布谷马西钾盐矿区卜育矿段盐系地层沉积旋回划分     

栾元滇  田宁  刘东义  岳伟佳  王宏伟 《化工矿产地质》2020,42(3):225-230

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海拉尔—塔木察格盆地中部富油凹陷高含凝灰质碎屑岩储层成因及油气勘探意义     

蒙启安  李军辉  李跃  邹越 《吉林大学学报(地球科学版)》2020,50(2):569-578

海拉尔—塔木察格盆地中部富油凹陷下白垩统铜钵庙组和南屯组广泛发育高含凝灰质碎屑岩储层，并已于其中获得了工业突破，但对其成因机制认识不清。在岩心、薄片、录井和测井等资料综合研究的基础上，结合大量海拉尔—塔木察格盆地及周边地区的火山事件分析，认为中部富油凹陷发育的高含凝灰质碎屑岩的岩石类型主要包括凝灰质砂岩、凝灰质泥岩、凝灰岩和沉凝灰岩。不同时期、不同凹陷高含凝灰质碎屑岩储层发育特点各异，整体来看从铜钵庙组到南屯组储层中的凝灰质含量越来越低，高含凝灰质碎屑岩储层主要发育在铜钵庙组和南一段沉积时期。高含凝灰质碎屑岩储层中的火山物质并非来源于自身断陷期发生的基性火山活动，而是来自于大兴安岭地区大规模的酸性火山喷发事件。海拉尔—塔木察格盆地高含凝灰质碎屑岩储层的成因机制包括两种类型：一种是同沉积期火山灰直接空降入湖型；另一种是同沉积期火山灰先沉降至陆上经河流搬运后再沉积的水携型。高含凝灰质碎屑岩储层中的火山碎屑物质受有机酸作用易于溶蚀，次生孔隙发育，为深部油气成藏提供了有效储层空间，并且火山喷发活动对优质烃源岩的形成具有促进作用，对于油气勘探具有重要意义。  相似文献   

Effects of current climate,paleo-climate,and habitat heterogeneity in determining biogeographical patterns of evergreen broad-leaved woody plants in China   总被引：1，自引：1，他引：0  

Xu  Yue  Shen  Zehao  Ying  Lingxiao  Zang  Runguo  Jiang  Youxu 《地理学报(英文版)》2019,29(7):1142-1158

Journal of Geographical Sciences - Understanding biogeographic patterns and the mechanisms underlying them has been a main issue in macroecology and biogeography, and has implications for...  相似文献   

一种潜艇装备作战能力比较研究方法     

罗浩  宁云晖  陶伟  尤岳 《数字海洋与水下攻防》2020,3(6):494-498

对潜艇装备作战能力评估问题进行了研究，发现运用定量评估方法的过程中存在指标评价所需数据无法完全获取的问题。结合美弗吉尼亚潜艇改进情况，分析了影响潜艇作战能力的一些关键因素，重点基于潜艇武器装载能力，对国外典型潜艇进行了作战能力比较分析，最后对分析结果进行了评价，并讨论了未来潜艇作战能力评估方法的发展方向。  相似文献   

大连市大气污染物质量浓度与气溶胶光学厚度的相关性分析     

顾吉林  汤宏山  刘淼  耿杨  于月  陶涛 《地理科学》2019,39(3):516-523

分别对2015年6~12月和2016年6~12月大连地区的大气污染物PM2.5、PM10、SO₂、NO₂、CO和O₃的浓度数据进行数据统计分析,基于ENVI软件平台利用MODIS数据反演大连地区的气溶胶光学厚度,通过回归建模研究气溶胶光学厚度与大连地区10个地面监测站点的大气污染物PM2.5、PM10、SO₂、NO₂、CO和O₃的浓度数据的相关性。回归建模以气溶胶光学厚度（AOD）为自变量,以大气污染物PM2.5、PM10、SO₂、NO₂、CO和O₃为因变量,在SPSS软件中分别选取线性、对数、三次、乘幂、指数5种函数类型进行研究,通过对比回归模型的拟合优度R²,选择最优拟合模型,探讨利用遥感数据反演气溶胶光学厚度监测大气污染的相关性。结果表明：气溶胶光学厚度与NO₂、PM2.5和PM10的最优拟合模型均为三次模型,其拟合优度R²分别是0.685、0.801和0.845;与O₃和SO₂的最优拟合模型为指数模型,其R²为0.367和0.482;与CO的最优拟合模型为对数模型,其拟合优度R²为0.810。该结果为分析大气气溶胶污染来源以及治理提供了数据。  相似文献   

