New Method of Fitting Pareto–Lognormal Size-Frequency Distributions to Worldwide Cu and Zn Deposit Size Data

Earlier methods of fitting Pareto–lognormal distributions to large samples of worldwide metal deposit size data are improved by using a sliding window method for estimating upper-tail Pareto coefficients and constructing best-fitting lognormal Q–Q plots with their corresponding probability-density curves. Lower-tail Pareto distributions are fitted to some extent as well. Copper and Zn deposits of the world are taken as example in this paper. Three principal statistical laws resulting in the basic lognormal with two Pareto tails are thought to underlie the generation of Pareto–lognormals for amounts of metal in primarily hydrothermal ore deposits. Historical trends in mining and exploration are thought to create an excess of smaller deposits with respect to the basic lognormal that decreases steadily with increasing deposit size until it changes into a deficit slightly before median size is reached. This deficit decreases for the largest metal deposit sizes for which the upper-tail Pareto and extrapolated basic lognormal show similar size frequencies again. The Pareto–lognormal model can also be used to describe metal size-frequency distributions for smaller geographically coherent regions on the continents. A new version of the original model of de Wijs is considered to help explain why regional Pareto–lognormal distributions with lesser logarithmic variances and Pareto coefficients can be combined to form worldwide size-frequency distributions of the same type.     

Pareto–Lognormal Modeling of Known and Unknown Metal Resources

Recently, large worldwide databases with statistics on amounts of metal in mineral deposits have become available. Frequently, most metal is contained in the largest deposits for a metal. A major problem in meaningful modeling of the size–frequency distributions of the largest deposits is that they are very rare. Until now it was rather difficult to establish the exact form of their size–frequency distribution. However, because of the new very large databases it can now be concluded that two commonly used approaches (lognormal and Pareto) thought to be mutually incompatible in the past, are both correct with a high probability. One approach does not necessarily exclude validity of the other. Patiño-Douce (Nat Resour Res 25(1):97–124, 2016b) has shown that metal tonnage frequency distributions for worldwide metal deposits are approximately lognormal with similar standard deviations (σ) of log-transformed data. In this paper, it is assumed that worldwide metals satisfy both lognormal and Pareto models simultaneously. Copper and Au are taken for example for comparison with results previously obtained for these two metals in the Abitibi area of the Canadian Shield. Worldwide there are 2541 Cu deposits approximately satisfying a lognormal distribution. Total amount of Cu in these deposits is 2.319 × 10⁹ tons of Cu. However, the 45 largest deposits, which together contain 1.281 × 10⁹ tons of Cu, satisfy a Pareto distribution. If their lognormal model would apply in the upper tail as well, these 45 largest deposits should have contained only about 0.076 × 10⁹ tons of Cu. It is shown in detail for Cu that the best statistical model for Cu deposits is a worldwide Pareto–lognormal model in which the basic lognormal size–frequency distribution is flanked by two juxtaposed Pareto distributions for the largest and smallest Cu deposits, respectively. Both Pareto distributions smoothly change into the central lognormal by means of bridge functions that can be determined separately. The worldwide Pareto–lognormal model also was found to be applicable to several other metals, especially Ag, Ni, Pb, and U. For Au, the model does not work as well for the upper tail Pareto distribution as it does for the other metals taken for example.     

Metallic Mineral Resources in the Twenty-First Century: II. Constraints on Future Supply

