储层建模中几种原型模型的建立

储层地质知识库的建立是储层建模过程中极为重要的一步，它为建模提供基本的条件数据及各种统计参数。本文总结了建立地质知识库的主要步骤及基本内容。在资料较少的情况下，需要借助原型模型来提供一些无法直接获得但对建模十分重要的参数，如砂体宽厚比、水平方向变差函数等。文中用3个实例较详细的介绍了建立原型模型的3种主要方法，分别是利用露头、成熟油田和沉积模拟实验建立原型模型，并比较了各自的优缺点。     

陕北砂黄土区公路地质灾害及防治对策

中国西北黄土的颗粒组成具有明显的地带性分布规律，自NW向SE可依次划分为砂黄土带、典型黄土带和粘黄土带。黄土高原北部地质灾害综合调查表明，砂黄土区公路地质灾害的主要类型包括黄土边坡滑塌灾害、路堤裂陷灾害、路桥变形和冲蚀灾害等。根据试验测试分析结果，公路地质灾害的形成主要受黄土本身的物质组成、结构及力学性质控制，人类工程活动的盲目性是诱发地质灾害的重要因素。文章在砂黄土公路地质灾害特征分析的基础上，提出加强边坡防护和冲蚀灾害防治是公路地质灾害防治的两个基本途径，并给出了针对性的防治对策。这不仅对该地区的公路建设具有重要的指导作用，而且对其它生命线工程如铁路、输油气管道、渠道等也具有重要的借鉴意义。     

莺歌海盆地断裂活动与地质灾害分析

莺歌海盆地是南海西北部海域地质灾害类型较齐全的地区之一。根据野外调查资料,本文简要地分析了该区的活动断裂和地质灾害类型。区内活动断裂主要走向呈NW向,该方向的活动断裂主要有红河断裂带、中央拗陷东部断裂带和中央拗陷西部断裂带。红河断裂带在地震资料上显示为一倾向SW的正断层,表现为明显的重力梯级带和磁异常分界带,NE向断裂带分布于盆地中部,在重磁异常上表现为明显的异常带,在北部表现为被NW向的断裂切割。莺歌海盆地地质灾害类型主要有地震活动、泥底辟构造、滑坡与崩塌等。同时,还对该区地质灾害基本特征和分布规律进行了初步分析。     

大兴安岭地区浅覆盖层对地面伽马能谱测量的影响

讨论在大兴安岭地区进行地质填图中浅覆盖层对伽马能谱测量的影响问题。通过放射性元素的取样分析、岩石—土壤的矿物分析以及实测剖面分析,得知了伽马能谱测量的影响因素,从而为应用伽马能谱测量解决地质填图中的问题提供了依据。     

Design of backfilled thin-seam coal pillars using earth pressure theory

In underground coal mining any increase in coal recovery rate is dependent on a decrease in pillar size. Backfilling is one way of reducing the required size of pillars and hence the volume of coal left underground. Therefore any comparisons made between a self-supported mine layout and backfill supported mine layout are based directly on pillar design. The most effective way to examine the effect of backfill on pillar support, and subsequently the rate of recovery, would be to incorporate the mechanisms of backfill support directly into the current design procedure for coal pillars. This paper presents a review of the mechanics of backfill support, a method of estimating the magnitude of that support based on earth pressure theory, and an example that incorporates backfill support into current coal pillar design.     

鹅湖岩体岩石谱系单位的建立及其就位机制分析

鹅湖岩体为S型花岗岩 ,具有结构和成分演化序列。运用岩石结构序列法 ,将其划分为 5个单元 ,归并为 1个超单元。按侵入体空间展布形式、岩体地质学、岩石学、构造等资料 ,探讨了岩体就位机制     

Effective resource estimates for primary diamond deposits from the EKATI Diamond Mine™, Canada

Primary economic diamond deposit modelling has rarely been documented in the public domain. This paper presents information collected from significantly diamondiferous kimberlite pipes located near Lac de Gras in the Arctic region of Canada's Northwest Territories. The resource estimation process is widely accepted as a cyclical iteration of data collection and evaluation processes. A resource database is typically assembled from a large inventory of exploration data. These data must be methodically quality checked before accepting the information for interpretive analysis. The foundation of a mineral resource model is based on clear understanding of the geology model along with subsidiary grade, volume, and density models. Defining these models is an iterative process of statistical analyses and interpretation. As a deposit progresses along a path towards development, reducing risk to acceptable levels is critical for identifying and realizing its maximum value.     

“Three-Component” Digital Prospecting Method：A New Approach for Mineral Resources Quantitative Prediction and Assessment

“Three-component” method consists of three clase-connected aspects: geological anomaly,diversity of mineralization and mineral deposit spectrum. All these three concepts are not new separately, but it is a new approach to combine these three aspects in one single concept for quantitative mineral resources prediction and assessment and it is also the first time to conduct a more detailed study in each aspect. Investigation and clarification of geological anomalies, diversity of mineralization and spectrum of mineral deposits are realized by digitization and quantification of ore forming controlling factors, oreexisting symbols or marks, characteristics of mineralization and regulation of ore-genesis and laws of distribution. These procedures lead to construction of a “digital model“ for mineral resources prediction andassessment.     

Effet de la teneur en eau d'un sol sur la réduction bactérienne d'oxydes de fer

Iron-reducing activity of autochthonous bacteria from two temporary hydromorphic soils is evaluated by the study of iron reductive dissolution, as a function of water content. The release of ferrous iron in solution is coupled to the mineralization of soil organic carbon. Water soil saturation is not necessary for iron reductive dissolution, since the highest dissolution is obtained for a wet, but not water-saturated soil (100% of water holding capacity WHC), and dissolution is also very high in a soil at 75% WHC. To cite this article: S.J. Stemmler et al., C. R. Geoscience 336 (2004).     

Mapping the Bonanza: Geographies of Mining Investment in an Era of Neoliberal Reform*

Geographic analyses of how national policies of economic liberalization influence global patterns of economic activity often draw their conclusions from studies of the paradigmatic sectors of manufacturing and, to a lesser extent, services. There is, by contrast, relatively little work examining how neoliberal policy reforms in the developing world may be driving changes in the geography of primary sector (i.e., extractive) activities at the global scale. This article presents and analyzes new data on direct investment in the international mining industry. It reports methods and results from a research project to systematically map and evaluate changes in the commodity mix and geographical spread of mining‐related investment in the world economy since 1990. It confirms and quantifies what was hitherto anecdotal evidence of a geographic shift in investment during the 1990s away from mature targets toward a small number of “rising stars” in the developing world, following the adoption in many countries of neoliberal economic policies from the mid‐1980s onward. However, the findings challenge conventional interpretations of this shift as an investment “bonanza” in the periphery and highlight how recent investment trends are highly specific in geographical scope, concentrated within a few commodities, and how the allocation of investment between established and emerging targets is variable over both time and space.