Facies recognition of some Tertiary coals applied to prediction of oil source rock occurrence

Coals are oil source rocks in many of the Tertiary basins of Southeast Asia. The precursors of these hydrogen rich and oxygen poor coals are coastal plain peats which have mainly developed in an everwet and tropical climate. In these environments water flow and reworking can concentrate liptinitic kerogen in preference to vitrinitic kerogen. The distribution, petrography and chemistry of the coaly Miocene source rocks present in the Kutai Basin are described. The recognition of environmental controls on the accumulation of potentially oil-prone coals and coaly shales in deltaic environments is an aid to predictive source bed recognition in petroleum exploration. Comments on the environment of deposition of coaly sediments in the basins of the Norwegian Sea are discussed with reference to their possible oil and/or gas sourcing potential. The Triassic - Jurassic coals of the Haltenbanken area may become more oil-prone towards the delta margins, and facies mapping could aid oil exploration in this area.     

Risk-based decision-making for drilling waste discharges using a fuzzy synthetic evaluation technique

Offshore petroleum drilling wastes contain toxic substances that are potentially harmful to the marine ecosystem. Despite environmentally benign characteristics, wastes associated with synthetic-based fluids still contain a certain amount of pollutants due to contamination with formation oil and the presence of trace heavy metals in barite, which may pose risk when discharged into the marine environment. A framework is presented here for a decision support system for the selection of the best drilling waste discharge option. Uncertainties in the quantification of risk, cost and technical feasibility are expressed by fuzzy numbers. An analytical hierarchy process with a technique called fuzzy synthetic evaluation is employed to determine the best management alternative (discharge scenario).     

On the Polyps of the Common Jellyfish Aurelia aurita in Kagoshima Bay

There is the natural habitat of polyps of the common jellyfish Aurelia aurita in the Taniyama area, Kagoshima Bay. We examined the attachment substrata, density, colony structure and strobilation of the polyps. The polyps were observed only on the horizontal undersurface of floating piers. They attached specifically to Mytilus shells, solitary ascidians, calcareous polychaete tubes, muddy amphipod tubes and the gap space that fouling animals peeled off the substrata. The polyp colonies were distributed in patches. Spatial distribution patterns of the polyps within their colonies were uniform. Strobilation occurred during late December to March, when water temperatures were 16–17°C, and a large number of ephyrae were released. An increase in man-made structures such as floating piers in coastal areas may lead to bloomings of Aurelia aurita medusae. This revised version was published online in July 2006 with corrections to the Cover Date.     

海洋天然气水合物的地震识别方法研究

天然气水合物作为21世纪新的自然能源将为人类的生存发展服务。20世纪60年代证实，俄罗斯西伯利亚的麦索亚哈气田为典型的天然气水合物形成的气田，70年代又在海底发现了固体天然气水合物岩样。1971年，RStoll首先将地震剖面中的似海底反向层解释为海洋天然气水合物存在的标志，后来被深海钻探证实，从此地震方法成为大面积研究天然气水合物的重要手段。天然气水合物既是潜在能源，也是影响环境和形成灾害的因素之一，因此，研究天然气水合物是人类在21世纪的重要课题。探讨海洋天然气水合物的地震识别方法，由于这项工作刚刚起步，还没有做出具体的成果，在此只能根据我们仅有的工作和参照国外分开的出版物，以及出国访问得到的有关资料进行分析，提出我们的一些基本设想，与各位专家探讨。     

基于RS与GIS技术的变更图斑自动识别方法研究

基于RS与GIS技术的土地利用变更图斑自动识别方法,即"以遥感正射影像图为基础,以地理信息和地物反射光谱为判别依据"的变更信息识别方法,能够尽量避免传统利用遥感影像分类技术进行地物变更识别存在的不足。本文通过对距离算法的改良,有效利用遥感数据的实时性和丰富性,在地理信息系统的支持下,提高了对地物变更地块的识别精度。     

Automated Kerogen Classification in Microscope Images of Dispersed Kerogen Preparation

We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty.     

On the physical model of earthquake precursor fields and the mechanism of precursors＇timespace distribution──origin and evidences of the strong body earthquake──generating model

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Chrysophyte stomatocyst taxonomy — classification of snowflakes?

The utility of classifying chrysophyte stomatocysts by their characteristic honeycomb and ridge patterns is questioned, because a strikingly similar expanding pattern appears on the surface of ionized polymer gels during osmotical swelling as a result of simple physical forces. The rapid accumulation of silicate into a spherical cyst inside a chrysophyte cell appears to be as a physical process sufficiently similar to result in an analogous pattern in microscopic scale. Chrysophyte stomatocysts that possess honeycomb or ridge patterns could be regarded as frozen moments of the pattern evolution during the silicate gel phase. As a consequence, such structures should have little taxonomical value.     

FS方法及其在综合多项震兆中的应用

本文提出了一种模式识别方法--FS方法.该方法的特征取为某些论域上的模糊子集.先以每三个原始特征组成子分类器的特征集,“训练”这些分类器,然后对子分类器进行筛选,最后用筛选出的子分类器的“软”分类结果的加权平均作为判别函数,形成总的分类决策.将FS方法应用于综合多项震兆,并进行了一系列控制试验,还与地震学中几种常用的方法进行了对比试验.结果表明,FS方法是稳定和有效的.