阿拉善高原沙漠地区植物钙质根管的矿物组成特征

在阿拉善高原地区,植物钙质根管的成因及其是否具有一定的环境指示意义,目前尚存在较大争论。分析该区域植物钙质根管的矿物组成,可以为植物钙质根管的成因提供新的证据解释。本文通过近5年的野外考察,先后采集了巴丹吉林沙漠、腾格里沙漠及乌兰布和沙漠腹地33组植物钙质根管和33个地表风积砂样品,通过X衍射的方法,分析了上述样品的矿物组成。结果显示:上述沙漠地区植物钙质根管和地表风积砂中矿物组成以硅酸盐矿物、氧化物和氢氧化物矿物、碳酸盐类矿物为主,没有明显的区域差异。其中碳酸盐类矿物均以方解石为主,较少含有其他盐类矿物,并且植物钙质根管中碳酸盐类矿物百分含量明显高于地表风积砂中碳酸盐类矿物的百分含量。因此,单纯的地下水重结晶作用无法解释本研究区内植物钙质根管中盐类矿物的组成以及碳酸盐类矿物的来源,并且在研究区内现代气候条件不利于植物根系的钙化和钙质根管的形成。植物钙质根管应是地质历史时期的产物,指示了相对湿润的气候条件。     

中国矿产资源生态补偿研究

中国是一个人口众多、社会经济快速发展的国家,如何实现矿产资源开发与生态环境保护的协调发展直接关系到整个国家社会经济的又好又快发展,而对矿产资源实施生态补偿是能有效协调资源开发和环境保护的重要途径。因此,矿产资源的生态补偿问题研究逐渐成为人们日益关心的热点和许多学者研究的焦点。采用文献资料法、综合分析归纳法,分析国内外矿产资源生态补偿的研究状况,从资源开采、生态环境保护和矿区周围农户生计三者协调发展的角度,对中国矿产资源生态补偿中存在问题及原因进行分析,并提出一些改进建议与对策。     

矿产资源开发的战略环境评价研究

分析中国矿产资源开发战略环境评价(SEA)的必要性及不同类型矿产资源开发SEA的作用,提出矿产资源开发SEA的工作原则,在公共参与的基础上,建立包括社会、经济、资源、环境和人口5 部分内容的评价指标体系,确定适用于矿产资源开发SEA的评价方法与程序。中国矿产资源开发SEA,目前只能适用于规划范畴,并以矿产资源开发预测性SEA为主。     

A Bat Algorithm-Based Data-Driven Model for Mineral Prospectivity Mapping

In data-driven mineral prospectivity mapping, a statistical model is established to represent the spatial relationship between layers of metallogenic evidence and locations of known mineral deposits, and then, the former are integrated into a mineral prospectivity model using the established model. Establishment of a data-driven mineral prospectivity model can be regarded as a process of searching for the optimal integration of layers of metallogenic evidence in order to maximize the spatial relationship between mineral prospectivity and the locations of known mineral deposits. Mineral prospectivity can be simply defined as the weighted sum of layers of metallogenic evidence. Then, the optimal integration of the layers of evidence can be determined by optimizing weight coefficients of the layers of evidence to maximize the area under the curve (AUC) of the defined model. To this end, a bat algorithm-based model is proposed for data-driven mineral prospectivity mapping. In this model, the AUC of the model is used as the objective function of the bat algorithm, and the ranges of the weight coefficients of layers of evidence are used to define the search space of the bat population, and the optimal weight coefficients are then automatically determined through the iterative search process of the bat algorithm. The bat algorithm-based model was used to map mineral prospectivity in the Helong district, Jilin Province, China. Because of the high performance of the traditional logistic regression model for data-driven mineral prospectivity mapping, it was used as a benchmark model for comparison with the bat algorithm-based model. The result shows that the receiver operating characteristic (ROC) curve of the bat algorithm-based model is coincident with that of the logistic regression model in the ROC space. The AUC of the bat algorithm-based model (0.88) is slightly larger than that of the logistic regression model (0.87). The optimal threshold for extracting mineral targets was determined by using the Youden index. The mineral targets optimally delineated by using the bat algorithm-based model and logistic regression model account for 8.10% and 11.24% of the study area, respectively, both of which contain 79% of the known mineral deposits. These results indicate that the performance of the bat algorithm-based model is comparable with that of the logistic regression model in data-driven mineral prospectivity mapping. Therefore, the bat algorithm-based model is a potentially useful high-performance data-driven mineral prospectivity mapping model.

