Complementary Entropy and Wavelet Analysis of Drilling-Ability Data

The paper combines wavelet and entropy analysis of nonstationary drilling-ability data in order to obtain optimum information on the mechanical behavior of different geological formations. Both methods are multiscale in nature, and while entropy analysis provides information on stationary subdomains, wavelet analysis identifies dominant scales or range of scales at which the entropy analysis is most useful. The combination of the techniques yields relatively simple results that can aid the drilling process by providing information on delays to be expected.     

基于时延三维电阻率反演的岩溶地下河管道空间分布识别物理模拟研究

岩溶地下河管道空间分布的识别对岩溶区的各类地球科学工作意义重大,文章阐述了采用时延三维电阻率反演技术,开展对地下河管道空间分布识别的研究,在室内灰岩介质下的物理模拟实验结果表明:对雨季管道充水和枯季管道干涸时采集的电阻率数据进行时延反演后,地下河管道的模拟三维空间分布被很好地突显出来,时延反演效果大大地优于对单次采集数据的反演效果,管道充填水时的反演效果次之,管道充填空气时的反演结果很难有效识别地下河管道的空间分布情况。物理模型试验成果可指导野外实践中对岩溶地下河管道的探测研究。      

基于数据融合的边坡临滑状态确定方法

安全监测及数值模拟是评估边坡稳定性状态的两种重要手段,但是,如何根据监测信息及数值模拟成果确定边坡的临界失稳状态一直是边坡工程领域关注的重点问题。首先基于层次聚类方法计算边坡不同类型状态变量监测点的欧式距离,根据距离大小筛选出边坡的有效监测点;然后,计算同种类型状态变量有效监测点的熵权值,采用熵权融合方法对有效监测点进行数据层融合,得到不同类型状态变量对应的融合监测指标曲线;其次,采用主成分分析法对多种数据层融合监测指标曲线进行特征层融合,得到可反映全部状态变量信息特征的综合监测信息曲线,进而构建了边坡渐进失稳过程中不同监测变量的信息挖掘融合框架;最后,提出了一种缓变曲线的变点搜索方法,采用该方法对综合监测信息曲线开展变点分析,搜索边坡状态渐进演化的突变点（即边坡临滑状态点）。将所提出的方法应用到某公路边坡临界失稳状态的确定中,结果表明,单个监测点或单个融合指标的累积值、变化速率作为边坡失稳判据存在不唯一性,融合多种监测数据建立的综合监测信息序列可以较好地反映边坡状态演化特征,可避免单一状态变量的单一监测点数据对边坡状态的误判,验证了所提方法的可行性和适用性。     

中国降水混沌识别及空间聚类

0-1混沌测试方法是一种新的可直接作用于时间序列的混沌识别方法,不需要进行相空间重构,通过对Chebyshev映射的检验验证了有效性。运用0-1方法对中国640个气象站1960-2011年月降水序列进行混沌识别,并运用基于密度的顾及非空间属性的空间聚类方法（DBSC）对计算结果进行空间聚类。结果表明,各气象站月降水序列均表现出明显的混沌特性,且K值的空间分布具有明显的分区特征：从大尺度上看,全国可分为西北高值区、南方次高区、华北-东北中值区和青藏低值区;从小尺度上看,全国分出了29个空间簇。中国降水混沌空间聚类结果不仅与大尺度的气候类型分布相吻合,而且也反映了局部降水动力系统变化特征,这就为降水系统的时空规律研究提供了一条新的途径和方法。     

基于Burgers模型考虑损伤的非定常岩石蠕变模型

Burgers模型只能描述岩石蠕变的前两个阶段,为了描述蠕变全过程,考虑蠕变参数的时间效应及损伤带来的影响,采用非定常黏性元件取代Burgers模型中串联的定常黏性元件,使其能描述加速蠕变阶段。根据损伤变量的变化特征,假定了一个函数,经过Lemaitre应变等效原理,代入Kelvin模型可得到能描述蠕变衰减阶段的模型。试验数据拟合结果显示,改进的Burgers模型能很好地描述加速蠕变阶段,模型拟合曲线与试验曲线基本吻合,相关系数高,参数取值也在合理范围内;非定常Burgers模型更适合描述不同应力下的岩石蠕变特征曲线。     

