辽南庄河地区栗子房变质核杂岩的发现及意义

在区域地质调查资料基础上,根据宏观与微观构造测量,通过分析区域岩浆活动性及其测年资料等,揭示了在辽南庄河栗子房地区存在另一个变质核杂岩构造,即栗子房变质核杂岩。该核杂岩具有3层结构和5个部分,即由新太古代变质深成岩及中生代花岗岩侵入体构成的下盘、由不同层次的构造岩组成的中部拆离断层带以及由前寒武纪沉积盖层和白垩纪伸展盆地构成的上盘。栗子房变质核杂岩形成于早白垩世,运动方向为上盘相对下盘由NWW向SEE方向运动,与辽南金州变质核杂岩和万福变质核杂岩在几何学、运动学极性和形成时间等方面具有很多相似性,形成于同一动力学背景。该变质核杂岩的厘定可为阐明华北克拉通东部晚中生代岩石圈减薄过程及岩石圈的力学和流变学属性提供依据。同时,变质核杂岩与金矿床成矿关系密切,栗子房变质核杂岩的拆离断层带附近可作为下一步金矿勘查的重点工作区,成矿潜力较大。     

溶剂萃取原子吸收光谱法测定高纯石英砂中痕量铁

高纯石英砂用HF等溶剂溶解并蒸干后,在微酸性介质中用抗坏血酸还原Fe^3＋为Fe^2＋,与1,10-二氮杂菲形成Fe2＋3络合物,加入适量ClO4^-阴离子与之形成离子缔合物,用硝基苯萃取,原子吸收测定有机相,本法检出限1.1μg/g,样品分析结果的RSD%为：4.52～10.3.     

祖母绿产地鉴别研究综述

祖母绿是一种名贵彩色宝石,其产地来源对祖母绿价值的评定具有重要影响。祖母绿的产地鉴别因而成为宝石实验室的重要技术,也是宝石学领域的研究热点。祖母绿的包裹体、谱学特征和化学成分是常用且关键的产地鉴别信息,但随着祖母绿产地研究数据的积累,传统的产地鉴别方法备受挑战。文章系统整理和归纳分析了全球各产地祖母绿的宝石学特征、包裹体信息、谱学特征和主微量成分数据,在综述前人研究结果的基础上,系统阐明了目前祖母绿产地鉴别的研究现状,总结了不同产地祖母绿的宝石学特征和包裹体特征,划分了紫外-可见光-近红外(UV-VIS-NIR)光谱类型,揭示了各产地祖母绿的成分指纹信息,并以案例的形式阐明区分祖母绿常见重要产地的方法。全球尺度的对比虽然表明不同产地祖母绿包裹体种类多数雷同、光谱趋同、成分含量范围重叠明显,但也从包裹体出现频率、UV-VIS-NIR光谱样式类型、重水吸收样式和成分投图参数的选择上提供了产地鉴别的新思路。综上所述,文章旨在促进祖母绿鉴别技术的发展,为祖母绿的产地溯源提供科学依据。     

苏北盆地高邮凹陷古近系戴南组滨浅湖沉积中的遗迹化石

苏北盆地高邮凹陷古近系戴南组滨浅湖沉积中动物遗迹化石共鉴定出6个遗迹属8个遗迹种,其中1个为未定种。包括Taenidium barretti、Taenidium satanassi、Beaconites coronus、Cystichnum curvativum、Palaeophycus isp.、Planolites montanus、Skolithos verticalis和Skolithos linearis等。这些遗迹化石主要是无脊椎动物的进食迹和居住迹,呈全浮痕或半浮痕保存。根据组合特征及沉积环境分析,可识别出两个遗迹化石组合:1）Taenidium—Beaconites遗迹组合,主要由具新月型回填纹构造的进食迹组成,反映了周期性干旱气候条件下的滨浅湖沉积环境;2）Skolithos linearis遗迹组合,主要由居住潜穴组成,代表了三角洲平原—前缘沉积环境。生物扰动根据扰动特点,可分为三种类型,即1）均一型,反映了湖平面缓慢上升之后较长时间保持稳定;2）增强型,反映了湖平面整体稳定条件下的小幅度快速上升,然后保持稳定和缓慢下降;3）复合型,反映了湖平面先缓慢上升,然后缓慢下降。三角洲平原-前缘分支河道沉积序列中遗迹化石的类型、丰度、分异度和扰动指数垂向上呈规律性的变化,结合其沉积学特征分析,可分为四个沉积单元,每个沉积单元的内部物理成因构造和生物成因构造明显不同。     

湖北宜昌震旦系陡山沱组储层特征及复杂体积压裂效果评价

鄂阳页2 HF井是国内首口针对震旦系陡山沱组的页岩气水平井,该井钻遇的陡山沱组页岩厚度大,岩石脆性好,含气性好且天然裂缝发育,具备良好的压裂改造基础.针对陡山沱组储层"高云质、地层常压、水平应力差异大、隔夹层发育"等压裂改造难点,通过采用"密分切割、多簇射孔、转向压裂"等复杂裂缝体积压裂工艺,采取变排量、暂堵转向、停泵...     

