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地应力对裂隙岩体渗透特性的影响 总被引：9，自引：0，他引：9
提出了地应力场中岩体不连续面变形的本构关系，讨论了渗流与应力耦合条件下裂隙岩体渗透张量的计算方法，阐述了地应力对裂隙岩体渗透特性的影响．研究表明，地应力对岩体渗透特性的影响主要是通过改变不连续面的开度和不连续面网络的水力传导路径而产生的；裂隙岩体渗透性随岩体埋深的增加呈负指数减小，随侧压系数的增大呈双曲线减小．渗流场与应力场的耦合理论可望应用于水库诱发地震的研究中 相似文献
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韩家岩体与天井山金矿空间上密切相关.对韩家岩体的成因存在不同看法：依据“斑状”外貌,有人主张是燕山期花岗斑岩;依据隐约可见的片麻状构造,有人认为是晋宁期灵山岩体.鉴于其具有重要的找矿指示意义,本文通过岩石学、岩石地球化学、同位素年代学等方面的研究,认为韩家岩体是由灵山岩体蚀变而成的绢英岩.天井山金矿中的金多以自然金形式产于石英大脉的晚期裂隙中,并与石英-绢云母-含铁碳酸盐-硫化物细脉共生.研究表明,这些裂隙与绢英岩体顶部的石英网脉带贯通,两者具有相同蚀变矿物组合和流体来源.据此,本文认为与绢英岩化有关的岩浆-构造-蚀变作用是天井山金矿的核心成矿事件.由于韩家绢英岩体具有区域尺度的找矿标志,这对天井山矿区及其外围进一步找矿具有重要的指导意义. 相似文献
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针对目前高坝坝址地震动参数确定方法的一些不足,本文尝试了一种基于地震学理论的坝址区三维地震动场生成方法.基本思路是将地震学和工程学结合,针对设定地震,建立震源-传播介质-坝址峡谷场地数值模型,通过超大规模的数值计算,模拟地震波从发震断层破裂开始到坝址场地的物理传播过程,生成坝址区的三维地震动参数.与传统基于衰减关系的地震动参数确定方法相比,这一方法可以考虑震源机制、传播介质和坝址峡谷场地效应等三大要素的影响.对于特定的坝址,可以生成符合实际地质构造、区域岩体动力特性以及坝址峡谷地质地形条件的地震动荷载分布,具有针对性,为重大高坝枢纽工程遭遇极端地震荷载作用时的抗震安全性提供了一种新的分析手段. 相似文献
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裂隙储层具有强烈的非均质性及储层渗透性预测难度大的特点,利用逾渗理论来研究裂隙储层深层复杂介质渗透性,是当前研究的热点问题.基于连续逾渗,将裂隙网络模型合理简化.使用排除体积对裂隙密度进行无量纲化,从而使裂隙的渗透性与裂隙的形状无关.首先使用Monte Carlo方法得到裂隙在不同密度时的网络图,而后使用ComsolMultiphysics中的有限元求解器得到流体在裂隙中的速度和压力分布图,数值模拟表明:随着裂隙密度的增加,裂隙的连通性增加,进而流体在裂隙中的渗透性也增加;最后使用有限尺度转换定律和尺度放大思想,通过重复子区域的方法求解每个小区域的渗透性,得到裂隙储层在不同尺度下的渗透性,分析得到储层平均渗透性和无量纲化裂隙密度之间的关系.模拟得到的渗透率值和FRACA软件得到渗透率泊松相关系数为0.885.该规则的发现为逾渗理论从小尺度放大到宏观物理模型即储层尺度提供了一个理论依据. 相似文献
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增强型地热系统(Enhanced Geothermal System,简称EGS)作为深层地热资源开采最有效方法已成为国际研究热点.其中多场耦合是EGS研究中的关键部分,但目前对最基础和最重要的热流耦合研究仍不充分,特别是对热流耦合下热传导过程和采热效率的研究还不透彻.本文构建了针对EGS单裂隙热流耦合的数学模型,模型主要控制热流耦合时水岩温度场的演化,以展现热流耦合下的热传导过程,并以此计算了裂隙宽度和裂隙水流速率对水岩温度场的影响,分析了裂隙特征对采热效率的影响.计算表明,在特定的开采条件下,都有相应的岩体温度场影响半径;热量从高温岩体传至裂隙流体的过程显示为进水口为低温区,以水流方向为轴,向两侧岩体对称展开的三角形热传导模式;裂隙宽度和裂隙流体速度对裂隙两侧的岩体温度场和采热半径产生明显影响,但裂隙长度总体上对采热率表现为正效应,而裂隙宽度和裂隙流体速度在一定范围内对采热率表现为负效应;裂隙宽度与裂隙流体速度对水岩温度场具有完全一致的影响效果.模型的对比验证确认了本模型的合理性和优越性.文中最大的创新点和亮点是首次推导给出了EGS热流耦合水岩温度场演化特征的简明数学表达式,另一亮点是基于岩体热传导系数来考虑耦合过程的热传导量. 相似文献
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采用声波测井、地震CT等综合物探方法,对沙坡头水利枢纽坝址基础岩体固结灌浆效果进行检测,基本查明了坝基岩体固结灌浆后的质量状况,取得了良好的应用效果. 相似文献
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冰架崩解是南极洲物质损耗的主要途径,崩解是应力作用引起的裂隙(或裂缝)传播的结果,裂隙位置和深度的探测是理解崩解机理过程的重要基础.本文提出了一种利用卫星激光测高ICESat-1/GLAS高程数据产品提取冰架表面冰裂隙的方法,并以南极洲埃默里冰架为例验证了这种方法探测裂隙位置的准确性和深度探测精度.同时,基于提取的裂隙点深度分布特征提出了裂隙峰值应力点的探测方法,可用于追踪冰裂隙初始裂口位置和探测导致冰架崩解的高危区.利用2003～2008年间16个运行时期内132条ICESat-1/GLAS高程轨迹线分析了埃默里冰架冰裂隙深度的时空分布和裂隙峰值应力点的空间分布.结果显示,探测到的裂隙点深度在2.0～31.7 m均在海平面以上;裂隙深度变化未显示出随时间推移和冰流移动而增加的趋势,说明平流移动到冰架前缘的裂隙基本不会直接导致冰架的崩解;冰架局部应力集中区主要分布在冰流的缝合区内. 相似文献
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Copula-based geostatistical modeling of continuous and discrete data including covariates 总被引：4，自引：3，他引：1
Hannes Kazianka Jürgen Pilz 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(5):661-673
It is common in geostatistics to use the variogram to describe the spatial dependence structure and to use kriging as the spatial prediction methodology. Both methods are sensitive to outlying observations and are strongly influenced by the marginal distribution of the underlying random field. Hence, they lead to unreliable results when applied to extreme value or multimodal data. As an alternative to traditional spatial modeling and interpolation we consider the use of copula functions. This paper extends existing copula-based geostatistical models. We show how location dependent covariates e.g. a spatial trend can be accounted for in spatial copula models. Furthermore, we introduce geostatistical copula-based models that are able to deal with random fields having discrete marginal distributions. We propose three different copula-based spatial interpolation methods. By exploiting the relationship between bivariate copulas and indicator covariances, we present indicator kriging and disjunctive kriging. As a second method we present simple kriging of the rank-transformed data. The third method is a plug-in prediction and generalizes the frequently applied trans-Gaussian kriging. Finally, we report on the results obtained for the so-called Helicopter data set which contains extreme radioactivity measurements. 相似文献
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Steve W. Lyon Arthur J. Lembo Jr. M. Todd Walter Tammo S. Steenhuis 《Advances in water resources》2006
