Spatial analysis of elements in soils from Chengdu City

Three kinds of spatial analysis methods （geostatistics, concentration-area fractal model and the multifractal analysis called the moment method） were used for almost 50 elements, including heavy metals, disperse elements, rare elements and even others, in 6586 top soil （0-20 cm） samples and 1833 deep soil （150-200 cm） samples from Chengdu metropolitan area of 12400 km^2, southwestern China. The ranges of spatial correlation revealed by variograms are quite different for different kinds of elements in the top and deep soils. The most interest is the fact that the multifractal spectra of environmentally important elements such as Pb, Cr, Cd and Ni in top soils in the metropolitan area show systematic change from those in the deep soils, revealing a strong anthropogenic addition, while Hg, Zn, As, Cu and all common elements show no such kind of addition. In terms of multifractal properties based on the multifractal spectrum curves, those disperse and rare elements show great deviation from other major and trace elements, which is also of great interest.     

Optimization of SAGD Well Elevation

The application of steam-assisted gravity drainage (SAGD) to recover heavy oil sands is becoming increasingly important in the northern Alberta McMurray Formation because of the vast resources/reserves accessible with this mechanism. Selecting the stratigraphic elevations of SAGD well pairs is a vital decision for reservoir evaluation and planning. The inherent uncertainty in the distribution of geological variables significantly influences this decision. Geostatistical simulation is used to capture geological uncertainty, which is used can be transformed into a distribution of the best possible well pair elevations. A simple exhaustive calculation scheme is used to determine the optimum stratigraphic location of a SAGD well pair where the recovery R is maximized. There are three basic steps to the methodology: (1) model the uncertainty in the top continuous bitumen (TCB) and bottom continuous bitumen (BCB) surfaces, (2) calculate the recovery at all possible elevation increments within the TCB and BCB interval, and (3) identify the elevation that maximizes R. This is repeated for multiple TCB/BCB pairs of surfaces to assess uncertainty. The methodology is described and implemented on a subset of data from the Athabasca Oilsands in Fort McMurray, Alberta.     

可持续发展评估指标、方法及应用研究

可持续发展评估指标及方法研究是可持续发展定量评估研究的基础,是实施可持续发展管理的依据,是生态经济学与可持续发展研究的前沿领域和热点问题之一. 在概括介绍可持续发展评估的工具--指标/指数的概念和功能、国际上代表性可持续发展研究机构指标选取的原则的基础上,全面分析归纳了可持续发展指标(体系)的类型及其框架模式. 详细介绍了联合国可持续发展委员会(UNCSD)、经济合作与发展组织(OECD)、世界保护同盟(IUCN)、世界银行等国际上代表性机构的可持续发展系统性指标体系的最新研究进展,并分析了这些系统性指标体系的优缺点. 深入分析了国际上典型的社会发展类、经济发展类、生态环境类可持续发展指标(指数)的研究、开发与实际评估应用的情况. 最后,总结了当前可持续发展指标(体系)研究的特点与趋势.     

锡铁山铅锌矿地质特征、矿床成因及找矿标志

通过找矿工作的实践，认为锡铁山铅锌矿床是由火山喷流沉积—后期热液叠加改造富集的块状硫化物多金属矿床。区域上NW—SE向早古生代形成的裂谷带，三级盆地内沉积的晚奥陶世滩间山群的大理岩与绿片岩系是表区找矿的最佳区段。而绢云绿泥斜长片岩、含碳质绢云绿泥片岩、白色大理岩、条带状大理岩是铅锌矿的最重要的找矿标志。     

深海岩芯高分辨率的古环境记录-以南海北部陆坡17940-2柱状样为例

本文将深海岩芯高分辩率记录的替代性指标分为沉积型和生物型两类。沉积型替代性指标主要包括沉积物的粒度，沉积速率，粘土矿物；生物型替代性指标主要包括有孔虫，氧同位素，古水温，有机碳通量。对比研究发现，17940—2柱状样沉积物的粒度、沉积速率、有孔虫，氧同位素，古水温，有机碳通量等指标记录海洋环境变化信息程度优于其它替代性指标；沉积型替代性指标与生物型替代性指标记录海洋环境变化信息不同步；海洋环境变化的突变与渐变影响替代性指标记录的同步性。     