玲珑金矿黄铁矿热电性与微量元素标型及深部金矿化评价

在前人对玲珑金矿矿体浅部的研究基础之上,通过对矿体深部黄铁矿的热电性测试与分析,得出：西山矿区380m—90m中段,黄铁矿导型以P—N型（空穴型-电子型导电）为主;东山矿区50m—850m标高范围内,黄铁矿导型以P—N或N—P（电子型-空穴型导电）混合型为主。东、西山矿区的P型出现率在垂向上呈高-低-高的韵律式脉冲变化...     

Using multivariate statistical analysis of groundwater major cation and trace element concentrations to evaluate groundwater flow in a regional aquifer

Groundwater samples were collected from 11 springs in Ash Meadows National Wildlife Refuge in southern Nevada and seven springs from Death Valley National Park in eastern California. Concentrations of the major cations (Ca, Mg, Na and K) and 45 trace elements were determined in these groundwater samples. The resultant data were subjected to evaluation via the multivariate statistical technique principal components analysis (PCA), to investigate the chemical relationships between the Ash Meadows and Death Valley spring waters, to evaluate whether the results of the PCA support those of previous hydrogeological and isotopic studies and to determine if PCA can be used to help delineate potential groundwater flow patterns based on the chemical compositions of groundwaters. The results of the PCA indicated that groundwaters from the regional Paleozoic carbonate aquifers (all of the Ash Meadows springs and four springs from the Furnace Creek region of Death Valley) exhibited strong statistical associations, whereas other Death Valley groundwaters were chemically different. The results of the PCA support earlier studies, where potentiometric head levels, δ¹⁸O and δD, geological relationships and rare earth element data were used to evaluate groundwater flow, which suggest groundwater flows from Ash Meadows to the Furnace Creek springs in Death Valley. The PCA suggests that Furnace Creek groundwaters are moderately concentrated Ash Meadows groundwater, reflecting longer aquifer residence times for the Furnace Creek groundwaters. Moreover, PCA indicates that groundwater may flow from springs in the region surrounding Scotty's Castle in Death Valley National Park, to a spring discharging on the valley floor. The study indicates that PCA may provide rapid and relatively cost‐effective methods to assess possible groundwater flow regimes in systems that have not been previously investigated. Copyright © 1999 John Wiley & Sons, Ltd.     

Statistical techniques for the classification of chromites in diamond exploration samples

A database of 1267 quality-screened major- and trace-element analyses of chromites (s.l.) from kimberlites, lamproites, ultramafic lamprophyres (UMLs) and crustal sources (‘greenstones’, including ophiolites, gabbros, basalts and komatiites) has been subjected to statistical analysis, in order to derive discriminants for use in diamond exploration. The techniques used included nearest-neighbour analysis, CART (classification and regression trees) and MARS (multivariate adaptive regression splines). The results show that both CART and MARS approaches can correctly discriminate kimberlite/lamproite chromites from UML/‘greenstone’ chromites at levels near 90%. Discrimination into the four classes separately is achieved at levels of ca. 80% by MARS and > 70% by CART; much of the misclassification is between the kimberlite and lamproite classes. These results probably represent the maximum probable level of discrimination on chemical criteria, given that ascending magmas may sample both mantle and crustal rocks. The CART approach produces a classification tree that requires no further computation to classify a given grain; the MARS approach requires the use of a simple software package. Tests on known samples illustrate the high level of accuracy of the methods in an exploration context, as well as the useful petrogenetic conclusions that can be drawn from some ‘misclassifications’.     

A semi‐distributed parallel‐type linear reservoir rainfall‐runoff model and its application in Taiwan

The main purpose of this paper is to introduce a semi‐distributed parallel surface rainfall‐runoff conceptual model. In this paper, a general solution of the instantaneous unit hydrograph (IUH) has been derived successfully for N linearly connected reservoirs, each having a different storage constant. The solution is a function of geomorphologic parameters, meteorologic factors and roughness coefficients. The model also takes into account the hydrologic response which is influenced by outflow downstream of a reservoir. For calibration, the shuffled complex evolution (SCE) algorithm is used to search for the global optimal parameters of the model. Because of the parallel structure, the mean roughness parameter of the channel becomes a “conceptual” parameter without a real physical meaning. To evaluate the adaptability of the model adopted, three watersheds around the city of Taipei in Taiwan were chosen to test the effectiveness of the model. The study provides an appropriate rainfall‐runoff model for planning flood mitigation in Taiwan. Copyright © 1999 John Wiley & Sons, Ltd.