Geostatistical simulation of random fields with bivariate isofactorial distributions by adding mosaic models

This work deals with the geostatistical simulation of a family of stationary random field models with bivariate isofactorial distributions. Such models are defined as the sum of independent random fields with mosaic-type bivariate distributions and infinitely divisible univariate distributions. For practical applications, dead leaf tessellations are used since they provide a wide range of models and allow conditioning the realizations to a set of data via an iterative procedure (simulated annealing). The model parameters can be determined by comparing the data variogram and madogram, and enable to control the spatial connectivity of the extreme values in the realizations. An illustration to a forest dataset is presented, for which a negative binomial model is used to characterize the distribution of coniferous trees over a wooded area.     

基于正交多项式逼近法的岩土参数概率分布推断

针对岩上参数样本容量较大的情况,基于数值分析中的逼近原理,直接根据试验样本值,运用勒让德正交多项式来拟合岩土参数的概率密度函数,并用K-S检验法从理论上证明所求的密度函数的正确性和实用性。     

Conditional Simulation of Random Fields with Bivariate Gamma Isofactorial Distributions

This work focuses on a random function model with gamma marginal and bivariate isofactorial distributions, which has been applied in mining geostatistics for estimating recoverable reserves by disjunctive kriging. The objective is to widen its use to conditional simulation and further its application to the modeling of continuous attributes in geosciences. First, the main properties of the bivariate gamma isofactorial distributions are analyzed, with emphasis in the destructuring of the extreme values, the presence of a proportional effect (higher variability in high-valued areas), and the asymmetry in the spatial correlation of the indicator variables with respect to the median threshold. Then, we provide examples of stationary random functions with such bivariate distributions, for which the shape parameter of the marginal distribution is half an integer. These are defined as the sum of squared independent Gaussian random fields. An iterative algorithm based on the Gibbs sampler is proposed to perform the simulation conditional to a set of existing data. Such ‘multivariate chi-square’ model generalizes the well-known multigaussian model and is more flexible, since it allows defining a shape parameter which controls the asymmetry of the marginal and bivariate distributions.     

深圳S波段与X波段双偏振雷达在定量降水估计中的应用

双偏振多普勒天气雷达的一个重要应用是进行定量降水估计（QPE）,它可以获得反射率（Z_H）、差分反射率（Z_DR）和差传播相移率（K_dp）这些与降水粒子有关的信息,常用的双偏振雷达降水估计方法有基于Z_H的R（Z_H）、基于Z_H和Z_DR的R（Z_H,Z_DR）、基于K_dp的R（K_dp）和基于K_dp与Z_DR的R（K_dp,Z_DR）这4种。文中利用深圳市S波段和X波段双偏振多普勒雷达探测资料,结合高精度地形数据和雨滴谱仪观测数据,设计了基于双偏振量的定量降水估计方法:首先利用地形数据和雷达地理信息,分析了雷达的遮挡状况,形成了这两部雷达的复合平面扫描仰角信息;随后利用雨滴谱仪观测资料,使用T矩阵方法统计得到了深圳地区的上述4种降水反演方法的参数;最后设计了混合降水反演方法,基于双偏振信号（即K_dp和Z_DR）的强弱,使用不同的降水反演方法进行定量降水估计。基于12个降水个例,利用各反演方法产生的定量降水估计结果与雨量计观测资料比较。结果表明,混合降水反演方法在降水反演的准确度和稳定性上均优于任何一种单一定量降水估计反演方法。基于文中介绍的定量降水估计方法,使用深圳S波段和X波段雷达产生了定量降水估计产品,并与深圳目前业务定量降水估计产品进行对比评估。结果表明,使用本方法产生的定量降水估计产品在准确度和稳定性上要优于目前的业务产品。此外,X波段雷达的定量降水估计产品性能要略高于S波段雷达的定量降水估计产品,这说明高时、空分辨率的X波段雷达可以提高定量降水估计精度。但由于雷达扫描平面内双偏振雷达对融化层和冰区的偏振量观测与降水的关系尚未明确,因此,本方法仅适用于雷达扫描平面内液态降水区。      

福建省高速公路沿线雷电活动特征分析

为了揭示福建省高速公路沿线雷电活动特征,做好高速公路机电设施的防雷工作,本文利用2015 2018年福建省三维闪电监测数据以及福建省高速公路路网资料进行统计分析.分析了高速公路沿线地闪的月、日活动特征,得出地闪活动主要分布在5 9月和14:00 18:00.根据高速公路沿线地闪密度绘制雷电活动等级分布图,结果表明高速公...     

昆明滇池周围磷矿资源现状及开发前景

云南磷矿探明储量居全国首位,滇池周围保有储量占全省保有储量68.64%。磷化工与磷复肥基地和国内最大露采矿山,均在此区域内。"优矿低用"、矿山规模化小、国营矿山效益差,均是发展中要解决的问题。合理开采富矿、发展磷肥要"湿、热并举"、实施"矿电联营"、政府给予优惠政策,是云南磷矿业可持续发展的重要举措。     

油田高含水期基于微观渗流机理的宏观岩心水驱油数值模拟研究

建立地层孔隙网络模型描述微观孔喉特征,利用逾渗方法计算基于微观渗流机理的相对渗透率曲线,并将之应用到数值模拟计算中,给出考虑微观渗流特征的方程,并进行数值求解,得到地层中流体分布特征。实例分析表明该方法可以得到基于微观特征的剩余油分布数量和形式,为调剖堵水、化学驱提供技术参数,实现微观渗流机理与宏观计算的结合。     

南海鱼类生物多样性与区系分布

分析了南海鱼类生物多样性与区系分布的生态地理条件,鱼类生物多样性特征。校核整理了南海鱼类2 321种,分属于六鳃鲨等35目,以鲈形目占绝对优势(979种),并以珊瑚礁栖,典型暖水种的隆头鱼科为优势科(占117种),而蝴蝶鱼和石斑鱼分别达到34种、31种,列为优势属,从而构成南海富有潜势的群落结构。文中进一步论述了南海鱼类区系属于以印度-西太平洋为主体的区系特征。