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Statistical analysis and evaluation of lithofacies from wireline logs over Beleema field, Niger Delta, Nigeria

机译:尼日利亚尼日尔三角洲贝雷马油田电缆测井岩相的统计分析和评估

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A statistical analysis of well-log data for the purpose of estimating and evaluating lithofacies with depth, around ‘Beleema’ field, Niger Delta, was carried out. The principal component analysis (PCA) technique and the bulk volume water and the grain size relationships formed the main principles of analysis. The PCA was applied to selected lithology-sensitive logs, each serving as a variable within the trivariate statistical system. It involved determining the first principal component (PC1) in each well, plotting them against depth and segmenting into intervals with similar statistical characteristics. The gamma ray log was used as control for the segmentation. A total of forty-three (43) electrofacie-blocked units, grouped into two major facies - sand and shale (major) - as well as two shaly-sand and sandy-shale (minor), were identified within the wells studied. Also, the bulk volume water (BVW) was observed to vary from 0.0224 in coarse grained sand facies to 0.0892 in silt grained sand facies. The grain size values obtained varied from about 0.0625 mm in silt grained facies to a range of 0.5 to 1.0 mm in coarse grained facies. The computed BVW curves closely mimic the field gamma ray traces; such that the former could be confidently employed where the latter is unavailable.
机译:为了估计和评估尼日尔三角洲“贝莱玛”油田附近的岩相,对测井数据进行了统计分析。主成分分析(PCA)技术和体积水与晶粒尺寸的关系构成了分析的主要原理。将PCA应用于选定的岩性敏感测井,每个测井在三变量统计系统中充当变量。它涉及确定每口井中的第一主要成分(PC1),将它们相对于深度绘制,然后细分为具有相似统计特征的区间。伽马射线测井曲线用作分割的对照。在研究的井中,总共识别出四十三(43)个电相封闭的单元,分为两个主要相-砂岩和页岩(主要)以及两个泥质砂岩和砂质页岩(次要)。而且,观察到的总体积水(BVW)从粗粒砂相的0.0224变化到粉粒砂相的0.0892。所获得的粒度值从粉粒相中的约0.0625mm变化到粗粒相中的0.5至1.0mm的范围。计算出的BVW曲线非常类似于场伽马射线迹线。这样,在没有后者的情况下,可以放心地雇用前者。

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