Multiple-Point Simulation with an Existing Reservoir Model as Training Image

The multiple-point simulation (MPS) method has been increasingly used to describe the complex geologic features of petroleum reservoirs. The MPS method is based on multiple-point statistics from training images that represent geologic patterns of the reservoir heterogeneity. The traditional MPS algorithm, however, requires the training images to be stationary in space, although the spatial distribution of geologic patterns/features is usually nonstationary. Building geologically realistic but statistically stationary training images is somehow contradictory for reservoir modelers. In recent research on MPS, the concept of a training image has been widely extended. The MPS approach is no longer restricted by the size or the stationarity of training images; a training image can be a small geometrical element or a full-field reservoir model. In this paper, the different types of training images and their corresponding MPS algorithms are first reviewed. Then focus is placed on a case where a reservoir model exists, but needs to be conditioned to well data. The existing model can be built by process-based, object-based, or any other type of reservoir modeling approach. In general, the geologic patterns in a reservoir model are constrained by depositional environment, seismic data, or other trend maps. Thus, they are nonstationary, in the sense that they are location dependent. A new MPS algorithm is proposed that can use any existing model as training image and condition it to well data. In particular, this algorithm is a practical solution for conditioning geologic-process-based reservoir models to well data.     

河流功率梯度在泥石流空间易发程度调查中的应用:以金沙江流域为例

泥石流空间易发程度调查是开展地质灾害防范和制定生态修复计划的基础之一。目前单纯依靠野外调查并结合遥感观测,或以小流域为单元的泥石流模拟,均难以在大空间范围内高效、准确地识别潜在泥石流沟。鉴于泥石流是一种高能重力流,此次研究以金沙江流域为例,在假定物源供给无差异条件下,提出通过求算河流功率梯度（ω）来实现地表外动力活动强度定量刻画和泥石流空间易发程度调查的新方案,并将泥石流沟验证点数与ω值关系曲线的比降趋势突变位置作为阈值（1×10?4 W/m2）,提取出大约3.2万条长度超过200 m的高能河谷或泥石流易发沟谷。这些沟谷基本位于金沙江和雅砻江干流中下游,在大约30 km距离的缓冲区范围内密集分布,其数量与缓冲区宽度存在乘幂函数关系。在全球变暖背景下,未来发生极端气象事件可能性趋于增加,这些地带,尤其是梯级库区河段应做为泥石流灾害的重点防范区。研究的最终结果提供了金沙江流域泥石流易发沟谷的空间位置及ω值的点阵数据集,可供检索高能河谷的准确位置,也可作为相关地质灾害与地表过程研究的基础数据和资料。      

地电场对青藏高原东北部季节冻土的响应特性

地电场的变化与台址环境的水文、气象及地质背景等相关,在青藏高原东北部季节冻土区,11个地电场台站处于较高的海拔,据台址下覆场地属性分为A类（黄土型）和B类（高原草场型）台站。通过对青藏高原季节冻土区域的地电场和大地电流场的计算和分析,联系区域构造活动和地质环境得出以下认识：青藏高原东北部季节冻土区地电场变化对水热环境响应明显,冬、夏两季测值可能发生跃变;长周期的地电场变化曲线可能与台址附近气温变化相关;台站大地电流矢量在冻土部分冻融交替过程中发生方向和幅度值的改变。A类和B类台址显示出不同的季节变化规律,地电场曲线上升和下降的时间节点各异,这种现象可应用于监测该区域冻土冻融情况和冻土的时空演变。     

黄河干流兰州站与花园口站年径流序列协整分析研究

协整理论是经济计量学中处理非平稳经济时间序列常用的一种理论，具有模型可靠的优点。将其引入河川径流序列分析中，以黄河为例，通过单位根检验，获得平稳的河川径流序列，在此基础上，建立了误差修正模型，用于描述流域上下游径流间的协整关系。     

Multivariate Correlation in the Framework of Support and Spatial Scales of Variability

This paper extends the concept of dispersion variance to the multivariate case where the change of support affects dispersion covariances and the matrix of correlation between attributes. This leads to a concept of correlation between attributes as a function of sample supports and size of the physical domain. Decomposition of dispersion covariances into the spatial scales of variability provides a tool for computing the contribution to variability from different spatial components. Coregionalized dispersion covariances and elementary dispersion variances are defined for each multivariate spatial scale of variability. This allows the computation of dispersion covariances and correlation between attributes without integrating the cross-variograms. A correlation matrix, for a second-order stationary field with point support and infinite domain, converges toward constant correlation coefficients. The regionalized correlation coefficients for each spatial scale of variability, and the cases where the intrinsic correlation hypothesis holds are found independent of support and size of domain. This approach opens possibilities for multivariate geostatistics with data taken at different support. Two numerical examples from soil textural data demonstrate the change of correlation matrix with the size of the domain. In general, correlation between attributes is extended from the classic Pearson correlation coefficient based on independent samples to a most general approach for dependent samples taken with different support in a limited domain.     