In humid, well-vegetated areas, such as in the northeastern US, runoff is most commonly generated from relatively small portions of the landscape becoming completely saturated, however, little is known about the spatial and temporal behavior of these saturated regions. Indicator kriging provides a way to use traditional water table data to quantify probability of saturation to evaluate predicted spatial distributions of runoff generation risk, especially for the new generation of water quality models incorporating saturation excess runoff theory. When spatial measurements of a variable are transformed to binary indicators (i.e., 1 if above a given threshold value and 0 if below) and the resulting indicator semivariogram is modeled, indicator kriging produces the probability of the measured variable to exceed the threshold value. Indicator kriging gives quantified probability of saturation or, consistent with saturation excess runoff theory, runoff generation risk with depth to water table as the variable and the threshold set near the soil surface. The probability of saturation for a 120 m × 180 m hillslope based upon 43 measurements of depth to water table is investigated with indicator semivariograms for six storm events. The indicator semivariograms show high spatial structure in saturated regions with large antecedent rainfall conditions. The temporal structure of the data is used to generate interpolated (soft) data to supplement measured (hard) data. This improved the spatial structure of the indicator semivariograms for lower antecedent rainfall conditions. Probability of saturation was evaluated through indicator kriging incorporating soft data showing, based on this preliminary study, highly connected regions of saturation as expected for the wet season (April through May) in the Catskill Mountain region of New York State. Supplementation of hard data with soft data incorporates physical hydrology of the hillslope to capture significant patterns not available when using hard data alone for indicator kriging. With the need for water quality models incorporating appropriate runoff generation risk estimates on the rise, this manner of data will lay the groundwork for future model evaluation and development. 相似文献
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Geostatistical methods are well suited for analyzing the local and spatial uncertainties that accompany the modeling of highly heterogeneous three-dimensional (3D) geological architectures. The spatial modeling of 3D hydrogeological architectures is crucial for polluted site characterization, in regards to both groundwater modeling and planning remediation procedures. From this perspective, the polluted site of Porto Marghera, located on the periphery of the Venice lagoon, represents an interesting example. For this site, the available dense spatial sampling network, with 769 boreholes over an area of 6 km2, allows us to evaluate the high geological heterogeneity by means of indicator kriging and sequential indicator simulation. We show that geostatistical methodologies and ad hoc post processing of geostatistical analysis results allow us to effectively analyze the high hydrogeological heterogeneity of the studied site. 相似文献
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Compositional Bayesian indicator estimation 总被引：1，自引：1，他引：0
Carolina Guardiola-Albert Eulogio Pardo-Ig��zquiza 《Stochastic Environmental Research and Risk Assessment (SERRA)》2011,25(6):835-849
Indicator kriging is widely used for mapping spatial binary variables and for estimating the global and local spatial distributions
of variables in geosciences. For continuous random variables, indicator kriging gives an estimate of the cumulative distribution
function, for a given threshold, which is then the estimate of a probability. Like any other kriging procedure, indicator
kriging provides an estimation variance that, although not often used in applications, should be taken into account as it
assesses the uncertainty of the estimate. An alternative approach to indicator estimation is proposed in this paper. In this
alternative approach the complete probability density function of the indicator estimate is evaluated. The procedure is described
in a Bayesian framework, using a multivariate Gaussian likelihood and an a priori distribution which are both combined according
to Bayes theorem in order to obtain a posterior distribution for the indicator estimate. From this posterior distribution,
point estimates, interval estimates and uncertainty measures can be obtained. Among the point estimates, the median of the
posterior distribution is the maximum entropy estimate because there is a fifty-fifty chance of the unknown value of the estimate
being larger or smaller than the median; that is, there is maximum uncertainty in the choice between two alternatives. Thus
in some sense, the latter is an indicator estimator, alternative to the kriging estimator, that includes its own uncertainty.
