嫩江组二段底部标志层岩石矿物学特征与成片套损因素新认识

大庆油田嫩江组二段底部与嫩江组一段顶部成片套损严重，从前一直认为泥岩吸水膨胀、蠕变是导致成片套损的主要因素。成片套损位置研究发现，嫩江组二段底部与嫩江组一段顶部成片套损实际集中于嫩江组二段底部标志层内，而嫩江组二段底部标志层岩石矿物学特征综合研究结果表明，其不含遇水膨胀的蒙脱石，且粘土矿物含量也低于其上下相邻岩石，表明其遇水膨胀与蠕变较弱，岩石遇水膨胀与蠕变不会构成成片套损的主要原因。嫩江组二段底部标志层岩石岩心观察描述、镜下鉴定、矿物成分综合测试和岩石强度性质研究发现，嫩江组二段底部标志层泥岩为富含长英质的质地坚硬岩石，含粘土矿物较少，不含蒙脱石，岩石吸水能力差、膨胀与蠕变能力弱；标志层中存在多个化石富集带，化石沿岩石层理分布形成沿层理方向的区域性力学薄弱面；沿化石层层理的抗张强度与抗剪强度远低于其他层位和垂直于层理方向的强度性质。因此，一旦注入水进入嫩江组二段底部标志层，富含化石的岩石沿岩石层理优先发生破坏，并迅速扩展，形成成片套损现象。     

小波分析方法在提取井水位潮汐因子震前变化特征的初步应用

运用小波分析方法对1990年常熟、1995年苍山和1996年南黄海三个中强地震前江苏地区井水位固体潮的变化特征进行了研究，发现井水位M2波潮汐因子在地震前几个月几乎都出现一个幅度较大、周期为半月或一个月左右的异常信号，表明小波分析方法在处理和分析井水位潮汐资料方面可能是一种有效的方法。     

Silicate‐oxide mineral chemistry of mafic–ultramafic rocks as an indicator of the roots of an island arc: The Chilas Complex,Kohistan (Pakistan)

The Chilas Complex is a major lower crustal component of the Cretaceous Kohistan island arc and one of the largest exposed slices of arc magma chamber in the world. Covering more than 8000 km², it reaches a current tectonic width of around 40 km. It was emplaced at 85 Ma during rifting of the arc soon after the collision of the arc with the Karakoram plate. Over 85% of the Complex comprises homogeneous, olivine‐free gabbronorite and subordinate orthopyroxene–quartz diorite association (MGNA), which contains bodies of up to 30 km² of ultramafic–mafic–anorthositic association (UMAA) rocks. Primary cumulate textures, igneous layering, and sedimentary structures are well preserved in layered parts of the UMAA in spite of pervasive granulite facies metamorphism. Mineral analyses show that the UMAA is characterized by more magnesian and more aluminous pyroxene and more calcic plagioclase than those in the MGNA. High modal abundances of orthopyroxene, magnetite and ilmenite (in MGNA), general Mg–Fe–Al spatial variations, and an MFA plot of whole‐rock analyses suggest a calc‐alkaline origin for the Complex. Projection of the pyroxene compositions on the Wo–En–Fs face is akin to those of pyroxenes from island arcs gabbros. The presence of highly calcic plagioclase and hornblende in UMAA is indicative of hydrous parental arc magma. The complex may be a product of two‐stage partial melting of a rising mantle diaper. The MGNA rocks represent the earlier phase melting, whereas the UMAA magma resulted from the melting of the same source depleted by the extraction of the earlier melt phase. Some of the massive peridotites in the UMAA may either be cumulates or represent metasomatized and remobilized upper mantle. The Chilas Complex shows similarities with many other (supra)subduction‐related mafic–ultramafic complexes worldwide.     

基于Google Earth Engine和NDVI时序差异指数的作物种植区提取

为提高农作物种植信息遥感监测的效率,扩展数据适用范围,本文提出了一种基于时间序列NDVI差异指数的作物种植区提取方法.随着海量遥感与云计算的发展,Google Earth Engine作为一个全球尺度地理空间分析云平台,弥补了单机计算耗时长的不足,为快速遥感分类带来了新机遇.基于Google Earth Engine平...     

中国贝类养殖对海洋碳循环的贡献评估

造成全球暖化的主要原因是温室气体的过量排放,其中CO2的贡献率达60 %,贝类养殖具有碳沉积作用。依据农业部渔业局编制的《中国渔业统计年签》,以2001年到2010年的年平均产量计算贝类捕获和养殖的碳沉积能力,并评估其碳沉积潜力;计算牡蛎、蛤、扇贝与贻贝四种贝壳单位面积的碳沉积能力并与森林、珊瑚礁的碳沉积能力进行比较分析。本文对我国浅海贝类养殖所具有的碳沉积能力进行评估,以了解贝类养殖对海洋碳循环的贡献,可为争取国家碳份额的合法权益提供基础数据。分析表明我国近十年贝类总产量稳定在1100万吨以上,并有增加的趋势,其中海水养殖贝类约占87.34 %。贝类养殖和捕获总产量的碳沉积和海水养殖产量的碳沉积量分别为58.57、51.15万吨/年,碳沉积能力分别相当于122.28、106.78万公顷的造林,可分别减少大气CO2增加量的0.0125 %、0.0109 %。牡蛎、蛤、扇贝与贻贝的单位面积碳沉积速率分别为1.573、0.388、0.301、1.039吨碳/(公顷?年);牡蛎和贻贝高于森林的碳沉积能力0.479吨碳/(公顷?年);但低于珊瑚礁的碳沉积能力1.8吨碳/(公顷?年)。我国贝类淡、海水养殖产量可分别创造约268.4万元/年、12,711.2万元/年的碳权商机。     

