四川省会理-会东地区铜矿产资源评价预查地质报告

完成单位 :四川省地质调查院矿产所内容简介 :通过对黎溪、通安、淌塘等铜矿资源富集区开展评价工作 ,查明会理 会东地区铜矿资源潜力。经工作确定红泥坡、通安老厂铜矿等 7处有利的找矿远景区。通安老厂铜矿经地表揭露和浅部坑探验证 ,工程系统取样 ,提交新发现矿产地一处 ,并估算 334铜资源量 ;另外淌塘铜矿、小街铜金矿、铁柳铅锌矿、红泥坡铜矿床 (点 )估算了部份资源量。根据铜矿成矿地质和地球化学条件选择了“拉拉式”、“东川式”铜矿找矿靶区 ,进行了铜矿预测。为今年部署铜矿找矿工作提供了一定依据。四川省会理会东地区铜矿产资…     

四川会理白云山铜矿:一个赋存于变质沉积岩中的IOCG

四川会理拉拉地区是我国重要的IOCG(铁氧化物铜金矿床)产地(李泽琴等,2002;朱志敏等,2009),产出有落凼铜矿、石龙铜矿、老虎山铜矿、红泥坡铜矿等大中型铜矿。目前已发现的这些铜矿均赋存于古元古河口群上部变质火山-沉积岩系,而下部层位由于出露较差,长期未引起重视,地质找矿进展一直未有突破。近年来,通过野外地质调查工作,我们在河口群下部的白云     

四川会理拉拉铜矿找矿预测模型构建与找矿示范

勘查区找矿预测理论与方法体系是基于全国129个典型矿床的深入研究,以及在勘查项目实践验证基础上总结而形成的一种特别适合生产找矿第一线使用的有效方法。该方法以成矿作用内因(元素的地球化学特征)和外因(地质作用类型)相结合的思路,构建以成矿地质体、成矿构造与成矿结构面和成矿作用特征标志为主要内容的找矿预测地质模型。四川会理地区位于扬子板块西缘,区域成矿地质条件优越,经历多期构造事件叠加,形成了一系列独具特色的铁铜矿床。近年来,在拉拉铜矿的深部及外围已取得了重大找矿突破和进展。本文以会理拉拉铜矿为典型实例及深部找矿预测成果示范,阐述该方法在深部找矿预测中的具体应用过程,得出了如下认识:早期成矿地质体为赋矿火山岩(河口群钠长岩类),成矿构造与成矿结构面主要为基(中)性火山岩与沉积岩的界面及可能的喷溢口;热液叠加期成矿地质体推测为深部隐伏岩体,成矿构造与成矿结构面主要为褶皱、断裂和裂隙。在总结成矿作用特征标志基础上,建立了拉拉铜矿勘查区找矿预测地质模型。通过与地质和物探方法相结合,圈定红泥坡南部为找矿靶区,经钻探验证,发现厚大矿体,打开了区域找矿空间。     

四川红泥坡铜矿床三维地质建模及控矿构造演化的新认识

红泥坡铜矿是近年来在四川拉拉地区发现的一个大型铜矿床,其包含铜储量64.2万t,平均品位1.31%。矿体赋存于元古宙老的褶皱基底河口群,与辉长岩侵入体具有时间上的联系,围岩发生了普遍的钠质蚀变。通过红泥坡铜矿区224个钻孔和23条勘探剖面建立了矿体、地层与构造要素的三维模型,该三维地质模型能够表达矿床的精细地质结构以及解释区域成矿作用与构造演化:矿区早期的南北向主应力使河口群形成轴向近东西向的大型向斜,晚期的东西向主应力在改造早期褶皱基底的基础上,形成了叠加在其之上的轴向北北东向的复向斜。经过两期主要的构造运动,该地区形成了现在北北东向与北西西向构造相叠加的格架。本项研究为拉拉地区的矿床学研究提供了新的思路,并能对该地区矿产勘查提供科学依据。     

