Accumulation characteristics and the main controlling factors of Lunnan multilayer oil province,Tarim Basin,China

Lunnan region is a large-scale paleohigh with many coexisting oil and gas bearing series.At present, about 2 billions tons of proved,probable and possible oil and gas reverses have been proved there.Eight oil and gas bearing series have been found in the Ordovician,Carboniferous,Triassic and Jurassic of Lunnan region,they all bear the characteristics of large-scale multilayer oil-gas province.Ordovician is the main reservoir series where over 0.8 billion tons of oil geologic reserves were discovered,and a super large-scale marine carbonate oil and gas field has formed.Reservoir space of the carbonate reservoirs is mainly composed of dissolved hole,dissolved pore and fracture in Lunnan paleo-burial hill.Generally, dissolved holes are widely distributed among them.Reservoir developments are mainly controlled by karstification and tectonic disruption.Due to the similar geochemical characters,the Ordovician,Carboniferous,Triassic and Jurassic oil and gas reservoirs present the same oil source rock of Mid-Upper Ordovician,the latter except Ordovician are mostly of secondary oil and gas reservoirs migrated vertically by faults during the process of multiple phase tectonic movement,adjustment and reconstruction. Lunnan composite oil and gas accumulation region is situated in the vicinity of large-scale hydrocarbon generation depressions in three directions,ample oil and gas from hydrocarbon generation depressions supplied the adjacent oil and gas reservoirs once.Hereby,the succeed paleohigh is the long-term hydrocarbon accumulation region,which is favor for the formations of high quality reservoirs,fault systems and huge-scale composite oil and gas accumulation.     

Modelling river temperature from air temperature: case of the River Drava (Croatia)

Abstract

Measurements made in the past few decades undeniably indicate change in the climate. The most visible sign of global climate change is air temperature, while less visible indicators include changes in river water temperatures. Changes in river temperature can significantly affect the environment, primarily the biosphere. The physical, biological and chemical characteristics of the river are directly affected by water temperature, although estimation of this relationship presents a complex problem. Although river temperature is influenced by hydrological and meteorological factors, the purpose of this study is to model daily water temperature using only one known parameter, mean air temperature. The relationship between the daily mean air and daily water temperature of the River Drava in Croatia is analysed using linear regression, stochastic modelling or nonlinear regression and multilayer perceptron (MLP) feed-forward neural networks. The results indicate that the MLP models are much better models which can be used for the estimation and prediction of daily mean river temperature.

Editor D. Koutsoyiannis; Associate editor M. Acreman     

下一代地球物理观测技术

地球物理观测技术所要解决的问题是观测什么、用什么来观测、怎样观测。下一代地球物理观测技术的发展是以解决上述问题为基础。论文详细论述了观测设备、观测系统以及地球外行星体结构探测等发展动态,并对下一代地球物理观测技术的发展方向进行了分析。     

AN ANALYSIS OF THE APPLICABILITY OF FUZZY CLUSTERING IN ESTABLISHING AN INDEX FOR THE EVALUATION OF METEOROLOGICAL SERVICE SATISFACTION

An evaluation index is a prerequisite for scientific evaluation of a public meteorological service. This paper aims to explore a technical method for determining and screening evaluation indicators. Based on public satisfaction survey data obtained in Wafangdian (China) in 2010, this study investigates the suitability of the fuzzy clustering analysis method in establishing an evaluation index. Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators, correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer, then one indicator could be removed, or the two indicators merged. For evaluation indicators in different sub-evaluation layers, although clustering reveals attribute correlations, these indicators may not be substituted for one another. Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.     

Prediction of temperature variation within a snowpack in open areas and under different canopy covers

Snow temperature is a major component of many physical processes in a snowpack. The temperature and the change in temperature across a layer have a dominant effect on physical properties of snow grains as well as its hardness, strength, and failure resistance. In this study, temperature and snow cover thickness were measured during the snow season of 2007–2008 in 11 elevation classes and in three different sampling locations, one in an open area and two under different forest canopy covers for each class along Kartalkaya road, Bolu. Each sampling site was visited 44 times to collect data including snow depth, snow surface temperature, ground temperature, and temperature within snowpack at 20‐cm intervals. Seven different models are developed to determine snowpack temperature variations under forest canopy covers and in an open area with different leaf area index values. All models were performed using a multilayer perceptron (MP) method for the Bolu–Kartalkaya area, Turkey. MP approach constitutes a standard form of neural network modeling and can modify two‐layer linear perceptron methods using three and more layers. The ability of MP is to handle complex nonlinear interactions, which ease the natural process of modeling. This method can overcome complex computations using neuron networks, and they can easily nonlinearly link input and output variables. The predictive errors are determined on the basis of mean absolute error and mean square error criteria. The Nash–Sutcliffe sufficiency score showing compliance between observed and predicted values is also calculated. According to the mean absolute error, the mean square error, and the Nash–Sutcliffe sufficiency score criteria, the predictive errors are within reasonable error intervals, justifying the use of the developed MP models for engineering applications. Copyright © 2012 John Wiley & Sons, Ltd.     

