岩浆驱动破裂的形态研究

轴地壳岩浆房是活动扩张中心海洋地壳结构的一个重要组成部分，轴地壳岩浆房通过深部岩浆源的补充，内部岩浆的同化熔融、结晶分异等岩浆房过程，其中的岩浆会破裂上覆的岩石层形成岩浆破裂，并沿岩浆破裂继续向上迁移。本文建立了岩浆迁移的层流模型，从理论上对岩浆迁移问题进行了探讨，并将遗传算法引入到该问题中来，用遗传算法求解了描述岩浆驱动破裂传播的积分方程。如果假设岩浆破裂在远离破裂末梢处的权限宽度为1M，则靠近末梢，破裂的宽度逐渐加大，在末梢处宽度为2m左右。并根据文献对岩浆流体的一些观测参数计算得出，岩浆破裂权限宽度不会很大，一般在1m左右的量级。     

矢量电子地图的线目标在线简化

为了适应实时ＧＩＳ的变比例尺显示与网络ＧＩＳ的快速矢量数据传输，提出了数字地图的在线综合概念，讨论了对线目标的在线简化算法。提出的两个在线简化算法都是对ＤＰ简化算法进行改造，使算法对时间的复杂度从θ（ｎ）～θ（ｎ２）的乘法运算改进为θ（１）～θ（ｎ）的赋值运算，并讨论了减少算法所涉及的空间复杂度的可能性     

井间电阻率层析成象的某些进展

用有限元法作电阻率层析成象的核心问题是Ｊａｃｏｂｉ矩阵的求取和反演成象算法的研究。本文主要论述了这两方面的最新进展，即求取Ｊａｃｏｂｉ矩阵的格林函数法，用于反演成象计算的平滑度约束反演。文中通过理论模型的成象计算，比较了两种反演算法的成象效果。     

遗传算法在上地幔速度结构研究中的应用

遗传算法是近年来发展较快的一种求解非线性优化问题的有效方法。本文通过对遗传算法基本原理的介绍，对该方法的特点进行了分析。我们采用ＷＫＢＪ理论地震图作正演，遗传算法作反演，对用体波波形反演上地幔速度结构的方法进行了研究。在ＷＫＢＪ理论地震图的计算中，通过计算主要射线的平均吸收特征时间，考虑了衰减随距离的变化，通过对不同震源引入不同的虚拟界面，同时对多个地震的波形记录进行反演。探讨了观测误差对反演结果的影响。对理论记录的反演表明，用遗传算法研究上地幔速度结构具有较好的效果。     

用非线性遗传反演方法进行自动静校正

静校正处理是消除近地层影响的一个重要地震资料数字处理方法，在近地表层纵，横向变化复杂，静校正量变化较大的地区，常规静校正方法和线性反演方法均不能解决问题，遗传算法是近年发展起来的一种模拟生物生化过程的较先进的非线性反演方法，对用遗传算法进行静校正的若干问题进行了讨论，说明它是可以解决表层情况复杂地区静校正问题的一个有效方法。     

Dynamic stochastic estimation of physical variables

A fundamental problem facing the physical sciences today is analysis of natural variations and mapping of spatiotemporal processes. Detailed maps describing the space/time distribution of groundwater contaminants, atmospheric pollutant deposition processes, rainfall intensity variables, external intermittency functions, etc. are tools whose importance in practical applications cannot be overestimated. Such maps are valuable inputs for numerous applications including, for example, solute transport, storm modeling, turbulent-nonturbulent flow characterization, weather prediction, and human exposure to hazardous substances. The approach considered here uses the spatiotemporal random field theory to study natural space/time variations and derive dynamic stochastic estimates of physical variables. The random field model is constructed in a space/time continuum that explicitly involves both spatial and temporal aspects and provides a rigorous representation of spatiotemporal variabilities and uncertainties. This has considerable advantages as regards analytical investigations of natural processes. The model is used to study natural space/time variations of springwater calcium ion data from the Dyle River catchment area, Belgium. This dataset is characterized by a spatially nonhomogeneous and temporally nonstationary variability that is quantified by random field parameters, such as orders of space/time continuity and random field increments. A rich class of covariance models is determined from the properties of the random field increments. The analysis leads to maps of continuity orders and covariances reflecting space/time calcium ion correlations and trends. Calcium ion estimates and the associated statistical errors are calculated at unmeasured locations/instants over the Dyle region using a space/time kriging algorithm. In practice, the interpretation of the results of the dynamic stochastic analysis should take into consideration the scale effects.     

Geostatistical regionalization of glacial aquitard thickness in northwestern Germany, based on fuzzy kriging

In many instances hydrogeological parameters obtained by conventional methods for selected localities within an aquifer or an aquitard are not sufficient for adequate regionalization at the scale of the entire layer. Here, we demonstrate an application of the fuzzy kriging method in regionalization of hydrogeological data, in which the set of conventional, crisp values is supplemented by imprecise information subjectively estimated by an expert. It is believed that such an approach eventually may reflect the real-world conditions more closely than a traditional crisp-value approach, because the former does not impose exactness artificially on phenomena which are diffuse by their nature. Spatial interpolation was done for the thickness of one of the major aquitards (till and glaciolacustrine clay) in northwestern Germany. The dataset consists of 329 crisp values from boreholes supplemented by 172 imprecise values defined as fuzzy numbers. It is demonstrated that the reliability of regionalization was higher, compared to regionalization performed with the crisp dataset only. Fuzzy kriging was performed with FUZZEKS (Fuzzy Evaluation and Kriging System) developed at the Ecosystem Research Center at the University of Kiel.     

论广义逆矩阵阶数增大的递推算法

本文针对加拿大地球物理学家ＥｄｏＮｇｌａｎｄ教授提出的问题，对Ｍ—Ｐ广义逆矩阵的递推算法进行了探分论述探讨的初步结果和对Ｇｒｅｖｉｌｌｅ递推算法的扩充。文中对算法的扩充给出严格的证明。     

Foliation fields and 3D cartography in geology: Principles of a method based on potential interpolation

A modeling method that takes into account known points on a geological interface and plane orientation data such as stratification or foliation planes is described and tested. The orientations data do not necessarily belong to one of the interfaces but are assumed to sample the main anisotropy of a geological formation as in current geological situations. The problem is to determine the surfaces which pass through the known points on interfaces and which are compatible with the orientation data. The method is based on the interpolation of a scalar field defined in the space the gradient in which is orthogonal to the orientations, given that some points have the same but unknown scalar value (points of the same interface), and that scalar gradient is known on the other points (foliations). The modeled interfaces are represented as isovalues of the interpolated field. Preliminary two-dimensional tests carried-out with different covariance models demonstrate the validity of the method, which is easily transposable in three dimensions.     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.