Declustering of Clustered Preferential Sampling for?Histogram and Semivariogram Inference |
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| Authors: | Ricardo A Olea |
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| Institution: | (1) Department of Petroleum Engineering, Stanford University, Stanford, 94305, USA;(2) Present address: U.S. Geological Survey, 12201 Sunrise Valley Dr., MS 956, Reston, VA 20192, USA |
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| Abstract: | Measurements of attributes obtained more as a consequence of business ventures than sampling design frequently result in samplings
that are preferential both in location and value, typically in the form of clusters along the pay. Preferential sampling requires
preprocessing for the purpose of properly inferring characteristics of the parent population, such as the cumulative distribution
and the semivariogram. Consideration of the distance to the nearest neighbor allows preparation of resampled sets that produce
comparable results to those from previously proposed methods. A clustered sampling of size 140, taken from an exhaustive sampling,
is employed to illustrate this approach. |
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| Keywords: | Cluster Preferential sampling Histogram Semivariogram |
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