内蒙古白音郭勒地区地球化学异常提取方法对比研究

勘查地球化学的基础性问题是如何合理地提取地球化学异常下限,这是影响勘查地球化学在矿产勘查中效果的主要因素。利用SPSS软件,通过含量对数频率直方图,结合偏度、峰度检验法检验元素的含量分布型式,发现研究区的Cu、Ag、Pb、Zn元素不服从正态或对数正态分布,而呈现多峰态、高丛集的多重分形特征。采用传统的统计学方法、85%累计频率法、含量-总量多重分形法提取相关元素地球化学异常,并进行对比研究。研究结果表明,基于元素空间分布及含量分布规律的含量-总量多重分形方法,有效克服了传统方法的局限,比较客观地反映研究区的地球化学异常信息,是研究地球化学异常比较合理的方法。     

分形方法在海南屯昌地区地球化学找矿中的应用

化探异常下限的确定是勘查地球化学有效地应用于矿产勘查的一个关键性环节。传统的异常下限计算方法是以地球化学元素含量数据服从正态或对数正态分布为前提,而本文采用的元素含量-总量多重分形计算异常下限的方法,则基于地球化学变量服从分形与多重分形分布的理论与方法。作者以海南屯昌某测区化探数据为例,运用传统元素含量对数正态分布和元素含量-总量多重分形两种计算模型确定了测区主要指示元素的异常下限并圈定、对比了其化探异常图。本区槽井探对化探异常的揭露表明,采用元素含量-总量的分形方法确定化探异常下限的尝试是成功而有效的。     

多重分形与地球化学元素的分布规律

为进一步探讨用分形与多重分形的方法研究地球化学场中元素的分布规律的重要意义，运用Q-Q图和直方图探讨了元素的空间分布规律，随后运用多重分形矩方法研究了安徽省长江以南以北各约22000km^2和18100km^2区域内5489个和4524个水系沉积物样品中14种元素的分形分布规律。结果表明，金属地球化学场元素在空间上的分布并不是简单的正态或对数正态分布，而四连续多重分形分布，其α-f(α)曲线上凸且连续，拥有主要大型矿床的安徽江南地区α-f(α)曲线的开口明显大于成矿相对较弱的安徽江北地区。元素的多重分形谱函数的形态特征对区域成矿潜力研究将具有一定的指示意义。     

矩分析法及其在粤北韶关地区金属成矿作用研究中的应用

采用多重分形矩分析法探讨了粤北韶关地区4292km^2内1448个基岩样品的25项元素的分形分布规律。结果表明，金属地球化学场元素的多重分形谱函数上凸且连续，其多重分形谱函数的开口大小在某种程度上能反映地球化学场的浓集程度。地球化学场中元素在空间上的分布具有连续多重分形特征，与成矿密切相关的微量元素一般服从左侧开口明显大于右侧开口的连续多重分形左偏模式，而非主要成矿元素则对应右侧开口大的连续多重分形右偏模式。     

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 .     

基于"元素含量-面积"模型方法的地球化学场的多重分形模式分析

从多重分形理论出发,在赤峰地区的2个区域应用"元素含量-面积(C-A)"模型方法.对"元素含量-面积"双对数图的形态进行分析,将地球化学异常多重分形特征模式分为3种类型:模式Ⅰ为可拟合为2条直线段的简单多重分形模式,具有该模式的元素在研究区内没有成矿富集的趋势,不存在实质性的致矿异常;模式Ⅱ为可以拟合为3条直线段的高富集多重分形模式,它在模式Ⅰ的基础上叠加有高含量的异常场,具有该模式的元素在研究区内存在较强的局部富集,成矿的可能性很大;模式Ⅲ为可拟合成3条直线段的低富集多重分形模式,它在模式Ⅰ的基础上叠加的是较弱的异常场,具有该模式的元素在研究区内有较弱的矿化作用.在此基础上,分析了元素的成矿富集规律和空间分布特征,确定了区域异常和局部异常的异常下限,划分了地球化学背景、区域异常和局部异常.     

