3500m岩心钻探装备在油气井勘查中的示范应用

3500 m岩心钻探装备（YDX—6型钻机）是我国自主研发的深部矿产资源勘查技术装备,采用N级口径钻深可达3500 m,其最大特点是采用长油缸钻进和起下钻。本文主要介绍了该钻机在油气井勘查中生产试验情况,同时对矿区地层、钻孔结构、钻进过程、钻进效果、遇到的主要问题及解决办法等进行了介绍。     

柴达木盆地西北缘石英闪长岩的形成时代、岩石成因及地质意义

柴达木盆地西北缘石英闪长岩Al2O3含量较高,全碱(Alk)含量较低,Na2OK2O,铝饱和指数A/CNK为0.87~0.91,属钙碱性准铝质岩石系列。球粒陨石标准化的稀土元素配分曲线表现为轻稀土元素富集型,轻、重稀土元素分馏明显,Eu弱负异常;微量元素地球化学特征显示,岩石富集Rb、Th、U等大离子亲石元素,亏损Nb、Ta、P、Ti等高场强元素,Nb/La和Rb/Nb比值较低,具有I型花岗岩的特征。石英闪长岩Ca O/Na2O比值较高(2.32~2.64),结合源岩判别图解综合推断其源于变玄武岩的部分熔融。全岩Zr饱和温度计算结果显示初始岩浆温度768℃;岩石地球化学特征表明岩浆源区压力1.5 Ga,源岩部分熔融的残留相可能为石榴子石+角闪石+金红石。经过锆石阴极发光分析和MC-LA-ICP-MS锆石U-Pb测年,获得206Pb/238Pb加权平均年龄为252±1 Ma,代表了柴达木盆地西北缘石英闪长岩的成岩年龄。结合区域地质演化特征,认为该岩体形成于与板块俯冲有关的火山弧构造环境,是晚二叠世末期宗务隆洋壳向柴北缘欧龙布鲁克地块俯冲,变玄武岩在相对较高的温压条件下发生部分熔融形成的。     

贵州松桃高地特大型富锰矿床主要地质特征

位于贵州铜仁松桃国家锰矿整装勘查区内的高地富锰矿床,(332)+(333)类碳酸锰富锰矿石资源量达7 166. 84万吨,锰平均品位25. 75%,矿体平均厚度4. 52 m,富锰矿体赋存于总资源量达1. 61亿吨的高地超大型锰矿床之中,由一个单一的富锰矿体构成,是我国新发现的首个特大型富锰矿床,富锰矿资源量相当于我国富锰矿资源量总和的2倍。成因类型属古天然气渗漏沉积型锰矿床,富锰矿产于古天然气渗漏沉积成矿系统中心相区。高地富锰矿床地处独特的"新月形"南华纪早期李家湾-高地-道坨(Ⅳ级)地堑盆地中心,菱锰矿体中均出现以块状构造夹被沥青充填的气泡状富菱锰矿石。地表燕山期北北东向的断裂构造十分发育,但主要为上陡下缓犁式正断层,未触及高地深部隐伏巨型锰矿体,以致富锰矿体保存亦十分完整,易于开发利用。     

Using landscape indicators and Analytic Hierarchy Process (AHP) to determine the optimum spatial scale of urban land use patterns in Wuhan,China

Quantifying land use patterns and functions is critical for modeling urban ecological processes, and an emerging challenge is to apply models at multiple spatial scales. Methods of determining the optimum scale of land use patterns are commonly considered using landscape metrics. Landscape metrics are quantitative indicators for analyzing landscape heterogeneity at the landscape level. In this study, due to their widespread use in urban landscape analyses and well-documented effectiveness in quantifying landscape patterns, landscape metrics that represent dominance, shape, fragmentation and connectivity were selected. Five metrics include Patch Density, Contagion, Landscape Shape Index, Aggregation Index and Connectivity. Despite a wide application of landscape metrics for land use studies, the majority mainly focuses on the qualitative analysis of the characteristics of landscape metrics. The previous models are limited in exploring the optimum scale of land use patterns for their lack of quantitation. Therefore, taking the City of Wuhan as an example, the land use unit was treated as a patch, and the landscape pattern metrics at different spatial scales were calculated and compared so as to find the optimum one. Furthermore, a mathematical model of landscape metrics was proposed to quantify the scale effect of urban land use patterns, generating a complementary tool to select the optimum scale. In addition, Analytic Hierarchy Process (AHP) was introduced to determine the respective weights of the chosen landscape metrics in this model. Fractal dimension was ultimately applied to verify the chosen optimum scale of our study region. The results indicated that 60 m is confirmed to be the optimum scale for capturing the spatial variability of land use patterns in this study area.     

