Application of the EnKF and Localization to Automatic History Matching of Facies Distribution and Production Data

The performance of the ensemble Kalman filter (EnKF) for continuous updating of facies location and boundaries in a reservoir model based on production and facies data for a 3D synthetic problem is presented. The occurrence of the different facies types is treated as a random process and the initial distribution was obtained by truncating a bi-Gaussian random field. Because facies data are highly non-Gaussian, re-parameterization was necessary in order to use the EnKF algorithm for data assimilation; two Gaussian random fields are updated in lieu of the static facies parameters. The problem of history matching applied to facies is difficult due to (1) constraints to facies observations at wells are occasionally violated when productions data are assimilated; (2) excessive reduction of variance seems to be a bigger problem with facies than with Gaussian random permeability and porosity fields; and (3) the relationship between facies variables and data is so highly non-linear that the final facies field does not always honor early production data well. Consequently three issues are investigated in this work. Is it possible to iteratively enforce facies constraints when updates due to production data have caused them to be violated? Can localization of adjustments be used for facies to prevent collapse of the variance during the data-assimilation period? Is a forecast from the final state better than a forecast from time zero using the final parameter fields?To investigate these issues, a 3D reservoir simulation model is coupled with the EnKF technique for data assimilation. One approach to enforcing the facies constraint is continuous iteration on all available data, which may lead to inconsistent model states, incorrect weighting of the production data and incorrect adjustment of the state vector. A sequential EnKF where the dynamic and static data are assimilated sequentially is presented and this approach seems to have solved the highlighted problems above. When the ensemble size is small compared to the number of independent data, the localized adjustment of the state vector is a very important technique that may be used to mitigate loss of rank in the ensemble. Implementing a distance-based localization of the facies adjustment appears to mitigate the problem of variance deficiency in the ensembles by ensuring that sufficient variability in the ensemble is maintained throughout the data assimilation period. Finally, when data are assimilated without localization, the prediction results appear to be independent of the starting point. When localization is applied, it is better to predict from the start using the final parameter field rather than continue from the final state.     

基于空间相似性的面实体匹配算法研究

同一地物在不同来源的地图上通常存在着差异,其识别或匹配对于不同数据源的地图编制来说很关键。面状地物要素在很多地图表示中都占有很大的比例。基于人眼综合已有信息来识别同名实体的思想,本文提出了基于空间相似性的面实体匹配算法。该算法将面实体作为一个整体看待,采用加权平均法来综合面实体的位置、形状、大小等特征的相似度,进而根据获得的总相似度大小确定匹配实体。算法在确定位置相似度时选择形状中心点对面实体进行惟一标识;采用形状描述函数来计算形状相似度,不容易受各种干扰而影响精度,避免了形状信息的丢失;面实体的大小通过其覆盖面积来度量。实验结果表明该方法具有良好的稳定性和可靠性。     

顾及尺度变化和数据更新的道路网匹配算法

道路网数据匹配是地理空间数据库进行变化探测和数据更新的重要前提,不同比例尺下的道路网之间的匹配是一个非常重要的部分。本文总结和分析了道路网匹配的已有算法,针对不同比例尺道路网之间的匹配可能存在的问题和难点,设计了一个融合多种匹配技术的算法。在考虑不同比例尺下道路网数据的特点基础上,改进了空间场景结构的评价方法;分析了stroke匹配算法在不同比例尺道路网数据下的局限性,提出了一种可针对不同比例尺下道路数据存在变化与更新的stroke部分匹配算法。试验表明,文中所提出的方法能够适应不同比例尺下道路网的匹配,匹配效果较好,运行效率较高。     

顾及纹理特征的航空影像自适应密集匹配方法

半全局匹配实质是在视差连续性假设下的离散优化方法。为克服视差断裂带影响,依赖一组参数控制视差不一致性。若参数过小,在平面内难以保证视差连续性,产生明显噪声,导致凹凸不平现象;若参数过大,将致使物体表面过于平滑,难以保留视差断裂等重要特征。为克服上述问题,本文提出了一种顾及纹理特征的自适应密集匹配方法:首先,检测影像纹理特征并定量表达纹理丰富性程度;其次,依据纹理丰富程度与视差差异存在正相关的规则知识,实现匹配参数依据纹理信息的自适应选择;最后,采用上述参数进行自适应的半全局匹配。通过ISPRS基准数据集和国产SWDC-5获取的倾斜影像进行试验分析证明,本文方法能够有效减少低纹理区域匹配噪声,同时更有效保留边缘特征。     

