共查询到20条相似文献，搜索用时 515 毫秒
1.
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
2.
《Chemie der Erde / Geochemistry》2015,75(1):117-132
The aim of this study is to discriminate the geochemical anomalies in the Zarshuran district, NW Iran, using different geochemical methods and present a more useful method where anomalous areas better coincide with the geological features. For this methods of delineation, geochemical anomalies were compared using geological features, occupied area of anomalies respect to the total study area, and field observations. Frequency based analysis such as mean + 2SDEV and median + 2MAD and concentration–area (C–A) multifractal methods were adopted for estimating thresholds and separating geochemical anomalies in uni-element data, as well as multi-element ones. Threshold values obtained from mean + 2SDEV and median + 2MAD, from original point geochemical data, are smaller than those of the pixel values; this may be due to the stronger variance of pixel values. In addition, the C–A multifractal method, as a useful tool to identify weak geochemical anomalies, was applied for defining the threshold values. Robust principal component analysis (RPCA) methods coupled with isometric log-ratio (ilr) transformations were utilized to open the geochemical data in order to reduce the effects of the data closure problem. The 20-quantile intervals decomposed anomaly maps from PC1 were obtained from the classical PCA, robust PCA showed that the upper quintile (>80 quintile) of classical PCA covers a larger area (32.54%) than the robust PCA (18.16%), and as a result, the robust PCA displayed smaller areas and has good spatial associations with outcrops of hydrothermal Au–As mineralization in this area; coincident with the known Zarshuran former mining area (ore field), Zarshuran unit, Ghaldagh silicified limestone occurrence and newly explored works confirmed by field observation. Although the C–A model shows a smaller area (8.06%), this anomaly location is limited to the Zarshuran old mining area with no new exploration targets. Comparison of the models indicates that the RPCA model is not only beneficial to further Au exploration in the study area, but also provides a meaningful geological study to the community of the compositional data analysis. 相似文献
3.
内蒙古额济纳旗道噶地区矿化类型为石英脉型,见含Au石英脉出露。通过对该地区进行土壤地球化学测量工作,在统计研究区各地层Cu、Ag、Au、Pb、Zn、Sb、Mo、Ni、Co、W、As、Sb等微量元素含量基础上,应用聚类分析方法分析元素间相关关系。在研究区圈定出61处单元素异常区,其中Au元素异常8处。根据地球化学异常分类规范,综合考虑地球化学异常的规模、形态、异常的强度、分带性、异常元素的组合及异常区成矿地质条件和地球化学条件,在单元素异常的基础上圈定出乙类综合异常区2个(Ⅰ号、Ⅱ号综合异常区),丙类综合异常区1个(Ⅲ号综合异常区)。在对研究区地质特征及土壤地球化学特征的基础上圈定出3个找矿靶区,并进行地表工程验证,为进一步找矿工作提供有利依据。 相似文献
4.
SHI Changyi ZHANG Jinhua China University of Geosciences Beijing Institute of Geophysical Geochemical Exploration Langfang Hebei 《《地质学报》英文版》2003,77(1):72-80
Regional stream sediment surveys at a 1:200,000 scale reveal positive and negative regional multi-element geochemical anomalies over medium to large copper-polymetallic orefields of different genetic types in China. Regional geochemical anomalies of orefield refer to those geochemical anomalies that are related to metallogenesis of an orefield in a certain area. The anomaly area is typically 10 to 100 km2. The regional multi-element anomalies related to mineralization can be divided into three groups, that is, the ore-element anomaly association, indicator element anomaly association, and metallogenic environmental element anomaly association. Their common spatial distributions over ore deposits or orefields possess unique structures.The model of spatial structure of regional multi-element geochemical anomalies (RAGSS) of an orefield delineates structural feature possessed by orderly spatial distributions of different groups of multi-element anomaly associations related to orefield metallogenesis. It is 相似文献
5.