Carbon dioxide and radon gas hazard in the Alban Hills area (central Italy)

The sudden and catastrophic, or slow and continuous, release at surface of naturally occurring toxic gases like CO₂, H₂S and Rn poses a serious health risk to people living in geologically active regions. In general this problem receives little attention from local governments, although public concern is raised periodically when anomalous toxic-gas concentrations suddenly kill humans or livestock. For example, elevated CO₂ concentrations have been linked to the death of at least 10 people in the central Italian region of Lazio over the last 20 years, while it was the CO₂ asphyxiation of 30 cows in a heavily populated area near Rome in 1999 which prompted the present soil-gas study into the distribution of the local health risk. A detailed geochemical survey was carried out in an area of about 4 km² in the Ciampino and Marino districts, whereby a total of 274 soil-gas samples were collected and analysed for more than 10 major and trace gas species. Data were then processed using both statistical and geostatistical methods, and the resulting maps were examined in order to highlight areas of elevated risk. General trends of elevated CO₂ and Rn concentrations imply the presence of preferential pathways (i.e. faults and fractures) along which deep gases are able to migrate towards the surface. The CO₂ and Rn anomalous trends often correspond to and are usually elongated parallel to the Apennine mountain range, the controlling structural feature in central Italy. Because of this fundamental anisotropy in the factors controlling the soil-gas distribution, it was found that a geostatistical approach using variogram analysis allowed for a better interpretation of the data. With regard to the health risk to local inhabitants, it was found that although some high risk areas had been zoned as parkland, others had been heavily developed for residential purposes. For example, many new houses were found to have been built on ground which has soil-gas CO₂ concentrations of more than 70% and radon values of more than 250 kBq m⁻³. It is recommended that land-use planners incorporate soil-gas and/or gas flux measurements in environmental assessments in areas of possible risk (i.e. volcanic or structurally active areas).     

Stepwise Conditional Transformation for Simulation of Multiple Variables

Most geostatistical studies consider multiple-related variables. These relationships often show complex features such as nonlinearity, heteroscedasticity, and mineralogical or other constraints. These features are not handled by the well-established Gaussian simulation techniques. Earth science variables are rarely Gaussian. Transformation or anamorphosis techniques make each variable univariate Gaussian, but do not enforce bivariate or higher order Gaussianity. The stepwise conditional transformation technique is proposed to transform multiple variables to be univariate Gaussian and multivariate Gaussian with no cross correlation. This makes it remarkably easy to simulate multiple variables with arbitrarily complex relationships: (1) transform the multiple variables, (2) perform independent Gaussian simulation on the transformed variables, and (3) back transform to the original variables. The back transformation enforces reproduction of the original complex features. The methodology and underlying assumptions are explained. Several petroleum and mining examples are used to show features of the transformation and implementation details.     

Disjunctive Kriging with Hard and Imprecise Data

This paper presents a methodology for assessing local probability distributions by disjunctive kriging when the available data set contains some imprecise measurements, like noisy or soft information or interval constraints. The basic idea consists in replacing the set of imprecise data by a set of pseudohard data simulated from their posterior distribution; an iterative algorithm based on the Gibbs sampler is proposed to achieve such a simulation step. The whole procedure is repeated many times and the final result is the average of the disjunctive kriging estimates computed from each simulated data set. Being data-independent, the kriging weights need to be calculated only once, which enables fast computing. The simulation procedure requires encoding each datum as a pre-posterior distribution and assuming a Markov property to allow the updating of pre-posterior distributions into posterior ones. Although it suffers some imperfections, disjunctive kriging turns out to be a much more flexible approach than conditional expectation, because of the vast class of models that allows its computation, namely isofactorial models.     

动态指标层析法介绍

参数值是影响模拟结果正确可信的重要因素。介绍了一、二维模拟中参数值确定的动态指标层析法，以及作为其发展基础的由多种热指标确定古充的反演方法，简述了动态指标和热指标相结合的确定参数值层析方法。