低饱和度油藏原始饱和度计算及含水上升规律

受低幅度构造、地层倾角小、储层渗透率低、油源供给不足等因素影响,油层中存在自由水,若整个开发层系的油层大面积内均为油水同层,则称为低含油饱和度油藏。低含油饱和度油藏油井投产初期就具有一定含水率。由于室内岩心试验获得的油水相对渗透率曲线是在饱和油情况下进行,因此,油田实际含水与采出程度和利用室内试验曲线计算出的理论含水与采出程度曲线不能较好吻合,当油藏原始含水饱和度较高时这种误差会很大,导致含水与采出程度理论曲线无法正确预测油藏含水上升规律。根据试验获得的相渗曲线和实际生产数据,采用试验数据与生产实际相互印讧的方法,修正油藏含水上升规律,计算油藏原始含水饱和度,解决了油藏原始含油饱和度计算以及具有原始含水饱和度油藏含水上升规律预测问题,对正确认识油藏和开发指标预测具有重要意义。     

多尺度地图的水系面目标与线目标匹配方法与实验

目标匹配是实现多比例尺地图数据变化探测和更新的一个关键技术,它是依据几何、拓扑、语义等来进行判断的。同一地物在多比例尺地图中表达方式各异,甚至差异很大,可将较大比例尺面目标与较小比例尺线目标间的匹配模式归纳为6种：1∶0、1∶1、0∶1、1∶M、N∶1和N∶M。本文通过计算较小比例尺线目标的最小约束矩形(简记为MBR)...     

多尺度矢量地图数据关联自动更新研究

多级比例尺矢量地图数据库一旦建成以后,数字制图的核心就从数据生产转为数据更新.小比例尺矢量地图数据库建库时必须依靠大量人机交互从大比例尺数据派生,但更新时再采取各比例尺分别独立更新的策略显然就不合时宜,既消耗大量人力和财力,又不能保证不同尺度数据之间的一致性.提出一种多尺度矢量地图数据关联自动更新方法,对于已经建成的多...     

基于Geo-SQL语言的导航电子地图质量检测规则库的实现

从导航电子地图的行业标准和实践经验出发,引出了成果地图所必须遵循的质检规则,接着描述了如何对规则项进行分类、合并,使其有序的存储在Access数据库中,并详细介绍了规则库的组织结构。最后说明了如何将规则与对应的代码关联,使质量检测软件可以实现对规则库的基于Geo-SQLSQL语言的访问。通过此种方法建立的规则库,具有灵活性强,易扩展,易维护的特点,且大大提高了质检代码的可重用性,减少了软件开发人员的工作量。     

The complete SRSS modal combination rule

The complete Square‐Root‐of‐Sum‐of‐Squares (c‐SRSS) modal combination rule is presented. It expresses the structural response in terms of uncoupled SDOF modal responses, yet accounting fully for modal response variances and cross‐covariances. Thus, it is an improvement over the classical SRSS rule which neglects contributions from modal cross‐covariances. In the c‐SRSS rule the spectral moments of the structural response are expressed rigorously in terms of the spectral moments of uncoupled modal responses and of some coefficients that can be computed straightforwardly as a function of modal frequencies and damping, without involving the computation of cross‐correlation coefficients between modal responses. An example shows an application of the c‐SRSS rule for structural systems with well separated and closely spaced modal frequencies, subjected to wide‐band and narrow‐band excitations. Comparisons with response calculations using the SRSS and the Complete Quadratic Combination rules are given and discussed in detail. Based on the c‐SRSS rule a response spectrum formulation is introduced to estimate the maximum structural response. An example considering a narrow‐band excitation from the great Mexico earthquake of September 19, 1985, is given and the accuracy of the response spectrum formulation is examined. Copyright © 2010 John Wiley & Sons, Ltd.     