《Chemie der Erde / Geochemistry》2021,81(4):125774
Recognition of geochemical anomalies is a pivotal assignment in exploration projects. This study aims to delineate different AuCu geochemical anomalies using number-size (N-S) and concentration-area (C-A) multifractal models in the Siah Jangal area, SE Iran. In this research, lithogeochemical datasets were applied for the exploration of Au and Cu. A comparison between geochemical anomaly maps based on the N-S and C-A fractal models shows the N-S fractal modeling is a powerful tool for separation of weak elemental geochemical anomalies in all of sampling zones. Based on a comparison between the results of these two methods and field studies, the geochemical anomaly zones, defined by the N-S fractal model, are more accurate than those recognized by the C-A fractal model. The obtained results of the N-S and C-A fractal models have been interpreted with the extensive set of information including structural interpretation, geological and alteration data. Au and Cu mineralization in the Siah Jangal area are hosted mainly by Oligocene-Miocene sub-volcanic rocks, especially strongly altered porphyric quartz diorite, hornblende diorite and diorite. Moreover, the positive dependence between various alteration zones and high concentrations of Au and Cu proves that strongly anomalous areas are correlated with these alteration zones. High grade Au (> 1000 ppb) and Cu (>150 ppm) are associated with the altered sub-volcanic rocks in the northern, eastern, and SW parts of the study area. Therewith, the strong anomaly populations are mostly occurred within the fault and fracture systems in the study area. This is a promising signal because quartz-sulfide veins and veinlets are associated with such structures. 相似文献
6.
《Chemie der Erde / Geochemistry》2016,76(4):491-499
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. 相似文献
7.
《Chemie der Erde / Geochemistry》2021,81(4):125830
Increasing the prediction rate in the identification of mineralization zones using the stream sediment geochemical data is an essential issue in the regional exploration stage. The various univariate (such as fractal and probability plot (PP) methods) and multivariate methods (such as principal component analysis (PCA)) have been performed for interpreting the geochemical data and detecting the mineralization areas. In this study, a new geochemical criterion named geochemical anomaly intensity index (GAII) was proposed for geochemical anomaly mapping. This approach was developed based on the PCA method and the catchment basin coefficient (CBC). The GAII as a weighted geochemical index is calculated using the mineralization principal component (MPC) scores and CBC. GAII can be mapped and utilized for geochemical anomaly mapping and detecting the mineralization areas. Besides, GAII can identify paragenesis elements better than the current methods. In this research, GAII was successfully used to generate geochemical anomaly maps on shear zone gold mineralization in the southwest of Saqqez, NW Iran. The geochemical data have been divided into three groups based on catchment basins and the host rock type. Then the MPCs and paragenesis elements of Au mineralization have been obtained individually using PCA. Three mineralization paragenesis groups consisting of (Au, Sn), (Au, W), and (Au, As, Sb and Ba) have been recognized for different catchment basins of the southwest of Saqqez district using PCA. GAII was calculated and mapped based on the CBC(Au, Sn), CBC(Au, W), CBC(Au, As, Sb, Ba), and their MPC scores. GAII accurately detected the Au mineralization zones and improved the geochemical anomaly map in this area compared to the PP method, concentration-area fractal model, and U-spatial statistics method. The results demonstrated that GAII was successfully used for (a) identifying the mineralization paragenesis elements, (b) intensifying the geochemical anomaly, and (c) increasing the prediction rate of mineralization zones. The shear zone gold mineralization areas in the southwest of Saqqez district were effectively detected using this new data analysis approach. GAII has provided better results than the current PP method, concentration-area fractal model, and U-spatial statistics method. 相似文献
8.
Identifying geochemical anomalies from background is a fundamental task in exploration geochemistry. The Gangdese mineral district in western China has complex geochemical surface expression due to complex geological background and 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. The results illustrate that weak anomalies are hidden within the strong variance of background and are not well identified by means of inverse distance weighted; neither are they clearly identified by the C–A method if this method is applied to the whole study area. On the other hand, singularity values provide new information that complements use of original concentration values and can quantify the properties of enrichment and depletion caused by mineralization. In general, producing maps of singularities can help to identify relatively weak metal concentration anomalies in complex geological regions. Application of singularity mapping technique in Gangdese district shows local anomalies of Cu are not only directly associated with known deposits in the central part of the study area, but also with E–W and N–E oriented faults in the north of the study area. Both types of anomalies should be further investigated for undiscovered Cu mineral deposits. 相似文献
9.
Fractal/multifractal modeling of geochemical data is an interesting topic in the field of applied geochemistry. Identification of weak anomalies for mineral exploration in covered areas is one of the most challenging tasks for utilization of geochemical data. In this study, three fractal models, consisting of the concentration–area (C–A), spectrum–area (S–A) and singularity index models were applied to identify geochemical anomalies in the covered area located in the Chaobuleng Fe polymetallic district, Inner Mongolia (China). The results show that (1) the grassland cover weakens the concentrations of geochemical elements; (2) the C–A model has a limitation to identify weak anomalies in covered areas; (3) the S–A model is a powerful tool to decompose mixed geochemical patterns into a geochemical anomaly map and a varied geochemical background map but suffers edge effects in an irregular shaped study area; and (4) the singularity index is a useful tool to identify weak geochemical anomalies. 相似文献
10.
