基于零立体像对立体匹配的配后质量控制

立体匹配的质量控制对数字摄影测量产品的质量起着关键的作用。本文首先分析了现有的各种质量控制策略，然后根据正射影像同ＤＴＭ及匹配点位存在的固有关系，提出了用零立体像对再匹配作为立体匹配的配后质量控制方案，为立体匹配质量控制开辟了崭新的途径。     

基于二进小波变换的遥感影像镶嵌方法

提出了一种新的影像镶嵌方法。通过与经典的直方图色调匹配方法实验结果比较，证明该方法克服了相邻影像中局部灰度差异大的问题，保证了接缝邻域处的图像清晰度和光滑度两个方面的要求。     

用于运动估计的高效三步法的VLSI实现

根据高效三步法的特点，提出了有效的数据流和相应的VLSI结构。该数据流充分利用参考帧搜索点之间数据重叠的特征，以减少数据存储器访问的次数，从而减少了运动估计中功率消耗最大部分的操作。通过对各种测试序列的仿真证明，该VLSI结构有效地实现了高效三步法，适合MPEG-4和HDTV应用。     

双金属抗震减灾复合材料设计与抗震特性分析

提出了Fe/Zn双金属抗震减灾复合材料的设计构想和复合理论基础。为验证Fe/Zn双金属复合材料具有抗震减灾作用,利用有限元软件ANSYS对材料的性能作数值仿真,分析了Fe/Zn复合材料试件在地震荷载下的动力特性。复合材料中,Fe保证构件刚度、恢复力及不发生过大变形;Zn的塑性变形改变材料的自振周期,同时吸收地震能量。     

基于位移的底部框架-抗震墙房屋抗震能力分析

在基于性能/位移抗震设计思想下,通过动力时程分析,研究了底部两层框剪砖房结构在不同地震强度作用下的弹塑性反应和变形特征;针对《规范》中对底部两层框剪砖房结构侧向刚度比的限定条件,研究了不同侧向刚度比条件下结构的抗震能力,得到了相关结论。     

A multiscale method for distributed parameter estimation with application to reservoir history matching

A method for multiscale parameter estimation with application to reservoir history matching is presented. Starting from a given fine-scale model, coarser models are generated using a global upscaling technique where the coarse models are tuned to match the solution of the fine model. Conditioning to dynamic data is done by history-matching the coarse model. Using consistently the same resolution both for the forward and inverse problems, this model is successively refined using a combination of downscaling and history matching until model-matching dynamic data are obtained at the finest scale. Large-scale corrections are obtained using fast models, which, combined with a downscaling procedure, provide a better initial model for the final adjustment on the fine scale. The result is thus a series of models with different resolution, all matching history as good as possible with this grid. Numerical examples show that this method may significantly reduce the computational effort and/or improve the quality of the solution when achieving a fine-scale match as compared to history-matching directly on the fine scale.     

CTM-DI磁力仪观测质量的探讨

介绍了CTM—DI磁力仪的性能及应用，根据实践经验提出了在使用该仪器过程中应注意的几个问题。     

The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery

In geological imaging spectrometry (i.e., hyperspectral remote sensing), surface compositional information (e.g., mineralogy and subsequently chemistry) is obtained by statistical comparison (by means of spectral matching algorithms) of known field- or library spectra to unknown image spectra. Though these algorithms are readily used, little emphasis has been given to comparison of the performance of the various spectral matching algorithms. Four spectral measures are presented: three that calculate the angle (spectral angle measure, SAM), the vector distance (Euclidean distance measure, ED) or the vector cross-correlation (spectral correlation measure, SCM), between a known reference and unknown target spectrum and a fourth measure that measures the discrepancy of probability distributions between two pixel vectors (the spectral information divergence, SID). The performance of these spectral similarity measures is compared using synthetic hyperspectral and real (i.e., Airborne Visible Infrared Imaging Spectrometer, AVIRIS) hyperspectral data of a (artificial or real) hydrothermal alteration system characterised by the minerals alunite, kaolinite, montmorillonite and quartz. Two statistics are used to assess the performance of the spectral similarity measures: the probability of spectral discrimination (PSD) and the power of spectral discrimination (PWSD). The first relates to the ability of the selected set of spectral endmembers to map a target spectrum, whereas the second expresses the capability of a spectral measure to separate two classes relative to a reference class. Analysis of the synthetic data set (i.e., simulated alteration zones with crisp boundaries at 1–2 nm spectral resolution) shows that (1) the SID outperforms the classical empirical spectral matching techniques (SAM, SCM and ED), (2) that SCM (SID, SAM and ED do not) exploits the overall shape of the reflectance curve and hence its outcomes are (positively and negatively) affected by the spectral range selected, (3) SAM and ED give nearly similar results and (4) for the same reason as in (2), the SCM is also more sensitive (again in positive and negative sense) to the spectral noise added. Results from the study of AVIRIS data show that SAM yields more spectral confusion (i.e., class overlap) than SID and SCM. In turn, SID is more effective in mapping the four target minerals than SCM as it clearly outperforms SCM when the target mineral coincides with the mineral phase on the ground.     

Application of the representer method for parameter estimation in numerical reservoir models

A data assimilation method was applied to estimate poorly known parameters (permeabilities) in a numerical reservoir model. Most variational methods for data assimilation are based on the assumption that the model is perfect except for the poorly known parameters. The representer method allows also for model errors, i.e. for uncertainties in the state variables (pressures and saturations). The method is based on minimizing a cost functional, assuming all the errors and parameters to be multivariate Gaussian random variables with given mean and covariances. The uncertain parameters and variables are expanded into a finite sum of basis functions called representers, and the gradients of the cost functional are obtained with an adjoint method. This approach gives an optimal parametrization in the sense that the final result is equal to the solution of the full inverse problem. The method was tested on a simple one-dimensional model to simulate two-phase (oil-water) flow through a heterogeneous reservoir. The results show that the method is able to provide an acceptable estimate of the permeability field. We used pressure measurements from a small number of observation wells in between the injection and production wells, but the representer method could be used equally well to assimilate data from other sources. The method appears to be a promising data assimilation tool for applications in reservoir engineering.