用于岩性和矿物学勘探的原位元素浓度测井数据分析。一个案例研究

Ahmed Amara Konaté , Houalin Ma , Heping Pan , Nasir Khan
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引用次数: 3

摘要

变质岩种类繁多,成分、结构和质地更为复杂。利用测井资料对变质岩进行岩石类型识别和预测是一项艰巨的任务。利用中国大陆科学钻探主孔4390 ~ 5089 m段的井内地球化学资料,研究了交叉图技术、Pearson相关和因子分析在变质岩解释中的应用。研究了岩性识别能力、地球化学和地球物理测井资料的相关性,建立了将原位化学元素与矿物联系起来的因素模型。结果表明,钾钍测井曲线是变质岩中最具鉴别性的测井曲线。Pearson相关性表明,钾和钍是伽马射线响应的最大贡献者。因子分析结果显示为2因子模型,其中因子1(角闪洞矿物)和因子2(钾长石矿物)描述了测井响应变化的76.261%。这些统计方法可以成为一个非常有用的工具,帮助地球科学家在研究钻井的背景下完成任务。
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Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case study

Metamorphic rocks are diverse with more compositions, structures, and textures that are complex. Rock type identification and prediction from metamorphic rocks using well log data are difficult tasks. This study shows the use of cross plot technique, Pearson correlation, and factor analysis in metamorphic rocks interpretation using borehole geochemical data from the 4390–5089 m interval depth of the Chinese Continental Scientific Drilling Main hole. Lithological identification abilities, correlation between geochemical and geophysical logs, and build a factor model which link in situ chemical element to minerals were studied. The results show that Potassium and Thorium logs are the most discriminating logs in metamorphic rocks. Pearson correlation shows that Potassium and Thorium are the largest contributors to the gamma ray responses. Factor analysis results show a 2 factor model-where factor 1 (amphibole mineral) and factor 2 (K-feldspar mineral) described 76.261% of the variation in log responses. These statistical methods can be a very helpful tool in helping the task of geoscientists in the context of research drillings.

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