in discrete multifractals. The latter result provides not only theoretical evidence for existence of discrete multifractals but also a fundamental model illustrating the general properties of discrete multifractals. Classical prefractal examples are used to show how asymmetrical Markov process can be applied to generate prefractal sets and discrete multifractals. The discrete multifractal model based on Markov processes was applied to a dataset of gold deposits in the Great Basin, Nevada, USA. The gold deposits were regarded as discrete multifractals consisting of three spatially interrelated point sets (small, medium, and large deposits) yielding fractal dimensions of 0.541 for the small deposits (<25 tons Au), 0.296 for the medium deposits (25--500 tons Au), and 0.09 for the large deposits (>500 tons Au), respectively.     

新疆阿尔泰地区矿床分布的多重分形分析

对新疆阿尔泰地区 175个热液金、铜、铅、锌、稀有金属矿床的研究表明 ,该区矿床的空间分布为多重分形分布。在 q=- 2～ 14范围内 ,标度指数为 - 5.4 915～ 12 .80 71,奇异指数 a( q)随 q值变化较大 ,为 0 .92 4 8～ 2 .2 865,分维谱具单峰曲线特征。q=0时 ,在 1～ 150 km尺度范围内出现二个分形关系 ,在 1～ 16km尺度范围内 D0 值为 0 .2 3,在 16～ 150 km尺度范围内 D0 值为 1.51。导致该区矿床多重分形分布的主要原因是在不同尺度下矿床的形成控制机理的不同和矿床的勘探研究程度较低 ,该区还有较大的找矿前景。     

红层软岩遇水作用的孔隙结构多重分形特征

红层软岩内部孔隙具有随机、多样化的分布特点,孔隙结构的变化是影响其宏观力学性能的关键所在。由SEM扫描电镜获取岩样不同饱水时间下的细观结构图像,根据盒维数法计算出孔隙的分形维数,发现随着饱水时间的加长,孔隙的分形维数呈现增大趋势。同时对孔隙的数量、大小进行统计分析,得出不同饱水时间下岩样内部孔隙的分布特征。基于多重分形理论,采用统计矩的方法对孔隙结构进行定量表征。结果表明,孔隙结构的分配函数与q阶次趋于线性关系,验证了该结构的自相似性与无标度性,由广义分形维数D(0)>D(1)>D(2)说明了孔隙具有多重分形特征,由多重分形谱参数分析了孔隙结构的不规则性与复杂程度,更好地表征孔隙大小各异的分布情况。结合孔隙结构的多重分形特征与岩样抗压强度,建立起孔隙结构变化与其力学性能的关联性,对研究红层软岩的损伤过程具有一定的指导意义。     

多重分形与地质统计学方法 用于勘查地球化学异常空间结构和奇异性分析

勘查地球化学和地球物理场的局部空间结构变化性应包括空间自相关性以及奇异性 .前者可通过地质统计学中常用的变异函数来实现 ;后者可用多重分形模型进行刻划 .具有自相似性或统计自相似性的多重分形分布 (multifractaldistributions)的奇异性 (α)可以反映地球化学元素在岩石等介质中的局部富集和贫化规律 .而多重分形插值和估计方法可以同时度量以上两种局部结构性质 (空间自相关性以及奇异性 ) ,因而 ,它不仅能够进行空间数据插值 ,同时还能保持和增强数据的局部结构信息 ,这对于地球化学和地球物理异常分析和识别是有益的 .应用该方法处理加拿大NovaScotia省西南部湖泊沉积物地球化学砷等元素数据表明 ,地球化学数据的局部奇异性在该区能够反映局部金和钨 -锡 -铀矿化蚀变带或岩相变化以及构造交汇等局部成矿有利部位 .     

