广东庞西垌地区地球化学组合异常识别与提取

为了解地球化学元素空间组合分布规律,采用因子泛克里格法构建组合模型用于识别组合地球化学异常,使用分形滤波技术强化弱异常并分离异常与背景.将组合异常模型和分形滤波技术用于钦杭结合带南段庞西垌地区1∶5万水系沉积物地球化学数据进行处理分析,目的在于寻求地球化学致矿异常,寻找未知矿床.研究结果表明,根据组合变量提取出的组合异常与研究区已知矿化地段重合性较高,尽管组合异常不足以体现局部异常但高异常区可为探寻未知矿床指明方向,且在此基础上采用分形滤波技术分离出的异常与背景能够为下一步的勘探提供指导作用.     

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.     

n维自仿射分形及其在地球化学中的应用

分形概念应用在地球科学中来刻画地质量和物体的自相似特征。研究表明分形模型常常提供有力工具来刻画地质量和物体的基本空间分布结构。本文提出了n维自仿射分形的检验与定量评定方法。通过实例，说明n维自仿射分形的方法在实际问题中的方法和步骤，并解释了分维数的实际意义。分维数足反映区域化变量在某方向变化程度的定量指标。该方法不仅适用于地球化学金元素和银元素数据，而且还适用于其他元素和地质数据，具有普遍的意义。     

分形技术在攀西地区铂族元素异常查证中的应用

本文在简要介绍分形技术及分形模型的基础上,应用分形模型研究了化探数据的元素含量与对应面积,发现数据存在分形结构,并确定了化探数据的异常下限,经和传统方法处理后所得到的结果进行比较,发现分形处理结果较传统方法的效果更好。     

分形求和法及其在地球化学数据分组中的应用

分形建模广泛地应用于具有自相似性不同尺度测量的地质现象空间分布特征。分形分布的特点要求大于等于某一尺度的数目,与物体大小之间存在幂函数关系,这种关系具有尺度不变性。这里提出的分形求和法可以确定地球化学数据分组界限。应用澳大利亚新南威尔士东北地区汇水沉积物地球化学数据,采用分形求和法确定其分组界限,并与传统的概率图模型结果进行比较。铜(Cu)元素数据划分二个部分,一部分是元素含量少于20 ppm的正态分布数据,另一部分是元素含量大于20 ppm的多个对数正态分布数据,能识别第三纪玄武岩区域和铜的主要矿化区。这一结论与使用传统的概率图模型方法得到的结论一致。该方法不仅适用于地球化学铜元素数据,而且还适用于其它元素和地质数据,具有普遍的意义。     

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.     

2011~2020年勘查地球化学数据处理研究进展

我国建立了包含海量数据的高质量的勘查地球化学数据库,为矿产勘查、环境评价和地质调查等提供了重要的数据支撑。如何高效处理勘查地球化学数据,并从中发掘和识别深层次信息一直是勘查地球化学学科研究的热点和前沿领域。本文在系统调研国内外学者过去十年发表的论著基础上,对勘查地球化学数据处理方法进行分析与对比,从勘查地球化学数据库建设、地球化学异常识别及其不确定性评价等方面概述了我国近十年来在该领域取得的主要研究进展,包括:(1)分形与多重分形模型由于考虑了地球化学空间模式的复杂性和尺度不变性,在全球范围内得到极大的发展和推广,我国学者引领了基于分形与多重分形的勘查地球化学数据处理;(2)机器学习和大数据思维开始在该领域启蒙,并迅速得到关注,正在成为研究热点和前沿领域,我国学者率先开展基于机器学习算法的勘查地球化学大数据挖掘研究;(3)我国学者需要进一步加强勘查地球化学数据缺失值处理以及成分数据闭合效应研究。今后该领域应进一步加强对弱缓地球化学异常识别、异常不确定性评价以及异常识别与其形成机理相结合等方面的研究。     

Comparison of mineralization pattern of geochemical data in spatial and position-scale domain using new DWT- PCA approach