Supplying worldwide demand of metallic raw materials throughout the rest of this century may require 5–10 times the amount of metals contained in known ore deposits. This demand can be met only if mineral deposits containing the required masses of metals, in excess of present day ore reserves, exist in the Earth’s crust. It is, by definition, not known whether or not such mineral deposits exist. On the basis of the statistical distribution of metal tonnages contained in known ore deposits, however, it is possible to place constraints on the size distribution of the deposits that must be discovered in order to meet the expected demand. A nondimensional analysis of the distribution of metal tonnages in deposits of 20 metals shows that most of them follow distributions that, although not strictly lognormal, share important characteristics with a lognormal distribution. Chief among these is the observation that frequency falls off symmetrically and geometrically with deposit size, relative to a median deposit size that is approximately equal to the geometric mean deposit size. An immediate consequence of this behavior is that most of the metal endowment is concentrated in deposits that are several orders of magnitude larger than the median deposit size, and that are much rarer than the most common deposits that cluster around the median deposit size. The analysis reveals remarkable similarities among the statistical distributions of most of the metals included in this study, in particular, the fact that distribution of most metals can be fully described with essentially the same value (about 2–3) of the scale parameter, σ, which is the only parameter needed to describe the behavior of a normalized lognormal variable. This observation makes it possible to derive the following general conclusions, which are applicable to most metals—both scarce and abundant. First, it is unlikely that undiscovered mineral deposits of sizes comparable to those that contain most of the known metal endowment exist in sufficient quantities to supply the expected worldwide demand throughout the rest of this century. Second, if the expected demand is to be met, one must hope that very large deposits, perhaps up to one order of magnitude larger than the largest known deposits, exist in accessible portions of the Earth’s crust, and that these deposits are discovered.     

中国主要含砷矿产资源的区域分布与砷污染问题

本文分析了我国主要含砷矿资源的区域分布及其开采所带来的环境污染问题。截至2003年底,我国累计探明砷矿资源储量为397.7万t,保有储量279.6万t,其中87.1%的保有储量以共生、伴生砷矿形式存在。砷矿资源分布相对集中于广西、云南、湖南,三省的保有储量占全国保有储量的58.0%;其中广西南丹县和云南个旧市的保有储量最大,分别占全国总保有储量的17.0%和10.2%。我国已经有大量的砷随矿产资源的开采而带至环境中。截至2003年底,全国砷采出量至少高达139.2万t,其中广西、云南、湖南采出量最大,分别达73.3、34.2和15.3万t。在矿产采冶过程中,采出的砷有70%弃留于尾矿中。矿业活动释放的砷已通过土壤及食物链途径威胁到人体健康,尤其是在矿冶活动密集的西南地区问题更加突出。     

Statistical sampling of the distribution of uranium deposits using geologic/geographic clusters

The concept of geologic/geographic clusters was developed particularly to study grade and tonnage models for sandstone-type uranium deposits. A cluster is a grouping of mined as well as unmined uranium occurrences within an arbitrary area about 8 km across. A cluster is a statistical sample that will reflect accurately the distribution of uranium in large regions relative to various geologic and geographic features. The example of the Colorado Plateau Uranium Province reveals that only 3 percent of the total number of clusters is in the largest tonnage-size category, greater than 10,000 short tons U₃O₈, and that 80 percent of the clusters are hosted by Triassic and Jurassic rocks. The distributions of grade and tonnage for clusters in the Powder River Basin show a wide variation; the grade distribution is highly variable, reflecting a difference between roll-front deposits and concretionary deposits, and the Basin contains about half the number in the greater-than-10,000 tonnage-size class as does the Colorado Plateau, even though it is much smaller. The grade and tonnage models should prove useful in finding the richest and largest uranium deposits.     

Sensitivity Analysis of a Feedforward Neural Network for Considering Genetic Mechanisms of Kuroko Deposits

Exploration for volcanogenic massive sulfide deposits of the kuroko-type is underway in many places. Clarifying the spatial patterns of the metals in kuroko deposits will be useful for understanding their genetic mechanisms and for future exploration of such types of deposits. This study represents a spatial distribution analysis on the contents of principal metals of kuroko deposits: Cu, Pb, and Zn, in the Hokuroku district, northern Japan, by a feedforward neural network and 1917 sample data at 143 drillhole sites. The network, which consists of three layers, was trained by the principle of SLANS in which the numbers of neurons in the middle layer and training data are changed to improve estimation accuracy. Using the weight coefficients connecting adjacent neurons, sensitivity analysis of the neural network was carried out to identify factors influencing spatial distributions of the three metals. The coordinates depth (z) direction, Bouguer gravity, and specific lithology such as dacite were determined to be influencing factors. The high frequency of the z coordinate signifies that the metal contents differ to a large extent by depth. The sensitivity vector was defined using sensitivity coefficients for x, y, and z coordinates of an estimation point. We determined that the directions of large vectors were different inside and outside of the Hanawa-Ohdate area. This characteristic is considered to originate from the differences in the permeability of fractures that became the paths for rising ore solutions, and the depths that the solutions mixed with sea water.     