多维分形理论和地球化学元素分布规律

多维分形模型不仅采用常规的低阶矩统计, 而且采用高阶矩统计对多维分形分布进行度量, 从而能较细致地刻划正常值以及异常值.地球化学元素的正常值往往服从统计学中的大数定量, 即满足正态分布或对数正态分布, 然而异常值会服从分形分布(Preato).介绍了多维分形领域中的最新发展以及在地球化学研究中特别是研究超常元素空间分布和富集规律中的应用.结果表明, 通常的统计方法只对应于多维分形围绕均值周围的局部特征.为了有效地研究异常值的分布和富集规律, 建议采用高阶矩统计方法和多维分形方法, 并给出了两种分析地球化学元素, 并突出异常值贡献的方法.这些方法不仅可应用于研究微量元素的空间分布和富集规律, 而且可以区分地球化学背景与矿化有关的异常值.还介绍了该方法在对加拿大B.C.省西北部Mitchell-Sulphurets地区金铜矿化蚀变带研究中的应用.      

Multifractality as a Measure of Spatial Distribution of Geochemical Patterns

To quantify the spatial distribution of geochemical elements, the multifractality indices for Zn, Cu, Pt, Pd, Cr, Ni, Co, Pb, and As in lake-sediment samples in the Shining Tree area in the Abitibi area of Ontario are determined. The characterization of multifractal distribution patterns is based on the box-counting moment method and involves three functions: a mass exponent function (q); Coarse Hölder Exponent (q); and fractal dimension spectrum f( (q)). Properties of these functions at different values of q, characterize the spatial distribution of the variable under study. It is shown that the degree of multifractality defined by (1) can be used as a measure of irregularity of geochemical spatial dispersion patterns. The variations of Zn and Cu in the study area are characterized by relatively low degree of multifractality, whereas those for Pt, Pd, Cr, Ni, and Co; and particularly for As and Pb are characterized by higher multifractality indices.In the case of Zn and Cu, singularity spectra are close to a monofractal compared to the ones for As an Pb. The determination of multifractality indices allows us, in a quantitative way, to study the pattern of metal dispersions and link them to different physical processes, such as metal adsorption by organic material or glaciogenic processes.     

Multifractal Modeling and Lacunarity Analysis

The so-called gliding box method of lacunarity analysis has been investigated for implementing multifractal modeling in comparison with the ordinary box-counting method. Newly derived results show that the lacunarity index is associated with the dimension (codimension) of fractal, multifractal and some types of nonfractals in power-law relations involving box size; the exponent of the lacunarity function corresponds to the fractal codimension (E – D) for fractals and nonfractals, and to the correlation codimension (E – lpar;2)) for multifractals. These results are illustrated with two case studies: De Wijs's zinc concentration values from the Pulacayo sphalerite-quartz vein in Bolivia and Cochran's tree seedlings example. Both yield low lacunarities and slightly depart from translational invariance.     

奇异性理论在个旧锡铜矿产资源预测中的应用: 成矿弱信息提取和复合信息分解

本研究的目的是应用非线性理论和高新信息处理技术获取矿产资源预测综合信息, 开展以有色金属和贵金属矿产资源潜力评价和预测靶区圈定, 提交个旧及周边地区矿产资源潜力分布图.围绕该研究任务, 重点开展了如何应用奇异性理论和方法, 对比个旧东西矿区的异同.由于区域构造和岩体分布等空间变化性, 导致东西区成矿背景存在较大差异, 受出露地表或近地表矿体分布和矿山开采的影响, 东西区的成矿异常强度和大小都存在较大差异, 东区总体呈高背景而西区为低背景, 因而, 对东西区的成矿信息对比研究和异常圈定相对困难.采用局部奇异性分析方法从地球化学分形密度的角度圈定了局部异常, 在东西区均较好地反映了致矿地球化学异常的分布, 同时采用广义自相似分析方法分解了综合地球化学异常和背景.结果表明, 东西区地球化学背景差异悬殊, 而局部异常具有显著的自相似性.据此在东西区同时圈定的局部异常具有内在的相似性和表现形式上的多样性, 以此为依据所圈定的靶区均具有找矿意义.      

