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1.
地质统计学发展现状及对若干问题的讨论 总被引：13，自引：0，他引：13
探讨了有关地质统计不发展现状的几个问题：（１）数学地质的发展现状及研究内容；（２）地质统计学的发展现状及研究内容；（３）普通克立克法及泛克立克法的方法及应用；（４）非参数地质统计学的方法及应用；（５）地质统计学方法在储量计算中的应用情况；（６）关于处理特异值的地质统计学方法；（７）关于矿石储量定量分级的地质统计学研究；（８）关于最优勘探网度的地质统计学研究；（９）可回采储量总体的问题。 相似文献
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地质统计学在固体矿产资源／储量分类中的应用 总被引：14，自引：6，他引：14
讨论了地质统计学（空间信息统计学）在固体矿产资源／储量分类中的若干问题，主要包括：1）矿产资源／储量估计方法的选择；2）两个重要概念－估计方差及离差方差；3）支持效应及其在矿产资源／储量评估中的重要作用；4）特异值（特高品位）的识别及处理方法；5）关于吨位－品位曲线；6）确定最优勘探网度及取样间距（及位置）的地质统计学方法；7）地质统计学在确定最优矿床工业指标中的应用；8）储量计算及固体矿产资源／储量分类的地质统计学实施方案。 相似文献
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地质统计学是数学地质领域最为活跃而实用的分支,它是以区域化变量理论为基础,以变异函数为基本工具,研究那些在空间分布上既具有随机性又具有结构性的自然现象的科学。在第四纪研究中的很多特征(变量)均可看成区域化变量进行地质统计学分析。作者在讨论了经典概率论及数理统计方法简单地应用于第四纪研究可能出现的问题后,着重介绍了用于第四纪研究中的若干地质统计学方法及基本理论,同时,对地质统计学方法应用于第四纪研究中的前景进行了分析。 相似文献
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关于《非参数地质统计学》的介绍法国统计学家G.Matheron的地质统计学均要求对母体作出多种假设。例如假定母体服从正态分布,二阶平稳性等等。由此须对分布参数(如均值)展开各种讨论。因而从统计学的分类上,它应属于参数地质统计学。地质现象的复杂性是有目共睹的,自然界中满足它们假设条件的观测对象实在太少了。在这种情况下,虽然采用较复杂的克里金变式以试图使观测数据符合这一理论,但它明显地增加了费用而降低了稳定性,它们的“最优性”充其量也只能是近似的。从统计理论和实用角度两方面看问题,较理想的估计方法应能在给定母体的一组观测时,有一个合理地拟合观测数据的简单模型,它应要求较简单的假设条件,同时模型应具有稳定性,能将特异值的干扰作用,以及有限观测带来的不确定性降低到最小程度。 相似文献
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地质统计学从解决固体矿产资源评价起源，应用领域迅速扩展。文章简要介绍了地质统计学的理论研究现状和应用现状。为了减轻人为因素在创建模型中的作用，非参数的地质统计学得到发展，文章重点介绍了非参数地质统计学的4种变异函数模型。此外，文章阐述了多点地质统计学的概念，这是一种用训练映像代替变异函数的地质统计学方法，使得地质现象的解释更直观。 相似文献
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地质统计学在我国的应用及其发展 总被引：4，自引：0，他引：4
地质统计学是数学地质领域内一个发展迅速且有广阔应用前景的新兴学科. 20多年的生产实践证明,地质统计学具有强大的生命力,它在地质科研、找矿勘探、采矿设计及矿山地质等领域日益显示出优越性,取得了一定的经济效益.地质统计学是以区域化变量理论为基础,以变异函数为主要工具,研究在空间分布上既有随机性又有结构性的自然现象的科学.由于地质统计 相似文献
9.
试论地质现象的分形统计学 总被引：15，自引：0，他引：15
基于近年来非线性科学的发展及其在地质科学中的应用，讨论了地质现象分形统计学的三个基本问题，即初始条件，临界状态和自相似性，并在此基础上阐述了地质现象分形统计学的主要内涵：地质数据的分形结构及其地质学意义，地质时空结构的自相似性及其动力学机制，地质现象的分形重建与矿床分形统计预测方法。 相似文献
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Facies reconstructions are used in hydrogeology to improve the interpretation of aquifer permeability distribution. In the absence of sufficient data to define the heterogeneity due to geological processes, uncertainties in the distribution of aquifer hydrofacies and characteristics may appear. Geometric and geostatistical methods are used to understand and model aquifer hydrofacies distribution, providing models to improve comprehension and development of aquifers. However, these models require some input statistical parameters that can be difficult to infer from the study site. A three-dimensional reconstruction of a kilometer scale fine-grain dominated Cenozoic alluvial fan derived from more than 200 continuously cored, closely spaced, and regularly distributed wells is presented. The facies distributions were reconstructed using a genetic stratigraphic subdivision and a deterministic geostatistical algorithm. The reconstruction is only slightly affected by variations in the geostatistical input parameters because of the high-density data set. Analysis of the reconstruction allowed identification in the proximal to medial alluvial fan zones of several laterally extensive sand bodies with relatively higher permeability; these sand bodies were quantified in terms of volume, mean thickness, maximum area, and maximum equivalent diameter. These quantifications provide trends and geological scenarios for input statistical parameters to model aquifer systems in similar alluvial fan depositional settings. 相似文献
12.