基于成矿系统的三维定量预测研究——以四川拉拉铜矿为例

随着矿产资源预测的发展,三维矿产资源定量预测评价已经成为矿产勘查领域的热点。然而真正决定矿产预测及矿产勘查成败的核心在于:如何构建恰当的预测变量来反映成矿作用过程。本文以四川拉拉铜矿为例,通过成矿系统分析“源-运-储-保”四大要素总结了该区矿产预测的地质找矿要素。基于三维地质建模技术以及成矿信息定量提取技术,构建了区域找矿要素三维地质信息。以找矿信息量为数学模型,确定了拉拉铜矿成矿有利区划,圈定了4个找矿靶区。本次研究将矿床成矿系统分析(知识驱动)与三维定量分析(数据驱动)相结合,将成矿作用过程及关键因素(源、运、储、保等)转化为可预测的具体空间要素,并使用三维可视化技术进行三维空间重构,该方法为今后的三维定量预测工作提供了有利参考。     

基于机器学习的三维矿产定量预测——以四川拉拉铜矿为例

在大数据蓬勃发展的时代背景下,矿产资源定量预测作为地质大数据的核心部分,其综合分析挖掘多元信息的基本思路与大数据的理念不谋而合。以四川拉拉铜矿为例,开展基于机器学习的三维矿产资源定量预测。通过建立三维地质模型,提取成矿有利信息,构建研究区定量预测模型;基于"立方块预测模型"找矿方法,采用机器学习随机森林算法,计算出研究区成矿概率分布,以此圈定出5个找矿远景区。结果表明,随机森林具有更高的预测准确度与稳定性,且能够对控矿要素重要性做出定量评价。该研究成功地将机器学习应用于三维矿产定量预测,为今后的矿产资源预测评价做出了积极的探索。     

基于MRAS的证据权重法在香格里拉地区的综合信息成矿预测

在成矿地质背景分析和以普朗斑岩型铜矿为主的典型矿床研究基础上,通过对香格里拉地区已知矿床点与区域地质、重力、航磁、水系沉积物、重砂和遥感等数据资料再次处理及与解译成果的空间关联分析,确定斑岩型铜多金属矿的找矿标志,以此为依据提取和构置各类地学综合成矿信息预测变量。基于MRAS证据权重法,以2 km×2 km网格单元计算得到的后验概率,最大值与最小值4级优选分级评价了研究区斑岩型铜多金属矿的A、B、C 3个级别的找矿预测远景区。结果显示,普朗特大型斑岩型铜矿,红山夕卡岩-斑岩型铜矿,目前已取得重要找矿进展的松诺、欠虽、亚杂等铜多金属矿床点和具有较大找矿潜力的拉巴铜矿点均落在A级远景区。这表明综合信息成矿预测图直观表达了香格里拉地区斑岩型铜多金属矿成矿系列总体找矿潜力。     

红泥坡铜矿床地质特征及找矿意义

红泥坡铜矿床位于扬子准地台攀西成矿带康滇地轴中段的有色、黑色金属成矿带,矿体赋存于元古界河口群河口组及天生坝组,呈似层状、透镜状产出。本文通过对该矿床区域成矿背景、矿区地质特征、矿体地质特征、物化探特征及成矿地质条件等方面的研究,阐述了该成矿区带找矿过程、找矿意义,对寻找同类型矿床具有重要的指导意义。     

基于MORPAS平台特征分析法的成矿远景区预测——以个旧西区锡多金属矿为例

通过对个旧西区成矿地质条件和东区典型矿床地质特征的研究,综合地质、地球物理、地球化学和遥感等找矿信息,建立了个旧西区锡多金属矿综合信息找矿模型.根据找矿模型,优选出地层、构造、物探、化探、遥感等12个预测变量,在MORPAS平台上应用特征分析法对矿区进行了成矿预测,圈定了3个一级成矿远景区和3个二级成矿远景区.其中,个旧西区的梨花寨区(A2)和陡岩区(A3)成矿地质条件良好,具有很大的找矿潜力,为个旧西区新一轮的找矿工作提供了依据.     

