页岩层系不同岩矿组合试样渗透率变化规律差异及其机理分析

页岩地层垂向岩矿组合变化大,页岩气开采需要对储层进行大规模人工水力压裂改造。笔者等基于样品的全岩X-射线衍射分析,通过对不同岩矿组合的3块页岩试样进行流—固耦合物理模拟实验,获得了3点认识,反映了不同岩矿成分的页岩在不同条件微裂缝与渗透率的变化特征,以及碳酸盐矿物含量高时的影响。这一实验对于研究页岩储层在压裂过程中的变化具有探索性,对于页岩气生产具有重要的参考意义。     

自适应顺序采样Kriging方法及其在增量动力分析中的应用

复杂结构的增量动力分析（IDA）对于结构的抗震设计和分析有着重要意义,但需对结构进行大量的非线性时程分析,计算量成本高。本文结合Kriging元模型和自适应顺序采样并用于结构增量动力分析以提高其计算效率和精度,其中:Kriging元模型用于预测结构的地震响应,顺序采样根据候选点的熵值补充非线性时程分析逐步增加Kriging模型的预测精度。借助本文方法,IDA曲线可通过少量的时程分析实现较高的精度。为了校验本文方法的可行性与有效性,对二层和九层钢框架结构模型应用直接IDA、hunt&fill方法和本文方法分析并比较了上述三种方法的计算误差、计算效率和IDA曲线差别。在此基础上本文将自适应顺序采样Kriging方法用于考虑结构不确定性参数的IDA分析,并和传统的蒙特卡洛方法进行比较。结果表明:该方法具有较高的计算效率,可以保证IDA曲线的精度。     

常见稀有气体采样容器研究进展及意义

稀有气体是地学研究的重要手段之一,在研究成矿流体来源、壳幔相互作用过程中具有重要的研究意义,其组成及同位素比值是研究天体和地质体来源、成岩机理及各种地质和物理化学过程的关键,可作为地球化学示踪剂。如何有效地在大气圈、水圈和岩石圈进行稀有气体同位素样品的提取,是气体同位素研究急需解决的基础科学问题,所以气体采样容器和取样技术显得尤为重要。本文在文献调研的基础上,对常见的采样容器的优缺点进行对比,并总结了不同采样容器对稀有气体取样的优劣性。常见的气体采集容器包括不锈钢瓶、铜管、玻璃瓶、气体采样袋、注射器等,而稀有气体的采集容器常为不锈钢瓶和铜管等;通过对比表明不锈钢瓶具有耐高温、耐高压、抗强腐蚀、不易燃、不易爆等特点和优越性,在气体样品采集和运输过程中稳定性最好,实验效果也最好;铜管采样效果和密封性好,但操作较为复杂;玻璃采样容器效果次之;石英玻璃瓶虽然操作简便,但是运输保存不便;气体采样袋和注射器的采集和运输储存效果较差。因此建议稀有气体样品采集使用不锈钢瓶和铜管以及钠钙材质的玻璃瓶,不建议将石英材质玻璃容器以及注射器和气袋作为稀有气体的采样工具。该工作可为气体地球化学的研究提供新的参考。     

电感耦合等离子体质谱法测定灌木枝叶中微量元素的样品预处理方法研究

利用电感耦合等离子体质谱法(ICP-MS)测定植物样品中微量元素的关键技术是消除植物样品的有机基体效应,本文通过预处理方法中的酸消解体系、称样量和消解方式消除其影响。以国家标准物质灌木枝叶组合样(GBW07603)为材料进行研究,对比分析了硝酸-过氧化氢、硝酸-氢氟酸、硝酸-氢氟酸-过氧化氢3种酸溶体系的消解效果,以确定最佳酸溶体系,进而定量研究2种称样量(50 mg和100 mg)和3种消解方式(密封高压二次消解、密封高压一次消解、微波消解)的消解效果,并以In作为内标采用ICP-MS测定微量元素含量。结果表明:硝酸-氢氟酸-过氧化氢酸溶体系的消解效果最好;50 mg的测定值更接近于参考值;微波消解法的测定值明显偏低,而密封高压二次消解法是灌木枝叶样品预处理的有效方法。     