Global Resource Assessments of Primary Metals: An Optimistic Reality Check

The mining of primary metals is critical for a range of modern infrastructure and goods and the continuing growth in global population and consumption means that these primary metals are expected to remain in high demand. However, metallic deposits are, in essence, finite and non-renewable—leading to some concern that we may run out of a given metal in the future. Here, we address this concern by presenting a brief review of the reporting of mineral resource estimates, compiling detailed datasets for national and global trends in mineral resources for numerous metals, and present detailed case studies of major mining projects or fields. The evidence clearly shows strong growth in known mineral resources and cumulative production over time rather than any evidence of gradual resource depletion. In addition, the key factors that already govern existing mining projects and mineral resources are certainly social, environmental and economic in nature rather than geological or related to physical resource depletion. Overall, there is great room for optimism in terms of humankind’s ability to supply future generations with the metals they will require.     

老挝万象通芒矿区成盐期元素地球化学特征研究

呵叻高原是世界上最大的钾盐矿床之一,老挝万象盆地是呵叻高原北部沙空那空盆地的一个次级盆地,通芒矿区则是万象盆地钾盐矿床的重要组成部分。近期,大量钾盐地质勘探工作的实施为该地区钾盐沉积的研究提供了良好条件和物质基础。研究表明,含盐地层包括上、中、下3个盐段,巨厚钾镁盐主要富集在塔贡组下盐段。盐类矿物主要包括石盐、光卤石、钾石盐、水氯镁石、溢晶石、硬石膏等,还包括一些碳酸盐和硼酸盐矿物。矿石类型以光卤石矿为主。含盐层位的Br含量、Br×10³/Cl比值在剖面上的变化指示了成盐期卤水不断蒸发浓缩,最终形成了具有重要经济价值的钾镁盐矿床。与世界其它海相及陆相钾盐矿床对比表明,通芒矿区钾盐沉积具有明显的海相特征,成盐成钾物质应该来自海水。     

Some Aspects of the Boundaries and Frontiers of Israel

Abstract

An intensive and comprehensively planned program of mineral exploration and discovery is the most important single factor in maintaining an adequate supply of available minerals.

This program requires the services of a large staff of geologists and geophysicists adequately equipped with the essential instruments of exploration.

Exploration, even tho it results in substantial discoveries, will not be adequate without the aid of the miners, metallurgists, engineers, architects, and contributions from deposits in foreign countries.

Developments in mining—such as diamond drilling, block caving, and removal of overburden—have contributed toward making ore deposits of low grade economically exploitable, thereby increasing the supply of metal that can be made available.     

Compositional changes in sediments of subalpine lakes,Uinta Mountains (Utah): evidence for the effects of human activity on atmospheric dust inputs

Sediments in Marshall and Hidden Lakes in the Uinta Mountains of northeastern Utah contain records of atmospheric mineral-dust deposition as revealed by differences in mineralogy and geochemistry of lake sediments relative to Precambrian clastic rocks in the watersheds. In cores spanning more than a thousand years, the largest changes in composition occurred within the past approximately 140 years. Many elements associated with ore deposits (Ag, As, Bi, Cd, Cu, In, Mo, Pb, S, Sb, Sn, and Te) increase in the lake sediments above depths that correspond to about AD 1870. Sources of these metals from mining districts to the west of the Uinta Mountains are suggested by (1) the absence of mining and smelting of these metals in the Uinta Mountains, and (2) lower concentrations of most of these elements in post-settlement sediments of Hidden Lake than in those of Marshall Lake, which is closer to areas of mining and the densely urbanized part of north-central Utah that is termed the Wasatch Front, and (3) correspondence of Pb isotopic compositions in the sediments with isotopic composition of ores likely to have been smelted in the Wasatch Front. A major source of Cu in lake sediments may have been the Bingham Canyon open-pit mine 110 km west of Marshall Lake. Numerous other sources of metals beyond the Wasatch Front are likely, on the basis of the widespread increases of industrial activities in western United States since about AD 1900. In sediment deposited since ca. AD 1945, as estimated using ^239+240Pu activities, increases in concentrations of Mn, Fe, S, and some other redox-sensitive metals may result partly from diagenesis related to changes in redox. However, our results indicate that these elemental increases are also related to atmospheric inputs on the basis of their large increases that are nearly coincident with abrupt increases in silt-sized, titanium-bearing detrital magnetite. Such magnetite is interpreted as a component of atmospheric dust, because it is absent in catchment bedrock. Enrichment of P in sediments deposited after ca. AD 1950 appears to be caused largely by atmospheric inputs, perhaps from agricultural fertilizer along with magnetite-bearing soil.     

