Nearest-neighbor classification for facies delineation
2007
Tartakovsky, D.M. | Wohlberg, B. | Guadagnini, A.
1 Geostatistics has become the dominant tool for probabilistic estimation of properties of heterogeneous formations at points where data are not available. Ordinary kriging, the starting point in the development of other geostatistical techniques, has a number of serious limitations, chief among which is the intrinsic hypothesis of the (second-order) stationarity of the underlying random field. Attempts to overcome this limitation have led to the development of ever more complex flavors of kriging. We pursue an opposite strategy that consists of finding the simplest possible technique that is adequate for the task of facies delineation. Guided by the principle of parsimony, we identify nearest-neighbor classification (NNC) as a viable alternative to geostatistics among deterministic techniques. We demonstrate that when used for the purpose of facies delineation, NNC, which has no fitting parameters and operational assumptions, outperforms indicator kriging, which has several parameters.
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