机载条纹管成像激光雷达在拍岸区探测水雷          下载免费PDF全文

王力  刘峡  王玥  吴中平 《数字海洋与水下攻防》2018,1(1):30-33

为了解决拍岸区水雷探测的问题，以无人机为载体的条纹管成像蓝绿激光雷达可以用来扫描、识别水雷，蓝绿激光成像雷达白天和夜晚均可以稳定成像，机载探测方式相对于水下、水面等传统探测方式效率也可以提高，机载激光雷达可由小型船舶、小型汽车等多平台携带使用。  相似文献   

三亚海域浮游病毒与细菌丰度的时空变化规律以及相关环境因子*     

荆红梅  韦誉  郑丽平  许秋彤  张玥  朱文达 《热带海洋学报》2018,37(2):36-46

在三亚海域设置3个站位, 分别于各站位连续采集12个月表层水样。利用流式细胞仪进行浮游病毒及浮游细菌丰度的测定, 并对两者及其与环境因子之间的相关性进行研究, 同时对不同站位之间进行差异性分析。结果表明, 调查海域浮游病毒丰度(平均7.63×10⁶viruses·mL^-1)高于浮游细菌丰度(平均1.52×10⁶cells·mL^-1)。浮游病毒及浮游细菌丰度在三亚河口最高, 且有明显的季节变化, 冬春季高于夏秋季, 并且其与鹿回头半岛西侧、小东海之间均有极显著差异(P<0.01), 不同类群病毒代表的宿主类群也有所不同。调查海域总体水平浮游病毒丰度与浮游细菌丰度显著正相关(r=0.800, P<0.01); 叶绿素(Chl a)和氮盐(NO- 2、NO- 2+NO- 3、NH+ 4)是影响两者的关键因子。  相似文献   

An algorithm to resolve γ-rays from charged cosmic rays with DAMPE     

Zun-Lei Xu  Kai-Kai Duan  Zhao-Qiang Shen  Shi-Jun Lei  Tie-Kuang Dong  Fabio Gargano  Simone Garrappa  Dong-Ya Guo  Wei Jiang  Xiang Li  Yun-Feng Liang  Mario Nicola Mazziotta  Maria Fernanda Munoz Salinas  Meng Su  Valerio Vagelli  Qiang Yuan  Chuan Yue  Jing-Jing Zang  Ya-Peng Zhang  Yun-Long Zhang  Stephan Zimmer 《天文和天体物理学研究(英文版)》2018,(3)

The DArk Matter Particle Explorer(DAMPE),also known as Wukong in China,which was launched on 2015 December 17,is a new high energy cosmic ray and γ-ray satellite-borne observatory.One of the main scientific goals of DAMPE is to observe Ge V-Te V high energy γ-rays with accurate energy,angular and time resolution,to indirectly search for dark matter particles and for the study of high energy astrophysics. Due to the comparatively higher fluxes of charged cosmic rays with respect to γ-rays,it is challenging to identify γ-rays with sufficiently high efficiency,minimizing the amount of charged cosmic ray contamination. In this work we present a method to identify γ-rays in DAMPE data based on Monte Carlo simulations,using the powerful electromagnetic/hadronic shower discrimination provided by the calorimeter and the veto detection of charged particles provided by the plastic scintillation detector. Monte Carlo simulations show that after this selection the number of electrons and protons that contaminate the selected γ-ray events at～10 Ge V amounts to less than 1% of the selected sample.Finally,we use flight data to verify the effectiveness of the method by highlighting known γ-ray sources in the sky and by reconstructing preliminary light curves of the Geminga pulsar.  相似文献   

Estimating the properties of weathered bedrock and pilerock interaction from the geological strength index     

Chun-mei Zhou  Wei Shao  Kun-long Yin  Zong-ji Yang 《山地科学学报》2018,15(8):1757-1776

The effect of variable rock mass properties on pile-rock interaction poses a great challenge to the design of stabilizing piles and numerical analysis of pile-rock interaction. The paper presents a novel method to estimate the properties of weathered bedrock, which can be applied to routine design of landslide-stabilizing piles for collivial landslides. The Ercengyan landslide located in the Three Gorges Reservoir, China, is the area of interest for this study. A geological investigation and triaxial tests were conducted to estimate the basic parameters, including Geological Strength Index(GSI), uniaxial compressive strength σ_(ci) and Hoek-Brown constant m_i of intact bedrock in the study area. Hoek-Brown criterion was used to estimate mechanical properties of the weathered rock, including elastic modulus E_m, cohesion c, friction angle Φ, and normal ultimate lateral resistance p_(max). A parametric study was performed to evaluate the effect of parameterizations of GSI, σ_(ci) and m_i on the bedrock properties and p-y curves. The estimated rock mass properties were used with PLAXIS 2D software to simulate pile-rock interaction. Effect of GSI on stress at the pile-rock interface and in the rock, pile bending moment, pile shear force, and p-y curve were analysed.  相似文献   

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing     

Peng Yue  Fan Gao  Boyi Shangguan  Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献