山东招掖与吉林夹皮沟地区金矿床品位—吨位模型对比研究

矿床品位—吨位模型系表征某一类矿床品位和吨位变化范围及其频率分布的定量化模型。基于大量可靠统计数据而建立起来的品位—吨位模型,与成矿地质背景结合起来分析,对探讨矿床形成条件、成矿规律、矿产资源预测以及基底岩石对成矿贡献等方面均具有广泛的应用前景。本文着重从品位—吨位模型角度,讨论招掖与夹皮沟地区基底岩石对成矿贡献方面所提供的有用信息。     

矿区尺度的品位-吨位模型研究探讨——以崤山金矿区为例

矿床品位-吨位模型属于矿床统计模型,是矿产资源潜力评价的重要组成部分。依据河南省陕县金矿储量核查成果数据,选取崤山金矿区为研究对象,利用SPSS软件及Excel对全矿区75个金矿矿体块段品位、吨位数据进行频率分布分析与处理,然后进行P-P图及Q-Q图正态检验,建立了矿体块段品位模型、吨位模型、品位-吨位联合模型。总结了崤山金矿区矿体块段品位及吨位分布的典型数学地质特征,并探讨了品位-吨位模型在该矿区资源预测评价中的作用,为今后矿区的地质工作提供指导。     

矿产资源定量评价中待发现矿床数目的估算—以委内瑞拉和波多黎各为例

美国地质调查所广泛应用的矿产资源定量评价方法建立在矿床模型之上，包括三部分工作内容：（１）选择合适的矿床模型并在地质因上圈出相应矿床的可能成矿区；（２）建立每类矿床的品位一吨位模型；（３）估算每类矿床的待发现数目。本文着重讨论如何用矿床密度法和靶区计算法对待发现矿床数目进行估算。矿床密度法是通过类比进行的，也就是把评价区与地质情况类似、勘探程度高的地区的矿床密度相比。此法适用于资料很少或没有的地区，本文给出了怎样用此法估算低硫化物石英脉型金矿（本文中委内瑞拉）的数目。靶区计算法是一种通过统计矿点，地球物理、地球化学异常或勘探基地的数目，并对每个靶区给定一个发现符合品位一吨位分布模型的矿床产出概率，最后获取某地区矿床数目的方法。此法适用于具有详尽地质、地球物理、地球化学和矿床、矿点资料的地区。本文运用这个方法对波多黎各岛斑岩金—铜矿床数目进行了估算。     

中国大型-超大型铜矿床品位-吨位模型

矿床品位-吨位模型研究属于学科前沿领域,它是系统勘查理论的重要组成部分.依据"97年全国矿产储量数据库"资料,对全国27个大型-超大型铜矿床建立了地质模型、品位模型、吨位模型、吨位-品位联合模型、以及中国斑岩型铜矿床吨位序列模型.模型类型包括频率直方图、累积频率分布图以及双对数坐标表示的理论分布模型.分别总结了中国大型超大型铜矿床的品位及吨位分布的典型数学地质特征,并探讨了吨位-品位模型在资源预测评价中的意义和作用.     

矿产资源潜力定量评价研究——以长江中下游斑岩铜矿为例

三部式定量评价是指(Singer,1993):①根据地质特征和矿床模型圈定各种矿床类型的成矿远景区;②使用品位一吨位模型评价潜在矿床规模和矿石特征;③估算各远景区内每种矿床类型的潜在矿床数目;最后,使用蒙特卡罗方法模拟计算所有远景区内的潜在资源量.本文以成矿系统理论(翟裕生,1999)为指导,运用三部式定量评价方法与地球化学块体评价方法在长江中下游地区开展了斑岩铜矿定量评价对比研究.     