In the current research to determine the mineralization pattern and discuss the mineralization components, the information of position - scale domain of geochemical data has been analyzed. A new method is proposed based on coupling discrete wavelet transforms (DWT) and principal component analysis (PCA) for mineralization elements forecasting applications. The results of this study indicate the potential of DWT–PCA method for geochemical data processing. Wavelet transform (WT), as a multi-spectral analysis method, can decompose the spatial and temporal signals into different frequencies. The features of mineralization can be identified using the position - scale domain of geochemical data that may not be achievable in spatial domain. The geochemical data from the Dalli region have been processed in the spatial domain using PCA. The surface geochemical data of 30 elements have been transformed to position–scale domain using two-dimensional discrete wavelet transform (2DDWT). Wavelet functions (WFs) of Haar, Coiflet2, Biorthogonal3.3 and Symlet7 have been applied separately to decompose the geochemical data to high and low frequencies in one level. To obtain more accurate and complete information of mineralization, a new index has been presented based on wavelet coefficients. Based on this new index, significant results have been obtained by using PCA of the index. The coefficients distribution map (CDM) as a new exploratory criterion has been generated based on 2DDWT to show the geochemical distribution map (GDM). Finally, the results of WT have been compared with the results of spatial domain and the best method of wavelet for interpretation of geochemical data has been introduced. The results of geochemical data analysis by DWT–PCA approach have been confirmed by the exploratory drillings in the study area.     

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.     

Geochemical baseline of trace elements in the sediment in Dexing area,South China

A baseline might be used as a point of reference to monitor change from some specific data without concern for whether the baseline determination is natural or has been changed by human activity. We selected 326 sediment samples from Dexing area, South China, and analyzed for 17 chemical elements. The geochemical baseline was predicted with the method of the normalization procedure combined with the relative cumulative frequency curve. The results indicate Al was the best reference element for the normalization procedure among four potential reference elements (Al, Fe, Ti, and Mn). The baseline value range obtained from the normalization procedure method included both the regional geochemical background of the sediment and the median value of the measured contents. The median value of baselines obtained from relative cumulative frequency method was lower than that obtained from normalization procedure method. In contrast to the geochemical patterns of heavy metals in 1987, the spatial distribution of anomalies sprawled in 2004 in study area, especially for Cu, Pb, Zn, Cd, As, Fe, and Cr.     

不同化探数据处理方法在找矿中的应用——以四川会理县银星铁铜矿为例

在四川会理县银星地区1:2.5万化探工作中,分别采用传统数据处理方法、衬度异常法、分形法进行数据处理,分析结果认为:衬度异常法计算过程简单,但对高背景区域异常的分解效果不明显;分形法计算过程复杂,却能强化不同背景区的地球化学异常。具体工作中通过不同数据处理方法的组合,择优进行推断解译,具有强化弱异常信息,提高找矿效率的重要功效。     

Multidimensional Self-Affine Distribution with Application in Geochemistry

In this paper, we present the conception of the multidimensional self-affine distribution and show that the multidimensional self-affine distribution possesses the fractal property of scale-invariance under truncation, which means that theoretical study of fractals has expanded from univariate cases to multivariate cases. Application of the multidimensional self-affine distribution is illustrated by means of geochemical Au and Ag elements data sets. The fractal dimension is a parameter which can quantitatively explain the variation of geochemical elements data on some orientation. This method is applied to Au data and Ag data, but also suited for other geochemical elements data or geological data. Theory of multivariate fractal can be applied for the study of change courses of fractal system, that is, fractal dynamics.     

