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Uncertainty propagation of arbitrary probability density functions applied to upscaling of transmissivities

机译:任意概率密度函数的不确定度传播应用于透射率的放大

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摘要

In many fields of study, and certainly in hydrogeology, uncertainty propagation is a recurring subject. Usually, parametrized probability density functions (PDFs) are used to represent data uncertainty, which limits their use to particular distributions. Often, this problem is solved by Monte Carlo simulation, with the disadvantage that one needs a large number of calculations to achieve reliable results. In this paper, a method is proposed based on a piecewise linear approximation of PDFs. The uncertainty propagation with these discretized PDFs is distribution independent. The method is applied to the upscaling of transmissivity data, and carried out in two steps: the vertical upscaling of conductivity values from borehole data to aquifer scale, and the spatial interpolation of the transmissivities. The results of this first step are complete PDFs of the transmissivities at borehole locations reflecting the uncertainties of the conductivities and the layer thicknesses. The second step results in a spatially distributed transmissivity field with a complete PDF at every grid cell. We argue that the proposed method is applicable to a wide range of uncertainty propagation problems.
机译:在许多研究领域中,当然在水文地质学中,不确定性传播是一个经常发生的话题。通常,参数化的概率密度函数(PDF)用于表示数据不确定性,这限制了它们对特定分布的使用。通常,此问题通过蒙特卡洛模拟解决,其缺点是需要大量计算才能获得可靠的结果。在本文中,提出了一种基于PDF的分段线性逼近的方法。这些离散PDF的不确定性传播与分布无关。该方法应用于透射率数据的放大,并分两个步骤进行:将电导率值从井眼数据垂直放大到含水层比例,以及对透射率进行空​​间插值。第一步的结果是井眼位置的透射率的完整PDF,反映了电导率和层厚度的不确定性。第二步将在每个网格单元上生成具有完整PDF的空间分布的透射率场。我们认为所提出的方法适用于各种不确定性传播问题。

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