Effects of vegetation restoration on soil physical properties of abandoned farmland on the Loess Plateau,China

To improve the ecological environment in China, the Chinese government implemented a country-wide ecological protection and reforestation project (namely the “Grain for Green Project”) in 1999 to return cultivated land with slopes of 25° or more to perennial vegetation. Vegetation restoration reduces soil erosion mainly by changing the soil physical properties. Different vegetation restoration methods might produce different impacts on soil physical properties. In this study, two vegetation restoration methods (i.e., natural restoration and artificial restoration) were compared on abandoned farmland in the typically hilly and gullied areas of the Loess Plateau of Northwest China. In the natural restoration method, the farmland was abandoned to natural vegetation succession without irrigation, fertilization or other artificial disturbances. In the artificial restoration method, the farmland was planted with black locust (Robinia pseudoacacia L.) and watered and cultivated for the first two years. Three soil physical properties (i.e., soil moisture, bulk density and aggregation) were investigated under the two vegetation restoration methods. The results showed that the soil moisture and soil bulk density were higher under artificial restoration than under natural restoration within the first three years of vegetation restoration. By the fourth year, the soil moisture and soil bulk density were higher under natural restoration than under artificial restoration. For the stability of soil aggregates?>?0.25 mm, the soil aggregates in the 0-20 cm soil layer were more stable under artificial restoration than under natural restoration, while the results were the opposite for the 40-60 cm soil layer. Overall, the soil physical properties were continuously improved during the restoration of vegetation on abandoned farmland. In choosing between vegetation restoration methods, natural restoration is preferable to artificial restoration, but artificial intervention is needed during the first three years.     

西藏雅鲁藏布江缝合带中段日喀则地幔橄榄岩中发现金刚石等异常矿物

本文报道了雅鲁藏布江缝合带中段日喀则蛇绿岩地幔橄榄岩中发现与该带东西段蛇绿岩岩体中相似的金刚石和特殊地幔矿物群。日喀则地幔橄榄岩体以方辉橄榄岩为主,含少量二辉橄榄岩和纯橄岩,辉石岩和辉长岩呈脉状产在方辉橄榄岩中。通过重砂分选实验,在465kg的方辉橄榄岩大样中发现了30余种特殊矿物群,包括金刚石、自然金、自然铬、自然铜等自然元素矿物类;碳硅石等碳化物类;方铁矿、赤铁矿、磁铁矿、刚玉、铬尖晶石、金红石、锡石、黑钨矿等氧化物类;镍黄铁矿、方铅矿、辉钼矿、辉锑矿、闪锌矿、毒砂等硫化物类;Ag-Au等合金矿物类;橄榄石、辉石、锆石等硅酸盐岩类;白钨矿等钨酸盐岩类;萤石等氟化物类。金刚石和自然金、自然铬、自然铜连同碳硅石的发现表明岩体存在强还原环境,这套特殊矿物组合指示日喀则地幔橄榄岩可能与雅鲁藏布缝合带其他蛇绿岩一样,经历了深地幔演化过程。     

不同颜色青海软玉微观形貌和矿物组成特征

青海软玉颜色丰富,近年来对青海软玉矿物学的研究不少,但针对不同颜色青海软玉矿物学特征的研究还存在欠缺。本文利用偏光显微镜、扫描电子显微镜、电子探针及粉晶X射线衍射仪器,从透闪石微形貌特征、微观结构、矿物组成及结晶度四个方面,研究了青海软玉颜色与矿物学特征的对应关系。结果表明:白玉、烟青玉、糖玉中透闪石主要为纤维状,显微纤维变晶结构,结晶度为96. 12%～96. 88%;青白玉和翠青玉中透闪石主要为叶片状,显微叶片变晶结构,结晶度为97. 35%,97. 32%;青玉和碧玉中透闪石主要为叶片状,显微叶片-隐晶质变晶结构,结晶度为95. 48%,95. 29%;黄玉中透闪石主要为柱状,显微柱状变晶结构,结晶度为97. 84%。青海软玉主要组成矿物均为透闪石,含量在95%以上,部分次要矿物如翠青玉中的榍石、黄玉中的钙长石、青玉中的菱镁矿、碧玉中的铬铁矿、糖玉中的斜黝帘石只出现在特定颜色的青海软玉样品中。研究认为不同颜色青海软玉矿物学特征确实存在差异,这些特征为研究不同颜色青海软玉成矿环境及成矿条件提供了科学依据。     

大数据环境下内蒙古浩布高地区铅锌多金属矿智能矿产预测研究

传统机器学习算法已广泛应用于矿产预测,但面对地质大数据的高维稀疏、不平衡小样本等特性仍缺乏有效处理和分析的方法,设计适合地质大数据特点的机器学习算法是智能矿产预测亟需解决的新问题。本文以内蒙古浩布高地区的铅锌多金属矿产预测为例,提出了一种面向地质大数据的半监督协同训练矿产预测模型。首先对研究区地质找矿信息和地球化学异常信息进行定量分析,提取断裂构造、二叠系地层、燕山期侵入岩、地层与岩体接触带、围岩蚀变及Pb、Zn、Sn、Cu地球化学异常共9种找矿因子。然后利用递归特征消除法优选找矿因子组合,不包括Sn异常在内的8个找矿因子组合被选为最优组合。最后,利用支持向量机和随机森林算法作为基分类器进行半监督协同训练矿产预测,绘制成矿概率分布图。ROC曲线和预测度曲线分析结果表明,半监督协同训练模型的AUC值和预测效率都高于随机森林和支持向量机模型。研究结果也为大数据环境下的智能矿产预测提供了一种新的思路。