冻融循环作用下土体冻结锋面移动规律试验研究

冻融循环作用改变了土体结构及热物理性质,进而影响了土体温度变化过程,土体冻结锋面的稳定位置也随之变化。为研究冻融循环作用下土体冻结锋面的移动规律,进行了开放系统下的兰州黄土冻融循环试验。试验结果表明：冻结初期冻结锋面迅速下移,冷端温度稳定后其下移速度降低,当土体温度达到平衡时,冻结锋面位置趋于稳定;冻结锋面稳定深度随冻融循环次数的增加而增加.为阐述黄土冻结锋面随着时间变化规律,采用时间比拟法得到了冻融循环次数与冻融时间相似比拟曲线。由拟合曲线得第6次冻融循环后土体冻结锋面稳定在土样高度24.4mm处,实测稳定在24.3mm处,相对误差为0.4%。     

0-1测试方法的径流时间序列混沌特性应用

径流时间序列混沌特性识别的常用方法是基于相空间重构的关联维数法、最大Lyapunov指数法和Kolmogorov熵法。引入一种新的时间序列混沌特性识别方法:0-1混沌测试方法。该方法直接应用于时间序列不需要相空间重构,并且通过量化指标K_c是否接近于0或1来识别时间序列的混沌特性。以Logistic映射生成的序列、金沙江流域和美国Umpqua河多年日径流序列为研究对象,首先利用0-1混沌测试方法进行了混沌特性识别和判定;然后基于相空间重构,运用相空间重构、伪最近邻点法、关联维数方法、最大Lyapunov指数法和Kolmogorov熵5种非线性研究方法分析了这两列径流时间序列混沌特性。研究结果表明0-1混沌测试方法简单有效。以上方法交互验证了该两列径流时间序列存在低维混沌特性。     

基于样本熵理论的自适应小波消噪分析方法

小波消噪方法的核心问题是阈值的选择及确定.依据样本熵的特性,将样本熵与小波分析方法耦合起来,提出了一种自适应确定阈值的小波消噪分析方法.该方法计算了不同阈值对应噪声序列的样本熵值,得到阈值与样本熵值之间的关系曲线,当样本熵值达到最大时,此时阈值为所求阈值.通过算例加以验证分析,结果表明,自适应小波消噪分析方法能较好地实现水文序列的信噪分离,其消噪结果符合序列本身的特性及评价指标的要求,这为合理确定阈值提供了一种新的途径和方法.     

Simulation of mineral grades with hard and soft conditioning data: application to a porphyry copper deposit

This work deals with the geostatistical simulation of mineral grades whose distribution exhibits spatial trends within the ore deposit. It is suggested that these trends can be reproduced by using a stationary random field model and by conditioning the realizations to data that incorporate the available information on the local grade distribution. These can be hard data (e.g., assays on samples) or soft data (e.g., rock-type information) that account for expert geological knowledge and supply the lack of hard data in scarcely sampled areas. Two algorithms are proposed, depending on the kind of soft data under consideration: interval constraints or local moment constraints. An application to a porphyry copper deposit is presented, in which it is shown that the incorporation of soft conditioning data associated with the prevailing rock type improves the modeling of the uncertainty in the actual copper grades.     

Conditioning Simulations of Gaussian Random Fields by Ordinary Kriging

Conditioning realizations of stationary Gaussian random fields to a set of data is traditionally based on simple kriging. In practice, this approach may be demanding as it does not account for the uncertainty in the spatial average of the random field. In this paper, an alternative model is presented, in which the Gaussian field is decomposed into a random mean, constant over space but variable over the realizations, and an independent residual. It is shown that, when the prior variance of the random mean is infinitely large (reflecting prior ignorance on the actual spatial average), the realizations of the Gaussian random field are made conditional by substituting ordinary kriging for simple kriging. The proposed approach can be extended to models with random drifts that are polynomials in the spatial coordinates, by using universal or intrinsic kriging for conditioning the realizations, and also to multivariate situations by using cokriging instead of kriging.     