柴达木盆地西部天青石矿区矿物学与元素地球化学特征研究

柴达木盆地天青石资源极为丰富,已发现有大风山、碱山、尖顶山等大型天青石矿床。通过元素分析、元素相关性分析、矿物组合分析等方法与手段,对柴达木盆地天青石矿区矿物特点及元素地球化学特征进行了研究。得到如下结论:大风山矿区以天青石—方解石—镁方解石矿物组合为主,矿物品位均值为59%;碱山矿区以天青石—文石矿物组合为主,矿物品位均值为39.6%;石膏、白云石在各矿区矿物均有分布,且含量较低。石膏与天青石成正相关关系,白云石的存在对天青石成矿来说是不利因素,铁白云石、文石和镁方解石的普遍存在可说明该区矿物成矿温度较高。Sr与S成正相关关系,证明Sr主要以天青石(硫酸锶)形式存在,锶与镁、钙成非线性关系,锶含量高则钙含量低,钙主要赋存在石膏中,而非方解石中。Sr/Ba比值、Sr/Cu比值分析表明该矿区经历过长期干旱的环境,Mg/Ca比值分析表明该区天青石成矿过程中微生物对其成矿作用起到了非常重要的作用。     

Multi-scale Quantitative Risk Analysis of Seabed Minerals: Principles and Application to Seafloor Massive Sulfide Prospects

The potential for mining hydrothermal mineral deposits on the seafloor, such as seafloor massive sulfides, has become technically possible, and some companies (currently not many) are considering their exploration and development. Yet, no present methodology has been designed to quantify the ore potential and assess the risks relative to prospectivity at prospect and regional scales. Multi-scale exploration techniques, similar to those of the play analysis that are used in the oil and gas industry, can help to fulfill this task by identifying the characteristics of geologic environments indicative of ore-forming processes. Such characteristics can represent a combination of, e.g., heat source, pathway, trap and reservoir that all dictate how and where ore components are mobilized from source to deposition. In this study, the understanding of these key elements is developed as a mineral system, which serves as a guide for mapping the risk of the presence or absence of ore-forming processes within the region of interest (the permissive tract). The risk analysis is carried out using geoscience data, and it is paired with quantitative resource estimation analysis to estimate the in-place mineral potential. Resource estimates are simulated stochastically with the help of available data (bathymetric features in this study), conventional grade–tonnage models and Monte Carlo simulation techniques. In this paper, the workflow for a multi-scale quantitative risk analysis, from the definition to the evaluation of a permissive tract and related prospect(s), is described with the help of multi-beam data of a known hydrothermal vent site.

     

沅江下游入湖段河床沉积物重金属污染特征

对沅江入湖沉积物进行钻探取样,利用等离子质谱仪（ICP-MS）对沉积物重金属进行分析。结果表明：重金属Ba、Sc、V、Th、U、Cu、Co、Ni、Cr等在沉积物中含量变化相对稳定,分布相对均匀;而Mn、Zn、Pb、Mo、Cd、Tl、Bi等重金属的含量变化大,分布不均匀。重金属含量柱状剖面变化特征及富集系数（EF值）的计算结果显示：沉积物中Cd达显著富集,而Sc、V、Mn、Pb、Bi等为中等富集程度。沉积物中存在3个重金属富集层,即中下部Pb、Tl、Bi富集层;中上部Pb、Cr、Ni、Cu富集层;浅表部V、Cr、Mn、Ni、Cu、Zn、Pb、Cd、Tl、Bi等多种重金属富集层。地累积指数（I_geo）和综合富集指数（EI）评价结果显示：沅江入湖沉积物重金属污染程度自河床深部向浅部,污染程度趋于增强,污染元素组合趋于由Pb-Bi的单一元素组合向由V-Cr-Mn-Ni-Cu-Zn-Pb-Cd-Bi组成的复合元素组合变化。且自上游向下游,沉积物重金属污染程度趋于降低。这种重金属污染空间变化特征与区域人为活动有关,值得进一步研究。     

