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首页> 外文期刊>Geophysical Research Letters >FACTORS CONTROLLING THE VARIANCES OF SEISMIC VELOCITY, DENSITY, THERMAL CONDUCTIVITY AND HEAT PRODUCTION OF CORES FROM THE KTB PILOT HOLE
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FACTORS CONTROLLING THE VARIANCES OF SEISMIC VELOCITY, DENSITY, THERMAL CONDUCTIVITY AND HEAT PRODUCTION OF CORES FROM THE KTB PILOT HOLE

机译:控制KTB导孔孔内地震波速,密度,热导率和产热变化的因素

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This paper presents a statistical analysis of about 50000 petrophysical data measured on core samples from the Continental Deep Drilling Project (KTB) of the Federal Republic of Germany. The scattering of the data must be taken into consideration using empirical relationships between pairs of parameters, e.g., sound velocity, density, heat production and thermal conductivity. Such covariances of parameters were calculated and used to find the principle components by applying factor analysis. The reduction of parameters by factor analysis may help other scientists to concentrate on the essential parameters to be measured. About 50% of the variance of all data can be explained by one background variable, the so-called ''lithology factor''. The variables that load a factor are either highly correlated or anticorrelated. The lithology factor combines gamma spectroscopy data, density and the mineral contents of quartz, amphibole, garnet and white mica. Seismic velocities and porosity data, however, were less well related to the lithology factor. Therefore, the KTB data indicate that correlation between seismic velocity and one of the lithology factor loading variables is unlikely. The lithology factor distinguishes 3 major ''rock types'': metabasites, gneisses and an intermediate type. The variance of the petrophysical parameters within the rock types, plotted in crossplots, show the level of validity of commonly used relationships among these parameters. Measurements under ambient and simulated in-situ conditions are included to enable discussion of chemical, mineralogical and microstructural characteristics of the rocks. [References: 14]
机译:本文提供了对来自德意志联邦共和国大陆深层钻探项目(KTB)核心样品的约50000个岩石物理数据的统计分析。必须使用成对的参数之间的经验关系(例如声速,密度,热量产生和热导率)来考虑数据的散射。计算这些参数的协方差,并通过应用因子分析将其用于查找主成分。通过因子分析来减少参数可能有助于其他科学家将精力集中在要测量的基本参数上。可以通过一个背景变量(所谓的“岩性因子”)来解释所有数据的约50%的方差。加载一个因子的变量是高度相关或反相关的。岩性因子结合了伽马能谱数据,密度,石英,闪石,石榴石和白云母的矿物含量。但是,地震速度和孔隙率数据与岩性因素的关系不太好。因此,KTB数据表明地震速度与岩性因子加载变量之一之间的相关性不太可能。岩性因素区分了三种主要的“岩石类型”:玄武岩,片麻岩和中间类型。岩石类型中岩石物理参数的方差(以交叉图表示)显示了这些参数之间常用关系的有效性。包括在环境条件和模拟原位条件下的测量,以便讨论岩石的化学,矿物学和微观结构特征。 [参考:14]

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