Application of fractal models to characterization of vertical distribution of geochemical element concentration

Characterization of the vertical distribution of geochemical element concentration is essential for economic planning in the mining industry. 10 mineralized boreholes and 1 non-mineralized borehole from the Qulong copper deposit, Tibet, western China, were collected to identify the vertical distribution properties of Cu values using fractal models. The vertical distribution of Cu values in mineralized and non-mineralized boreholes shows a positive skewed distribution in the former and multimodal distribution in the latter. The results obtained by the box counting method show that the vertical distributions of Cu values in mineralized and non-mineralized boreholes exhibit self-similarity with box dimensions ranging from 1.28 to 1.37. The box dimensions of mineralized boreholes are greater than that of Cu values in the non-mineralized borehole, indicating that the mineralization makes the distribution of Cu values more irregular. The power-law frequency analysis reveals that Cu values in mineralized boreholes are bifractal. The two portions of the plot define a crossover point at 0.33%, for Cu values less than and greater than 0.33, fractal dimensions range from 0.1 to 0.65, in non-mineralized rocks, and range from 2.71 to 5.79, in the mineralized rocks. Hurst exponents for mineralized boreholes occur at 0.8, which are greater than 0.5, indicating that Qulong copper deposit has a good continuity of mineralization.     

The geochemical multi-fractal characteristics and mineralization of the Dehelongwa copper-gold deposit

The spatial distribution of ore-forming elements is the result of interaction and influence among multiple factors in the process of mineralization, and is the specific embodiment of non-linearity and coupling of mineralization. The fractal theory has such functions as to characterize non-lineariry and coupling, and can find out the deterministic law from the complicated coupling process. The primary geochemical fractal distribution of metallogenic elements such as Cu and Au possesses the characteristics of multi-fractal distribution in the Dehelongwa copper-gold deposit. Copper follows 2-d fractal distribution, and Au follows 3- or 4-d fractal distribution. The primary geo- chemical fractal distribution has a certain similarity on the same prospecting line, and this similarity is not obvious among different prospecting lines. The secondary geochemical fractal distribution of Cu and Au is higher in similar- ity, and simpler than the primary geochemical fractal distribution. These results show that the mineralization of Cu and Au is out of sync and also is inconsistent in this deposit, and the mineralization of Cu mainly experienced two mineralization stages, while the mineralization of Au experienced three to four mineralization stages. Besides the mineralization of Cu and Au shows a certain direction and along the strike of vertical orebodies it is relatively bal- anced. While along the strike of the ore bodies the mineralization of Cu and Au shows a significant difference. The hypergenic geologic process has a certain effect on the balance of spatial distribution of Cu and Au. From these it can be seen that the mineralization process of this deposit is well characterized by the geochemical fractal distribu- tion of Cu and Au.     

分形方法在金矿化时空结构分析中的应用

以川西北地区微细浸染型金矿为例 ,采用分形方法探讨了金矿化的时空结构特征。研究表明 ,分数维 D值的大小能表征金矿化品位分布的复杂性 ,成矿过程中相关元素组合存在相似的分形结构。利用主成矿元素及相关元素品位数据的分形结构特征可以指示成矿期次 ,厘定成矿演化的时间结构 ;利用地球化学数据的二维空间序列的 R/ S分析方法 ,可以较精确有效地厘定金矿化的空间结构特征。分形方法在矿化时空结构分析中有着极为广阔的应用前景     

Stream sediment geochemical exploration for gold in Central Eastern Desert,Egypt: Application of the concentration-number fractal model,factor analysis,and geochemical mineralization probability index

Geochemical exploration by stream sediment sampling using bulk leach extractable gold (BLEG) technique and applying concentration-number (C-N) fractal model, factor analysis (FA), and geochemical mineralization probability index (GMPI) resulted in the recognition of new Au occurrences around the Sukari gold mine in the central Eastern Desert of Egypt. The geochemical data of 128 stream sediment samples collected from the study area was used for delineating the geochemical anomalies and characterizing the dispersion trains of ore and associated elements (Au, Ag, As, Sb, Cu, Pb, Zn, Mo). Statistical analysis of the geochemical data applying the C-N fractal modeling enabled us to identify significant anomaly and background populations of the investigated elements and to construct reliable geochemical anomaly maps. Factor analysis using centered log-ratios (CLR), to address the problem of closed compositional data, revealed significant element associations for mineralization (Au, As, Mo, Zn, Ba), country rock compositions (Rb, Li, Be, Sn, Bi for granite, and Co, Cr, Ni for mafic rocks), and element mobility (e.g. Sb, Zr, and Ag). Weak and moderate Au anomalies that cannot be detected by factor score maps can be delineated clearly by using the C-N fractal method and GMPI distribution map. Our study revealed that Ag, As, and Sb are the main pathfinder elements for gold mineralization in arid to semiarid regions exemplified by the Sukari gold district. Silver can be used as a “direct” pathfinder, whereas As and Sb are “indirect” pathfinders for Au in such regions. The spatial distribution of Au and Ag anomalies indicate that gold mineralization in the Sukari district is structurally controlled. However, the spatial distribution of Cu, Pb, Zn, and Mo is controlled by mineralogical and lithological factors and is not related to any significant base metal deposits.     

