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1.
A technique called SCORESUM was developed to display a maximum of multi-element geochemical information on a minimum number of maps for mineral assessment purposes. The technique can be done manually for a small analytical data set or can be done with a computer for a large data set. SCORESUM can be used with highly censored data and can also weight samples so as to minimize the chemical differences of diverse lithologies in different parts of a given study area.The full range of reported analyses for each element of interest in a data set is divided into four categories. Anomaly scores — values of O (background), 1 (weakly anomalous), 2 (moderately anomalous), and 3 (strongly anomalous) — are substituted for all of the analyses falling into each of the four categories. A group of elements based on known or suspected association in altered or mineralized areas is selected for study and the anomaly scores for these elements are summed for each sample site and then plotted on a map. Some of the results of geochemical studies conducted for mineral assessments in two areas are briefly described. The first area, the Mokelumne Wilderness and vicinity, is a relatively small and geologically simple one. The second, the Walker Lake 1° × 2° quadrangle, is a large area that has extremely complex geology and that contains a number of different mineral deposit environments. These two studies provide examples of how the SCORESUM technique has been used (1) to enhance relatively small but anomalous areas and (2) to delineate and rank areas containing geochemical signatures for specific suites of elements related to certain types of alteration or mineralization. 相似文献
2.
新疆博格达东段地表岩石风化剥蚀严重,直接找矿标志不明显,以大功率激电中梯测量为辅助功能的大比例尺岩石地球化学测量方法对发现和圈定隐伏矿体起到了重要作用。研究区原生晕微量元素定量分析结果表明,Cu、Zn、Mo、As等4种元素在勘查区为强富集元素,Pb、Sn、Co、Ba为富集元素,单元素具有水平分带性。根据化探原生晕元素组合特点及空间分布特征,以单元素异常下限值和陆壳克拉克值为划分标准,圈定了4个Ⅲ级化探异常带,异常评价初步认为Cu-Pb-Zn-Mo-As-Sn-Co-Ba-Fe-Ni-Hg多元素叠加异常区为找矿有利区。选择元素共生组合特点较明显的三个异常带开展大功率激电工作并进行化探异常的验证,最后在推断出的成矿有利部位布设钻孔并见矿。初步认为预测区成矿地质条件有利于形成黄铁矿型铜矿床。 相似文献
3.
A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization. A favorable main factor with a strong association of the elements Zn, Cu and Pb, related to mineralization, was selected for interpretation. The median + 2MAD (median absolute deviation) method of exploratory data analysis (EDA) and C-A (concentration-area) fractal modeling were then applied to the Mahalanobis distance, as defined by Zn, Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies. As a result, the median + 2MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model. The soil anomaly identified by the median + 2MAD method on the Mahalanobis distances defined by three principal elements (Zn, Cu and Pb) rather than thirteen elements (Co, Zn, Cu, V, Mo, Ni, Cr, Mn, Pb, Ba, Sr, Zr and Ti) was the more favorable reflection of the ore body. The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation. The results showed that the median + 2MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization, which is therefore useful at the reconnaissance drilling stage. 相似文献
4.