分形不变分布及其在山东地区金矿床中的应用

自相似性(标度不变性)是地学中的一个普遍现象。研究表明,地球化学元素含量、矿床储量规模及其空间分布具有分形结构。分形不变分布的特点要求大于某一尺度物体的数目与物体大小之间存在幂指数关系。论证了幂函数分布、帕累托分布、对数正态分布和齐波夫定律在一定条件下具有分形不变性质,它们是分形模型的数学基础。基于分形模型,用求和方法确定中国山东省金地球化学元素异常值范围。等值线大于或等于金地球化学元素临界值(200×10-9)围成的异常面积包含了已知的大型、超大型金矿床。     

个旧锡多金属矿集区高松矿田矿化元素局部富集的奇异性特征

多重分形理论能够有效地分析地球化元素局部富集和贫化规律。对取自个旧高松矿田的1 783件断裂构造地球化学样品的13种元素进行了多重分形统计以及局部奇异性方法分析。结果表明:多重分形维谱函数α-f(α)曲线呈连续上凸的特征,曲线的不对称反映了元素局部富集程度差异,并据此将13种元素划分为包含Sn、Cu、Pb、Ag、As、Mn在内的主要成矿元素组合以及包含Zn、Sb、Cd、W、Mo、Bi、Hg的次要成矿元素或伴生元素组合。多重分形的特征值τ″(1)以及Dq的变化规律表明:在主要成矿元素中,Sn在断裂空间上局部富集程度最高,其次为Ag,而Cu相对最低,各元素的τ″(1)值与对应的变异系数的大小具有较为显著的相关性;各元素在空间上的奇异性指数α增强了地球化学富集地段的指示信息,可以作为判别局部富集的重要参数。运用多重分形方法可揭示矿化元素局部富集的奇异性特征以及空间局部富集规律。     

基于“元素含量-面积”模型方法的地球化学场的多重分形模式分析

从多重分形理论出发，在赤峰地区的2个区域应用“元素含量-面积（C—A）”模型方法。对“元素含量-面积”双对数图的形态进行分析，将地球化学异常多重分形特征模式分为3种类型：模式Ⅰ为可拟合为2条直线段的简单多重分形模式，具有该模式的元素在研究区内没有成矿富集的趋势，不存在实质性的致矿异常；模式Ⅱ为可以拟合为3条直线段的高富集多重分形模式，它在模式Ⅰ的基础上叠加有高含量的异常场，具有该模式的元素在研究区内存在较强的局部富集，成矿的可能性很大：模式Ⅲ为可拟合成3条直线段的低富集多重分形模式，它在模式Ⅰ的基础上叠加的是较弱的异常场，具有该模式的元素在研究区内有较弱的矿化作用。在此基础上，分析了元素的成矿富集规律和空间分布特征，确定了区域异常和局部异常的异常下限，划分了地球化学背景、区域异常和局部异常。     

多重分形与地质统计学方法在粤北刘家山地区矿化指示中的应用

为了解地球化学元素在岩石等介质中的局部富集和贫化规律,采用多重分形和地质统计学方法来分析其空间自相关性及奇异性,多重分形方法通过多重分形模型来刻画,地质统计学方法通过变异函数来实现。应用这两种方法处理粤北刘家山地区1∶5万水系沉积物地球化学各元素数据表明,地球化学数据的局部奇异性在该区可反映铅锌铜矿化蚀变带等局部成矿有利部位。为进一步研究异常与奇异性区的关系采用分形滤波技术(S-A法)对该区成矿主元素Pb、Zn进行分析,发现由S-A法分解得到的异常区与奇异性区一致,并且得出由S-A法分解的异常具有局部奇异性的结论。研究区内具有明显奇异性的地区也即元素富集区域是铅锌矿异常区域,它们与铅锌矿成矿作用和已知矿床的赋存密切相关, 这也为该地区元素的成矿潜力评价提供了重要的线索。     

Separation of a geochemical anomaly from background by fractal and U-statistic methods,a case study: Khooni district,Central Iran

Separation of geochemical anomalies from background are one of the important steps in mineral exploration. The Khooni mineral district (Central Iran) has complex geochemical surface expression due to a complex geological background. This region was chosen as a study area for recognition of the spatial distribution of geochemical elements and separating anomalies from background using stream sediment geochemical data. In the past decades, geochemical anomalies have been identified by means of various methods. Some of these separation methods include: statistical analysis methods, spatial statistical methods and fractal and multi-fractal methods. In this article, two efficient methods, i.e. U-statistics and the fractal concentration-area for separation and detection of anomalous areas of the background were used. The U spatial statistic method is a weighted mean, which considers sampling point positions and their spatial relation in the estimation of anomaly location. Also, fractal and multi-fractal models have also been applied to separate anomalies from background values. In this paper, the concentration–area model (C–A) was suggested to separate the anomaly of background. For this purpose, about 256 stream sediment samples were collected and analyzed. Then anomaly maps of elements were generated based on U spatial statistics and the C-A fractal methods for Au, As and Sb elements. According to obtained results, the U-statistics method performed better than C-A method. Because the comparisons of the known deposits and occurrences against the anomalous area created using thresholds from U-statistics and C-A method show that the spatial U-statistics method hits all of 3 known deposits and occurrences, the C-A fractal method hits 1 and fails 2. In addition, the results showed that these methods with regard to spatial distribution and variability within neighboring samples, in addition to concentration value frequency distributions and correlation coefficients, have more accurate results than the traditional approaches.     

