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Alberto Patino E Douce - One of the best experts on this subject based on the ideXlab platform.
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Metallic Mineral resources in the twenty first century i historical extraction trends and expected demand
Natural resources research, 2016Co-Authors: Alberto Patino E DouceAbstract:Industrial, technological, and economic developments depend on the availability of Metallic raw materials. As a greater fraction of the Earth’s population has become part of developed economies and as developed societies have become more affluent, the demand on Metallic Mineral resources has increased. Yet Metallic Minerals are non-renewable natural resources, the supply of which, even if unknown and potentially large, is finite. An analysis of historical extraction trends for eighteen metals, going back to the year 1900, demonstrates that demand of Metallic raw materials has increased as a result of both increase in world population and increase in per-capita consumption. These eighteen metals can be arranged into four distinct groups, for each of which it is possible to identify a consistent pattern of per-capita demand as a function of time. These patterns can, in turn, be explained in terms of the industrial and technological applications, and in some cases conventional uses as well, of the metals in each group. Under the assumption that these patterns will continue into the future, and that world population will grow by no more than about 50% by the year 2100, one can estimate the amount of Metallic raw materials that will be required to sustain the world’s economy throughout the twenty-first century. From the present until the year 2100, the world can be expected to require about one order of magnitude more metal than the total amount of metal that fueled technological and economic growth between the age of steam and the present day. For most of the metals considered here, this corresponds to 5–10 times the amount of metal contained in proven ore reserves. The two chief driving factors of this expected demand are growth in per-capita consumption and present-day absolute population numbers. World population is already so large that additional population growth makes only a small contribution to the expected future demand of Metallic raw materials. It is not known whether or not the amount of metal required to sustain the world’s economy throughout this century exists in exploitable Mineral resources. In the accompanying paper, I show that it is nevertheless possible to make statistical inferences about the size distribution of the Mineral deposits that will need to be discovered and developed in order to satisfy the expected demand. Those results neither prove nor disprove that the needed resources exist but can be used to improve our understanding of the challenges facing future supply of Metallic raw materials.
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Metallic Mineral resources in the twenty first century ii constraints on future supply
Natural resources research, 2016Co-Authors: Alberto Patino E DouceAbstract: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.
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response to comment on Metallic Mineral resources in the twenty first century i historical extraction trends and expected demand by d a singer and w d menzie
Natural resources research, 2016Co-Authors: Alberto Patino E DouceAbstract:Singer and Menzie (2010, p. 24) state: ‘‘The pattern of increasing per-capita consumption with increasing income...defines a growth curve, which may be modeled by a logistic function...’’. Menzie et al. (2005, p. 46) write: ‘‘This pattern defines a growth curve that may be modeled by a logistic function...’’, and then state that they used this function to estimate future levels of copper consumption for the twenty most populous countries, for the year 2020. In their comment, Singer and Menzie (2015) suggest that I may have misinterpreted these statements as implying that they have said that future metal consumption can be modeled by a logistic function of time. There is no misinterpretation. The function that they present (e.g., Singer and Menzie 2010, Eq. 2.1) is a function of time. The variable P (population) in the authors equation is a function of time, and the same is true of the variable i in their equation, that stands for percapita GDP. These facts make consumption, C, a function of time too. Whether time is an explicit variable in the function, or is introduced as a hidden variable that controls the behavior of another variable (or variables), that is (are) explicitly shown in the function, the goal is the same: one is attempting to predict per-capita consumption as a function of time. The authors use the word future, they comment on metal consumption in the year 2020, and they plot Cu consumption as a function of time (Singer and Menzie 2010, Fig. 2.7; Menzie et al. 2005, Figs. 2–7). Singer and Menzie (2010) and Menzie et al. (2005) appear to have used GDP and population estimates generated by the UN (see Singer and Menzie 2009) in order to estimate 2020 copper consumption with a logistic function. Those UN estimates must have been generated by functions of time. Moreover, Singer and Menzie (2010, p. 25) discuss growth of world copper consumption in terms of annual growth rate, i.e., of the first derivative of consumption relative to time. One can only differentiate a variable relative to another variable that it is a function of. Singer and Menzie (2015) also state that ‘‘...direct use of time as a predictor of metal consumption doesn t make sense...’’. I prefer to base scientific arguments on data and rigorous mathematical arguments, rather than on ‘‘sense’’. None of the references given by Singer and Menzie (2015), nor any other publications that I am aware of, proves that worldwide metal consumption of any metal follows a logistic function, nor a Kuznets curve, nor, for that matter, any other specific functional relationship, regardless of whether time appears in the function explicitly or as a hidden variable. Conclusions are derived either from philosophical considDepartment of Geology, University of Georgia, Athens, GA 30602, USA. To whom correspondence should be addressed; e-mail: alpatino@uga.edu
Graeme F Bonhamcarter - One of the best experts on this subject based on the ideXlab platform.