Using Dummy Variables to Estimate Economic Base Multipliers

Economic base analysis is a cost-effective and accurate means of predicting employment impacts in relatively small and uncomplicated regional (community) economies. Extending previous research using the Arizona Community Data Set, this paper estimates economic base multipliers in different types of communities by introducing dummy variables into regression equations. Total employment, transfer payments, and population potential are used as explanatory variables. Manufacturing centers are shown to have larger multipliers than diversified places, mining settlements, service and trade communities, and utility towns.     

Boosting for Mineral Prospectivity Modeling: A New GIS Toolbox

With an increasing demand for raw materials, predictive models that support successful mineral exploration targeting are of great importance. We evaluated different machine learning techniques with an emphasis on boosting algorithms and implemented them in an ArcGIS toolbox. Performance was tested on an exploration dataset from the Iberian Pyrite Belt (IPB) with respect to accuracy, performance, stability, and robustness. Boosting algorithms are ensemble methods used in supervised learning for regression and classification. They combine weak classifiers, i.e., classifiers that perform slightly better than random guessing to obtain robust classifiers. Each time a weak learner is added; the learning set is reweighted to give more importance to misclassified samples. Our test area, the IPB, is one of the oldest mining districts in the world and hosts giant volcanic-hosted massive sulfide (VMS) deposits. The spatial density of ore deposits, as well as the size and tonnage, makes the area unique, and due to the high data availability and number of known deposits, well-suited for testing machine learning algorithms. We combined several geophysical datasets, as well as layers derived from geological maps as predictors of the presence or absence of VMS deposits. Boosting algorithms such as BrownBoost and Adaboost were tested and compared to Logistic Regression (LR), Random Forests (RF) and Support Vector machines (SVM) in several experiments. We found performance results relatively similar, especially to BrownBoost, which slightly outperformed LR and SVM with respective accuracies of 0.96 compared to 0.89 and 0.93. Data augmentation by perturbing deposit location led to a 7% improvement in results. Variations in the split ratio of training and test data led to a reduction in the accuracy of the prediction result with relative stability occurring at a critical point at around 26 training samples out of 130 total samples. When lower numbers of training data were introduced accuracy dropped significantly. In comparison with other machine learning methods, Adaboost is user-friendly due to relatively short training and prediction times, the low likelihood of overfitting and the reduced number of hyperparameters for optimization. Boosting algorithms gave high predictive accuracies, making them a potential data-driven alternative for regional scale and/or brownfields mineral exploration.

     

Probabilistic Estimates of Number of Undiscovered Deposits and Their Total Tonnages in Permissive Tracts Using Deposit Densities

Empirical evidence indicates that processes affecting number and quantity of resources in geologic settings are very general across deposit types. Sizes of permissive tracts that geologically could contain the deposits are excellent predictors of numbers of deposits. In addition, total ore tonnage of mineral deposits of a particular type in a tract is proportional to the type’s median tonnage in a tract. Regressions using size of permissive tracts and median tonnage allow estimation of number of deposits and of total tonnage of mineralization. These powerful estimators, based on 10 different deposit types from 109 permissive worldwide control tracts, generalize across deposit types. Estimates of number of deposits and of total tonnage of mineral deposits are made by regressing permissive area, and mean (in logs) tons in deposits of the type, against number of deposits and total tonnage of deposits in the tract for the 50th percentile estimates. The regression equations (R ² = 0.91 and 0.95) can be used for all deposit types just by inserting logarithmic values of permissive area in square kilometers, and mean tons in deposits in millions of metric tons. The regression equations provide estimates at the 50th percentile, and other equations are provided for 90% confidence limits for lower estimates and 10% confidence limits for upper estimates of number of deposits and total tonnage. Equations for these percentile estimates along with expected value estimates are presented here along with comparisons with independent expert estimates. Also provided are the equations for correcting for the known well-explored deposits in a tract. These deposit-density models require internally consistent grade and tonnage models and delineations for arriving at unbiased estimates.     