Fractal and Multifractal Properties of the Spatial Distribution of Natural Fractures--Analyses and Applications

The Cantor's dust theory is applied to investigate the scaling properites of the spatial distribution of natural fractures obtained from detailed scanline surveys of 27 field sites in the Appalachian Plateau of western New York, USA. The results obtained in this study indicate: 1) fracture spacing is characterized by fractal and multifractal properties. On small scales analyses yield an average fractal dimension of 0.15, which suggests a very high degree of clustering. In contrast, on large scales, fractures tend to be more regular and evenly distributed with an average fracture dimension of 0.52; 2) fractal dimension varies with different sets in different orientations, which can be attributed to interactions between pre-existing fractures and younger ones, as well as variations of the intensity of the stresses under which the fractures were formed; 3) a time sequence of fracture set formation can be proposed based on fractal and multifractal analyses, which consists of (from old to young): N-S, NW, ENE, and NE-striking sets. This time sequence is confirmed by the study of the abutting relationships of different fracture sets observed in the field.     

Fractal and Multifractal Propertiesof the Spatial Distribution of Natural Fractures——Analyses and Applications

The Cantor's dust theory is applied to investigate the scaling properties of the spatial distribution of natural fractures obtained from detailed scanline surveys of 27 field sites in the Appalachian Plateau of western New York, USA. The results obtained in this study indicate: 1) fracture spacing is characterized by fractal and multifractal properties. On small scales analyses yield an average fractal dimension of 0.15, which suggests a very high degree of clustering. In contrast, on large scales, fractures tend to be more regular and evenly distributed with an average fracture dimension of 0.52; 2) fractal dimension varies with different sets in different orientations, which can be attributed to interactions between pre-existing fractures and younger ones, as well as variations of the intensity of the stresses under which the fractures were formed; 3) a time sequence of fracture set formation can be proposed based on fractal and multifractal analyses, which consists of (from old to young): N-S, NW, EN     

Fractal and Multifractal Modeling of Hydrothermal Mineral Deposit Spectrum： Application to Gold Deposits in Abitibi Area, Ontario, Canada

A number of fractal/multifractal methods are introduced for quantifying the mineral de-lmsit spectrum which include a number-size, grade-tonnage model, power spectrmn model,multi-fractal model and an eigeavalue spectrmn model The first two models characterize mineral deposits spec-tra based on relationships among the measures of mineral deposits.These include the number of deposits,size of deposits,concentration and volume of mineral deposits.The last three methods that deal with the spatial-temporal spectra of mineral deposit studies are all expected to be popularized in near future.A case study of hydrothermal gold deposits from the Abitibi area,a world-class mineral district is used to demonstrate the principle as well as the applications of methods proposed in this paper,It has been shown that fractal and multifractal models are generally applicable to modeling of mineral deposits and occurrences.Clusters of mineral deposits were identified by several methods including the power spectral eral deposits in the Timmins and Kirkland Lake camps.     

Random Difference of the Trace Element Distribution in Skarn and Marbles from Shizishan Orefield,Anhui Province,China

Spatial distribution patterns of element concentrations can reflect the information of the mineralization processes. Both the Hurst exponent calculated by R/S analysis and the generalized fractal dimension calculated by using the multifractal model are important parameters for describing the spatial distribution of elements. Five long drill holes, named as M1, S1, S2,S3, and S4, have been selected in the Shizishan (狮子山) skarn orefield in Tongling (铜陵), Anhui (安徽) Province, China. Marbles are well developed around MI and skarn rocks are largely distributed along S1, S2, S3, and S4 drill holes. The drill holes were sampled evenly with an interval of 10 m and 16 trace elements have been measured. The mean of the △D(q) (the height of the generalized dimension spectrum) in the MI drill hole is the lowest. In addition, the mean of the Hurst exponents of the 16 elements in the MI drill hole is also much smaller than that of S1, S2, S3, S4 drill holes, which is in accordance with the analysis of the generalized dimension. It is indicated by the generalized dimension and Hurst exponent that the distribution of trace elements in the marbles is more random than that in the skarn. The result suggests that the mineralization process can change the randomness and persistence features of the element distribution.