模拟退火算法在控制网平差中的应用

线性最小二乘估计在对非线性函数进行线性近似的过程中会产生模型误差,而一些非线性参数估计方法可能因为函数复杂而难以求导,法方程系数矩阵秩亏或呈病态矩阵时难以求解,非线性迭代解法有时对初始值的选择存在依赖性,不恰当的初始值会导致迭代无法收敛。针对这些问题,引入了模拟退火算法,介绍了该算法的基本原理、计算步骤和收敛性,并以3个控制网平差应用为例,说明该算法具有无需求导求逆,简洁实用,易于编程等优势,并能实现全局优化,获得高精度的平差结果。     

准噶尔盆地中部III 区块原油中25-降藿烷分布特征与成因意义

通过对准噶尔盆地中部Ш区块原油或油砂抽提物的饱和烃气相色谱-质谱分析,研究了原油或油砂抽提物中25-降藿烷的分布规律.结果表明,不同井区或同一口井不同深度(层位)的原油25-降藿烷的相对含量存在比较明显的差别,表明其所遭受的生物降解程度有所差异,沿构造带从南到北,同一油层中原油的生物降解程度增强,比如位于构造北部(构造部位相对较高)的永1井、永3井侏罗系原油25-降藿烷丰度较高,表明生物降解比较明显,而位于南部(构造低部位)的永6井白垩系和侏罗系油层中的原油均无明显的生物降解现象;同一口井随深度增大生物降解作用将弱,如永2井浅部白垩系油层的原油降解较严重,而深部西山窑组的原油降解作用则不明显.根据原油生物降解的特征,结合车-莫古隆起调整对研究区油气成藏的影响,讨论了原油生物降解差异分布的成因机制.     

Numerical simulation of a stratigraphic model

A multi-lithology diffusive stratigraphic model is considered, which simulates at large scales in space and time the infill of sedimentary basins governed by the interaction between tectonics displacements, eustatic variations, sediment supply, and sediment transport laws. The model accounts for the mass conservation of each sediment lithology resulting in a mixed parabolic, hyperbolic system of partial differential equations (PDEs) for the lithology concentrations and the sediment thickness. It also takes into account a limit on the rock alteration velocity modeled as a unilaterality constraint. To obtain a robust, fast, and accurate simulation, fully and semi-implicit finite volume discre tization schemes are derived for which the existence of stable solutions is proved. Then, the set of nonlinear equations is solved using a Newton algorithm adapted to the unilaterality constraint, and preconditioning strategies are defined for the solution of the linear system at each Newton iteration. They are based on an algebraic approximate decoupling of the sediment thickness and the concentration variables as well as on a proper preconditioning of each variable. These algorithms are studied and compared in terms of robustness, scalability, and efficiency on two real basin test cases.     

基于ICCP算法的重力辅助惯性导航

迭代最近等值线算法(ICCP)是一种重要的匹配导航算法,文中首先介绍ICCP算法的基本原理,随后在0.2′×0.2′重力异常数据库的基础上,利用ICCP算法进行仿真计算得到最佳匹配位置。最后为了验证匹配位置是否可用于修正惯导误差,提出将匹配位置误差作为观测量,用卡尔曼滤波对惯导系统误差进行最优估计。由最后的仿真结果可以看出,ICCP算法可有效抑制惯导纬度误差的增长,且最大纬度误差不超过2,′以匹配位置误差作为观测量可以用来估计惯导方位误差角。     

顾及DEM误差自相关的坡度计算模型精度分析

基于DEM的坡度计算,其误差来源于DEM误差、DEM结构和坡度计算模型。在顾及DEM误差自相关的前提下,对四种DEM坡度计算模型进行了分析和评价。研究表明,三阶不带权差分能给出较高的坡度计算精度;在局部窗口中,格网点数量越多,坡度计算越准确;等权比不等权的坡度计算模型更准确;DEM误差自相关结构形式对坡度计算无影响。进一步的理论分析和试验分析还表明：DEM误差自相关性的存在,不仅能够改善地形分析的精度,也能改善DEM自身精度。     