Resources of the complex of metals in the iron ore field on the territory of Jewish Autonomous Oblast

In the southern part of Jewish Autonomous Oblast, large resources of iron ores and accompanying metals contained in them have been assessed. As regards the resources of iron ores, it is one of the largest deposits in the Far East, and according to the complex of satellite metals, it is similar to some deposits in China, while with respect to the value of the resources, it refers to world class objects.     

Ore value-tonnage diagrams for resource assessment

An ore value-tonnage diagram has been proposed for assessing mineral resources. Diagrams of W+Mo, and Pb+Zn deposits show a good linearity between ore value and logarithms of cumulative ore tonnage. Diagrams of the massive sulfide, orthomagmatic, placer, porphyry, replacement, and stratabound types are also linear. It is assumed, therefore, that deposits of each of these commodities and these types belong to a single population. In contrast, the ore value-tonnage relations of all the deposits analyzed here is approximated by the combination of two exponential functions. The same feature is seen for deposits of the Cu+W+Mo, Cu+Pb+Zn, and Au+Ag commodities, and of the vein and unconformity-related types. This suggests that deposits belonging to each of such categories are divided into the high and low value groups. We can expect, accordingly, to find high value deposits of such categories.     

STORAGE OF MINING-RELATED ZINC IN FLOODPLAIN SEDIMENTS,BLUE RIVER,WISCONSIN

This study investigates spatial patterns of sediment-associated zinc (Zn) storage in floodplain deposits and the potential reintroduction of these metal-contaminated sediments to the active channel by bank erosion. We estimate patterns of Zn mass storage by combining longitudinal trends in Zn concentrations with measurements of sediment mass storage in overbank and point-bar deposits. Overbank deposits are the largest contaminant sink, storing five times more Zn than the point-bar deposits. While Zn concentrations decrease downstream because of dilution effects, the total mass of Zn stored in floodplains is greatest in both the upstream reaches and in the wider lower valleys where low channel gradients promote rapid sedimentation. Zn storage is low in middle reaches where steep, narrow valleys with high stream power favor sediment transport over deposition. Overall, more than half of the Zn released by mining remains stored in floodplain deposits within the watershed. The remobilization of Zn from storage is more likely in the upstream and mid-basin reaches where high stream power increases rates of lateral channel migration. Channels in the lower valley lack the stream power to migrate laterally and remobilize the large Zn mass stored in overbank sediments. [Key words: floodplains, Zn contamination, mining, stream power, Wisconsin.]     

Application of the Geo-Anomaly Unit Concept in Quantitative Delineation and Assessment of Gold Ore Targets in Western Shandong Uplift Terrain,Eastern China

A number of large and giant ore deposits have been discovered within the relatively small areas of lithospheric structure anomalies, including various boundary zones of tectonic plates. The regions have become the well-known intercontinental ore-forming belts, such as the circum-Pacific gold–copper, copper–molybdenum, and tungsten–tin metallogenic belts. These belts are typical geological anomalous areas. An investigation into the hydrothermal ore deposits in different regions in the former Soviet Union illustrated that the geologic structures of ore fields of almost all major commercial deposits have distinct features compared with the neighboring areas. These areas with distinct features are defined as geo-anomalies. A geo-anomaly refers to such a geologic body or a combination of bodies that their composition, texture–structure, and genesis are significantly different from those of their surroundings. A geo-anomaly unit (GU) is an area containing distinct features that can be delineated with integrated ore-forming information using computer techniques on the basis of the geo-anomaly concept. Herein, the GU concept is illustrated by a case study of delineating the gold ore targets in the western Shandong uplift terrain, eastern China. It includes: (1) analyses of gold ore-forming factors; (2) compilation of normalized regional geochemical map and extraction of geochemical anomalies; (3) compilation of gravitational and aeromagnetic tectonic skeleton map and extraction of gravitational and aeromagnetic anomalies; (4) extraction of circular and linear anomalies from remote-sensing Landsat TM images; (5) establishment of a geo-anomaly conceptual model associated with known gold mineralization; (6) establishment of gold ore-forming favorability by computing techniques; and (7) delineation and assessment of ore-forming units. The units with high favorability are suggested as ore targets.