Fractal-Based Wavelet Filter for Separating Geophysical or Geochemical Anomalies from Background

The widely used wavelet filtering technique holds potential to approach anomaly–background separation in geophysical and geochemical data processing. Wavelet statistics provide crucial information on such filtering methods. In general, conventional (Gaussian-type) statistical modeling is insufficient to adequately describe the heavily tailed and sharply peaked (at zero) distribution of the wavelet coefficients of irregular geo-anomaly patterns. This paper demonstrates that the cumulative (frequency) number of the wavelet coefficient yields a power-law scaling relationship with the coefficient based on wavelet transform of a fractal/singular measure. This wavelet coefficient–cumulative number power-law model is proven to be more flexible and appropriate than the Gaussian model for characterizing the scaling nature of the coefficient distribution. Accordingly, a fractal-based filtering technique is developed based on the wavelet statistical model to decompose mixed patterns into components based on the distinct self-similarities identified in the wavelet domain. The decomposition scheme of the fractal-based wavelet filtering method considers not only the coefficient frequency distribution but also the fractal spectrum of singularities and the self-similarity of real-world features. Finally, a synthetic data test and real applications from two metallogenic provinces of China are used to validate the proposed fractal filtering method for anomaly–background separation and identification of geophysical or geochemical anomalies related to mineralization and other geological features.     

基于MAPGIS的分形方法确定化探异常

地球化学元素的异常下限值确定是地球化学中重要的问题之一,目前还没有一个令人满意的具有科学依据的计算方法。传统的化探异常下限值计算是基于元素的地球化学分布呈正态分布或元素含量在空间上呈连续的变化这一假设为基础的,而事实上地球化学元素含量的空间分布是极其复杂的,研究表明,地球化学景观可能是一个具有低维吸引子的混沌系统,元素的地球化学背景值和异常具有各自独立的幂指数关系,由此导致了一种多重分形分布,因而可以利用元素的分形分布求出其异常下限。利用元素的分形分布求异常下限的几种常用方法均是以求取不同尺度r下,对应的N(r)数。如果用手工统计方法计算,计算过程简单但繁琐,地理信息系统((}IS)可以实现图形单元的动态查询和属性统计,这种特性很适合于统计不同尺度r下对应的N(r),因此,可以将分形方法与地理信息系统加以结合,在CIS平台上对地学图形和属性信息进行分析及统计处理,将原来比较繁杂的分形计算操作变得方便简捷,易于实现。本文以武汉中地信息公司开发的．MAPGIS地理信息系统为例,对河北某地1：5万Cu元素化探数据进行了处理,具体说明了以MAPGIS为工具,利用分形方法求取元素化探异常下限的过程,并将计算结果与传统异常下限计算方法所得的结果进行了对比,所得的异常下限值相近或一致,但由于传统的计算方法不仅要求对原始数据进行预处理,而且在下限值的确定上需要结合本地区的实际地质情况确定,因此人为干扰因素较大,而利用基于MAPGIS的分形方法计算元素异常下限值不仅操作简单,而且计算时由于不受元素特高值的影响,因而不用对原始数据进行预处理,人为干扰因素较少。通过对比得知该方法在实践工作中可行。     

Identification of Geochemical Anomaly by Multifractal Analysis

The separation of anomalies from geochemical background is an important part of data analysis because lack of such identifications might have profound influence on or even distort the final analysis results. In this article, 1 672 geochemical analytical data of 11 elements, including Cu, Mo, Ag, Sn, and others, from a region within Tibet, South China, are used as one example. Together with the traditional anomaly recognition method of using the iterative mean ±2σ, local multifractality theory has been utilized to delineate the ranges of geochemical anomalies of the elements. To different degrees, on the basis of original data mapping, C-A fractal analysis and singularity exponents, Sn differs from the other 10 elements. Moreover, geochemical mapping results based on values of the multifractal asymmetry index for all elements delineate the highly anomalous area. Similar to other 10 elements, the anomalous areas of Sn delineated by the asymmetry index distribute along the main structure orientations. According to the asymmetry indexes, the 11 elements could be classified into 3 groups: (1) Ag and Au, (2) As-Sb-Cu-Pb-Zn-Mo, and (3) Sn-Bi-W.This paragenetic association of elements can be used to interpret possible origins of mineralization, which is in agreement with petrological analysis and field survey results.     