Research involving secondary negative anomalies and their application in regional stream sediment surveys has been scarce. Conventionally, negative anomalous threshold values have been calculated in the same way as positive anomalous threshold values. But the conventional methods all have drawbacks which hinder their application. In this paper, we have chosen to delineate negative (and/or positive) anomalies using contrast values in order to overcome the drawbacks.Regional stream sediment surveys at a scale of 1 : 200 000 have been carried out in western Jungger, Shanxi, Kunlun, northwestern Jiangxi, and other areas in China. The geochemical data were processed using System RESMA.On the basis of the distribution of negative and positive single-element anomalies, three possible arrangements may occur: (1) negative anomalies accompanied by positive anomalies; (2) only positive anomalies occurring with no negative anomaly nearby; (3) only negative anomalies, with no positive anomaly nearby. These situations reflect different geological settings and different mineral forming processes. Basically, two different distribution patterns of regional negative anomalies in relation to the backgrounds — low background (LB) and high background (HB) —may be observed in different geological environments: (1) regional negative anomalies are distributed only around the positive anomalies in the LB area; (2) regional negative anomalies can exist on the periphery of positive anomalies in both LB and HB areas.Two kinds of patterns for regional multi-element negative and positive anomalies reflecting different geological processes have been noted: (1) coincident positive anomalies for one group of elements and negative anomalies for another group of associated elements can be used to uniquely define ore deposition; (2) regional positive multi-element anomalies of some elements (including ore and associated elements) occurring over a deposit are accompanied by negative anomalies on the periphery of the deposits. Two regional models of negative and positive anomalies are established for Au and Cu deposits.Integration of multi-element positive and negative composited geochemical anomalies are much more useful than positive anomalies or positive composited anomalies to delineate regional structures. 相似文献
11.
12.
粤北某铀矿勘查区深部铀矿找矿潜力分析 总被引：1，自引：0，他引：1
基于大比例尺区域地质调查工作,在粤北某铀矿勘查区通过分量化探和土壤氡气测量开展深部铀矿找矿工作。已知的隐伏铀矿区测量结果表明,铀矿赋存在断裂之中,在含矿断裂上方形成U的分量化探异常和土壤氡气异常;在该异常区内,同时伴随W、Be、Ba、Mo、Li、Ni的分量化探异常。综合分析分量化探和土壤氡气资料,勘查区内北北东向F_2、F_1处的分量化探和土壤氡气异常具备已知隐伏铀矿区的全部异常特征,推测该处异常具有较大的深部找矿前景,进一步的钻探工作正在进行中。 相似文献
13.
Geochemical data are typical compositional data which should be opened prior to univariate and multivariate data analysis. In this study, a frequency-based method (robust principal component analysis, RPCA) and a frequency-space-based method (spectrum–area fractal model, S–A) are applied to explore the effects of the data closure problem and to study the integrated geochemical anomalies associated with polymetallic Cu mineralization using a stream sediment geochemical dataset collected from the Zhongteng district, Fujian Province (China). The results show that: (1) geochemical data should be opened prior to RPCA to avoid spurious correlation between variables; (2) geochemical pattern is a superimposition of multi-processes and should be decomposed; and (3) the S–A fractal model is a powerful tool for decomposing the mixed geochemical pattern. 相似文献
14.
《Chemie der Erde / Geochemistry》2021,81(2):125733
This research aims to take the effect of drainage sediment dilution into consideration by using catchment weighted-bulk leachable extractable gold (CW-BLEG) data in order to enhance and recognize Au anomalies. As a case study, an area in the Eskisehir region in Western Turkey was selected. In this area, gold-bearing crystalline quartz veins, of probable orogenic type, containing up to 20 g/t Au, occur in low-grade schists and marbles of the Karakaya Complex in the vicinity of the Sogut area. To classify the final geochemical maps of the BLEG data to differentiate Au anomalies from background, the singularity model was applied. After that, in order to take the sediments dilution effect (DE) into account, the other important factors in the study area such as the sinuosity index (SI) of the stream sediments per catchment, and the topography slope and area of each catchment were taken into consideration and implemented on the BLEG data. To do so, the CW-BLEG models based on the relation between the Au concentrations and each factor (i.e., C × sinuosity as DE-sinuosity, C × slope as DE-slope, and C × area as DE-area) were generated. Because of the insufficient number of known mineral deposits within the study area to evaluate the effectiveness of the models statistically, the models generated were compared with each other and studied using cross-validation. It demonstrated that the DE-area and DE-sinuosity models work better than the other model in recognizing strong and very strong anomalies considering the known mineral deposits. The cross-validation results show that the DE-area model provides a more robust result compared the other models. Considering the models generated, the very strong and strong Au anomalies in the western part of the study area are corresponded to the known gold mineralization (e.g., Sogut and Mayislar) hosted by the Karakaya Complex, and the anomalies in the eastern and central parts of the study area are associated with the Damdaca mineralization. 相似文献
15.