中国岩金矿床品位-吨位模型研究

矿床品位-吨位模型研究属于学科前沿领域, 它是系统勘查理论的重要组成部分.依据1997年全国矿产储量数据库资料, 对全国680个岩金矿床建立了地质模型、品位模型、吨位模型、吨-品位联合模型, 以及中国石英脉型金矿床吨位序列模型.模型类型包括频率直方图、累积频率分布图及双对数坐标表示的理论分布模型.分别总结了我国岩金矿床的品位及吨位分布的典型数学地质特征, 并探讨了吨位序列模型在资源预测评价中的意义和作用.      

矿床地质经济模型法在东天山铜镍矿预测中的应用

以中国铜镍硫化物矿床成矿规律研究现状和2005年全国储量平衡表为依据,在分析总结国内外品位-吨位模型研究的基础上,建立了中国铜镍硫化物矿床的矿床地质经济模型,主要包括描述性模型和品位-吨位模型。并以新疆东天山为例,采用矿床地质经济模型法对铜镍硫化物矿床的资源潜力进行评价,共圈定29个矿田级远景区,估算铜资源量453×104t,镍资源量448×104t,表明东天山地区该类型矿床资源潜力较大。     

中国硫矿床品位-吨位模型

矿床品位一吨位模型是矿产资源潜力评价的重要组成部分.以1999年全国矿产储量数据库的资料为依据,在对全国285个硫矿床进行频率直方图、正态及对数正态统计检验的基础上,建立了不同类型硫矿床的品位一吨位模型.不同类型的模型分布特征表明,中国硫矿资源的找矿前景良好、潜力巨大,其中热液黄铁矿型硫矿床和黄铁矿沉积型硫矿床是今后主要的找矿类型和方向.     

区域矿产定量评价的矿床综合信息评价模型

控制矿床生成的地质要素和识别矿床存在的勘查信息对区域矿产预测评价是至关重要的。矿床综合信息评价模型要从传统的矿床模型出发,将其总结和转化为区域预测评价的控矿关键预测要素,研究识别矿床存在的物、化、遥勘查信息,开展矿床品位-吨位统计特征研究,形成预测评价的要素集,进行矿产预测。     

待发现矿产资源三步定量评价中的基本概念

１９７５年以来，已运用三步定量评价方法对总面积为５×１０￣６ｋｍ￣２的２７个地区进行了不同比例尺的矿产资源评价。在评价过程中，（１）根据地质条件圈定各种矿床类型的可能产出范围；（２）使用品位一吨位模型估算出金属量和矿石特征；（３）估算每类待发现矿床的数目。一类或数类矿床的成矿允许边界（Ｐｅｒｍｉｓｓｉｖｅｂｏｕｎｄａｒｉｅｓ．）是这样固定的：矿床位于界线以外的概率应小于１０￣（－５）～１０￣（－６），也可以忽略不计。品位一吨位模型与矿床数目的估算相结合，是把地质术语转化为经济学家所能理解的经济术语的基本方法。矿床数目的估算实际上代表了预测区内，实际存在但数目未知的待发现矿床的概率（信度）。估算要按矿床类型进行，并且必须与品位一吨位模型中的矿床类型相一致。估算应考虑的其它方面包括：（１）勘探程度高的地区某类矿床的产出频率；（２）局部矿床的外推；（３）对异常和矿化现象的估算并且指定产出概率；（４）成矿控制因素；（５）有关矿床类型的相对产出频率；（６）区域矿床产出空间界线。许多情况下，如同气象、掷骰和其它地质解释一样，估算往往具有某些主观性。在三步定量评价过程中，估算过程具有内在一致性：成矿区的地质特征与描述性模     

Some Suggested Future Directions ofQuantitative Resource Assessments

Like most journeys, success depends critically on wherewe are going to be in the end. Thus, if we are to have someideas about future directions of quantitative assessments ofmineral resources, we need some basic understanding of whatthe assessments will be used for. What will be expected ofquantitative resource assessments in the future? It would behelpful to identify who will use these future assessments, howthe assessments will be used, and what are acceptable forms ofproducts. The purpose o…     

