我国藻菌生物成因的金矿研究

生物成矿作用分为生物直接成矿作用和生物间接成矿作用,生物直接成矿作用的标志结构为生物有机胶体结构。生物间接成矿作用的标志结构为“矿交代生物”结构,我国陕西二台子－半仓沟金矿,四川东北寨金矿、川甘拉尔玛金矿和云南金厂金矿等均为典型为实例,矿石中普遍含有多种金属矿物生物结构,还含多种生物有机组分。成矿物质具有多源性特征,硫同位素具混合型特征,矿床成型机制可与“人工碳吸附系统”聚金机制相类比,含金层位可     

环境矿物材料治理镉（Cd^2＋）污染研究进展

近年来,环境矿物材料以其经济、有效、无二次污染等特点,在重金属废水处理和土壤修复方面显示出了众多优势,可替代传统的镉污染处理方法。本文综述了国内外环境矿物材料在处理镉污染方面的研究进展,并对今后应用环境矿物材料治理镉污染提出了一些建议。     

得尔布干成矿带中段八大关——新峰山成矿地质条件分析

得尔布干成矿带中段八大关—新峰山地区断裂构造发育 ,北东向得尔布干深大断裂是重要的控岩控矿构造。与成矿有关岩浆岩主要为燕山期的中性—中酸性侵入岩及次火山岩。赋矿层位主要有上库力组、塔木兰沟组及谢尔塔拉组。在分析典型矿床的成矿地质特征基础上 ,进一步指出找矿方向     

华北板内深部构造

华北板块的形成经历了早前寒武纪、燕山期及喜马拉雅期3个主要构造发展期，由于华北板块自身运动及所受应力场的作用，加之上地幔岩石圈的不均一性等因素，在中、新生代形成许多特殊的板内构造块。综合应用地质、地球物理和地球化学的成果，对华北板内深部结构进行了研究。从深部构造角度划分出6个金及金金属成矿带、4个金刚石成矿带，并对华北地区的地震及地热资源与新生事大陆裂谷的关系进行了探讨。     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

大洋多金属结核研究概况

从多金属结核的分布及富集规律、物质成分、内部结构、形成机制等方面论述了目前国内外的一些研究动态,对目前在这一研究领域提出的一些新概念、新方法作了一定的介绍.在分析和总结前人研究成果的基础上,指出了在这一研究领域还存在的一些问题及今后研究的方向.     

应用航放资料寻找非放射性金属矿产效果探讨

本通过对粤北地区已知的52个非放射性金属矿床（点）的地质、物化探特征的统计资料综合分析，建立了评价非放射性金属矿产成矿远景的航空能谱参数模型，结合重磁测量、重砂测量及金属量测量成果，预测了4片非放射性金属矿产成矿远景区。     

深圳市东湖矿泉水形成机理探讨

深圳市东湖矿泉水是自然界十分稀少的锶—锌—偏硅酸碳酸复合型矿泉水，通过对矿泉水赋存地的地质与水文地质条件的分析，并结合其水文地球化学特征，认为东湖矿泉水形成的主要控制性因素是构造作用和变质作用；在特定的水文地质条件下，深部碳酸盐类岩石受热硅化变质而产生大量CO2气体，使得各种化学元素在含有大量CO2的地下水的溶滤作用下不断迁移和富集而形成该区地下水中良好的元素组合。在其特征成分中，偏硅酸来自裂隙渗透水的溶滤和岩浆期后热液水的作用，微量元素锶主要来源于钾长石、钙长石，锌则主要来自岩浆活动以及岩脉中的黑云母、角闪石、辉石等铁镁硅酸盐矿物；并认为目前矿泉水含水层仍处于良好的地质环境保护下。     

Theory and Method of Mineral Resource Prediction Based on Synthetic Information

Metallogenic prognosis of synthetic information uses the geological body and the miaeral resource body as a statistical unit to interpret synthetically the information of geology, geophysics, geo-chemistry and remote sensing from the evolution of geology and puts all the information into one entire system by drawing up digitalized interpretation maps of the synthetic information. On such basis, differ-ent grades and types of mineral resource prospecting models and predictive models of synthetic informa-tion can be established. Hence, a new integrated prediction system will be formed of metallogenic prog-nosis (qualitative prediction), mineral resources statistic prediction (determining targets) and mlaeral resources prediction (determining resources amount).