F-K变换与预测反褶积压制多次波效果对比

多次波压制是地震资料处理中一个重要步骤。根据多次波发生下行反射的位置,可以把多次波分为两类:自由界面多次波和层间多次波。不同的多次波有着不同特性,一种压制多次波的方法往往只能针对特定的某一种多次波进行压制。F-K域压制多次波和预测反褶积分别利用了多次波的可分性和周期性这两种具有代表性压制多次波的处理方法。这里首先利用声波时差有限差分的方法对模型进行了正演计算,得到了包含不同类型多次波的地震数据;然后对正演数据分别应用F-K域压制多次波和预测反褶积两种压制多次波技术对自由界面多次波和层间多次波进行处理;最后对比分析了两种方法的处理效果,总结了两种方法的适用条件。F-K域多次波压制手段适用于多次波与一次波时差差异较大的情况,预测反褶积对小炮检距附近严格满足周期性的多次波去除效果较好。     

A Digital Map Library – Electronic Information in the Map Collection

Abstract

The ETH-Bibliothek (the Library of the Swiss Federal Institute of Technology) in Zurich has employed electronic resources to vastly enhance access to its collections. This article examines how ETH has set about the task of incorporating electronic data into the map collection, and then explores how access to hard copy map materials has been revolutionized by electronic means.     

多尺度气象干旱与土壤相对湿度的关系研究

通过分析我国东北、华北、西北地区东部、西南以及黄淮、江淮和江汉5个区域不同时间尺度气象干旱指数与20 cm土壤相对湿度的相关关系, 探讨了前期气象干旱对后期土壤湿度的影响, 并利用多元线性回归方法分区域、分季节建立了土壤湿度预测模型.结果表明: 春季, 东北地区土壤湿度主要受前5~6个月, 尤其是上年秋末冬初的降水的影响, 而其他4个区域土壤湿度主要受前1~2个月大气水分的影响;各区域夏季土壤湿度与前1~2个月时间尺度上的大气水分相关最密切;秋季, 东北地区20 cm土壤湿度主要受前2~4个月的气象干旱的影响, 其余区域土壤湿度仍与前1~2个月尺度的大气水分相关最密切.基于前期气象干旱指数建立的各区域、各季节的土壤湿度回归模型对当地土壤湿度具有一定的拟合能力, 平均估计偏差在10.1%~13.9%之间, 其中, 西北地区东部和华北地区春、夏季偏差较大, 2008-2011年间干旱等级拟合准确率在65%~74.9%之间;东北、西南、黄淮、江淮和江汉区域拟合较好, 拟合准确率在88%以上.     

A comparison of predictive methods in modelling the distribution of periglacial landforms in Finnish Lapland

This study compares the predictive accuracy of eight state‐of‐the‐art modelling techniques for 12 landforms types in a cold environment. The methods used are Random Forest (RF), Artificial Neural Networks (ANN), Generalized Boosting Methods (GBM), Generalized Linear Models (GLM), Generalized Additive Models (GAM), Multivariate Adaptive Regression Splines (MARS), Classification Tree Analysis (CTA) and Mixture Discriminant Analysis (MDA). The spatial distributions of 12 periglacial landforms types were recorded in sub‐Arctic landscape of northern Finland in 2032 grid squares at a resolution of 25 ha. First, three topographic variables were implemented into the eight modelling techniques (simple model), and then six other variables were added (three soil and three vegetation variables; complex model) to reflect the environmental conditions of each grid square. The predictive accuracy was measured by two methods: the area under the curve (AUC) of a receiver operating characteristic (ROC) plot, and the Kappa index (κ), based on spatially independent model evaluation data. The mean AUC values of the simple models varied between 0·709 and 0·796, whereas the AUC values of the complex model ranged from 0·725 to 0·825. For both simple and complex models GAM, GLM, ANN and GBM provided the highest predictive performances based on both AUC and κ values. The results encourage further applications of the novel modelling methods in geomorphology. Copyright © 2008 John Wiley & Sons, Ltd.     