Methods of Three-part Quantitative Assessments of Undiscovered Mineral Resources: Examples from Victoria,Australia

Quantitative mineral resource assessments following the 3-part form rely on grade and tonnage models and probabilistic estimates of the number of undiscovered deposits. Assessments completed in Victoria, Australia, indicate that undiscovered mineral resources can be effectively estimated using grade and tonnage sub-models constructed using only medium- and large-tonnage deposits. Numbers of undiscovered deposits can be estimated on the basis of expert judgement or entirely by statistical means. Appropriate mathematical aggregation of individual expert views, expressed at interactive expert workshops, provides robust estimates of the number of undiscovered deposits. Underestimation of uncertainty, which is common in expert judgement, can be compensated by the statistical modification of individual interval estimates. In this study, the linear opinion pool was used as a simple and robust method of mathematical aggregation of multiple expert estimates of the number of undiscovered deposits. A general regression model, which estimates numbers of undiscovered deposits based on the size of the geologically permissive area and the median deposit tonnage, provided results generally compatible with those based on expert judgement or local deposit density models.     

辽宁省杨家杖子钼矿田成矿模式与找矿标志

杨家杖子钼矿田位于著名的八家子-杨家杖子岩浆热液成矿带的中部,成矿带内由于沉积地层有利、岩浆岩发育、断裂构造复杂等一系列有利条件而形成了一大批大、中型钼矿床.以区域地质特征为基础,重点对矿田内最发育的兰家沟钼矿、杨家杖子钼矿和北松树卯钼矿成矿地质背景、矿床地质特征进行了详尽的研究,并结合成矿物质来源、成矿温度、成矿时代重新确定矿床成因,总结成矿主要过程,从而建立矿田区域成矿模式.在此基础上总结了杨家杖子钼矿田地质、物探、化探找矿标志.     

西藏自治区谢通门县斯弄多铅锌矿区地球物理特征及找矿方向

浅成低温热液型矿床是一类主要产于陆相火山岩或与陆相火山岩有关的低温热液矿床,矿床埋藏深度浅是其最大的特点,这也使地球物理勘探方法在这类矿床的勘查中具有先天优势。本文通过对西藏斯弄多Pb-Zn-Ag多金属浅成低温热液型矿床的地球物理参数特征研究,采用激发极化法等综合物探技术在矿体外围探获具有巨大前景的Pb-Zn-Au-Ag浅成低温热液型矿体。目前单工程控制有3段矿体:顶部Au-Ag矿体,中部Au矿体,底部Pb-Zn-Ag矿体。矿体最高Au品位可达5.3g/t,Ag最高品位410g/t,Pb+Zn综合平均品位5.9%。研究结果表明,斯弄多地区林子宗群火山岩物性参数稳定,对矿体异常干扰较小,产于该套火山岩中极强硅化体中的浅成低温热液型Au矿多具有中高极化率和中低阻特征。     

Modeling Combined Geological and Grade Uncertainty: Application of Multiple-Point Simulation at the Apensu Gold Deposit, Ghana

Traditionally within the mining industry, single models for both grade and geology of orebodies are created upon which all mine development decisions are based. These models provide a single interpretation of the extent and continuity of the mineralization envelope based on solids and sections interpreted from relatively widely spaced drilling. The inherent variable behavior of grade and geology cannot be understood from a single estimated resource model. To account for uncertainty in the geology and mineralization envelope, Newmont Mining Corporation uses multiple-point statistics (MPS), an emerging spatial simulation framework, which can be employed to generate multiple, geologically realistic, realizations of data representing attributes of mineral deposits that display complex non-linear features. MPS uses a conceptual model of the geology, termed a training image, to infer these high-order spatial relationships. A detailed application of the MPS algorithm at the structurally controlled Apensu gold deposit, Ghana, demonstrates the practical intricacies of the MPS framework and documents efficiency and effectiveness. Multiple realizations of the Apensu deposit allow for an assessment of the geologic and volumetric uncertainty, which is further combined with grade simulations to generate a more complete picture of the true uncertainty of the deposit.     

