广西荣华锰矿床地质特征及发现意义

广西荣华锰矿位于三叠系百逢组,在该地层中发现的工业锰矿床尚未见报道。通过对该矿区大比例尺地质填图,并结合地质工程和测试分析等手段,对矿床地质背景、沉积环境、矿体和矿石特征、沉积演化等进行分析研究,推测荣华锰矿为沉积-淋滤锰帽型矿床,矿体顺层分布于靠近罗楼组碳酸盐岩的百逢组第一段泥岩、泥质粉砂岩中,严格受地层和构造控制。矿石主要由偏锰酸矿、软锰矿等组成,矿石品位偏低,伴生Co等金属元素。百逢组之下的碳酸盐岩和百逢组第一段浊积砾岩层可作为该类锰矿上下界线典型的找矿标志。中三叠世桂西北处于盆包台构造格局,中晚古生代富含锰的台地在三叠纪遭受风化剥蚀,成矿元素被带入弧后盆地。随着特提斯洋闭合,挤压作用使盆地面积变小,水位加深,氧化还原界面波动,在百逢组第一段锰元素初步富集。后右江盆地抬升露出水面遭受剥蚀,风化淋滤作用最终形成该区顺层分布的氧化锰矿床。桂西广泛出露百逢组地层,其第一段具有良好的找矿前景。     

热释卤素法在安徽胡村铜钼矿深部的找矿试验

热释卤素找矿方法是一种深穿透地球化学找矿方法,但一直未推广应用。笔者选择了湿润中低山丘陵冲洪积物覆盖地球化学景观区的狮子山矿田胡村深部铜钼矿,开展了热释卤素找矿方法可行性研究。将土壤热释卤素及常规土壤测量结果对比发现:土壤热释卤素( F、Cl)异常能够有效指示深部矿体,且能有效排除岩体等因素的干扰;常规土壤卤素异常对深部矿体指示意义有限,但不具普遍性;常规土壤测量元素异常受岩体、接触带及浅表矿化影响较大,对深部矿体指示意义具有局限性,其中Ba负异常对热液蚀变带具有一定指示意义。土壤热释卤素异常位置与深部矿体赋存空间有良好的对应,含量变化趋势基本一致,异常表现为多峰形式,而且异常一般形成于矿体垂直投影正上方,这与前人研究结论相似。初步认为,在长江中下游冲洪积物覆盖区深部矿体定位阶段,可以试用土壤热释卤素找矿方法。     

江西瑞昌市仙姑台铜多金属矿综合勘查模型

江西仙姑台铜多金属矿位于九瑞矿集区,是近年整装勘查区中发现的斑岩—矽卡岩—热液充填型铜多金属矿床. 本文在系统分析其成矿地质背景、控矿条件、找矿标志、土壤地球化学及地球物理等特征的基础上,归纳并提取了矿床的找矿信息. 根据前二者基本可以圈定找矿区段,再结合1:1万土壤异常、1:1万高精度磁测上延50 m磁异常、激电探测视极化率与视电阻率异常,以及EH-4连续电导率剖面测量异常等多元信息,便能较为有效地确定隐伏矿体的大致分布位置. 依此建立了仙姑台铜多金属矿床的综合勘查模型,对该区寻找此类矿床有着十分重要的意义.     

Geochemistry of ore-forming fluids and geological significance of the Kuoerzhenkuola gold field in Xinjiang, China

The Kuoerzhenkuola gold field (including the Kuo- erzhenkuola and the Buerkesidai gold deposits), lo- cated 68 km east of Jimunai County in northern Xing- jiang, China, is an important component of the Sawuer gold belt which is the eastward extending part of the Zarma-Sawur gold-copper belt in Kazakhstan. Some studies are concerned with the geology of the gold ores[1―3], the associated volcanic rocks[4], radiogenic isotope[5―8], and the ore-forming environment[8]. Most researchers inferr…     

Application of <Superscript>137</Superscript>Cs fingerprinting technique to interpreting sediment production records from reservoir deposits in a small catchment of the Hilly Loess Plateau,China