Previous interpretations of surface-rock geochemical data from the sheeted-vein tin mineralization in the Emmaville district have been carried out using classical statistics. These investigations revealed low-contrast geochemical patterns of 3 to 5 ppm Sn, supported by 80 to 160 ppm F, block-average contours defining four of the six known mineral occurrences. Principal component scores for the association dominated by F-Li-Rb have defined the same four mineral occurrences. For the prospecting of similar deposits it is highly desirable to improve the data processing techniques to achieve more acceptable geochemical contrasts between anomalous and background levels. Minimum volume ellipsoid (MVE) estimation, a high-breakdown method (capable of accommodating up to 50% outliers) recently developed in robust statistics is applied to a subset of the data from the northeastern part of the Emmaville district. The anomalies related to mineralization in this part of the district are not as well developed compared to those in the west. The data set used in this study consists of 133 observations with 6 elements, namely Cu, Li, Rb, F, As and Sn.The detection of multivariate outliers (anomalous observations) by Mahalanobis distance calculation was carried out on the surface rock geochemical data. The robust Mahalanobis distances computed from MVE estimates of location and scatter shows little variation over background areas but are sharply enhanced over mineralization. In contrast, the usual Mahalanobis distances either fail to indicate the presence of mineralization altogether, or, at best, respond with feebly enhanced values that do not satisfactorily indicate the presence of mineralization.Graphical display of results from classical RQ-PCA performs poorly, revealing only 6 weakly anomalous observations related to mineral occurrences. Several additional observations from these occurrences have also gone undetected. On the other hand, results from MVE-robust RQ-mode principal component analysis show that the background observations cluster tightly within the 95% tolerance ellipse while the anomalous observations (related to mineral occurrences) are greatly enhanced and the variables that characterize them are clearly indicated. Results are consistent with those of robust Mahalanobis distance procedure; both techniques indicate essentially the same observations as being anomalous. 相似文献
5.
Analysis and mapping of geochemical anomalies using logratio-transformed stream sediment data with censored values 总被引：1，自引：0，他引：1
There is lack of research and documentation of actual (as opposed to theoretical) benefits (e.g., mineral deposit discovery) of developments in compositional data analysis and imputation of censored values to mineral exploration geochemistry. In the present study, analyses of logratio- and ln-transformed stream sediment geochemical data containing ca. 30% of samples with censored values of a pathfinder element for the mineral deposit-type of interest yielded the following findings. Exclusion of those samples supports interpretation of multi-element anomalies reflecting the presence of mineralization. However, the multi-element anomaly maps obtained by exclusion of those samples are barely better than the multi-element anomaly maps derived by inclusion of those samples after replacing the censored values with 1/2 of detection limit or with imputed values. Logratio (i.e., alr, clr, or ilr) transformation, compared to ln-transformation, of stream sediment geochemical data does not improve mapping of pathfinder element anomalies reflecting the presence of mineralization. However, stream sediment geochemical data, excluding or including censored values (replaced with 1/2 of detection limit or with imputed values), should be clr- or ilr-transformed to enhance recognition of anomalous multi-element associations reflecting the presence of mineralization. The anomaly maps of multi-element associations derived from ilr-transformed data are better, albeit slightly, than the anomaly maps of multi-element associations derived from clr-transformed data. In the present study, the main benefit of either clr- or ilr-transformation, compared to either ln- or alr-transformation, of stream sediment geochemical data is the enhancement of anomalous multi-element associations reflecting the presence of mineralization. This is an important benefit because variations in trace element concentrations in regional-scale stream sediment geochemical data are mostly due to lithology and other factors (or processes) unrelated to mineralization. Further investigations of various exploration geochemical data are needed to demonstrate and document the actual (as opposed to theoretical) benefits of developments in compositional data analysis and imputation of censored values to mineral exploration. 相似文献
6.
A new quantitative transportation model for geochemical elements in stream sediment samples is proposed and used to estimate mineral sources of anomalous concentrations and to adjust both location and concentration for the transportation effect. Subsequent to transportation analysis, data on 14 geochemical elements in the Walker Lake quadrangle are analyzed for geochemical signatures for three types of mineralization environments: epithermal gold-silver deposits, porphyry-skarn copper deposits, and a mixed occurrence. Geochemical signatures are analyzed using a multidimensional scaling method referred to as the pijk model, which is a factor-like model generalized to include nonlinear associations, as well as linear, among triple variables (elements). A result of this analysis is that Pb is the best indicator for epithermal gold-silver mineralization, Mo and Zn for mixed mineralization, and Cu for porphyry-skarn mineralization. 相似文献
7.
