各向异性序贯高斯随机模拟研究.pdf-资料库

qq_21407363-10124864-16359647627731163710.pdf-第1页.png

第1页 / 共82页

qq_21407363-10124864-16359647627731163710.pdf-第2页.png

第2页 / 共82页

qq_21407363-10124864-16359647627731163710.pdf-第3页.png

第3页 / 共82页

qq_21407363-10124864-16359647627731163710.pdf-第4页.png

第4页 / 共82页

qq_21407363-10124864-16359647627731163710.pdf-第5页.png

第5页 / 共82页

qq_21407363-10124864-16359647627731163710.pdf-第6页.png

第6页 / 共82页

qq_21407363-10124864-16359647627731163710.pdf-第7页.png

第7页 / 共82页

qq_21407363-10124864-16359647627731163710.pdf-第8页.png

第8页 / 共82页

分类号密级 UDC 注 1 学位论文各向异性序贯高斯随机模拟研究（题名和副题名）毕文一（作者姓名）指导教师姚兴苗副教授电子科技大学成都申请学位级别硕士学科专业信息与通信工程（姓名、职称、单位名称）提交论文日期 2014.05.13 论文答辩日期 2014.05.29 学位授予单位和日期电子科技大学 2014 年 06 月 30 日答辩委员会主席评阅人注 1：注明《国际十进分类法 UDC》的类号。

RESEARCH ON SEQUENCIAL GAUSSIAN SIMULATION WITH ANISOTROPY A Master Thesis Submitted to University of Electronic Science and Technology of China Major: Information and Communication Engineering Author: WenYi Bi Advisor: XingMiao Yao School: School of Communication & Information Engineering

独创性声明本人声明所呈交的学位论文是本人在导师指导下进行的研究工作及取得的研究成果。据我所知，除了文中特别加以标注和致谢的地方外，论文中不包含其他人已经发表或撰写过的研究成果，也不包含为获得电子科技大学或其它教育机构的学位或证书而使用过的材料。与我一同工作的同志对本研究所做的任何贡献均已在论文中作了明确的说明并表示谢意。作者签名：日期：年月日论文使用授权本学位论文作者完全了解电子科技大学有关保留、使用学位论文的规定，有权保留并向国家有关部门或机构送交论文的复印件和磁盘，允许论文被查阅和借阅。本人授权电子科技大学可以将学位论文的全部或部分内容编入有关数据库进行检索，可以采用影印、缩印或扫描等复制手段保存、汇编学位论文。（保密的学位论文在解密后应遵守此规定）作者签名：导师签名：日期：年月日

摘要摘要随机模拟技术是地质统计学的新发展，在储层建模中由于地质环境的复杂性及观测数据的间接性和微量性，为储层建立的模型存在很高的不确定性。随机模拟是为储层建立随机模型并产生具有差异的多种结果来表征建模的不确定性。这些模拟结果称为实现，每一次实现都具有期望的结构及对条件数据的遵从，都是对已知信息的全面利用，每一次实现都是合理的建模。随机模拟的技术发展出丰富的算法集，为储层建模提供可靠多样的建模手段。并且，随机模拟已被各种需要建立空间模型的学科所采纳并发展。本文先对地质统计分析基本理论作了论述，包括地质变量、随机函数和变差函数的阐述，尤其是作为空间结构分析与表征的变差函数作了详尽论述，阐明了实验变差函数分析方法，变差函数模型的构建及已有的具有空间各向异性表征能力的变差函数构建方法。随后是本文的主要工作，对具有各向异性再现能力的序贯高斯模拟和具有强数据整合能力的模拟退火的随机模拟方法做了研究和改进。具体工作如下： 1.针对现有序贯高斯模拟算法只能构建各向同性的变异性和简单的变程各向异性及基台各向异性的不足，提出了一种新的各向异性构建方法。这种新方法是在表征结构的变差函数模型构建环节，进行主方向与次方向的区分，并对主方向构造强连续性变差模型，对次方向构造弱连续性变差模型，并作主次方向间的有机过渡，得到了各向异性特征更鲜明的序贯高斯模拟。同时，针对观测数据和模拟过程中产生数据的不同分布特点，提出了采用分区搜索与螺旋搜索有机结合的搜索策略。将新算法应用到实际工区进行二维模拟分析，与现有的各向同性模拟和变程各向异性模拟作比较分析，验证了新方法的有效性。 2.针对现有的模拟退火随机模拟方法中存在的温度参数调试复杂及模拟过程收敛慢的问题，提出在退火机制上采用自适应退火机制，使得温度参数自适应调节且模拟退火以近似热平稳的状态退火，收敛速度明显提高。并将新算法应用到二维实际工区作模拟和分析，模拟结果验证了改进算法的有效性。关键词：储层建模，序贯高斯模拟，各向异性，自适应退火 I

