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Spatial prediction of the variability of Early Pleistocene subsurface sediments in the Netherlands - Part 2

机译:荷兰早期更新世地下沉积物变异性的空间预测-第2部分

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We started a geochemical mapping campaign in the Early Pleistocene fluviatile Kedichem Formation in the Netherlands in order to meet the demand for more information about subsurface sediment compositions. Geochemical data were collected during a sampling campaign, and about 600 samples from the Kedichem Formation were analyzed. By linking the geochemical data with lithological classifications from the TNO-NITG borehole database, we established a geochemical model.Elements were divided into classes according to their geochemical behaviour in relation to lithological parameters. For each of the classes, we combined lithological groups in to groups with relevant geochemical differences. By calculating for each element the average composition in each of these groups, we were able to predict the geochemical composition of subsurface sediments by 'translating' the spatial lithological data from the TNO-NITG borehole database into geochemical subsurface this model by calculating and interpolating the average composition of horizontal slices of the Kedichem Formation. The model performance is fairly good, although it has a tendency to underestimate extreme values.
机译:为了满足人们对地下沉积物成分更多信息的需求,我们在荷兰的早更新世可溶的Kedichem组开始了地球化学制图活动。在一次采样活动中收集了地球化学数据,并对来自Kedichem组的约600个样品进行了分析。通过将TNO-NITG钻孔数据库中的地球化学数据与岩性分类联系起来,我们建立了一个地球化学模型。根据其与岩性参数有关的地球化学行为,将元素分为几类。对于每个类别,我们将岩性组合并为具有相关地球化学差异的组。通过计算每个组中每个元素的平均组成,我们能够通过将TNO-NITG钻孔数据库中的空间岩性数据“转化”为该模型,通过计算和内插该模型,从而预测地下沉积物的地球化学组成。 Kedichem组水平切片的平均组成。尽管模型模型倾向于低估极值,但模型性能还是相当不错的。

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