According to variations of 137Cs and clay contents, 44 flood couplets were identified in a profile of reservoir deposit with a vertical length of 28.12 m in the Yuntaishan Gully. Couplet 27 at the middle of the profile had the highest average 137Cs content of 12.65 Bq kg-1, which indicated the 1963s' deposits, then 137Cs content decreased both downward and upward in the profile. The second top and bottom couplets had average 137Cs contents of 2.15 Bq kg-1 and 0.92 Bq kg-1, respectively. By integrated analysis of reservoir construction and management history, variations of 137Cs contents over the profile, sediment yields of flood couplets and rainfall data during the period of 1958-1970, individual storms related to the flood couplets were identified. 44 floods with a total sediment yield of 2.36×104 m3 occurred and flood events in a year varied between 1 and 10 times during the period of 1960-1970. 7-10 flood events occurred during the wet period of 1961-1964 with very wet autumn, while only 1-2 events during the dry period of 1965-1969. Average annual specific sediment yield was 1.29×104 t km-2 a-1 for the Yuntaishan Gully during the period of 1960-1970, which was slightly higher than 1.11 ×104 t km-2 a-1 for the Upper Yanhe River Basin above the Ganguyi Hydrological Station and slightly lower than 1.40 ×104 t km-2 a-1 for the nearby Zhifang Gully during the same period. Annual specific sediment yields for the Yuntaishan Gully were correlated to the wet season's rainfalls well.     

兰坪—思茅盆地钾盐矿床的物质来源探讨

云南兰坪—思茅盆地是我国重要的成钾盆地。综合前人的研究成果,简要介绍了该地区的地质概况。对兰坪—思茅盆地钾盐矿床的物质来源进行了阐述和讨论,认为该盆地钾盐矿床的物质来源以残存古海水为主,并有陆源水体的补给。盆地内的富钾火山凝灰岩、古盐和风化盐也可能为该盆地钾盐矿床提供物源,至于深部地下卤水是否提供物源还需更深入的研究论证。兰坪—思茅盆地钾盐矿床成矿物源具有多源性。     

Application of GIS Processing Techniques for Producing Mineral Prospectivity Maps—A Case Study: Mesothermal Au in the Swayze Greenstone Belt,Ontario, Canada

A Geographic Information System (GIS) is used to prepare and process digital geoscience data in a variety of ways for producing gold prospectivity maps of the Swayze greenstone belt, Ontario, Canada. Data used to produce these maps include geologic, geochemical, geophysical, and remotely sensed (Landsat). A number of modeling methods are used and are grouped into data-driven (weights of evidence, logistic regression) and knowledge-driven (index and Boolean overlay) methods. The weights of evidence (WofE) technique compares the spatial association of known gold prospects with various indicators (evidence maps) of gold mineralization, to derive a set of weights used to produce the final gold prospectivity map. Logistic regression derives statistical information from evidence maps over each known gold prospect and the coefficients derived from regression analysis are used to weight each evidence map. The gold prospectivity map produced from the index overlay process uses a weighting scheme that is derived from input by the geologist, whereas the Boolean method uses equally weighted binary evidence maps.The resultant gold prospectivity maps are somewhat different in this study as the data comprising the evidence maps were processed purposely differently for each modeling method. Several areas of high gold potential, some of which are coincident with known gold prospects, are evident on the gold prospectivity maps produced using all modeling methods. The majority of these occur in mafic rocks within high strain zones, which is typical of many Archean greenstone belts.     

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.     

华南沿海老红砂的成因与红化作用

根据野外调查和室内实验分析，以及测年数据，本文讨论了华南沿海老红砂的成因、年龄与形成环境。认为老红砂是晚更新世末次冰期海岸风沙堆积，红色特征与亚间冰期的温暖古气候有关。在湿热气候下，古风成砂中含铁硅酸盐矿物氧化生成赤铁矿，而使无色石英沙粒染成红色，是其红化的主要机制。风成砂形成红色的时间不超过１万年。     

Spatial Analysis Techniques as Successful Mineral-Potential Mapping Tools for Orogenic Gold Deposits in the Northern Fennoscandian Shield,Finland

Geoscientific Information Systems (GIS) provide tools to quantitatively analyze and integrate spatially referenced information from geological, geophysical, and geochemical surveys for decision-making processes. Excellent coverage of well-documented, precise and good quality data enables testing of variable exploration models in an efficient and cost effective way with GIS tools. Digital geoscientific data from the Geological Survey of Finland (GTK) are being used widely as spatial evidence in exploration targeting, that is ranking areas based on their exploration importance. In the last few years, spatial analysis techniques including weights-of-evidence, logistic regression, and fuzzy logic, have been increasingly used in GTK’s mineral exploration and geological mapping projects. Special emphasis has been put into the exploration for gold because of the excellent data coverage within the prospective volcanic belts and because of the increased activity in gold exploration in Finland during recent years. In this paper, we describe some successful case histories of using the weights-of-evidence method for the Au-potential mapping. These projects have shown that, by using spatial modeling techniques, exploration targets can be generated by quantitatively analyzing extensive amounts of data from various sources and to rank these target areas based on their exploration potential.