Sampling procedure for small-scale heterogeneities (crossbedding) for reservoir modelling

Sampling permeability from individual laminae in crossbedded rocks is very well possible by making use of a so-called probe permeameter. The methodology and calculation of permeabilities from the output of this instrument are fairly well-established. However, what is hardly established is a sampling strategy that guarantees adequate representation of permeability contrast between laminae. Especially so, because finer foreset and bottomset are difficult to sample, yet their permeabilities are critical to fluid flow through a crossbed. Therefore we propose to systematically sample laminae. To this end we suggest a sampling strategy that is adapted to the heterogeneity under study, namely to the thickness of the finer foreset.     

GVG采样线代表性检验

通过在实验区内设置不同类型的采样线,对GVG采样线的代表性进行检验.结果表明,高速公路和乡村道路类型的采样线对区域代表性的精度在95%以上;国道为86.726%;省道为65.447%.对于不同的缓冲区,高速公路、省道和乡村道路类型采样线,以200m缓冲区的代表性最好.而国道则以800m缓冲区的代表性最好.对于不同的作物而言,无论何种类型的采样线或者缓冲区,种植面积最大的棉花的精度是最好的.最低的是省道采样线1000m缓冲区,精度是78.146%,最好的是国道采样线800m缓冲区,精度是99.974%.除省道外,其他精度都在94.8%以上.这说明GVG采样线所获得的成数对于区域主要作物的代表性是很好的.     

Hierarchical decomposition of variance with applications in environmental mapping based on satellite images

A quadtree-based image segmentation procedure (HQ) is presented to map complex environmental conditions. It applies a hierarchical nested analysis of variance within the framework of multiresolution wavelet approximation. The procedure leads to an optimal solution for determining mapping units based on spatial variability with constraints on the arrangement and shape of the units. Linkages to geostatisiics are pointed out, but the HQ decomposition algorithm does not require any homogeneity criteria. The computer implementation can be parameterized by either the number of required mapping units or the maximum within-unit variance, or it can provide a spectrum of significances of nested ANOVA. The detailed mathematical background and methodology is illustrated by a salt-affected grassland mapping study (Hortobágy, Hungary), where heterogeneous environmental characteristics have been sampled and predicted based on remotely sensed images using these principles.     

Improved reliability in the interpretation of geochemical measurements by the quantification of uncertainty from sampling

All geochemical measurements require the taking of field samples, but the uncertainty that this process causes is often ignored when assessing the reliability of the interpretation, of the geochemistry or the health implications. Recently devised methods for the estimation, optimisation and reduction of this uncertainty have been evaluated by their application to the investigation of contaminated land. Uncertainty of measurement caused by primary sampling has been estimated for a range of six different contaminated land site investigations, using an increasingly recognized procedure. These site investigations were selected to reflect a wide range of different sizes, contaminants （organic and metals）, previous land uses （e.g. tin mining, railway sidings and gas works）, intended future use （housing to nature reserves） and routinely applied sampling methods. The results showed that the uncertainty on measurements was substantial, ranging from 25% to 186% of the concentration values at the different sites. Sampling was identified as the dominant source of the uncertainty （〉70% of measurement uncertainty） in most cases. The fitness-for-purpose of the measurements was judged using the optimized contaminated land investigation （OCLI） method. This identifies the optimal level of uncertainty that reduces to overall financial loss caused by the measurement procedures and the misclassification of the contamination, caused by the uncertainty. Generally the uncertainty of the actual measurements made in these different site investigations was found to be sub-optimal, and too large by a factor of approximately two. The uncertainty is usually limited by the sampling, but this can be reduced by increasing the sample mass by a factor of 4 （predicted by sampling theory）. It is concluded that knowing the value of the uncertainty enables the interpretation to be made more reliable, and that sampling is the main factor limiting most investigations. This new approach quantifies this problem for the first time, and allows sampling procedures to be critically evaluated, and modified, to improve the reliability of the geochemical assessment.     

T -distributed Random Fields: A Parametric Model for Heavy-tailedWell-log Data1

Histograms of observations from spatial phenomena are often found to be more heavy-tailed than Gaussian distributions, which makes the Gaussian random field model unsuited. A T-distributed random field model with heavy-tailed marginal probability density functions is defined. The model is a generalization of the familiar Student-T distribution, and it may be given a Bayesian interpretation. The increased variability appears cross-realizations, contrary to in-realizations, since all realizations are Gaussian-like with varying variance between realizations. The T-distributed random field model is analytically tractable and the conditional model is developed, which provides algorithms for conditional simulation and prediction, so-called T-kriging. The model compares favourably with most previously defined random field models. The Gaussian random field model appears as a special, limiting case of the T-distributed random field model. The model is particularly useful whenever multiple, sparsely sampled realizations of the random field are available, and is clearly favourable to the Gaussian model in this case. The properties of the T-distributed random field model is demonstrated on well log observations from the Gullfaks field in the North Sea. The predictions correspond to traditional kriging predictions, while the associated prediction variances are more representative, as they are layer specific and include uncertainty caused by using variance estimates.     

黑龙江省中部森林沼泽区 超低密度深穿透地球化学调查采样介质的确定

通过对王水溶矿法与四酸溶矿法的对比,元素在泛滥平原A层、B层沉积物及水系沉积物中的分配,以及这3种介质圈定的异常对比等综合因素的研究,确定了泛滥平原A层沉积物是黑龙江省中部森林沼泽区开展超低密度深穿透地球化学调查的有效采样介质。     

理学3080E3型X射线荧光光谱仪维修实例

介绍理学3080E3型X射线荧光光谱仪样品驱动单元及高压发生器部分的故障现象及维修实例。     

地球化学异常再现性与可对比性

不同密度采样是否可以获得稳定的和可追索的地球化学模式是检验采样是否具有代表性，分析技术是否成熟的重要依据。笔者选择新疆哈密大南湖地区约6400km^2面积，进行了从超低密度(1个样／100km^2)，甚低密度(1个样／25km^2)直到低密度(1个样／4km^2)地球化学采样，对比了3种密度地球化学采样所获得的地球化学数据和异常分布模式。得出如下结论：超低密度、甚低密度、低密度地球化学调查获得的元素含量平均值和背景值非常接近；超低密度、甚低密度、低密度调查所圈定的地球化学省在形态上和变化趋势上非常相似，浓集中心的位置重合，表明不同调查阶段可获得稳定的和可追索的地球化学模式；采样密度越大数据离散程度越高，即最小值更小，最大值更大，表明元素分布的局部不均匀性，正是这种局部的不均匀性才能通过加密采样刻画出地球化学模式的细节变化，为逐步追踪矿化体奠定了基础；超低密度和甚低密度采样可以有效圈定矿集区所形成的大规模地球化学异常，低密度地球化学调查不仅可以圈定矿集区异常，同时可以圈定分散矿化的小规模局部异常。