云南个旧高松矿田芦塘坝研究区三维预测模型及靶区优选

通过对云南个旧芦塘坝研究区成矿信息分析,结合三维可视化技术,对其进行深部隐伏矿体预测。根据研究区的地质概况与成矿规律,确定地层和断裂是主要的控矿条件,利用三维建模软件建立该研究区的数字矿床模型,应用立方体预测模型找矿方法,提取成矿有利因子——地层、断裂、构造定量化信息、化学元素异常,将其作为预测变量,最终通过计算圈定出预测远景区进而优选出4个预测靶区。预测远景区结果表明,该研究区有较好的找矿潜力,其矿产预测方法有效性较好。构造定量化信息分析方法的应用有助于实现三维找矿。     

GIS Predictive Model for Producing Hydrothermal Gold Potential Map Using Weights of Evidence Approach in Gengma Region, Sanjiang District, China

Gengma region, Sanjiang district is known to have some large-scale gold deposits. GIS predictive model for hydroghermal gold potential was carried out in this region using weights of evidence modeling technique. Datasets used include large-scale hydroghermal gold deposit records, geological, geophysical and remote sensing imagery. Based on the geological and mineral characteristics of areas with known gold occurrences in Sanjiang, several geological features were thought to be indicative of areas with potential for the occurrence of hydroghtermal gold deposits. Indicative features were extracted from geoexploration datasets for use as input in the predictive model. The features include host rock lithology, geologic structures, wallrock alteration and associated (volcanic-plutonic) igneous rocks. To determine which of the indicative geological features are important spatial predictors of area with potential for gold deposits, spatial analysis was done through the modeling method. The input maps were buffered and the optimum distance of spatial association for each geological feature was determined by calculating the contrast and studentized contrast. Five feature maps were converted to binary predictor patterns and used as evidential layers for predictive modeling. The binary patterns were integrated in two combinations, each of which consists of four patterns in order to avoid over prediction due to the effect of duplicate features in the two structural evidences. The two produced potential maps define almost similar favorable zones. Areas of intersections between these zones in the two potential maps placed the highest predictive favorable zones in the region.     

A comprehensive VIKOR method for integration of various exploratory data in mineral potential mapping

The central Iranian volcanic-sedimentary belt in Kerman province of Iran that is located within the Urumieh-Dokhtar magmatic arc zone is chosen to integrate diverse evidential layers for mineral potential mapping. The studied area has high potential of mineral occurrences especially porphyry copper, and the prepared potential maps aim to outline new prospect zones for further investigation. Two evidential layers including the downward continued map and the analytic signal of filtered magnetic data are generated to be used as geophysical plausible traces of porphyry copper occurrences. The low values of the resistivity layer acquired from airborne frequency domain electromagnetic data are also used as an electrical criterion in this study. Four remote sensing evidential layers including argillic, phyllic, propylitic, and hydroxyl alterations are extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images in order to map the altered areas associated with porphyry copper deposits. The Enhanced Thematic Mapper Plus (ETM+) images are used as well to prepare iron oxide layer. Since potassic alteration is generally the mainstay of copper ore mineralization, the airborne potassium radiometry data is used to explore both phyllic and potassic alteration. Finally, the geochemical layers of Cu/B/Pb/Zn elements and the main geochemical component responsible for ore mineralization extracted from principal component analysis are included in the integration process to prepare final potential maps. The conventional and the extended version of VIKOR method (as a well-known algorithm in multi-criteria decision making problems) produced two mineral potential maps, and the results were compared with the ones acquired from prevalent methods of the index overlay and fuzzy logic operators of sum and gamma. The final mineral potential maps based upon desired geo-data set indicate adequately matching of high potential zones with previous working and active mines of copper deposits.     

