大地电磁与地震资料仿真退火约束联合反演

在对仿真退火算法研究的基础上,将非常快速仿真退火的连续模型空间改为可变的离散化形式,理论模型试算表明,使用本文方法可提高工作效率5-10倍. 为适应联合反演的需要, 对非常快速仿真退火的误差"单判断"检验准则改为误差"双判断"检验准则,避免Metrop olis接受准则的判断失误. 在此基础上,实现了一维及二维起伏地形条件下大地电磁与地震资料多参量信息的联合反演. 理论模型的试算及实例说明了约束联合反演的有效性.     

Modeling of Fluvial Reservoirs with Object Models

An object model for fluvial reservoirs that has been developed from 1985 to present is described. It uses a formal mathematical object model (marked point process) describing the distributions of four facies: channel, crevasse, barrier, and background. Realisations from the model are generated using the Metropolis-Hastings simulation algorithm with simulated annealing conditioning on the volume ratios and well observations. The main challenge has been to find a suitable parameterization of the geology of fluvial reservoirs, and to find and implement the generating function of the channels in the simulation algorithm. The model and simulation algorithm can be conditioned on arbitrary well paths including horizontal wells and paths with partly missing observations, well test data, well contacts, seismic data, and general geological knowledge.     

Two-dimensional non-linear inversion of VLF-R data using simulated annealing

The VLF-R (very low frequency-resistivity) data, i.e. the apparent resistivity ( ρ _a ) and phase ( φ ) data, were inverted individually and jointly using the VFSA (very fast simulated annealing) global inversion approach. Global inversion results for synthetic data without and with various amounts of random and normally distributed Gaussian noise reveal that the inversion of neither the ρ _a nor φ data alone yields the true parameters of the structures. However, the joint inversion of the ρ _a and φ data yields very good estimates of the model parameters. Five models, representing typical subsurface structures in the shield areas, are studied here. Various models achieved after 10 VFSA runs were used to compute the mean model and the corresponding covariance and correlation matrices, which were used to estimate the uncertainties in the mean model parameters and correlations between the model parameters. We observe that these correlations follow the physics associated with the problem. VLF-R field data due to a nearly vertical contact structure and a very thick dyke-like structure were also inverted to demonstrate the efficacy of the approach in the delineation of the parameters of 2-D structures.     

磷灰石裂变径迹分析（AFTA）——一种研究含油气盆地古热构造史的新方法

磷灰石裂变径迹分析近年来广泛地被用来研究含油气盆地古热定史与古构造史及指导油气勘探，这主要是根据磷灰石裂变径迹退火是时间和温度的函数，而烃的生成与热成熟同是也是和温度的函数，而且磷灰石裂变径迹退火温度范围与石油的生成门限相吻合，退火除受温度、时间影响外、还受化学成分，取向因素控制。ＡＦＴＡ包括裂变径迹年龄分析和裂变径迹长度分析，通过前者可获得退火方面信息，通过后者可获得最大古地温及其随时间的变化及     

基于可变模板的航空影像中建筑物提取

针对航空影像中目标提取的困难，提出了一种基于可变模板的航空影像中建筑物提取方法，并针对几种比较典型的建筑物，详细讨论了模板的设计、目标初始参数的获取及模板最优参数求解等几个关键性的问题。采用这种方法进行航空影像中目标的提取时，可以将影像中的多种信息和人的识别能力进行有效的融合，因而能够达到可靠地提取影像中目标的目的。作为一种有效的优化求解方法，模拟退火被用于目标提取的优化过程。为了验证这种方法提取航空影像中目标的能力，给出了利用可变模板提取航空影像中几种不同类型的建筑物的例子     

磷灰石裂变径迹退火动力学模型研究进展综述

裂变径迹退火过程是非线性动力学过程，在一系列磷灰石裂变径迹室内退火实验基础上，研究者提出许多经验退火模型，其中扇型模型与实验数据拟合最好，多组分退火模型将扇型模型的应用扩展到复杂物源成分的磷灰石，理论物理退火模型建立在原子尺度动力机制上，并经由实验数据确定具物理意义的未知参数，目前还不如经验模型成功，室内退火实验表明除了温度、受热时间，退火行为与磷灰石的化学成分，径迹与结晶c轴的方位关系、由Dpar定量表征的颗粒溶蚀度等因素有密切关系。     

基于Markov链模型的储层岩相随机模拟

在油气储层随机建模研究中，基于Markov链模型的方法是一类较受欢迎的技术，同时也是一类不成熟的技术，问题的症结之一在于侧向的转移概率矩阵很难求取，针对这种情况，作者在深入理解Walther相律的基础上，借鉴模拟退火算法的相应思路，提出了一种岩相模拟的新方法，该方法依据不同岩相的百分比进行随机模拟得到一幅初始图象，而后以按岩相组织剖面得到的垂向和侧向的岩相转移概率矩阵的相似性作为判别标准对图象进行扰动，直至得到满意的图象，二维模型试算结果表明了这种岩相随机模拟方法的可行性。     

On Modelling Discrete Geological Structures as Markov Random Fields

The purpose of this paper is to extend the locally based prediction methodology of BayMar to a global one by modelling discrete spatial structures as Markov random fields. BayMar uses one-dimensional Markov-properties for estimating spatial correlation and Bayesian updating for locally integrating prior and additional information. The methodology of this paper introduces a new estimator of the field parameters based on the maximum likelihood technique for one-dimensional Markov chains. This makes the estimator straightforward to calculate also when there is a large amount of missing observations, which often is the case in geological applications. We make simulations (both unconditional and conditional on the observed data) and maximum a posteriori predictions (restorations) of the non-observed data using Markov chain Monte Carlo methods, in the restoration case by employing simulated annealing. The described method gives satisfactory predictions, while more work is needed in order to simulate, since it appears to have a tendency to overestimate strong spatial dependence. It provides an important development compared to the BayMar-methodology by facilitating global predictions and improved use of sparse data.     

模拟退火算法在水驱气藏物质平衡计算中的应用

在利用物质平衡方程计算水驱气藏地质储量时 ,传统的试凑法虽然有一定科学合理性 ,但由于存在很多不确定参数 ,在精确计算中因工作量大 ,很难推广。为此 ,在分析水驱气藏物质平衡方程的基础上 ,建立最优化模型 ,并引入全局寻优性较好的模拟退火方法进行求解。经实际计算表明 ,方法具有全局收敛性 ,计算结果有较高可信度。     

极大熵准则在降雨强度-历时-频率模型参数估计中的应用

根据频率与重现期的关系推导出三类常用降雨强度-历时-频率模型的无条件及条件概率分布(概率密度)函数及与模型相对应的约束。极大熵与极大似然准则产生一致估计,本文尝试基于极大熵准则建立降雨强度-历时-频率模型参数估计的优化模型,应用模拟退火算法求解该优化模型。根据比较发现,极大熵估计有时比常用的极大似然估计和最小二乘估计更精确。