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.     

A case history of regional geoscience data integration and analysis for the purpose of mineral resource appraisal, kasmere lake area, Manitoba

The methods used to generate a unified cell structured data base for geological, mineral occurrence, geochemical, and three different types of geophysical data are reviewed. The extremes of both excess and paucity of data were encountered and procedures for data compression and interpolation between known values were required. In the latter case a weighted moving average was used to take advantage of knowledge of the regional geological structure in an informal kriging. Classical approaches based on training data sets were investigated and found to be wanting in the area due to the inadequate mineral occurrence data base. The few data cells containing mineral occurrences were known with certainty; however, many of the cells classified as non-mineral occurrence containing, due to the immature exploration history, probably contained mineral occurrences of equal or greater significance. This inadequacy in the mineral occurrence data base confounded formal statistical analysis. An empirical scoring approach was developed which draws on general exploration criteria. This methodology, based on the geochemical and geophysical data, was used to prepare an Athabasca type uranium deposit favorability index. The favorable areas are examined in terms of the known geology. Results show that the majority fell in areas that would also be considered favorable by geologic models for Athabasca type uranium deposits. This empirical approach, based on geochemical and geophysical interpretive procedures, may have particular potential in poorly explored areas lacking good training sets.Paper presented at the 10th Geochautauqua: Computer Applications in the Earth Sciences, 23–24 October 1981, Ottawa, Canada.     

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.     

青海长征沟地区铁矿床地质特征及成因探讨

青海长征沟地区铁矿床位于南祁连地块与柴达木地块拼接部位北缘,是近年来发现的一个重要铁矿床。为查明该地区铁矿床特征及成因类型,主要通过地质学手段进行详细的地质调查研究,为后续区域地质矿产工作规划部署和矿产勘查提供依据。 研究表明: 区内主要出露滩间山群安山玄武岩地层,区域变质程度较低,多表现为微弱的绿帘石化; 在西部黑山泉及藏羊沟中段局部夹含透镜状大理岩,普遍发育矽卡岩化,代表性蚀变有透辉石化、绿帘石化及石榴子石化等,局部发育矽卡岩型磁铁矿; 侵入岩发育,从基性到酸性均有出露,北部以基性为主,向南逐渐过渡为(中)酸性侵入岩为主。 因此认为该矿床属于与中酸性侵入岩有关的矽卡岩型铁矿床,并指出岩性、构造、蚀变和物探4种找矿标志。     

Assessment of undiscovered nickel sulphide resources,Kalgoorlie Terrane,Western Australia: Part 1. Deposit and endowment density models

The use of mineral deposit density regression models to estimate the number of undiscovered deposits is gaining acceptance in mineral resources assessments. The deposit density regression models currently in use are based on well-established power law relationships between deposit density (deposits/km²) and the areal extent of the host rocks in well explored regions (control areas) worldwide. Although these generalized or global deposit density models can generate guideline estimates that are useful at the terrane scale, locally-derived terrane-based deposit density regression models may potentially yield more relevant estimates at the terrane scale. Using 12 selected komatiite-defined control areas in the Kalgoorlie Terrane, Western Australia, we found that the size (km²) of the control areas had power law relationships with (i) nickel sulphide deposit density, and (ii) nickel endowment density (nickel metal/km²). Regression analyses showed that both power law relationships are statistically significant at the 5% level. This suggests that nickel sulphide deposit and endowment density models could be used to estimate the number of undiscovered nickel sulphide deposits and amount of nickel metal endowment in less explored komatiites in the Kalgoorlie Terrane. This study shows that global geological relationships can be viably downscaled onto local geological terranes thereby supporting the hypothesis that the processes of mineral deposit formation and preservation are scale-independent and self-similar.