The homogenization of climate data is of major importance because non-climatic factors make data unrepresentative of the actual
climate variation, and thus the conclusions of climatic and hydrological studies are potentially biased. A great deal of effort
has been made in the last two decades to develop procedures to identify and remove non-climatic inhomogeneities. This paper
reviews the characteristics of several widely used procedures and discusses the potential advantages of geostatistical techniques.
In a case study, the geostatistical simulation approach is applied to precipitation data from 66 monitoring stations located
in the southern region of Portugal (1980–2001). The results from this procedure are then compared with those from three well
established statistical tests: the Standard normal homogeneity test (SNHT) for a single break, the Buishand range test, and
the Pettit test. Promising results from the case study open new research perspectives on the homogenization of climate time
series. 相似文献
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Non-stationary models often capture better spatial variation of real world spatial phenomena than stationary ones. However, the construction of such models can be tedious as it requires modeling both statistical trend and stationary stochastic component. Non-stationary models are an important issue in the recent development of multiple-point geostatistical models. This new modeling paradigm, with its reliance on the training image as the source for spatial statistics or patterns, has had considerable practical appeal. However, the role and construction of the training image in the non-stationary case remains a problematic issue from both a modeling and practical point of view. In this paper, we provide an easy to use, computationally efficient methodology for creating non-stationary multiple-point geostatistical models, for both discrete and continuous variables, based on a distance-based modeling and simulation of patterns. In that regard, the paper builds on pattern-based modeling previously published by the authors, whereby a geostatistical realization is created by laying down patterns as puzzle pieces on the simulation grid, such that the simulated patterns are consistent (in terms of a similarity definition) with any previously simulated ones. In this paper we add the spatial coordinate to the pattern similarity calculation, thereby only borrowing patterns locally from the training image instead of globally. The latter would entail a stationary assumption. Two ways of adding the geographical coordinate are presented, (1) based on a functional that decreases gradually away from the location where the pattern is simulated and (2) based on an automatic segmentation of the training image into stationary regions. Using ample two-dimensional and three-dimensional case studies we study the behavior in terms of spatial and ensemble uncertainty of the generated realizations. 相似文献
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The variogram is a critical input to geostatistical studies: (1) it is a tool to investigate and quantify the spatial variability of the phenomenon under study, and (2) most geostatistical estimation or simulation algorithms require an analytical variogram model, which they will reproduce with statistical fluctuations. In the construction of numerical models, the variogram reflects some of our understanding of the geometry and continuity of the variable, and can have a very important impact on predictions from such numerical models. The principles of variogram modeling are developed and illustrated with a number of practical examples. A three-dimensional interpretation of the variogram is necessary to fully describe geologic continuity. Directional continuity must be described simultaneously to be consistent with principles of geological deposition and for a legitimate measure of spatial variability for geostatistical modeling algorithms. Interpretation principles are discussed in detail. Variograms are modeled with particular functions for reasons of mathematical consistency. Used correctly, such variogram models account for the experimental data, geological interpretation, and analogue information. The steps in this essential data integration exercise are described in detail through the introduction of a rigorous methodology. 相似文献
15.
