Discrimination of sedimentary facies by association analysis

The ability of association analysis to discriminate sedimentary facies was tested on Purdy's modal analyses of modern sediments of the Great Bahama Bank. Purdy's data set has served in the past as a standard reference for evaluating various multivariate classification algorithms. In order to adapt Purdy's data to association analysis, the percent abundance of the 12 constituents was converted to binary form by dichotomizing each variable on its mean value. The results obtained by association analysis are virtually identical to those obtained by Purdy and other authors. The same four main sedimentary facies were discriminated; 86% of the samples were identically classified (97% when misclassified borderline cases are counted as matches); the total partition variance of the classification is only negligibly greater (4%); and the grouping of the variables yielded the same four groups. The rank order of the three division-attributes responsible for the sample classification is fines, oolites, and corals. Association analysis has been employed by other authors to differentiate meaningful facies groups in studies of ancient reef carbonates, modern reef sediments, and heavy minerals in stream sediments. In all these studies, the results were found to be compatible with those obtained by using the continuous quantitative measurements, indicating that qualitative binary data may often be sufficient for the purpose of facies discrimination in many branches of geology and that association analysis is an effective method for this purpose.     

Elasto-Plastic Analysis of Tubular Joints of Offshore Platforms by Finite Element Method

The plastic node method is reformulated by the variational principle and is applied to elasto-plastic finite element analysis of tubular joints, eventually including the effect of internal and external gussets, stiffener rings, etc., if necessary. Four different joints are studied here in detail for the elasto-plastic behavior, the strain at the hot spot, the strain concentration factor around the intersection line, and the propagation of the plastic region with loading up to collapse in order to determine the ultimate strength, safety factor, and development of the plastic field. The present results are in good agreement with the experimental results.     

曲靖盆地生物气成藏条件及主控因素分析

曲靖盆地新近系茨营组第三段的晚期生物气藏是新近系沉积之后,喜山运动时期各种成藏条件有效的时空配置的结果.在讨论曲靖盆地构造和沉积演化的基础上,综合分析了生物气源、储集层和盖层、圈闭形成以及天然气输导等成藏条件,阐述了生物气晚期聚集成藏条件的时空匹配关系.指出自第四纪以来,生物气源岩持续高效的产气作用是生物气成藏的物质保障,气藏的形成是生物气连续的补充大于逸散动态平衡的产物;背斜构造、砂岩上倾尖灭和砂岩透镜体圈闭是该区主要的圈闭类型;断裂和不整合面是沟通生物气源岩到圈闭的垂向和侧向输导通道,茨营组的连通砂岩体是生物气近距离运移的输导层.蔡家冲组大套湖相暗色泥岩的生物产气效率、断裂的垂向输导能力和圈闭的保存条件及其在时空上的动态配置是生物气晚期成藏的主控因素.     

江西省永平铜矿西部排土场极限堆载高度确定

国内外对排土场极限堆载高度的理论计算缺乏研究,目前尚无成熟的统一理论计算方法。文章结合永平铜矿西部排土场的工程实例,在进行边坡工程地质条件勘察与排土场岩土物理力学性质试验研究的基础上,采用数值计算方法对排土场进行了分层堆载数值模拟计算。通过对计算结果的分析,得到位移、塑性区与安全系数随堆载高度的变化规律,并确定了该排土场的极限堆载高度。     

RUSLE及其影响因子的快速计算分析

RUSLE是目前应用最广泛的土壤侵蚀模型。虽然是一种经验模型,但是其影响因子计算仍然非常复杂,满足不了区域土壤侵蚀的快速提取要求。针对这种状况,文章在介绍RUSLE手册中每个影响因子计算方式基础上,分析总结了可进行快速计算的方法,实验表明,采用文章推荐的因子计算方式,可达到快速有效的目的。     

构建基于GIS的房产管理

阐述了基于GIS房产管理的关键是建立统一的数据分类与编码标准,核心是建立房屋的空间地理属性信息、自然属性信息、社会人文属性信息的链接,基础是建立房产地理信息数据库。并提出了建立房产地理信息数据库的方法、设计思路和方式。     

Automatic classification of volcanic earthquakes by using Multi-Layered neural networks

The application of neural networks as classifiers of seismic events is described with the aim of developing an automatic system for the classification of explosion quakes at the Stromboli volcano. The architecture of the network that we trained to identify four different classes of shocks was a Multi-Layer Perceptron, using the Back Error Propagation algorithm. Five different approaches for representing the information embedded in the seismograms, both in the time and in the frequency domain, were considered, and the results compared. The direct use of the time series of the shocks was not satisfactory. The auto-correlation function worked well, but in some cases it was misleading. A better performance was obtained with a frequency domain representation. Finally, the use of the envelope function did not work well. Combining parameters such as the auto-correlation and envelope functions can improve one source of error, but it may introduce new ones. The performance obtained highlights the importance of the data attributes used for the training of the network. Topologies with eight neurons in a single hidden layer gave, on average, the best results among the considered neural network structures. The overall results provide a large number of events (89% with the best performance) correctly classified, indicating that this automatic technique is reliable, and encouraging further applications in the field of volcanic seismology.     

洪山预测区煤层赋存的可能性分析

分析了洪山预测区西部洪山岩体地质特征及其向外围扩散的范围和程度，研究了北掌勘查区和焦窑煤矿两邻区煤层受岩浆岩影响的程度，认为洪山岩体对预测区煤系及煤层赋存的影响较小，岩体外围仍有煤系赋存。为下一步找煤指明了方向。