化探异常信息识别是化探数据分析最重要的任务之一, 也是化探数据在资源勘查领域受到广泛关注的最重要原因, 前人对化探异常信息识别做过大量研究, 这些研究中的大多数主要关注化探示踪元素的含量, 近而根据含量指标计算异常阈值, 而对示踪元素在空间中的分布特征关注较少。本文选择 1: 20万比例尺的克拉玛依幅为研究区, 根据区内金矿的矿床地球化学特征选择Ag、As、Au和Sb等4种元素为本区内金矿的示踪元素, 以地球化学元素分散晕形成理论为依据, 使用GIS技术和Matlab软件绘制研究区内4种金矿示踪元素的综合地球化学异常图。结果表明, 与传统阈值方法得到的化探异常图相比, 本文得到的化探异常图能够更好地指示研究区内已知金矿。 相似文献
8.
The southern Sanjiang region, southwestern China, comprises various continental blocks, tectonic sutures and arcs. This complex structural area is a proper place for the recognition of geochemical patterns and understanding of regional metallogenesis. Considering each individual tectonic unit (i.e., western South China block, Ailaoshan suture, Simao block, Changning–Menglian suture, Baoshan block and Tengchong block) as a statistical unit, this study identifies the distribution patterns of geochemical elements, distinguishes elemental associations for different geological backgrounds (controlled by the regional lithology) and diverse mineralizations, and thereby delineates the mineralized anomalies. To achieve the goals, the kriging interpolation, staged factor analysis and local singularity technology were utilized after the centered logratio (clr) transformation of stream sediment geochemical data. The spatial distributions of metallogenic elements (Au, Ag, Cu, Pb, Zn and Sn) show that not all the areas with high concentrations of elements contain ore deposits. It means that the formation of ore deposits is an independent anomalous geological event, not necessarily related to the original regional abundance of geochemical elements. The different element associations obtained by staged factor analysis of 28 elements are able to reveal the geological backgrounds and metallogenic signatures for different tectonic units. For example, the element associations for the first, second and third factors (Fs) in the western South China block are groups of Ti–Co–V, Sb–Ag–As and Th–U–Be (see text for the detailed element associations), which represent the Emeishan flood basalts, Ag–Pb mineralization and felsic rocks, respectively. Similarly, the element associations Co–V–Cu, Be–U–Th and Sb–Ag–Au for F1, F2 and F3 in the Ailaoshan suture respectively represent the ophiolite complex and mafic rocks, felsic rocks and Au mineralization. The associations from F1 to F4 in the Simao block are Th–U–Sn, V–Co–Cr, Cd–Ag–Pb and Au–Sb, which represent the Linchang batholith, mafic rocks, Ag–Pb–Zn mineralization and Au mineralization, respectively. The distribution patterns of their factor scores can roughly distinguish the anomalies caused by regional backgrounds and mineralizations. The local singularity of factor scores for mineralization can further identify mineralized areas in most of the tectonic units. Nevertheless, an exception occurs in the western South China block where the background element association, Ti–Co–V–Cu–Ni–Cr–P–Mn–Nb–Zn (F1), obscures the Au signature. Therefore, we substituted the single element Au for mineralized element association (F1) to perform singularity mapping, and obtained better result. It was concluded that the combination of staged factor analysis, local singularity and tectonic setting is effective in regional metallogenic potential analysis. 相似文献
9.
因子分析在地球化学分区中的应用:以内蒙古石板井地区1∶5万岩屑地球化学测量数据为例 总被引：1，自引：0，他引：1
利用R型因子分析方法,对内蒙古西部石板井地区1∶5万岩屑地球化学测量数据进行了分析,提取出6个具有代表性的因子,绘制出地球化学分区图及因子得分等值线图,并讨论了各分区与其地质背景的对应关系。依据分区结果,结合北山区域成矿背景、工作区地质特征及野外地质调查发现的孔雀石矿化点,确定了Cu-Zn分区是有利的成矿地段,并与志留系公婆泉组变质安山岩有关,90%的孔雀石矿化点位于该分区中。通过对工作区进行地球化学分区,结合各分区中Cu元素含量的统计特征,绘制了Boxplot对比图,分析Cu元素在各分区中的聚集特征,为地球化学勘查提供了找矿方向,确定了成矿有利的地质体。 相似文献
10.