Fractally Invariant Distributions and an Application in Geochemical Exploration

Fractal modelling has been applied extensively as a means of characterizing the spatial distribution of geological phenomena that display self-similarity at differing scales of measurement. A fractal distribution exists where the number of objects exhibiting values larger than a specified magnitude displays a power-law dependence on that magnitude, and where this relationship is scale-invariant. This paper shows that a number of distributions, including power-function, Pareto, log-normal and Zipf, display fractal properties under certain conditions and that this may be used as the mathematical basis for developing fractal models for data exhibiting such distributions. Population limits, derived from fractal modelling using a summation method, are compared with those derived from more conventional probability plot modelling of stream sediment geochemical data from north-eastern New South Wales. Despite some degree of subjectivity in determining the number of populations to use in the models, both the fractal and probability plot modelling have assisted in isolating anomalous observations in the geochemical data related to the occurrence of mineralisation or lithological differences between sub-catchments. Thresholds for the main background populations determined by the fractal model are similar to those established using probability plot modelling, however the summation method displays less capacity to separate out anomalous populations, especially where such populations display extensive overlap. This suggests, in the geochemical data example provided, that subtle differences in the population parameters may not significantly alter the fractal dimension.     

多重地球化学背景下地球化学弱异常增强识别与信息提取

为对钦州湾-杭州湾成矿带(南段)庞西垌地区地球化学数据进行异常识别研究与信息提取,利用含量-面积法(C-A)得出庞西垌地区成矿主元素的异常下限,得到各元素异常分布图,并与已知矿(床)点进行叠加分析,发现已知矿(床)点与C-A法分析得到的异常区基本吻合,可根据该异常区预测未知矿床,从而为该研究区矿产资源潜力评价提供依据。为进一步从研究区复杂的地球化学背景中分离出与成矿有关的地球化学异常,采用分形滤波技术(S-A)提取致矿异常。研究表明,S-A法可在C-A法揭示的区域异常的基础上更深层次地提取出与矿化有关的局部异常用以反映研究区的多重地球化学背景,S-A法可有效地使弱异常增强进而提取出致矿异常,为庞西垌地区探寻隐伏矿体提供依据。     

Multifractal IDW interpolation and fractal filtering method in environmental studies: an application on regional stream sediments of (Italy), Campania region

In recent years environmental geochemical mapping has assumed an increasing relevance and separation of background values to evaluate pollution is, probably, even more critical than the separation between background and anomalies in mineral prospecting studies. The recognition of background values assumes particular relevance as a function of national environmental legislation, which fixes intervention limits for some elements, such as the harmful ones (e.g. As, Cd, Hg, Pb). In this paper a recently developed multifractal IDW interpolation method and a fractal filtering technique are applied to separate natural background and anthropogenic values for the compilation of environmental geochemical mapping from stream sediment samples of Campania region (Italy), where no mineralization occurs. To discuss the application of these recently developed techniques the elements Pb and U were selected because they show two completely different situations, the high Pb values being mostly of anthropogenic origin and high U values being mostly of geogenic origin. The new fractal filtering method works well in both extreme situations.     

多重分形方法识别铜陵矿区土壤中Cd的地球化学异常

土壤元素异常下限值的确定对环境地球化学评价具有重要意义。传统异常下限值计算方法仅适用于元素含量数据呈正态分布的情况,而事实上土壤元素含量的空间分布极其复杂,很可能具有多重分形分布特征。本文利用校正累积频率分形方法确定铜陵矿区土壤中Cd的异常下限值为1．687mg／kg。并据此圈定了异常范围。与传统方法所确定的异常下限值及相应异常区域对比,分形方法圈定的异常区域范围更广,更为合理、有效。     

S-A多重分形法在地球化学异常 圈定中的对比应用—以甘肃文康地区为例

通过对甘肃省陇南文康地区的地质背景分析,采用区域1:5万水系沉积物测量的17种常量元素含量数据,分别运用传统统计学方法、S-A（能谱密度-累计面积）多重分形滤波法,确定成矿元素（以Au为例）异常下限值,圈定化探异常。结果表明,与传统方法相比,S-A多重分形法所圈定的异常面积小、数量多,传统统计法圈定的面积较大;两种方法圈定的异常展布方向基本一致,与研究区内已知的矿点吻合度高。本次研究认为S-A多重分形法所圈定的异常基本位于传统方法所圈定异常的内带之中,重点突出,与矿床空间位置对应关系较好,便于野外开展工作。同时在传统异常周边提取了部分低背景区的弱异常,这些弱异常可作为下一步找矿工作的新靶区。