区域近震直达纵波走时变化和小震活动规律

以震报震是我们测震学预报地震方法中的一种。各个区域每年发生的小地震事件较多,了解区域小震与小震之间的联系规律,对于今后发生的地震,我们可以通过近期发生的地震,找出未来应力变化的区域,对潜在震源区提前做出预判,也为今后大震发生找出点研究线索。本文通过对区域直达纵波走时的变化来研究地下应力的变化,从而了解区域地震与地震之间的活动规律。     

多尺度地图面目标匹配的统一规则研究

以居民地为例,通过求较小比例尺面目标的最小外接矩形(MBR),将与该MBR交集非空的较大比例尺面目标进行分析判断,构建候选匹配集。在此基础上,通过分析各匹配模式的特点,制定相应的判断规则,提出了较为完整、统一的适用于多尺度矢量空间面目标的几何匹配解决方案。实验结果证明了该方法的有效性和实用性。     

基于加权时空关联规则的公交扒窃犯罪模式识别

近年来,公交扒窃案呈上升趋势,为了预防和打击此类犯罪,需要有效识别其犯罪模式。传统的犯罪分析方法,往往将时间和空间分割开来研究,本文则引入加权时空关联规则进行挖掘分析,试图找出公交扒窃的案发时空规律。首先,对公交扒窃数据进行时间粒度和空间粒度的划分,将公交主要运营时间以2 h为单位划分成等间隔的公交时段并对其进行编码,将公交线路按公交站点划分成公交路段;其次,对数据进行空间分析和时间归并,提取出每个案件发生的公交路段和案发时段,并将案发时段归并到公交时段中;再次,由于每个公交路段的案发率不同,其对结果的贡献率也不同,因此,给每个路段赋予一个权重;最后,用Apriori算法进行加权关联规则挖掘,得到公交扒窃的时空犯罪模式。研究表明,这种挖掘方法具有以下特点:(1)按公交站点进行公交路段的划分具有创新性;(2)通过对案发路段的加权,能将空间位置重要程度的差异区分开来,更符合实际情况;(3)挖掘过程中同时考虑了时间与空间属性。     

How to Enhance Cartographic Visualisations of Natural Hazards Assessment Results

Abstract

Cartographic visualisations are important tools for the communication of hazard related data among stakeholders. Although these representations are essential for various hazard management tasks, an analysis of existing hazard visualisations showed that they often disregard cartographic principles. This leads to confusion on the part of users through poor representations and consequently to an impairment of the information flow. The objective of this research is to offer suggestions for enhanced hazard visualisations to facilitate hazard management tasks and decision making. Existing cartographic shortcomings are identified based on an extensive analysis of hazard visualisations and an expert survey. These shortcomings are discussed and improvements for important cartographic elements are presented.     

A GeoAgent‐based framework for knowledge‐oriented representation: Embracing social rules in GIS

While current Geographic Information Systems (GISs) can represent observational spatial data well, they have limited capabilities in representing some non‐observational social elements and goal‐driven behaviours that can be important factors in a wide range of geographic issues. Such social components may include laws, regulations, polices, plans, culture, and customs, as well as their relations and interactions with the geographic environment at different scales. Getting beyond traditional data‐centred approaches, this research presents a knowledge‐oriented strategy in order to address these issues within a GIS context. We incorporate two major conceptual elements. First, extending from conventional agent notions and their geographic applications, geographic agents (GeoAgents) are considered as a basic representation component to specifically address social rules and goal‐driven behaviours that impact the Earth and environmental systems. Second, in order to incorporate GeoAgents with current space–time representation, a new conceptual representation framework, called ‘fields, objects, time, GeoAgents, and relations’ (FOTAR), is introduced to address the cross‐scale processes of both social and natural interactions. A Java‐based prototype, GeoAgent‐based Knowledge System (GeoAgentKS), is described to implement this framework by integrating agent technologies with multiple data and knowledge representation techniques, such as expert systems, concept maps, mathematical models, and geospatial databases. The application of this prototype in a case study is also presented, investigating scale‐dependent human–environment interactions under different emergency situations for community water systems in Central Pennsylvania, USA. In this case study, a systematic set of methodologies of knowledge acquisition, representation, and confirmation for constructing GeoAgents' knowledge bases by using expert systems were explored to formalize high‐level knowledge and social behaviours in the FOTAR‐based representations. The results show that the proposed conceptual representation framework is achievable at both implementation and application levels, and the prototype tool is demonstrated to be valuable in facilitating knowledge sharing, policymaking, municipal management, and decision‐making, especially for real‐world emergency management.