Principal components analysis using the hypothetical closed array

The application of R-mode principal components analysis to a set of closed chemical data is described using previously published chemical analyses of rocks from Gough Island. Different measures of similarity have been used and the results compared by calculating the correlation coefficients between each of the elements of the extracted eigenvectors and each of the original variables. These correlations provide a convenient measure of the contribution of each variable to each of the principal components. The choice of similarity measure (variance-covariance or correlation coefficient)should reflect the nature of the data and the view of the investigator as to which is the proper weighting of the variables—according to their sample variance or equally. If the data are appropriate for principal components analysis, then the Chayes and Kruskal concept of the hypothetical open and closed arrays and the expected closure correlations would seem to be useful in defining the structure to be expected in the absence of significant departures from randomness. If the data are not multivariate normally distributed, then it is possible that the principal components will not be independent. This may result in significant nonzero covariances between various pairs of principal components.     

Eigenvector analysis of reconstructed Holocene July temperature departures over northern Canada

July temperatures for the past 6000 yr at 11 sites in northern Canada have been predicted by transfer-function equations. Normalized departures from the mean of each time series at 250-yr intervals are analyzed by principal component (eigenvector) analysis. An initial analysis included 9 sites and the first three principal components accounted for 85.7% of the variance. Maps of the loadings on the principal components show broad spatial coherence on all three components. Temporal coefficients (principal component scores) illustrate major regional and local midsummer temperature variations. An additional 2 sites were then included but the spatial pattern of the loadings remained essentially unchanged. A further test of this approach, with a view toward predicting paleoclimates of northern regions, was to use the spatial coefficients (loadings) to estimate the July temperature departures at an “unknown” site (Long Lake, Keewatin). This reconstruction compares favorably with an independent transfer-function reconstruction (Kay, 1979). Power spectrum analysis of the significant principal component scores (temperature departures) over the 6000 yr showed that the temporal fluctuations associated with the first three principal components follow a “red noise” spectrum, indicative of strong persistence in the reconstructed climatic records. The scores on the fourth principal component approximate a “white noise” spectrum. A peak in power between 2000 and 3000 yr occurs in the variance spectrum of the second principal component (significance 10%). We conclude that eigenvector analysis of Holocene paleoclimatic data has considerable power and may be useful for identifying regional and local climatic variations.     

Analysis of noble gases in water using a quadrupole mass spectrometer in static mode

A quadrupole-based mass spectrometer used in static mode has been employed to determine noble gas concentrations of water samples by isotope dilution. Water samples are degassed and spiked with minor isotopes of each noble gas. After separation of the various gas components, the isotopic ratios are measured in the mass spectrometer. Because a spike is added to each sample, the recovery of each gas component does not have to be quantitative. Equilibration temperatures are calculated from the gas concentrations, based on noble gas solubility data. An accuracy of ±1°C, from the air equilibration temperature, is attainable for air-saturated water samples prepared under controlled conditions in the laboratory. The method has been applied to groundwaters from the London Basin Chalk aquifer. The noble-gas-derived temperatures are consistent with climatic conditions prevailing at the periods of recharge.     

基于支持向量机的水库诱发地震分析

将诱发水库地震的主要因素（岩性、岩体完整性、断层性质、库区区域应力状态、库区地震活动背景）划分为11个因子,并进行定量化;再根据每个样本到所属类内超平面的距离计算每个样本点的模糊因子,确定其对分类超平面影响大小;然后建立水库地震的支持向量机（SVM）和模糊支持向量机（FSVM）模型,并应用于水库诱发地震等级预测。实例分析表明,两种模型均可用于水库诱发地震等级预测,具有预测精度较高、考虑因素全面的特点,相比之下SVM模型预测结果略优于FSVM模型。另外,在应用SVM和FSVM进行分类时,如果样本离散性较高,则SVM模型优于FSVM模型;相反,如果样本离散性较低,则FSVM模型优于SVM模型。     

基于灰色关联度分析法和主成分分析法对泥页岩储层评价方法的探讨

泥页岩储层的影响因素众多,明确各因素间的内部联系才能更好地评价储层。为对比灰色关联法和主成分分析法在储层评价中的适用性,本文选取鄂尔多斯盆地东缘上古生界Y88井丰富的储层数据进行分析。通过对比两种多元统计方法的原理、算法和结果,认为主成分分析法把各项因子视为离散变量,通过降维后用三个综合评价指标来反映储层的优劣,是对各项指标的概括性分析;灰色关联法将参数分为参考数据列和比较数据列,参考数据列的有机碳含量高低与储层的优劣成正相关,参考数据列对评价对象具有可测性。因此,若是对评价对象的概括性分析,用主成分分析法比较合适;若是对评价对象的可测性分析,如有机碳含量的高低决定能不能形成泥页岩储层,则用灰色关联法评价更合理。     

Analysis of the effect of geology, soil properties, and land use on groundwater quality using multivariate statistical and GIS methods