新型压电变摩擦阻尼器的研发与性能试验

本文采用商用标准件叠层压电驱动器和圆形摩擦盘,研发了能提供水平任一方向可调摩擦阻尼力的新型压电变摩擦阻尼器,能与圆形隔震垫协同工作复合而成智能隔震系统.文中首先提出了新型压电阻尼器的基本结构,制作了试验室比例的模型;其次针对压电驱动器变形在微米数量级的特点和约束钢架的刚度特性,提出了基于有限元分析的形状系数和可调正压力计算方法.并用约束钢架变形试验验证了有限元分析的正确性;最后通过阻尼器性能试验提出了连续型的阻尼力计算模型,一种适合于实际工程应用的摩擦阻尼力模型.提出的新型压电摩擦阻尼器构造简单,阻尼力调节方便,响应速度快,特别是便于进一步增大阻尼力调节倍数,能够较大地推动压电阻尼器实用化进程.     

多种群并行进化神经网络的研究及应用

提出一种新的多种群并行遗传算法 (NMPGA) ,并将其作为多层前馈神经网络(MFNNs)的学习算法 ,从而形成一类新的 MFNN模型——多种群并行进化神经网络(MPENNs)。首先 ,对一给定的网络结构 ,随机产生一初始权重的集合 ,这个集合实际上对应着一组具有相同结构但不同权重的神经网络。然后 ,采用 NMPGA对 MFNNs的权重进行进化。最后 ,性能最好的网络被选作目标问题的解。在 NMPGA算法中 ,作者采用浮点数编码来克服传统二进制编码的精度不足问题 ,并设计了专门的杂交算子和变异算子来增强算法性能。实验结果表明 ,MPENNs能成功解决异或问题、三元奇偶问题及成品烟的感官质量评价问题。     

华南多层推滑构造系的物理模拟实验

利用物理模拟的方法,研究华南多层推滑构造系的变形特征、变形过程和力学机制.在实验室条件下,根据实际地质条件,物理模拟实验再现了多层推滑构造系的形成和演化过程;论证了岩石能干性差异和岩系能干性结构对变形产生的影响.在挤压应力背景下,岩石发生逆冲推覆,能干性层在非能干性层上滑脱、变形,形成断坪-断坡逆冲推覆变形构造.由于非...     

独库高速公路克扎依—巩乃斯段雪崩易发性评价

独库高速公路克扎依—巩乃斯段以高山地貌为主,地形切割剧烈,为雪崩发育提供了有利的地形条件,对该区域进行雪崩易发性评价是独库高速公路安全建设及运行的重要前提。通过遥感解译和现场调查等手段获取149个雪崩点的因子数据,通过对因子进行相关性检测,筛选出10个评价因子,构成雪崩评价因子体系。在此基础上,运用K均值聚类法和随机法提取出非雪崩点和原始雪崩点构成样本集,通过机器学习中的多层感知器、支持向量机算法对研究区域开展雪崩易发性评价。研究结果表明,随机法和K均值聚类法提取出的样本集分别带入算法中训练,R-SVM、R-MLP、K-SVM、K-MLP四种模型的Kappa系数均大于0.6,4组模型对验证数据集的预测结果与实际值存在高度的一致性。经多层感知器训练的AUC值由0.762提高至0.983,经支持向量机训练的AUC值由0.724提高至0.951。基于本研究预测性能最佳的K-MLP模型分区显示该研究区雪崩发育对拟建线路影响较小,但对于隧道洞口可能会造成威胁。本研究可为独库高速公路建设、运营以及雪崩灾害防治工作提供理论支撑和方法参考。     

任意方向发射源在柱状多层介质中的电磁场的理论计算

针对柱状多层介质测井模型,本文给出了井轴上沿任意方向的发射源在介质空间的电磁场的理论公式,利用递推方法可以很方便地进行数值计算.文中还分别对轴向与径向的电偶极子源和磁偶极子源共4种情况,给出了井轴上接收区磁场强度与侵入半径的关系曲线.