基于计算机模拟的植物返青期遥感监测方法比较研究

植物返青期变化与气象和气候因素密切相关,已成为研究全球变化对陆地生态系统影响和反馈机理的一个重要参数。利用遥感手段及时准确地监测区域及全球尺度植物返青期变化,是当前地学、生态学研究的一个前沿课题。但是目前国内外对植物返青期遥感监测方法缺乏有效比较,还没有形成统一认识。因此,在综述植物返青期传统测量方法和遥感监测方法最新研究进展的基础上,利用计算机模拟手段,对目前常用的4种遥感监测方法（滑动平均方法、NDVI比率阈值方法、最大变化斜率方法及Logistic函数拟合方法）进行了比较研究。模拟结果表明：4种方法的返青期计算值最大相差20天,突出反映了它们在构建原理方面的差别,即滑动平均方法将NDVI突增点对应的时期作为植物返青期;NDVI比率阈值方法将最大上升斜率点对应的时期作为植物返青期;最大变化斜率方法将NDVI数据斜率角变化最大的点对应的时期作为植物返青期;Logistic函数拟合方法则将拟合曲线上曲率变化最大的点对应的时期作为植物返青期;同时,4种方法所得返青期均满足一个共同的特点,即返青期之后NDVI曲线应保持最大持续增长。该研究也表明计算机模拟技术在帮助认识和理解植物返青期遥感监测方法中的巨大潜力。     

不排水抗剪强度非平稳随机场模拟及边坡可靠度分析

边坡可靠度分析中通常假定采用平稳或准平稳随机场表征土体参数的空间变异性,然而大量现场试验数据表明,土体参数如不排水抗剪强度沿土体埋深常呈现明显的非平稳分布特征,即其均值和标准差均随埋深发生变化,因此亟需发展土体参数非平稳随机场模型及其模拟方法。针对目前不能有效单独模拟土体参数趋势分量和随机波动分量的不确定性,提出了一种有效的不排水抗剪强度参数非平稳随机场模型,并给出了土体参数二维非平稳随机场模拟方法计算流程,同时将新提出的模型与现有非平稳随机场模型及平稳随机场模型进行了系统比较。最后通过不排水饱和黏土边坡算例验证了提出模型的有效性,并揭示了不排水抗剪强度非平稳分布特征对边坡可靠度的影响规律。结果表明：提出模型能够有效地单独模拟土体参数趋势分量和随机波动分量的不确定性,考虑土体参数均值和标准差随埋深增加而增大的特性,可为表征土体参数非平稳分布特征提供了一条有效的途径。此外,与采用非平稳随机场模拟土体参数空间变异性相比,采用常用的平稳随机场模型会低估边坡失效概率,从而造成偏危险的边坡工程设计方案。     

初论地质信息有序系列

信息有序系列（ＩＯＳ）是笔者提出的一个新概念，是指具有非随机性定义的信息、非周期性、存在于大量无序中的有序部分特征的有序性。ＩＯＳ的理论是应用基于较少假设的、较为简单的数字或几何模式去研究地质体客观存在的复杂性，减少类似概率分布、周期性、平稳性、遍历理论等假设要求。ＩＯＳ中的一组现象，表面上看类似于周期，但被广义地定义，它们不能被谱分析和统计分析发现。“系列”一词用以与“模型”相区别，其特点是仅在有限范围和短时间内存在，是不平稳和遍历的。“有序”一词是强调在混沌中存在的有序部分，可应用于预测目的。所以，ＩＯＳ是有序性中一部分。大地震、热点、超大型矿床、节理等时空分布表明了ＩＯＳ的客观存在。     

Direct Pattern-Based Simulation of Non-stationary Geostatistical Models

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.     

Some Results on the Spatial Breakdown Point of Robust Point Estimates of the Variogram

The effect of outliers on estimates of the variogram depends on how they are distributed in space. The ‘spatial breakdown point’ is the largest proportion of observations which can be drawn from some arbitrary contaminating process without destroying a robust variogram estimator, when they are arranged in the most damaging spatial pattern. A numerical method is presented to find the spatial breakdown point for any sample array in two dimensions or more. It is shown by means of some examples that such a numerical approach is needed to determine the spatial breakdown point for two or more dimensions, even on a regular square sample grid, since previous conjectures about the spatial breakdown point in two dimensions do not hold. The ‘average spatial breakdown point’ has been used as a basis for practical guidelines on the intensity of contaminating processes that can be tolerated by robust variogram estimators. It is the largest proportion of contaminating observations in a data set such that the breakdown point of the variance estimator used to obtain point estimates of the variogram is not exceeded by the expected proportion of contaminated pairs of observations over any lag. In this paper the behaviour of the average spatial breakdown point is investigated for cases where the contaminating process is spatially dependent. It is shown that in two dimensions the average spatial breakdown point is 0.25. Finally, the ‘empirical spatial breakdown point’, a tool for the exploratory analysis of spatial data thought to contain outliers, is introduced and demonstrated using data on metal content in the soils of Sheffield, England. The empirical spatial breakdown point of a particular data set can be used to indicate whether the distribution of possible contaminants is likely to undermine a robust variogram estimator.