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lithodiversity and its spatial association with Metallic Mineral sites great basin of nevada
Natural resources research, 2001Co-Authors: Mark J Mihalasky, Graeme F BonhamcarterAbstract:Geographical information system (GIS) techniques were used to investigate the spatial association between Metallic Mineral sites and lithodiversity in Nevada. Mineral site data sets include various size and type subsets of about 5,500 metal-bearing occurrences and deposits. Lithodiversity was calculated by counting the number of unique geological map units within four sizes of square-shaped sample neighborhoods (2.5-by-2.5, 5-by-5, 10-by-10, and 20-by-20 km) on three different scales of geological maps (national, 1:2,500,000; state, 1:500,000; county, 1:250,000). The spatial association between Mineral sites and lithodiversity was observed to increase with increasing lithodiversity. This relationship is consistent for (1) both basin-range and range-only regions, (2) four sizes of sample neighborhoods, (3) various Mineral site subsets, (4) the three scales of geological maps, and (5) areas not covered by large-scale maps. A map scale of 1:500,000 and lithodiversity sampling neighborhood of 5-by-5 km was determined to best describe the association. Positive associations occurred for areas having >3 geological map units per neighborhood, with the strongest observed at approximately >7 units. Areas in Nevada with more than three geological map units per 5-by-5 km neighborhood contain more Mineral sites than would be expected resulting from chance. High lithodiversity likely reflects the occurrence of complex structural, stratigraphic, and intrusive relationships that are thought to control, focus, localize, or expose Mineralization. The application of lithodiversity measurements to areas that are not well explored may help delineate regional-scale exploration targets and provide GIS-supported Mineral resource assessment and exploration activity another method that makes use of widely available geological map data.
Xinliang Xu - One of the best experts on this subject based on the ideXlab platform.
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gold copper deposits in wushitala southern tianshan northwest china application of aster data for Mineral exploration
Geological Journal, 2018Co-Authors: Yuan Li, Jun Zhou, Xinliang XuAbstract:The Southern Tianshan area is one of the most important gold belts identified by many world-class, super large and large gold deposits such as Muruntau (Uzbekistan), Kumtor (Kyrgyzstan), and Jilau (Tajikistan). Some medium- to small-scale gold deposits, such as Sawayaerdun and Bulong, have been discovered and reported in recent years at the China part of the belt. The study area, named the Wushitala area, is located in the eastern part of Southern Tianshan, and it has a strong potential for gold and other Metallic Mineral deposits. This study utilizes various image processing techniques, including false colour composite, band ratios, and matched filtering, to process Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and map the distribution of hydrothermal Minerals (e.g., muscovite, kaolinite, chlorite, epidote, goethite, and malachite) related to the known deposits in the Wushitala area. The identified alteration zones are coincident with the known gold and copper deposits and field samples from the study area. The distribution of the alteration zones also indicates that the acid intrusions and regional structures play an important role in focusing the Mineralizing fluids. The results show that ASTER data accompanied with image processing methods and reference spectra (e.g., JPL, lab, or field measured) could be an effective technique for mapping hydrothermal alteration zones in areas with no dominant vegetation cover. Due to the extensively distributed acid intrusions and structures along the Southern Tianshan Belt, the Mineral prospecting methodology is suggested for application in similar geological settings in the belt.
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Mineral mapping and ore prospecting using landsat tm and hyperion data wushitala xinjiang northwestern china
Ore Geology Reviews, 2017Co-Authors: Jun Zhou, Xinliang XuAbstract:Abstract The Southern Tianshan area, situated in central Asia, is one of the most important gold belts identified by many world-class, superlarge and large gold deposits. The Wushitala area, located in the eastern part of Southern Tianshan, Xinjiang (China), has a strong potential for gold and other Metallic Mineral deposits. However, no Metallic Mineral deposit or occurrence has been reported in detail for the Wushitala area in the past, apparently due to poor exploration. This study attempts to map alteration zones and acquire ore prospecting targets in the Wushitala area by integrating Landsat TM and Hyperion data with the ASTER spectral library Mineral spectra. The Crosta technique and the anomaly-overlaying selection method were combined to process four temporal Landsat TM data (acquired in the same season in different years) so as to eliminate the random interference-caused false anomalies of alteration Minerals (iron oxides and hydroxyl-bearing Minerals and carbonates) while retaining the real anomalies. The matched filtering method was applied on Hyperion data for the detailed identification of hydrothermally altered Minerals surrounding the granites in the north. The results of Hyperion data are spatially consistent with those of Landsat TM data. Furthermore, the results of Hyperion data show that the alteration Minerals associated with the potash feldspar granite are dominated by muscovite and goethite. In our field campaign, fourteen sites (eleven acid intrusion-related and three structure-associated) distributed throughout the study area were inspected, all of which proved to be of geological genesis. Our study led to the discovery of three Mineralization sites associated with acid intrusions and structures that were not previously documented. Due to the extensively distributed acid intrusions and structures along the southern Tianshan Belt, several other gold-iron-copper Mineralized locations could be found with more detailed investigations. Our Mineral prospecting methodology proved effective in the study area and is hereby suggested for application in similar geological settings.