基于激光反射率的点云与图像自动融合

提出一个基于激光反射率的点云图像自动融合算法,数字图像与点云反射率图像特征点匹配,得到数字图像特征点像点坐标和相应物点物方空间坐标对,采用直接线性变换算法(DLT)建立点云数据反投影至二维图像点的投影模型,实现点云图像自动融合,得到目标表面的全面信息,包括物体表面三维坐标和纹理信息。自动地实现点云图像融合,无需人工参与,提高效率和准确率,同时结合实验验证该算法的可行性。     

Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references

Terrestrial laser scanning has been widely used to analyze the 3D structure of a forest in detail and to generate data at the level of a reference plot for forest inventories without destructive measurements. Multi-scan terrestrial laser scanning is more commonly applied to collect plot-level data so that all of the stems can be detected and analyzed. However, it is necessary to match the point clouds of multiple scans to yield a point cloud with automated processing. Mismatches between datasets will lead to errors during the processing of multi-scan data. Classic registration methods based on flat surfaces cannot be directly applied in forest environments; therefore, artificial reference objects have conventionally been used to assist with scan matching. The use of artificial references requires additional labor and expertise, as well as greatly increasing the cost. In this study, we present an automated processing method for plot-level stem mapping that matches multiple scans without artificial references. In contrast to previous studies, the registration method developed in this study exploits the natural geometric characteristics among a set of tree stems in a plot and combines the point clouds of multiple scans into a unified coordinate system. Integrating multiple scans improves the overall performance of stem mapping in terms of the correctness of tree detection, as well as the bias and the root-mean-square errors of forest attributes such as diameter at breast height and tree height. In addition, the automated processing method makes stem mapping more reliable and consistent among plots, reduces the costs associated with plot-based stem mapping, and enhances the efficiency.     

基于物方地面元的多视最小二乘匹配

以地图测绘、空间信息遥感、摄影测量学为背景的,根据多视影像匹配的理念和方法,按单点最小二乘匹配扩展为基于地面元的多点(以三片为例)的最小二乘匹配,基于改进的VLL讨论了一种基于多视影像的最小二乘影像匹配的方法,高精度的像素影像可以由这种特有的方法进行处理分析,像素的精度可达千分之一。进行相关分析后表明:进行高精度数字影像匹配融合时选择恰当影像匹配模型的匹配策略或由差异的匹配策略结合使用可更好地提高匹配的成功率和可适应性,从而降低误匹配或者漏匹配的同名点。     

地名地址数据库多源集成方法研究

地名地址数据库属于基础地理信息数据库,是构成数字城市地理空间框架不可或缺的重要组成部分,随着我国数字城市的逐步推进,城市建设和管理工作对基础地理信息的需求日益增加,地名地址数据库的建设和更新工作显得尤为重要。面对当前城市发展日新月异的现状,如何有效地提升数据完整性、时效性以及权威性成为数据库更新工作中必须解决的问题。本文以德州市地名地址数据库更新项目为例,指出外业调查中存在的数据问题,在对多来源地名地址数据进行广泛收集,分析这些数据的空间特征、时间特征以及利用方式的基础上,提出基于多源数据集成的数据库建设思路,利用地名地址匹配技术及人机交互的方式将官方资料与调查数据进行有机融合,并详细地从数据体系化检核、地名地址拓展、名称标准化3个方面进行阐述。项目成果表明,数据的质量明显提升。     

基于物方空间几何约束最小二乘匹配的建筑物半自动提取方法

提出了一种从数字航空立体像对半自动提取建筑物的方法。操作员通过人机界面选择房屋的种类并输入初始位置，然后经过边缘检测、直线段提取和据此房屋几何模型的线段自动编组等处理得到各房屋角点的初始位置，最后，为了获得房屋的精确定位和符合物方严格几何约束的结果，基于物方空间几何约束的最小二乘匹配平差模型用于求取房屋直线边缘和物方几何模型的最优匹配，试验表明，该方法能提高建筑物的提取精度并可为半自动建筑物提取提供一个灵活的框架。     

GIS组件分类与检索技术的研究和应用

讨论了组件分类和匹配原理，并对签名匹配法进行了研究，把它作为从已知的组件中获取可重用组件的方法，最后提出了在国土信息管理领域中GIS组件的解决方案。