Laboratory study and predictive modeling for thaw subsidence in deep permafrost

Oil wells on the North Slope of Alaska pass through deep deposits of permafrost. The heat transferred during their operation causes localized thawing, resulting in ground subsidence adjacent to the well casings. This subsidence has a damaging effect, causing the casings to compress, deform, and potentially fail. This paper presents the results of a laboratory study of the thaw consolidation strain of deep permafrost and its predictive modeling. Tests were performed to determine strains due to thaw and post-thaw loading, as well as soil index properties. Results, together with data from an earlier testing program, were used to produce empirical models for predicting strains and ground subsidence. Four distinct strain cases were analyzed with three models by multiple regression analyses, and the best-fitting model was selected for each case. Models were further compared in a ground subsidence prediction using a shared subsurface profile. Laboratory results indicate that strains due to thaw and post-thaw testing in deep core permafrost are insensitive to depth and are more strongly influenced by stress redistributions and the presence of ice lenses and inclusions. Modeling results show that the most statistically valid and useful models were those constructed using moisture content, porosity, and degree of saturation. The applicability of these models was validated by comparison with results from Finite Element modeling.     

基于多手段异常结果的地震综合概率预测

地震综合预测是,根据地震地质、地震活动性、地震前兆异常和环境因素等多种分析手段,与前兆信息监测所进行的现代防震减灾研究.最初的综合预测方法主要以预报经验的数学化统计为主,主要包含测震学、地壳形变学、地磁地电、地下流体等4种学科的预测方法,以及衍生出的,如综合概率法、模糊聚类、模式识别、专家系统以及模糊综合判定等分析方法...     

开封春季24h大风预报方法

利用开封1981-2000年3—5月的大风资料，依据冷空气路径，将大风分为东北型、西北型；选出预报因子，用逐步回归方法，对因子进行筛选，选出效果较好的预报因子建立方程。     

自动气象站蓄电池预测性维护的监测系统评定

为提高自动气象站蓄电池的维护效率,本文将预测性维护引入气象保障领域,通过对蓄电池预测性维护的技术要点、测试方案及流程等的介绍,选取3种不同劣化程度的蓄电池依次进行离线状态测试、浮充状态测试以及放电测试,通过数据对比分析初步给出了蓄电池预测性维护监测系统的综合评定。结果表明,在浮充状态下,监测系统电压和内阻的测试精度良好,能够很好地测试出蓄电池在不同健康状况下的电压与内阻值,即对报废电池、具有一定劣化程度电池和新电池的测试数据存在显著差别,在自动气象站蓄电池预测性维护中可利用浮充状态下测得的内阻数据对蓄电池劣化程度进行有效判别。     

华南冬季异常冷月预测概念模型Ⅱ──大气环流、极冰、积雪等物理因子特征

统计分析了华南冬季异常冷月及其前期大气环流及外部强迫因子的变化特征。结果表明,异常冷月当月至其前期３月西太平洋副热带高压带高压持续偏弱或位置偏东偏南。前一年东亚夏季风弱,当年冬季风强。前期７、８、９月和当年冬季亚洲极涡扩展。１月前期１１月和１２月青藏高原积雪日数偏少。２月前期１１个月,特别是３～８月北极Ⅳ区极冰偏多,１２月前期１～１１月Ⅱ期极冰偏多,３～８月Ⅲ区极冰偏少。综合上述因子以及５００ｈｐ     

基于透岩浆流体成矿理论的GIS矿产预测研究

本文以内生金属矿床透岩浆流体成矿理论为基础,以分级预测体制的思想为指导,认为在成矿理论指导下提出的各级预测体制对应的宏观地质标志是连接透岩浆流体成矿理论与GIS成矿信息的纽带,并从成矿地质背景、成矿作用触发机制和金属大规模堆积三方面,分别说明了各级预测体制及可能利用的宏观地质标志,最后通过研究目前广泛使用的GIS评价方法,初步建立起透岩浆流体成矿理论应用于宏观地质标志矿产预测的GIS预测系统框架。