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. 相似文献
11.
多龙矿集区控矿构造信息提取、识别与融合 总被引：1，自引：0，他引：1
西藏多龙矿集区近年来发现了大量的铜、金矿床,具有可观的资源潜力而倍受关注。通过对区内地质调查及矿产勘查数据的系统梳理与二次开发,利用基于分形理论的空间分析方法对该区成矿背景、构造格架等方面进行了深入细致的研究与探索。通过主成分分析方法,将水系沉积物地球化学数据中与斑岩铜金成矿相关元素和构造活动指示元素进行融合,并利用S-A(能谱-面积)模型对元素组合异常进行信息挖掘工作。结果表明,与区内构造格架相关的地球化学异常空间分布模式在指示矿化的同时,还对其与区域断裂构造之间的成生关系具有相当程度的指示意义。此外,区内开展的空间定量研究同时表明,S-A(能谱-面积)模型对描述由特定地质作用所造成的异常空间分布模式的自相似性有效,特别是针对地球化学背景模式的空间定量化描述,能更加深刻地刻画区内的构造格架并反映成矿背景。其结果推断了控制区内斑岩成矿系统的网格状断裂体系。此外,数据分析建模过程为在该区开展进一步的多元信息提取与融合提供了思路和借鉴经验,有利于找矿新靶区的发现与圈定。 相似文献
12.
《Journal of Geochemical Exploration》1997,60(2):157-171
A systematic approach for identifying mineral exploration target areas from reconnaissance stream sediment data without sufficient a-priori control information has been demonstrated in a portion of western Albay Province in the southern Bicol Peninsula of the Philippines. The approach involved devising a rapid method of catchment basin mapping using a geographic information system (GIS) so that the areal influence of the catchment basins may be incorporated in the geochemical data analysis. Areal proportions of mapped rock units occurring in the sample catchment basins and observed Mn and Fe contents in stream sediments are used as independent variables in multiple regression analysis to predict element contents in stream sediments related to lithologic and chemical controls. The predicted element contents are filtered-out from the original data to leave residuals in which the effects of other factors (e.g., mineralization) may be seen. A simple correction for the effects of downstream dilution is applied; this allows for the different sizes of the sample catchment basins so that positive geochemical residuals are enhanced. The inter-relationship of the different positive residuals in ‘highly enriched’ samples are investigated through principal components analysis to determine and quantify an ‘anomalous geochemical signature’. Lastly, the ‘anomalous geochemical signature’ is integrated with ‘proximity’ to faults/fractures to determine favourable target areas. For the test region, the lithologic controls explain between 80% and 100% of the variability in most of the elements studied. Chemical controls account for generally less than 5% of the variability in the data. Most of the dilution-corrected residuals reveal high relative enrichment in certain areas underlain by andesite and/or diorite. An anomalous Cu-Mg-Fe-Zn geochemical signature is disclosed by the principal components analysis of the dilution-corrected residuals in ‘highly enriched’ samples. Most sample catchment basins defined by this ‘anomalous geochemical signature’ pertain to areas underlain by andesitic rocks. Integration of the ‘anomalous geochemical signature’ and ‘proximity’ to faults/fractures reveals that some of these anomalous sample catchment basins are favourable target areas. These areas are interpreted to contain andesite-hosted stockwork or stringer zones that once formed part of a complete stratigraphic sequence of a volcanogenic massive sulphide occurrence. The results demonstrate the usefulness and ability of the procedures followed to extract significant anomalies from the reconnaissance geochemical data without the benefit of sufficient a-priori control data to aid in anomaly recognition. Similar procedures could also be applied elsewhere. 相似文献
13.