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
16.
以研究区成矿地质背景为基础，将其划分为4个地球化学区，从多重分形理论出发，应用“元素含量—面积”模型方法，对各区主要成矿元素的地球化学(异常)场进行分析研究。结果表明，由于地质构造背景和化探元素富集的成因机理不同，各区元素地球化学(异常)场具有两种不同的多重分形特征模式：只有两个无标度区的简单多重分形模式和有两个以上无标度区的高丛集多重分形模式，具有相同成因的元素组合具有相似的多重分形特征。在此基础上．探讨了各区元素的成矿富集规律和空间分布特征，进而划分了地球化学背景和异常，经检验对比，证明了该方法的有效性和实用性。 相似文献
17.
地球化学异常靶区优选一直是勘查地球化学所面临的核心问题。目前地球化学异常靶区优选所采取的方法,主要是基于不同地质构造单元的地球化学异常评价方法和基于多元统计而发展的多元素定量化评价指标方法,然而这些异常评价方法缺少对水系中沉积物的物质来源区域进行限定。由于在一级水系中沉积的水系沉积物主要由一级水系流域内的岩石经过风化、剥蚀、搬运,最后在水系内沉积而成,因此一级水系中的水系沉积物的物源区域可近似与水系流域等同。本文通过水系流域的提取,以水系流域作为分析单元,对1∶50000丫他幅水系沉积物进行地球化学分析评价,通过与地质矿产资料对比,证明了本方法的有效性,并且缩小了地球化学异常区域,更精确地进行靶区定位。根据本文提出的方法,通过分析区内已知矿点所处流域的地球化学元素特征,将丫他幅内已有金矿划分为两种类型,对后期找矿工作有一定的指导意义。 相似文献
18.
西藏撞多勒地区位于班公湖—怒江缝合带西段南侧燕山晚期火山—岩浆弧带,经历了多阶段复合造山作用,各类地质体和构造形迹复杂多样。本文在总结1:5万水系沉积物地球化学特征及分布规律基础上,分析不同地质体中元素的背景值、标准离差、富集系数、变异系数。依据地球化学示踪作用原理,运用多元素背景值推断主要地质体的空间展布和构造形迹,制作As、Sb、Hg元素组合及Cr、Ni、Zn元素组合的衬值累加图分别解译构造和岩浆岩,厘清宏观地质体与微观元素之间的关系,进行地层划分、地质体圈定和断裂追踪,对区域地质填图起到了较好的辅助作用。 相似文献
19.
《Comptes Rendus Geoscience》2018,350(4):180-191
The delineation of populations of stream sediment geochemical data is a crucial task in regional exploration surveys. In this contribution, uni-element stream sediment geochemical data of Cu, Au, Mo, and Bi have been subjected to two reliable anomaly-background separation methods, namely, the concentration-area (C–A) fractal and the U-spatial statistics methods to separate geochemical anomalies related to porphyry-type Cu mineralization in northwest Iran. The quantitative comparison of the delineated geochemical populations using the modified success-rate curves revealed the superiority of the U-spatial statistics method over the fractal model. Moreover, geochemical maps of investigated elements revealed strongly positive correlations between strong anomalies and Oligocene–Miocene intrusions in the study area. Therefore, follow-up exploration programs should focus on these areas. 相似文献
20.
A regional geochemical survey using soils, stream sediment and stream water sampling revealed multi-element geochemical anomalies, though of low environmental mobility, associated with Mesozoic sedimentary ironstones in Lincolnshire, UK. The most prominent of these anomalies were of As and V in soils and sediments, but elevated levels of elements such as Cr, La, Ce and Th were also observed. These were initially thought to be part of a residual resistate element or heavy-mineral suite, but careful examination suggests that these too may be primarily associated with the process of Fe oxide precipitation during the initial formation of the ironstones. 相似文献