     

Classifying mineral potential in support of land-use policy decisions in British Columbia,Canada

British Columbia covers a vast segment of the Cordillera Mountain system that is richly endowed with a diversity of resources. British Columbia's historic patterns of resource development increasingly have been in conflict with demands for greater environmental protection. To avoid such conflicts, a recently legislated process that provides for detailed mineral resource assessments in candidate park areas has stimulated the creation of a mineral potential classification system for use in land-use planning and policy decisions.A mineral potential study of the Chilko Lake Planning Area provided three unique categories of field data on which to build the classification system. These categories are geological setting, geochemistry, and mineral occurrences. Data in each category were compiled independently to provide indicators of mineral potential. The field data were used to develop a widely understood classification of mineral potential. The classification is based on two factors: favorability and degree of confidence.     

A Comparative Analysis of Weights of Evidence,Evidential Belief Functions,and Fuzzy Logic for Mineral Potential Mapping Using Incomplete Data at the Scale of Investigation

Large amounts of digital data must be analyzed and integrated to generate mineral potential maps, which can be used for exploration targeting. The quality of the mineral potential maps is dependent on the quality of the data used as inputs, with higher quality inputs producing higher quality outputs. In mineral exploration, particularly in regions with little to no exploration history, datasets are often incomplete at the scale of investigation with data missing due to incomplete mapping or the unavailability of data over certain areas. It is not always clear that datasets are incomplete, and this study examines how mineral potential mapping results may differ in this context. Different methods of mineral potential mapping provide different ways of dealing with analyzing and integrating incomplete data. This study examines the weights of evidence (WofE), evidential belief function and fuzzy logic methods of mineral potential mapping using incomplete data from the Carajás mineral province, Brazil to target for orogenic gold mineralization. Results demonstrate that WofE is the best one able to predict the location of known mineralization within the study area when either complete or unacknowledged incomplete data are used. It is suggested that this is due to the use of Bayes’ rule, which can account for “missing data.” The results indicate the effectiveness of WofE for mineral potential mapping with incomplete data.     

准噶尔盆地沙漠沙矿物组成的多源性

对准噶尔盆地87件沙漠沙矿物分析结果进行了研究。通过对比各样区沙丘沙和丘间地下伏沙重矿物组合特征、矿物成分离散度和轻矿物组合中石英/长石比值,查明沙漠沙物源多样性主要表现是:各小区沙物质矿物组合特征因地而异;沙丘沙虽主要由下伏沙经风力改造而成,但二者的上述各参数存在着一定差异,风力"搀杂"的结果使前者比后者具有更广泛的物源。     

秦岭—大别地区矿产资源区划与开发

分析秦岭—大别地区矿产资源与开发利用现状 ,划分该区矿产资源经济区和测算矿产资源开发利用价值 ,提出该区矿产资源开发利用的对策与建议。     

A Modified Weights-of-Evidence Method for Mineral Potential Prediction Based on Structural Equation Modeling

Structural equation modeling (SEM) was applied here to modify the ordinary weights-of-evidence (WofE) method for calculating posterior probability to improve conditional independence (CI) in the application of this method mineral potential prediction. The new method attempts to reduce the effect of CI by defining new binary patterns with an optimum combination of cutoff values of patterns. The solution is calculated through SEM, and the goodness of fit between evidence and mineral deposit occurrences is evaluated by a specified target function. The main difference between the new WofE and ordinary WofE is that evidence in the new method maintains a balance between the significance for mineral potential prediction and CI, rather than the significance for mineral prediction only as in ordinary WofE. A case study of prediction of potential for hydrothermal Au mineral deposits in Nova Scotia, Canada, is discussed here. The results indicate that the new method performs better than the ordinary WofE.