Data- and knowledge-driven mineral prospectivity maps for Canada's North

Data- and knowledge-driven techniques are used to produce regional Au prospectivity maps of a portion of Melville Peninsula, Northern Canada using geophysical and geochemical data. These basic datasets typically exist for large portions of Canada's North and are suitable for a “greenfields” exploration programme. The data-driven method involves the use of the Random Forest (RF) supervised classifier, a relatively new technique that has recently been applied to mineral potential modelling while the knowledge-driven technique makes use of weighted-index overlay, commonly used in GIS spatial modelling studies. We use the location of known Au occurrences to train the RF classifier and calculate the signature of Au occurrences as a group from non-occurrences using the basic geoscience dataset. The RF classification outperformed the knowledge-based model with respect to prediction of the known Au occurrences. The geochemical data in general were more predictive of the known Au occurrences than the geophysical data. A data-driven approach such as RF for the production of regional Au prospectivity maps is recommended provided that a sufficient number of training areas (known Au occurrences) exist.     

Exploration feature selection applied to hybrid data integration modeling: Targeting copper-gold potential in central Iran

A Sugeno-type fuzzy inference system is implemented in the framework of an adaptive neural network to map Cu–Au prospectivity of the Urumieh–Dokhtar magmatic arc (UDMA) in central Iran. We use the hybrid “Adaptive Neuro Fuzzy Inference System” (ANFIS; Jang, 1993) algorithm to optimize the fuzzy membership values of input predictor maps and the parameters of the output consequent functions using the spatial distribution of known mineral deposits. Generic genetic models of porphyry copper–gold and iron oxide copper–gold (IOCG) deposits are used in conjunction with deposit models of the Dalli porphyry copper–gold deposit, Aftabru IOCG prospect and other less important Cu–Au deposits within the study area to identify recognition criteria for exploration targeting of Cu–Au deposits. The recognition criteria are represented in the form of GIS predictor layers (spatial proxies) by processing available exploration data sets, which include geology, stream sediment geochemistry, airborne magnetics and multi-spectral remote sensing data. An ANFIS is trained using 30% of the 61 known Cu–Au deposits, prospects and occurrences in the area. In a parallel analysis, an exclusively expert-knowledge-driven fuzzy model was implemented using the same input predictor maps. Although the neuro-fuzzy analysis maps the high potential areas slightly better than the fuzzy model, the well-known mineralized areas and several unknown potential areas are mapped by both models. In the fuzzy analysis, the moderate and high favorable areas cover about 16% of the study area, which predict 77% of the known copper–gold occurrences. By comparison, in the neuro-fuzzy approach the moderate and high favorable areas cover about 17% of the study area, which predict 82% of the copper–gold occurrences.     

Unmasking multivariate anomalous observations in exploration geochemical data from sheeted-vein tin mineralization near Emmaville, N.S.W., Australia

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.     

Use of Thematic Mapper Imagery to Identify Mineralization in the Santa Teresa District,Sonora, Mexico

Integrated multispectral, geologic, mineralogic, and geochemical studies of the Santa Teresa district, Sonora, Mexico, were used to map the lithology and identify zones of alteration characteristic of known gold deposits within the area. Forty sedimenthosted, bulk-mineable, leachable, fine-grained, disseminated gold prospects have been identified. These deposits vary in size and grade from 1.5 million tons of ore averaging up to 2.8 grams Au/ton to less than 2,000 tons of ore averaging less than 1.0 gm Au/ton. A variety of deposit types exist in the district, having the characteristics of hot-spring sinter, skarns, epithermal high-level veins, bonanza silver veins, granite and porphyry-related mineralization, and sedimenthosted disseminated deposits. The latter is presently the most important economically and is characterized by decalcification, silicification, argillic alteration, and anomalous Au, Ag, As, Hg, and Te.

Digital image processing techniques were used with Landsat 5 Thematic Mapper data to enhance lithologies and to detect alteration associated with the mineral deposits. Thematic Mapper imagery was combined with field mapping and laboratory analysis into a geographic information system. Pertinent information was integrated in order to produce lithologic and alteration maps for regions of interest within the Santa Teresa district to aid exploration.     