Importance sampling based algorithm for efficient reliability analysis of axially loaded piles

In reliability analysis, the crude Monte Carlo method is known to be computationally demanding. To improve computational efficiency, this paper presents an importance sampling based algorithm that can be applied to conduct efficient reliability evaluation for axially loaded piles. The spatial variability of soil properties along the pile length is considered by random field modeling, in which a mean, a variance, and a correlation length are used to statistically characterize a random field. The local averaging subdivision technique is employed to generate random fields. In each realization, the random fields are used as inputs to the well-established load transfer method to evaluate the load–displacement behavior of an axially loaded pile. Failure is defined as the event where the vertical movement at the pile top exceeds the allowable displacement. By sampling more heavily from the region of interest and then scaling the indicator function back by a ratio of probability densities, a faster rate of convergence can be achieved in the proposed importance sampling algorithm while maintaining the same accuracy as in the crude Monte Carlo method. Two examples are given to demonstrate the accuracy and the efficiency of the proposed method. It is shown that the estimate based on the proposed importance sampling method is unbiased. Furthermore, the size of samples can be greatly reduced in the developed method.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.     

Accuracy and precision of different sampling strategies and flux integration methods for runoff water: comparisons based on measurements of the electrical conductivity

Because of their fast response to hydrological events, small catchments show strong quantitative and qualitative variations in their water runoff. Fluxes of solutes or suspended material can be estimated from water samples only if an appropriate sampling scheme is used. We used continuous in‐stream measurements of the electrical conductivity of the runoff in a small subalpine catchment (64 ha) in central Switzerland and in a very small (0·16 ha) subcatchment. Different sampling and flux integration methods were simulated for weekly water analyses. Fluxes calculated directly from grab samples are strongly biased towards high conductivities observed at low discharges. Several regressions and weighted averages have been proposed to correct for this bias. Their accuracy and precision are better, but none of these integration methods gives a consistently low bias and a low residual error. Different methods of peak sampling were also tested. Like regressions, they produce important residual errors and their bias is variable. This variability (both between methods and between catchments) does not allow one to tell a priori which sampling scheme and integration method would be more accurate. Only discharge‐proportional sampling methods were found to give essentially unbiased flux estimates. Programmed samplers with a fraction collector allow for a proportional pooling and are appropriate for short‐term studies. For long‐term monitoring or experiments, sampling at a frequency proportional to the discharge appears to be the best way to obtain accurate and precise flux estimates. Copyright © 2006 John Wiley & Sons, Ltd.     

Sensitivity analysis of geologic computer models: A formal procedure based on Latin hypercube sampling

Mathematical models in which a response variableY is calculated, usually via a computer program, as a function of input variablesX ₁ ,X ₂, ...,X _k are encountered frequently in earth sciences literature. In many cases, uncertainty in the knowledge of the correct values of the input variables exists, leading to uncertainty in the correct value of the response. Sensitivity analysis procedures can be used to identify which input variable uncertainties contribute most to uncertainty in the response variable.This paper presents the technique of Latin hypercube sampling, a structured, formal sampling process used in the sensitivity analysis procedure. Output resulting from the sample is analyzed using stepwise regression analysis, leading to identification of key input variables. Future data gathering activities can then be done efficiently, focusing on these variables. The technique is applied to a model, developed by Sudicky and Frind, which represents the flow of a contaminant through a porous media.     

Some consequences of applying lognormal theory to pseudolognormal distributions

A logarithmic transformation may be used to improve the efficiency of estimates of the mean when observations follow the lognormal distribution. But if this transformation is applied to observations that follow another distribution, bias may be introduced. We consider some consequences of erroneously applying lognormal estimation theory and demonstrate that biased estimates may be obtained for certain classes of distributions. Illustrations of bias obtained in gold sampling are given.