Budi Sulistijo - One of the best experts on this subject based on the ideXlab platform.
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Application of Time Domain Induced Polarization (TDIP) Methods to Metallic Minerals Prospect on Kasihan Region, Pacitan Regency, East Java, Indonesia
2019Co-Authors: Yatini, Djoko Santoso, Agus Laesanpura, Budi Sulistijo, Syaiful Bahri, SuyantoAbstract:Metallic Mineral exploration activities primarily base metals often have problems because the resources ofMetallic Minerals located below surface are associated with the surrounding rock. Application of Induced Polarizationmethod was carried out in the area of Mineral prospects at Kasihan Village, Pacitan District, East Java. The InducedPolarization (IP) data were taken by Syscal Junior 458, using Dipole-dipole and Wenner configuration for mapping andSchlumberger configuration for sounding. Magnetic data were obtained by Geotron Magnetometer. Estimation of pyriteMineral deposit was done using modeling of Res2Dinv and RockWork15. Combination of resistivity and chargeabilityis conducted to identify the boundaries of Mineralization zones. The high resistivity value is correlated with the contentof silicate Minerals in the Mineralized zone, whereas the higher chargeability means high degree of Metallic Mineraldeposits (pyrite). The assesment of two different Mineralized zones in metal content is known by combiningchargeability and resistivity with magnetic anomaly.
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Effects of changes in Metallic Mineral to time domain induced polarization (TDIP) response on physical modeling fieldscale
2016Co-Authors: Yatini, Djoko Santoso, Agus Laesanpura, Budi SulistijoAbstract:Induced Polarization (IP) is one of the Geophysical methods that utilize the polarization properties of the rocks. This method is widely used in Metallic Mineral exploration. In this method, it is known a specific method that called as Time Domain Induced Polarization (TDIP). The physical modeling of IP is used to study the behavior of TDIP response to the subsurface parameters. The fieldscale physical modeling is the development of the laboratory physical model. This modeling is realized by burying objects with a specific geometry that have contrasting physical parameter to host medium in the area that is not too extensive. Soil is used as host medium, sphere and block object which has variation in Metallic Mineral content as a target. The extreme targets was also made to evaluate the electrodes measurements. Data acquisitions are using the Dipole-dipole and Wenner configurations. The purpose of this study is obtaining the relations between TDIP response to changes of Metallic Minerals content. Res2DInv ...
Mark J Mihalasky - One of the best experts on this subject based on the ideXlab platform.
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lithodiversity and its spatial association with Metallic Mineral sites great basin of nevada
Natural resources research, 2001Co-Authors: Mark J Mihalasky, Graeme F BonhamcarterAbstract:Geographical information system (GIS) techniques were used to investigate the spatial association between Metallic Mineral sites and lithodiversity in Nevada. Mineral site data sets include various size and type subsets of about 5,500 metal-bearing occurrences and deposits. Lithodiversity was calculated by counting the number of unique geological map units within four sizes of square-shaped sample neighborhoods (2.5-by-2.5, 5-by-5, 10-by-10, and 20-by-20 km) on three different scales of geological maps (national, 1:2,500,000; state, 1:500,000; county, 1:250,000). The spatial association between Mineral sites and lithodiversity was observed to increase with increasing lithodiversity. This relationship is consistent for (1) both basin-range and range-only regions, (2) four sizes of sample neighborhoods, (3) various Mineral site subsets, (4) the three scales of geological maps, and (5) areas not covered by large-scale maps. A map scale of 1:500,000 and lithodiversity sampling neighborhood of 5-by-5 km was determined to best describe the association. Positive associations occurred for areas having >3 geological map units per neighborhood, with the strongest observed at approximately >7 units. Areas in Nevada with more than three geological map units per 5-by-5 km neighborhood contain more Mineral sites than would be expected resulting from chance. High lithodiversity likely reflects the occurrence of complex structural, stratigraphic, and intrusive relationships that are thought to control, focus, localize, or expose Mineralization. The application of lithodiversity measurements to areas that are not well explored may help delineate regional-scale exploration targets and provide GIS-supported Mineral resource assessment and exploration activity another method that makes use of widely available geological map data.