     

大柴旦盐湖固体钾盐分布特征及其转化利用的初步探讨

大柴旦盐湖固体钾盐矿物主要为软钾镁钒,其分布范围小,现有储量仅为1.04×106 t,不具备直接开采的条件。根据其特有的溶解性可通过固液转化的技术,在开采卤水钾的同时,将部分资源加以利用,是卤水钾矿的后备资源。     

Data-Driven Predictive Modeling of Mineral Prospectivity Using Random Forests: A Case Study in Catanduanes Island (Philippines)

The Random Forests (RF) algorithm is a machine learning method that has recently been demonstrated as a viable technique for data-driven predictive modeling of mineral prospectivity, and thus, it is instructive to further examine its usefulness in this particular field. A case study was carried out using data from Catanduanes Island (Philippines) to investigate further (a) if RF modeling can be used for data-driven modeling of mineral prospectivity in areas with few (i.e., <20) mineral occurrences and (b) if RF modeling can handle predictor variables with missing values. We found that RF modeling outperforms evidential belief (EB) modeling of prospectivity for hydrothermal Au–Cu deposits in Catanduanes Island, where 17 hydrothermal Au–Cu prospects are known to exist. Moreover, just like EB modeling, RF modeling allows analysis of the spatial relationships between known prospects and individual layers of predictor data. Furthermore, RF modeling can handle missing values in predictor data through an RF-based imputation technique whereas in EB modeling, missing values are simply represented by maximum uncertainty. Therefore, the RF algorithm is a potentially useful method for data-driven predictive modeling of mineral prospectivity in regions with few (i.e., <20) occurrences of mineral deposits of the type sought. However, further testing of the method in other regions with few mineral occurrences is warranted to fully determine its usefulness in data-driven predictive modeling of mineral prospectivity.     

Application of Mineral Exploration Models and GIS to Generate Mineral Potential Maps as Input for Optimum Land-Use Planning in the Philippines

The inherent problems of classifying or inventorying potential mineral resources (as opposed to known mineral resources) pose specific challenges. In this paper, the application of a conceptual mineral exploration model and GIS to generate mineral potential maps as input to land-use policy decision-making is illustrated. We implement the criteria provided by a conceptual exploration model for nickeliferous-laterites by using a GIS to classify the nickeliferous-laterite potential of an area in the northeastern part of the Philippines. The spatial data inputs to the GIS are geological map data, topographic map data, and stream sediment point data. Processing of these data yields derivative maps, which are used as indicators of nickeliferous-laterite potential. The indicator maps then are integrated to furnish a nickeliferous-laterite potential map. This map is compared with present land-use classification and policy in the area. The results indicate high potential for nickeliferous-laterite occurrence in the area, but the zones of potential are in places where mineral resources development is prohibited. The prohibition was imposed before the nickeliferous-laterite potential was assessed by this study. Mineral potential classification therefore is a critical input to land-use policy-making so that prospective land is not alienated from future mineral resource development.     

西藏盐湖矿产资源遥感定量预测方法研究

西藏自治区地域广大,湖泊众多,盐湖矿产资源十分丰富,但调查研究程度较低,资源潜力不明,家底不清。以遥感信息为基础,采用多因素综合评判模型法进行盐湖矿产定量预测,初步摸清现阶段西藏盐湖矿产资源家底,为地方政府和有关部门进行盐湖矿产资源勘查开发提供了重要参考依据。该预测方法具有较强探索性,和已知查明资源量进行比较,预测结果基本可靠,是西部高海拔地区盐湖矿产资源快速评价的有效方法。     

Multiple Regression-Based Calculation of Iron Ore Resource Royalty Rate and Analytical Study of Its Influencing Factors: Example from Anhui Province of China

Mineral resource royalty is the economic manifestation of mineral resource ownership benefits. In the context of globalized mineral resource allocation, it is inevitable to research the royalty evaluation in order to improve the marketized allocation efficiency of mineral resources. Current studies mostly include theoretical discussions on connotations of royalty and discussions on royalty levy criteria from the macroeconomic perspective. Studies of royalty calculation and application from the microeconomic perspective are not very common. Based on defining the connotations of equity value, a theoretical royalty calculation formula is suggested first in this paper and then a royalty evaluation model is constructed from the perspective of mineral resource endowment conditions with the methods of multiple regression-based analysis and dummy variables. The feasibility and scientific justification of the evaluation model were verified through empirical analysis of iron mines in Anhui Province of China. Compared to previous studies, this paper better interprets the linear relationship between mineral resource endowment conditions and royalty through simulation analysis of their corresponding relation, making up for the inadequacy of macroeconomic royalty studies. Empirical results indicate the following. (1) Endowment conditions of mineral resources are the key influencing factors of royalty rate, and five of these factors (average geological grade, average mining depth, average ore body thickness, hydrogeological condition and beneficial and harmful elements) are important indices in royalty evaluation. (2) Royalty increases with the price rise in the market of mineral products, but the royalty rate will infinitely approach a constant (60.1%). Based on endowment conditions of mineral resources, the royalty evaluation model constructed in this paper can accurately and objectively evaluate mineral resource royalty in different endowment conditions and provide a convenient and practical evaluation method for establishing royalty levy criteria.     