华南陆块铜的地球化学块体与成矿省的关系

在区域化探全国扫面计划1∶20万水系沉积物样品Cu含量的基础上,描述了华南陆块铜地球化学块体的空间分布特征,并分析了它们与地质体、已知的铜成矿省(矿集区)在空间上的对应关系。发现华南陆块的铜地球化学块体主要分布于扬子地块西南缘,长江中下游、西秦岭、三江地区和湘粤桂交界区。其中扬子地块西南缘铜地球化学块体主要与峨眉山玄武岩的铜高背景值有关,其他异常与海西期镁铁质超镁铁质岩有关的铜矿和层控型铜矿有关;长江中下游地球化学块体与长江中下游成矿带吻合;西秦岭铜地球化学块体与岩体、铜矿和以铜为伴生元素的矿床有关;三江、湘粤桂交界区的铜地球化学块体也有与之对应的铜矿床或铜为伴生元素的矿床。通过这些地球化学块体与已知的地质体、成矿省(矿集区)的对比得出如下结论,铜地球化学块体的形成可能与岩石的高背景值、铜成矿省(矿集区)或铜为伴生元素的矿床有关。巨量的成矿物质的供应只是形成大型、超大型矿床的必要条件,如长江中下游铜地球化学块体为铜成矿省提供物质来源;但每个地球化学块体并不一定都有与之对应的矿集区,如峨眉山玄武岩铜地球化学块体与玄武岩高背景值有关,并没有形成大型的铜矿床。     

“关键资源地球化学勘查”专辑特邀主编寄语——关键元素分布与关键资源勘查

关键资源已经成为工业4.0和低碳能源不可替代的原材料。构成关键资源的元素有50余种, 这些元素是现代社会的先进制造、电子产品、低碳能源、国防安全、生物医药等必须的原材料, 因此也称为关键元素。地球化学勘查是研究和探测关键元素分布和超常富集, 寻找关键资源行之有效的方法。中国在关键元素的分布和深部探测地球化学领域走在了国际前列, 形成了从全球尺度、全国尺度、矿区尺度直到纳米尺度地球化学探测技术体系, 实现从二维到三维、从浅表矿到千米深度矿产探测能力的飞跃, 不仅圈定了一批全国稀土、锂、铀的超常富集区, 而且取得了多处深部金矿和铜矿勘查的重大突破。本专辑选择部分研究成果介绍了稀土元素、新能源金属(铀、锂、钴)、金、铜等关键资源地球化学勘查中取得的新进展和成果。为了响应国家号召“把论文写在祖国大地上”, 专辑作者把优质素材形成的论文发表在自己的杂志上, 作为本期特邀主编对他们的奉献精神表示衷心感谢和崇高的敬意！     

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。     

区域地球化学异常空间分形结构及其意义——以浙江省诸暨地区区域地球化学数据为例

区域地球化学数据既具有确定性的特征 ,又具有随机性的特征 ,从而地球化学异常的空间分布具有标度不变性的特征 ,即空间分形结构。本文运用元素含量 等值线面积模型、元素含量的周长与面积模型 ,查明区域地球化学异常分形结构 ,初步探讨了其形成机制 ,并讨论了元素含量与等值线面积的空间分形模型用于划分地球化学异常与背景的意义。