The regional survey of groundwater used as a small water supply system was performed to know the effect of geology, soil properties and land use on groundwater quality at Nonsan City, Korea. A total of 126 groundwater samples were collected and analyzed at the study area. The multivariate statistical methods, principal components analysis and discriminant analysis, and GIS technique were used for the quantitative interpretation of groundwater quality. The study area is mainly composed of Precambrian gneiss, Jurassic granite, and Cretaceous volcanics, and metasedimentary rocks of the Ogcheon zone. The land use was grouped as paddy, upland, grassland, resident, point source, industrial area, and water system. The soil properties were classified as 4 major groups, Entisols, Alfisols, Inceptisols, and Ultisols, by the degree of development, and reclassified as 11 subgroups. The modified and simplified geologic map, soil map, and land use map were made by using ARCGIS soft-ware. The area of geology, soil property, and land use affecting the groundwater quality for each well were also calculated by ARCGIS soft-ware to acquire the quantitative parameters for multivariate statistical analysis. The monitoring results of groundwater in the study area showed that 13%-21% of the groundwater samples exceeded the portable water guideline and the main causes were turbidity, bacteria, arsenic and nitrate-N. The spatial distribution of each component showed the close relationship between groundwater quality and geology reflecting the topography, land use.     

Variation of heavy metals in recent sediments from Piratininga Lagoon (Brazil): interpretation of geochemical data with the aid of multivariate analysis

In the last decade, the Atlantic coast of south-eastern Brazil has been affected by increasing deforestation and anthropogenic effluents. Sediments in the coastal lagoons have recorded the process of such environmental change. Thirty-seven sediment samples from three cores in Piratininga Lagoon, Rio de Janeiro, were analyzed for their major components and minor element concentrations in order to examine geochemical characteristics and the depositional environment and to investigate the variation of heavy metals of environmental concern. Two multivariate analysis methods, principal component analysis and cluster analysis, were performed on the analytical data set to help visualize the sample clusters and the element associations. On the whole, the sediment samples from each core are similar and the sample clusters corresponding to the three cores are clearly separated, as a result of the different conditions of sedimentation. Some changes in the depositional environment are recognized using the results of multivariate analysis. The enrichment of Pb, Cu, and Zn in the upper parts of cores is in agreement with increasing anthropogenic influx (pollution).     

山东省东营凹陷古近系沙河街组碎屑岩储层定量评价及油气意义

采用＂主因素＂定量评价方法对东营凹陷古近系沙河街组碎屑岩储层质量进行了评价。首先选取储集性能参数（孔隙度、渗透率）、颗粒分选性、泥质含量、粒径、埋藏压实程度、溶蚀作用及胶结作用强度等参数作为储层质量评价参数,按灰色关联分析法计算其他子因素相对于母因素—孔隙度的权重系数,然后,采用极大值标准化法计算各评价参数的单项分数,求取储层质量综合评价因子Q,在缺乏孔、渗资料的情况下,利用其他参数的权重系数,求得储层质量综合评价因子Q1。根据Q和Q1划分评价标准,并进行储层分类评价,结果与利用中国石油天然气集团总公司碎屑岩储层分类标准进行评价的结果基本一致。用此方法对沙河街组碎屑岩储层进行分类评价,把评价结果与试油结果进行比较,发现其符合率较高。这说明该定量评价方法用于储层综合评价具有可行性,根据Q或Q1的大小,可以快速直观地判定或预测某一地区某一层段的储层质量。     

Ordination and character correlations of selected recent British ostracoda

Forty-six characters were measured on each of 14 Recent ostracode specimens representing 13 species collected along the British coast. Results obtained from ordination using principal components analysis agreed closely with results from cluster analysis, but ordination gave a better representation of taxonomic distances computed from the original data. Cophenetic correlations were 0.857 for the cluster analysis and 0.935 for distances computed from projections used in ordination. Characters showed considerable intercorrelation, and the first principal component was reified as a general-size factor correlated highly with height. The remaining principal components could not be reified precisely.     

核主成分分析与支持向量机模型在储层识别中的应用

针对低孔、低渗致密储层识别较常规储层难这一问题,首次应用核主成分分析与支持向量机(KPCA-SVM)模型进行储层识别.该模型先通过核主成分分析(KPCA)进行非线性特征参数提取,然后将提取的特征参数作为支持向量机(SVM)的输入变量,最终实现储层识别.由于KPCA-SVM模型集成了核函数、主成分和支持向量分类机的优点,较好地解决非线性小样本的问题,能消除数据之间的噪音,降低维数,而又不缺失有效信息,达到准确快速预测的功能.将该模型应用到新场须二气藏新856井区储层预测中,预测结果验证了本模型的优越性,可作为致密储层预测的可选方法.     