利用多元素组合异常指示元素平均值与大兴安岭森林沼泽区水系沉积物地球化学元素丰度值的差,以及与其所在地球化学子区元素变化系数的乘积关系,度量多元素组合异常指示元素在成矿地质作用中的聚集变化强度;计算多元素组合异常元素变化强度的和,对多元素组合异常进行元素变化强度和的评序,遴选主要组合异常.利用多元素组合异常指示元素蕴涵R型因子分析因子结构组合元素矿化类型的意义,判别多元素组合异常因子矿化类型.依据主要组合异常分布、因子矿化类型以及与测区物探、遥感解译线性、环形构造的关系,建立测区主要组合异常聚集带、聚集区.依照主攻矿种元素、相应主要组合异常因子矿化类型信息和相关成矿地质理论,开展测区多元素组合异常优中选优的找矿验证工作. 相似文献
14.
《Chemie der Erde / Geochemistry》2021,81(4):125811
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. 相似文献
15.
Jean S. KANE 《Geostandards and Geoanalytical Research》1985,9(2):181-190
A simultaneous multi-element method is described for the determination of six elements of importance in geochemical investigations of mineralization processes in granites. After a mixed acid sample digestion, the elements Be, Li, Nb, W, Mo and Sn are determined by inductively coupled plasma spectrometry. Possible sources of bias due to incomplete sample dissolution and from spectral interferences were investigated. Analysis of 16 geological reference standard samples and a number of enriched samples demonstrates the accuracy and precision of the method for the study of mineralized granites and for several other geochemical sample types as well. 相似文献
16.
《Chemie der Erde / Geochemistry》2019,79(2):323-336
Delineation of mineralization-related geochemical anomalies of stream sediment data is an essential stage in regional geochemical exploration. In this study, principal component analysis (PCA) was applied to 12 selected elements to acquire a multi-element geochemical signature associated with Cu-Au mineralization in Feizabad district, NE Iran. The spatial distribution of enhanced multi-element geochemical signature of the second component (PC2) was modeled by different geostatistical procedures including variogram calculation, ordinary kriging (OK) and inverse distance weighting (IDW) interpolation techniques. Concentration-area (C-A) fractal and U-spatial statistics models were then applied to the continuous-value interpolated models for delineation of geochemical anomalies. Quantitative comparison of results based on the known mineral occurrences in the study area was carried out using normalized density index and success-rate curves. All generated models represent a high positive relation with known Cu (±Au) deposits in the study area, although, comparison of the results revealed that the OK-based U-spatial statistics model was superior to the rest of models. Besides, the low, moderate and high-intensity anomalies are spatially associated with geological-structural features in the study area. 相似文献
17.
东昆仑地区是我国重要成矿带,地球化学勘查作为该区基础性的勘查手段在区域找矿、矿区及其外围找矿发挥了重要作用。地球化学勘查工作中,异常下限的确定是圈定地球化学异常的基础和关键。拉浪麦钨多金属矿区地球化学勘查工作中利用传统统计法、EDA法、含量—面积分形法分别对土壤地球化学分析元素计算确定异常下限,并结合成矿地质条件对三种方法计算出的异常下限进行综合对比研究,发现EDA法得出钨等元素异常不漏掉隐伏矿床形成的矿致异常,从而达到快速精准高效的找矿效果,具有很好代表性。因此,在东昆仑地区寻找钨多金属矿地球化学勘查中,采用EDA法确定异常下限是可行的。 相似文献
18.
19.
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 总被引：1，自引：0，他引：1
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。 相似文献
20.
内蒙古沙锡拉特地区位于大兴安岭多金属成矿带中段,为明确找矿方向,对研究区进行1∶1万土壤地球化学测量。采用单元素异常、组合异常与因子分析对研究区土壤地球化学数据进行评价。单元素异常显示,Ag、Pb、Zn与Sn元素的异常规模大、强度高。组合异常圈定4个异常,分为Ag—Au—As—Sb与Bi—W—Pb—Zn—Sn两类。因子分析将所分析元素分为五组,其中F1因子由Ag—Au—As—Sb元素组成,F2因子由Pb—Zn—Sn元素组成。根据土壤地球化学异常特征与区域成矿地质条件,在本区圈定2个找矿靶区,BQ—1为Pb—Zn—Sn找矿靶区,BQ—2为Ag找矿靶区。 相似文献