ABSTRACT ABSTRACT Stochastic simulation is the new development of geostatistics, the reservoir model is of high uncertainty due to the complex geology environment and the indirectness of the observations and the small number of direct observations. Stochastic simulation is to build the reservoir model with various realizations to characterize the uncertainty of the reservoir. Every realization holds the expected space structure and honors the conditional data, thus they are all plausible models of the reservoir. As to now, the technique of stochastic simulation has breed a rich set of simulation algorithms which offer diverse reliable means to build model for reservoir. And the theory and methods have been widely adopted and developed by many other disciplines which requiring building space model for analysis. This thesis first descripted the basic theory of geostatistics, including the concept of geology variable and stochastic function and the variogram. Particularly, the variogram as a critical tool in space structure analysis and characterization was discussed in detail, including the method of analyzing experimental variogram and building the variogram model with space anisotropy features. As the traditional estimation method and the basic parameters estimation method, kriging was discussed in detail. The key part of this thesis was on the study of two widely used stochastic simulation methods. One is sequential Gaussian simulation with the ability to reproduce the anisotropy structure feature in the realizations , the other one is the simulated annealing simulation capable of integrating various types data. The work of this thesis is detailed as follows: 1.For the fact that the current sequential Gaussian simulation algorithm can only construct the isotropic variograms and simple range-based anisotropic variograms and sill anisotropic vairograms, a new method constructing anisotropy in realizations was proposed. The new method exploited the variogram’s anisotropy characterizing ability, distinguished the primary continuous direction and the secondary direction , configured the primary direction with strong continuous variogram models and the secondary direction with weak continuous variogram models. The transition means from primary direction to the secondary direction was also studied. At the same time, based on the different space distribution characteristics of observations and simulated points during II

ABSTRACT the simulation, a combination searching method of section-based method and spiral method was proposed. The proposed algorithm was applied to a 2d work area and compared the realizations with the results from isotropic algorithm and range-based algorithm. The new features validated the effectiveness of the new method. 2.For the complexness in temperature parameters adjusting and the slow convergence in current simulated annealing algorithm in constructing realizations, we borrowed the advanced adaptive annealing skill and assembled it into the simulation method to relieve the troublesome manual adjusting job of temperature and the annealing process is tracked on the D equilibrium to speed up the convergence process. Through the simulation and analysis of a real reservoir the effectiveness of the improved simulated annealing simulation was validated. Keywords: reservoir modeling, sequential Gaussian simulation, anisotropy, adaptive annealing III

目录目录第一章绪论 .................................................................................................................. 1 1.1 研究工作的背景与意义 .................................................................................... 1 1.2 研究现状 ............................................................................................................ 2 1.2.1 空间连续性的各向异性 ........................................................................... 2 1.2.2 克里金技术 ............................................................................................... 3 1.2.3 随机模拟 ................................................................................................... 4 1.3 本文的主要贡献与创新 .................................................................................... 6 第二章随机模拟的基本理论 ........................................................................................ 7 2.1 地质统计分析的基本概念 ................................................................................ 7 2.1.1 区域化变量、随机函数、变差函数 ....................................................... 7 2.1.2 平稳条件 ................................................................................................... 7 2.1.3 变差函数的理论模型 ............................................................................... 8 2.2 实验变差函数分析 .......................................................................................... 10 2.2.1 实验变差函数计算 ................................................................................. 10 2.2.2 实验变差函数的拟合 ............................................................................. 12 2.3 变差函数各向异性的建模 .............................................................................. 13 2.3.1 各向异性变差函数 ................................................................................. 14 2.3.2 基台值各向异性 ..................................................................................... 18 2.5 克里金技术 ...................................................................................................... 20 2.5.1 简单克里金 ............................................................................................. 20 2.5.2 普通克里金 ............................................................................................. 21 2.6 高斯随机数的产生 .......................................................................................... 22 2.6.1 累积密度函数求逆法 ............................................................................. 23 2.6.2 变换方法 ................................................................................................. 23 2.6.3 拒绝法 ..................................................................................................... 25 2.6.4 递归方法 ................................................................................................. 26 2.7 本章小结 .......................................................................................................... 27 第三章各向异性序贯高斯模拟 .................................................................................. 29 3.1 各向异性序贯高斯模拟方法 ........................................................................... 29 3.1.1 数据的正态变换与反变换 ..................................................................... 29 IV

资料库

各向异性序贯高斯随机模拟研究.pdf

相关推荐

行业

热门标签

最新资料