Controls on mineral deposit occurrence inferred from analysis of their spatial pattern and spatial association with geological features

In this paper, point pattern analysis, fractal analysis and Fry analysis were employed to study the spatial pattern of known occurrences of mineral deposits of the type sought, whereas distance distribution method was applied to study the spatial associations between various geological features and known occurrences of mineral deposits of the type sought. In the Aroroy district (Philippines), the results of the applications of these spatial analytical techniques support a conceptual model of district-scale mechanism of geologic controls on low-sulphidation epithermal Au mineralization, which involves a more-or-less regular mesh of interlinked zones of extension faults/fractures at and/or around intersections of NNW- and NW-trending strike-slip faults/fractures. Integration of spatial evidential data layers representing these structural controls and surficial geochemical anomalies, via knowledge-guided application of data-driven evidential belief functions, results in delineation of prospective areas occupying about 25% of the district, in which there is about 70% likelihood of undiscovered occurrences of low-sulphidation epithermal Au deposits.     

Exploring Placer Gold Deposits through Integrated Geophysical and Geochemical Techniques at the Confluence of the Indus and Kabul Rivers, NW Pakistan

Analysis of the anomalous magnetic mineral intensities and geochemistry for placer gold deposits are presented for those of the Attock area at the confluence of the Indus and Kabul rivers in northwestern Pakistan. Two grids covering an area of 10x18 m2 and 8x10 m2 were analyzed using a G-858 Cesium Vapor Magnetometer. The anomalous zones obtained were plotted on contour maps, 2D and 3D magnetic intensity maps. Based on the magnetic anomalies, grid-1 of the study area was sampled at three different anomalous zones for geochemical analysis. These zones contain gold concentrations, ranging from 2.11 ppm to 6.109 ppm with an average of 4.01 ppm. Increase in gold concentration in the subsurface within the anomalous zones indicates that magnetometer survey followed by a geochemical analysis can potentially narrow down the gold-bearing anomalous zones.     

基于GIS和证据权重法的那仁宝力格地区铜多金属矿成矿预测

根据那仁宝力格地区主要铜多金属矿床成矿规律,利用GIS平台提取地、物、化、遥等多元地质找矿信息,在MRAS系统中开展了基于18个成、控矿要素的铜多金属矿成矿预测与评价。根据后验概率值大小编制了成矿后验概率等值线图,划分了4个等级的找矿条件和9个找矿远景区。结果表明,预测模型有效,近95%的已知矿床（点）位于D级及以上找矿有利地区。在众多成、控矿要素中,增隆昌组与阿古鲁沟组、构造信息、遥感组合异常、铁族元素地球化学组合异常等具有较大权重。新圈定的那仁宝力格找矿远景区和霍各乞南部找矿远景区是下一步研究区寻找新的铜多金属矿床的重点地区。     

长江中下游地区不同尺度铜地球化学异常的意义与大型矿床预测

以长江中下游1∶20万铜区域地球化学数据为基础,研究了铜元素地球化学异常特征,认为不同尺度的地球化学异常图具有不同的研究意义:(1)1∶20万地球化学异常可以圈定矿床异常,用于大型矿床预测。研究区内13个大型矿床中有12个落在具有三层套合结构的地球化学异常中,已知矿床储量与异常面金属量、异常面积之间的相关系数分别为0.94、0.95,显示区域地球化学异常规模与储量之间的较好相关性。(2)1∶50万地球化学异常可以圈定矿区异常,用于在成矿带中预测有利成矿区。(3)1∶100万地球化学异常可以圈定大型矿集区或成矿带,用于矿集区预测。如果把研究区内面积大于1 000km2且含有3个以上已知矿床的异常作为矿集区的话,则长江中下游存在3个大型矿集区:马鞍山—南京矿集区、九江—瑞昌—大冶矿集区和德兴—黄山—安庆—铜陵矿集区(实际上包含德兴和铜陵2个矿集区)。大型矿床多产于多层套合的地球化学异常中,大型矿集区所形成的异常具有至少3层套合结构,浓集中心与大型矿床存在对应关系,这些规律的发现为在不同成矿域预测新的大型矿集区提供了重要地球化学标志。