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Improved inverse distance weighting method application considering spatial autocorrelation in 3D geological modeling

机译:考虑3D地质建模中的空间自相关的改进的逆距离加权方法应用

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摘要

Spatial interpolation is a main research method in 3D geological modeling, which has important impacts on 3D geological structure model accuracy. The inverse distance weighting (IDW) method is one of the most commonly used deterministic models, and its calculation accuracy is affected by two parameters: search radius and inverse-distance weight power value. Nevertheless, these two parameters are usually set by humans without scientific basis. To this end, we introduced the concept of "correlation distance" to analyze the correlations between geological borehole elevation values, and calculate the correlation distances for each stratum elevation. The correlation coefficient was defined as the ratio of correlation distance to the sampling interval, which determined the estimation point interpolation neighborhood. We analyzed the distance-decay relationship in the interpolation neighborhood to correct the weight power value. Sampling points were selected to validate the calculations. We concluded that each estimation point should be given a different weight power value according to the distribution of sampling points in the interpolated neighborhood. When the spatial variability was large, the improved IDW method performed better than the general IDW and ordinary kriging methods.
机译:空间插值是3D地质建模中的主要研究方法,对3D地质结构模型精度具有重要影响。逆距离加权(IDW)方法是最常用的确定性模型之一,其计算精度受两个参数的影响:搜索半径和反向距离功率值。然而,这两个参数通常由人类设定,没有科学的基础。为此,我们介绍了“相关距离”的概念,以分析地质钻孔升降值之间的相关性,并计算每个层高度的相关距离。相关系数被定义为与采样间隔的相关距离与采样间隔的比率确定,其确定了估计点内插邻域。我们分析了插值邻域中的距离衰减关系以校正重量功率值。选择采样点以验证计算。我们得出结论,根据内插邻域中的采样点的分布,每个估计点应给出不同的权重功率值。当空间变异性大时,改进的IDW方法比一般IDW和普通的克里格化方法更好。

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