Teacher''s Aide Variogram Interpretation and Modeling 总被引：13，自引：0，他引：13
The variogram is a critical input to geostatistical studies: (1) it is a tool to investigate and quantify the spatial variability of the phenomenon under study, and (2) most geostatistical estimation or simulation algorithms require an analytical variogram model, which they will reproduce with statistical fluctuations. In the construction of numerical models, the variogram reflects some of our understanding of the geometry and continuity of the variable, and can have a very important impact on predictions from such numerical models. The principles of variogram modeling are developed and illustrated with a number of practical examples. A three-dimensional interpretation of the variogram is necessary to fully describe geologic continuity. Directional continuity must be described simultaneously to be consistent with principles of geological deposition and for a legitimate measure of spatial variability for geostatistical modeling algorithms. Interpretation principles are discussed in detail. Variograms are modeled with particular functions for reasons of mathematical consistency. Used correctly, such variogram models account for the experimental data, geological interpretation, and analogue information. The steps in this essential data integration exercise are described in detail through the introduction of a rigorous methodology. 相似文献
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研究区域为洛带气田遂宁组,该储层具有厚度薄、低孔隙度、低渗透层等特征,单一的约束稀疏脉冲反演难以达到精确刻画有利相带。地质统计学反演适用于复杂储层的地震预测和描述,与常规波阻抗反演相比,具有较高的垂向分辨率,能更有效地反映厚度薄的储层,反演结果更接近实际地质特征,能够很好地弥补约束稀疏脉冲反演缺陷,实现对储层特征的精细描述。针对研究区地质特点,根据储层发育特征和地质规律,基于地质统计学理论,采用岩性划分及统计学参数分析等技术方法进行储层预测,有效地预测了洛带气田的砂体厚度、平均孔隙度平面以及储层厚度。 相似文献
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Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design 总被引：4，自引：2，他引：2
Wolfgang Nowak 《Mathematical Geosciences》2010,42(2):199-221
Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess
the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation.
Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further
rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study.
It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical
significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures
are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation
variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty,
with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain
mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework.
Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear
problems are discussed. 相似文献
18.
储层宏观非均质性研究——以吉林油田大208区黑帝庙油层为例 总被引：1，自引：0，他引：1
储层非均质性是影响油气藏中油、气、水渗流及油气采收率的主要内因。进行储层非均质研究,对查明油藏剩余油分布、采取合理注采措施、提高采收率显得十分必要。以吉林油田大208区黑帝庙油层三角洲前缘亚相储层为例,采用隔夹层识别对比、沉积微相分析、地质统计学系数和劳伦兹系数方法分析了层间、层内和平面非均质性。研究表明:黑帝庙油层发育3套稳定隔层,据此可划分为3套开发层系;夹层在各单砂体中比较发育,应将夹层分割的注采井归为不同注采井网;非均质性受沉积微相影响明显,水下分流河道和河口坝微相的非均质性最强;地质统计学参数和劳伦兹系数研究表明,黑帝庙油层10个单砂体均为极强的非均质性,统计学参数往往偏离强非均质标准甚远,而劳伦兹参数值分布于0～1间,更能直观定量的表现出储层宏观非均质性强弱。 相似文献
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为了解黄河三角洲地下水生态环境功能,采用数理统计、地统计和同位素方法及3S技术,对"地下水-陆生植被"系统中关键水盐因子及其植被效应进行了深入研究。结果显示,区域典型植被主要以埋深普遍较浅(1.0～3.0 m)的地下水为水源,说明地下水是生态环境的敏感要素。潜水c(Cl-)与c(TDS)均呈显著的方向性空间变异(沿地下水流向二者浓度递增),且二者具有空间分布一致性(R=0.999),表明Cl-是潜水水质的主控离子。归一化植被指数(INDVI)与潜水c(Cl-)间呈较显著的Logistic关系,揭示潜水c(Cl-)是地下水这一生态环境敏感要素中的关键因子,其对上覆植被强烈的胁迫和驱动作用引发了区域典型的生态环境效应。在黄河三角洲高效生态经济区的开发建设过程中,应特别重视植被与潜水c(Cl-)间极为密切的作用与反作用关系,积极采取有效的人为调控措施。 相似文献
20.
储层非均质性是影响油气藏中油、气、水渗流及油气采收率的主要内因。进行储层非均质研究,对查明油藏剩余油分布、采取合理注采措施、提高采收率显得十分必要。以吉林油田大208区黑帝庙油层三角洲前缘亚相储层为例,采用隔夹层识别对比、沉积微相分析、地质统计学系数和劳伦兹系数方法分析了层间、层内和平面非均质性。研究表明：黑帝庙油层发育3套稳定隔层,据此可划分为3套开发层系; 夹层在各单砂体中比较发育,应将夹层分割的注采井归为不同注采井网; 非均质性受沉积微相影响明显,水下分流河道和河口坝微相的非均质性最强; 地质统计学参数和劳伦兹系数研究表明,黑帝庙油层10个单砂体均为极强的非均质性,统计学参数往往偏离强非均质标准甚远,而劳伦兹参数值分布于0～1间,更能直观定量的表现出储层宏观非均质性强弱。 相似文献