主成分分析与Bayes判别法在突水水源判别中的应用

准确有效地判别突水水源是解决矿井水害的前提条件。基于淮北袁店二矿各含水层共59个水样水质化验资料,利用主成分分析法,计算各水样的因子得分,并进行系统聚类,剔除错误样本。利用剩余水样作为学习样本,检验Bayes判别函数的判定准确性,得出准确率为92.5%,并进行交叉验证。利用该判别函数对某工作面底板下一富水区水样进行判别,结果与实际情况吻合。结果指示基于主成分分析与Bayes判别法较单一Bayes判别法更加准确,能够消除样本变量之间的相互影响,实现对突水水源的快速有效判别。      

巴林石、寿山石透明度研究

通过分析巴林石、寿山石样品的FTIR与XRD光谱特征,指出有序度指数（OI）、结晶度指数（HI,DHI）及半高宽（FWHM（00l））在用于研究高岭石与地开石混合相样品的组分时具有局限性;计算了样品的有序度指数和结晶度指数并研究了各自与透明度之间的关系,结果证实,寿山石样品的透明度随其有序度与结晶度的增加而增大,但没有发现巴林石样品存在类似规律。     

煤层气测井资料解释初探

探讨了用于煤层气测井资料解释的煤层气储层的组成模型。煤层气储层具有双重孔隙结构,因此它可以分成裂隙和含微孔隙的基质两部分。就煤层气储层的组成成分而言,它由有机质、矿物质、水和气四个部分组成。从此组成模型出发,用以“岩心刻度测井”为主的解释方法,对煤层气储层的灰分、含气量和渗透率等储层参数进行了实测解释分析。     

Petrophysical software for interpreting integrated well-logging data based on spectrometric gamma-logging

This paper discusses modern techniques of identification of reservoir rocks of complex mineral composition in low-thickness layers. The principal purpose of the study is the elaboration of an optimal set of petrophysical investigations used for interpretation of well-logging (WL) data. The solution of the problem lies in generating a mineral-component model of sediments and in finding a range of admissible values of every macro component and its petrographic parameters.     

Geochemical study of pottery sherds from an archaeological site near Mošnje (Slovenia)

This study is a geochemical analytical approach to the characterization of pottery samples from an archaeological site near Mo?nje (Slovenia). Inductively coupled plasma–mass spectrometry and statistical analyses were used to determine detailed geochemical properties of the pottery sherds and to identify potentially individual groups among the samples studied. The geochemical results indicated the existence of four major groups of the pottery sherds: the first and second groups are assembled from eight samples, all generally characterized by their high CaO and TOT/C content; the third group comprised the samples with the highest SiO₂ concentrations; and the fourth group is represented by the samples K3, K5 and K13. The principal component analysis and cluster analysis validated the existing groups and revealed a high degree of chemical similarity between these groups. The geochemical and statistical data confirmed the archaeologists’ hypothesis and interpretation of a similar origin/alteration of source material/probable local ceramic production for the majority of the pottery sherds; the imported origin of samples K3 and K13 was recognized, while sample K5 had been intentionally imported as a sample for comparative purposes.     

应用地热温标估算地下热储温度

利用6省区49个热水样品的测试数据,分4类方法估算热储温度,以天津地区为例,讨论区域地质背景下热储温度的估算,并对怀疑发生混合作用的水样点建立混合模型。结果表明,不同地热温标的应用条件各不相同,应用到实际水样后得到的温标估算结果差异很大,需要利用Na-K-Ca三角图和lg （Q/K）图判断矿物-流体的平衡状态,还要综合考虑蒸汽散失、混合等对温度的影响。天津地区8个地热井估算的热储温度在83～120 ℃之间;广州三元里井热水混合前的深部热储温度为79.3 ℃,混入的冷水比例为83%。     

主成分分析在地质样品分类与浓度预测中的应用研究

用主成分分析方法研究地质样品的Ｘ荧光光谱强度与浓度的关系,对未知样分类并预测样品浓度。对标准化后的数据计算各样品的主成分得分,根据得分分布图可快速分类样品。对训练样品作主成分回归分析,建立降维的主成分回归模型,用主元回归预测各组分浓度,效果好于多元回归分析方法。     

主分量分析方法在航空伽玛能谱测量数据解释中的应用

航空伽玛能谱测量所提供的钾、铀和钍含量等放射性参数之间通常存在着显着的相关性,从而掩盖了一些有用信息。应用主分量分析方法可以从相关性强的多个观测变量中提取出少数几个互不相关的新变量,因此能克服上述不足之处。在CDM盆地中部地区应用主分量分析方法对航空伽码能谱数据解释的结果表明,该方法可用来协助进行岩性和构造填图,识别有利于铀矿和钾盐沉积的环境,可以建立铀和钾盐矿床的成矿模式,进行铀和钾盐成矿远景的预测。可见,在航空伽玛能谱测量中它很可能成为一种新的有潜力的解释技术。     

Environmental factors of road slope stability in mountain area using principal component analysis and hierarchy cluster

Nine environmental factors of 147 roadside soil samples were administered in Sichuan Basin of China and principal component analysis was conducted using the Pearson correlation matrix. The results show that the first four principal components whose eigenvalue is over 1.00 can be extracted. The first principal component which is consisted of rock type, soil type, weathering degree, and soil depth is the most important factor of all. The geographical position which is consisted of altitude, longitude, and latitude is included in the second and the third principal components. The fourth principal component shows that the terrain factor influences the rock slope stability. The hierarchy cluster shows that rock type and soil type play the maximum positive correlation, while the slope and the aspect present the maximum negative correlation.