Economic Filters Applied to Quantitative Mineral Resource Simulations

The U.S. Geological Survey has developed a technique that allows mineral resource experts to apply economic filters to estimates of undiscovered mineral resources. This technique builds on previous work that developed quantitative methods for mineral resource assessments. A Monte-Carlo calculation uses mineral deposit models to estimate commodity grades and tonnages of undiscovered deposits. The results then are analyzed using simple estimates of capital expenditures and daily operating costs for a mine and associated mill. The daily operating costs and the value of the ore are used to calculate the net present value of the deposit, which is compared to the capital expenditures to determine whether the deposit is economic. Repetition of these calculations for many deposits produces a table that can be interpreted in terms of the probability of there being deposits that have anet present value exceeding some specified amount. Sample calculations indicate that applying economic filters to simulated mineral resources might change the perception of the results compared to presenting the calculations in terms of the expected mean gross-in-place value of the minerals.     

青藏高原矿产资源的分布、形成及开发

通过分析青藏高原矿产资源的分布及储量,探讨青藏高原的成矿作用,指出青藏高原矿产资源极为丰富,能够作为我国"东部经济带"的战略资源接替基地,这对于保证我国矿产资源的可持续供应具有举足轻重的地位.但青藏高原生态环境脆弱、开发成本高、难度大,应坚持科学发展观,加速青藏高原优势矿产资源的勘查和开发,处理好资源开发与环境保护的关系.     

秦岭-大别地区矿产开发与利用对策

文章对秦岭－大别地区矿产资源开发的区域经济环境进行了分析，在矿产资源开发利用现状分析的基础上，对矿产资源的潜在价值、提取价值 以及经济效益进行了测算，提出了该区矿产资源开发利用的5条措施：即强化矿产勘查工作，保证矿业可持续发展；建设综合性矿物原料基础和加工产业基础；综合开发、综合回收利用；矿产资源开发实行统筹管理、保护性开采利用；重视生态环境的影响和保护，走可持续发展之路。     

Mineralogical Study of Beneficiated and Carbonized Indian Coking Coal for Better Utilization: A Case Study

Coking/metallurgical coal is one of the essential raw materials for steel industries. The metallurgical coal in India contains high ash content (mineral matters), is rich in inertinite, and requires optimization before its proper utilization. Distribution of mineral matter in coking coal plays a significant role in achieving the desired product for blast furnace and coke-making operations. The present paper reports a case study on the distribution and nature of mineral matter in Indian coking coals at varying densities with respect to the coal’s beneficiation behavior. The maceral analysis indicated the maximum liberation of reactives at the relative density (RD) of 1.2–1.3 g/cm³ while maximum inerts concentrated at the highest density (RD?>?1.8 g/cm³). The most dominating mineral matter found in the coal is argillaceous minerals containing substantial amounts of quartz followed by carbonate and sulfides existing as cavity fillings or in disseminated form. X-ray diffraction (XRD), X-ray fluorescence (XRF), and electron-probe microanalysis (EPMA) techniques were used to study the mineral distribution and transformation behavior of coke produced from the coking coal during carbonization process. A case study on the reactivity of dispersed mineral matter in coke and the implication of mineral transformation behavior on coke is also discussed in this paper.

     

China’s Belt and Road Initiative in Support of the Resourcing Future Generations Program

The Resourcing Future Generations (RFG) program is a global strategy proposed by the International Union of Geological Sciences to meet global demand for natural resources. The Belt and Road (B&R) initiative of China provides a great opportunity for promoting the RFG across much of the Eurasian continent. The countries covered by the B&R initiative are mostly low-income economies. With rapid developments of economy and infrastructure construction, these countries are set to have huge demands for mineral resources in the future. However, the proven mineral reserves in this region are too limited, and the region’s overall level of metal recycling is far from optimistic. These countries are expected to have obstacles in meeting future demands. However, the regional Tethyan metallogenic domain and Central Asia metallogenic district are key areas for new discoveries of mineral resources, possessing a variety of mineral resources with a positive prospecting potential. The B&R initiative of China provides favorable opportunity for mutual beneficial cooperation to improve regional exploration and prospecting through geological mapping, inter-comparison study on Tethyan metallogenic domain, joint assessment of mineral resource potentials, joint training of geological engineers and workers and building information systems.