充填处理红宝石的鉴定

对红宝石的天然、合成、优化处理成因已有许多研究,其中有不少争议［１］。争议的焦点在于对其内含物（包裹体）的认识。因此,在鉴定工作中思路要宽,对内含物的一切可能成因要作全方位推断,然后一一甄别。１　测试样品及其一般宝石学特征１－１　测试样品本文测试样品为一条红宝石伴钻石手链,来自于广州市对一家有信誉的国营大公司的市场抽查。样品重７－５４ｇ,由１０粒规格为５－１×４－２ｍｍ的椭圆形刻面红宝石及１８粒圆形钻石组成,工艺精美,商家称为“镶嵌红宝石手链”。１－２　一般宝石学特征１０粒红宝石颜色统一,为较均…     

Oceanic climatology in the coupled model FGOALS-g2: Improvements and biases

The present study examines simulated oceanic climatology in the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 (FGOALS-g2) forced by historical external forcing data. The oceanic temperatures and circulations in FGOALS-g2 were found to be comparable to those observed, and substantially improved compared to those simulated by the previous version, FGOALS-g1.0. Compared with simulations by FGOALS-g1.0, the shallow mixed layer depths were better captured in the eastern Atlantic and Pacific Ocean in FGOALS-g2. In the high latitudes of the Northern Hemisphere, the cold biases of SST were about 1°C–5°C smaller in FGOALS-g2. The associated sea ice distributions and their seasonal cycles were more realistic in FGOALS-g2. The pattern of Atlantic Meridional Overturning Circulation (AMOC) was better simulated in FGOALS-g2, although its magnitude was larger than that found in observed data. The simulated Antarctic Circumpolar Current (ACC) transport was about 140 Sv through the Drake Passage, which is close to that observed. Moreover, Antarctic Intermediate Water (AAIW) was better captured in FGOALS-g2. However, large SST cold biases (>3°C) were still found to exist around major western boundary currents and in the Barents Sea, which can be explained by excessively strong oceanic cold advection and unresolved processes owing to the coarse resolution. In the Indo-Pacific warm pool, the cold biases were partly related to the excessive loss of heat from the ocean. Along the eastern coast in the Atlantic and Pacific Oceans, the warm biases were due to overestimation of shortwave radiation. In the Indian Ocean and Southern Ocean, the surface fresh biases were mainly due to the biases of precipitation. In the tropical Pacific Ocean, the surface fresh biases (>2 psu) were mainly caused by excessive precipitation and oceanic advection. In the Indo-Pacific Ocean, fresh biases were also found to dominate in the upper 1000 m, except in the northeastern Indian Ocean. There were warm and salty biases (3°C–4°C and 1–2 psu) from the surface to the bottom in the Labrador Sea, which might be due to large amounts of heat transport and excessive evaporation, respectively. For vertical structures, the maximal biases of temperature and salinity were found to be located at depths of >600 m in the Arctic Ocean, and their values exceeded 4°C and 2 psu, respectively.     

乳山金矿煌斑岩及流体和氢、氧、锶同位素研究

乳山金矿床是胶东近年来探明的一个赋存在花岗岩中的石英脉型金矿床。矿出露的煌斑岩金含量较低，不可能是金矿化的重要物源者。     

Quantitative analysis of the impact factors of conventional energy carbon emissions in Kazakhstan based on LMDI decomposition and STIRPAT model

Quantitative analysis of the impact factors in energy-related CO₂ emissions serves as an important guide for reducing carbon emissions and building an environmentally-friendly society. This paper aims to use LMDI method and a modified STIRPAT model to research the conventional energy-related CO₂ emissions in Kazakhstan after the collapse of the Soviet Union. The results show that the trajectory of CO₂ emissions displayed U-shaped curve from 1992 to 2013. Based on the extended Kaya identity and additive LMDI method, we decomposed total CO₂ emissions into four influencing factors. Of those, the economic active effect is the most influential factor driving CO₂ emissions, which produced 110.86 Mt CO₂ emissions, with a contribution rate of 43.92%. The second driving factor is the population effect, which led to 11.87 Mt CO₂ emissions with a contribution rate of 4.7%. On the contrary, the energy intensity effect is the most inhibiting factor, which caused–110.90 Mt CO₂ emissions with a contribution rate of–43.94%, followed by the energy carbon structure effect resulting in–18.76 Mt CO₂ emissions with a contribution rate of–7.43%. In order to provide an in-depth examination of the change response between energy-related CO₂ emissions and each impact factor, we construct a modified STIRPAT model based on ridge regression estimation. The results indicate that for every 1% increase in population size, economic activity, energy intensity and energy carbon structure, there is a subsequent increase in CO₂ emissions of 3.13%, 0.41%, 0.30% and 0.63%, respectively.     

基于Hilbert排列码与R树的海量LIDAR点云索引

本文分析当前索引方法存在问题,针对高效海量点云数据的要求,提出一种基于Hilbert码与R树的二级索引方法。论文阐述了二级索引的建立原理与方法,可通过聚类方法与R树度M值来的优化第一级索引;使用Hilbert R树作为第二索引,可以有效控制两级R树的高度,同时点云的增加与更新可只在局部进行。最后本文通过两组实验来验证该数据组织方法的可行性和跟其他索引(KD树与四叉树)进行比较,得出它是一种高效管理海量点云的方法。