基于规则库和网格算法的土地利用现状图自动数字注记

图形自动注记可极大地提高制图的工作效率。针对土地利用现状图数字注记的特点,本文从地图认知角度出发,建立注记自动配置的规则库,提出面状要素自动注记的一种新的算法——网格法。该算法最大的优点是容易实现、效率高,可方便地解决注记压盖冲突等问题。通过开发一个程序实例,对图斑要素进行了自动数字注记,实验表明95％以上的图形注记效果都较为理想。     

Aspherical correction for free vibration of elastically anisotropic solid by means of theXYZ algorithm

By applying the perturbation theory to theXYZ algorithm (a kind of variational method), the difference f in free vibration frequencies between sphere and ellipsoid was approximated as , where i and _i (i = x,y andz) (i=x, y andz) are aspherical coefficients and asphericities of the ellipsoid, respectively. We developed an analytic method to compute the aspherical coefficients719-4 by using theXYZ algorithm. A numerical example was given for an ellipsoidal olivine, and an attempt was made to estimate the asphericities of the specimen by a least-squares method, based on the relationship between frequency shift and asphericity.     

上扬子区(四川盆地)寒武系的含盐性与地质背景

据记载,分布于上扬子区寒武系的石膏岩仅有零星资料。如今,大量蒸发岩如溶蚀角砾岩、硬石膏、石盐岩及富钾卤水等已被发现。沉积相经历了从盆地相、台地相到蒸发岩相的演化过程。在中、下寒武统中找到海退沉积序列。古构造-古地理背景是蒸发岩沉积的重要控矿条件之一。周边板块运动及塑性基底的褶皱,导致台缘隆起及台内坳陷的形成。岩相古地理图展示从碳酸盐、硫酸盐到氯化物盐类的“泪滴式”沉积相带。蒸发岩沉积于台缘隆起及礁生长进入堰塞潟湖至盐湖阶段。在稳定坳陷区沉积盆地中蒸发岩系发育;石盐岩较厚,其溴氯比值为0.2—0.4;古气候炎热、干燥;在蒸发岩体周围有沉积(封层)水及溶滤水,其含钾(K~+)量为0.10—4.76g/L;水文地球化学比值(如钾氯比值、钾盐比值及钾溴比值等)指示含钾异常;盐湖浓缩卤水达到氯化物盐类沉积阶段及相应的构造封闭程度;含盐地质标志广泛分布等等。鉴于上述,估计该区可能具备钾盐成矿条件。然而目的层埋藏太深,因此笔者建议,应在浅埋部位进行有效的成矿预测,为普查指出远景区。     

Estimation for partially observed Markov processes

Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (X_n, n 0) or (X_t, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Y_n, n 0) or (Y_t, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.     

Reservoir description using dynamic parameterisation selection with a combined stochastic and gradient search

There is a correspondence between flow in a reservoir and large scale permeability trends. This correspondence can be derived by constraining reservoir models using observed production data. One of the challenges in deriving the permeability distribution of a field using production data involves determination of the scale of resolution of the permeability. The Adaptive Multiscale Estimation (AME) seeks to overcome the problems related to choosing the resolution of the permeability field by a dynamic parameterisation selection. The standard AME uses a gradient algorithm in solving several optimisation problems with increasing permeability resolution. This paper presents a hybrid algorithm which combines a gradient search and a stochastic algorithm to improve the robustness of the dynamic parameterisation selection. At low dimension, we use the stochastic algorithm to generate several optimised models. We use information from all these produced models to find new optimal refinements, and start out new optimisations with several unequally suggested parameterisations. At higher dimensions we change to a gradient-type optimiser, where the initial solution is chosen from the ensemble of models suggested by the stochastic algorithm. The selection is based on a predefined criterion. We demonstrate the robustness of the hybrid algorithm on sample synthetic cases, which most of them were considered insolvable using the standard AME algorithm.