On the other hand, the mode of the posterior distribution estimator, assuming a uniform prior, is coincidental with the simple
kriging estimator. Additionally, because the indicator estimate can be considered as a two-part composition which domain of
definition is the simplex, the method is extended to compositional Bayesian indicator estimation. Bayesian indicator estimation
and compositional Bayesian indicator estimation are illustrated with an environmental case study in which the probability
of the content of a geochemical element in soil being over a particular threshold is of interest. The computer codes and its
user guides are public domain and freely available. 相似文献
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The response of two arch dams to spatially varying ground motions recorded during earthquakes is computed by a recently developed linear analysis procedure, which includes dam–water–foundation rock interaction effects and recognizes the semi‐unbounded extent of the rock and impounded water domains. By comparing the computed and recorded responses, several issues that arise in analysis of arch dams are investigated. It is also demonstrated that spatial variations in ground motion, typically ignored in engineering practice, can have profound influence on the earthquake‐induced stresses in the dam. This influence obviously depends on the degree to which ground motion varies spatially along the dam–rock interface. Thus, for the same dam, this influence could differ from one earthquake to the next, depending on the epicenter location and the focal depth of the earthquake relative to the dam site. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
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A typical fractured rock mass is intersected by several sets of discontinuities, which provide the main flowpath for ground water. Due to the limitations of data obtained by conventional field measurements, it is often difficult to estimate the anisotropic permeability tensor associated with the joints existing in the rock mass. For that reason, determining permeability tensors for fractured rocks is an important topic in rock mass hydraulics. Based on field surveys, joint parameters can be analyzed by using probabilistic and statistical tools, and three-dimensional mapping of the jointed rock mass. Through analysis of a single joint's hydraulic characteristics, the principal value of the permeability tensor for the jointed rock mass can be determined by using Monte Carlo methods and the searching percolation trace method, which is developed in this paper. The study reports on practical examples demonstrating that results from the methods discussed in this paper are in agreement with those from field hydrogeological surveys and measurements. 相似文献
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P. Bogaert 《Stochastic Environmental Research and Risk Assessment (SERRA)》2002,16(6):425-448
Being a non-linear method based on a rigorous formalism and an efficient processing of various information sources, the Bayesian
maximum entropy (BME) approach has proven to be a very powerful method in the context of continuous spatial random fields,
providing much more satisfactory estimates than those obtained from traditional linear geostatistics (i.e., the various kriging
techniques). This paper aims at presenting an extension of the BME formalism in the context of categorical spatial random
fields. In the first part of the paper, the indicator kriging and cokriging methods are briefly presented and discussed. A
special emphasis is put on their inherent limitations, both from the theoretical and practical point of view. The second part
aims at presenting the theoretical developments of the BME approach for the case of categorical variables. The three-stage
procedure is explained and the formulations for obtaining prior joint distributions and computing posterior conditional distributions
are given for various typical cases. The last part of the paper consists in a simulation study for assessing the performance
of BME over the traditional indicator (co)kriging techniques. The results of these simulations highlight the theoretical limitations
of the indicator approach (negative probability estimates, probability distributions that do not sum up to one, etc.) as well
as the much better performance of the BME approach. Estimates are very close to the theoretical conditional probabilities,
that can be computed according to the stated simulation hypotheses. 相似文献
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V. Demyanov S. Soltani M. Kanevski S. Canu M. Maignan E. Savelieva V. Timonin V. Pisarenko 《Stochastic Environmental Research and Risk Assessment (SERRA)》2001,15(1):18-32
This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical
prediction (kriging) is proposed. The method – wavelet analysis residual kriging (WARK) – is developed in order to assess
the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have
very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals
focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present
work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network
residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear
trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing
global statistical characteristics of the distribution and spatial correlation structure. 相似文献