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- W7266772 abstract "Accurate information about autocorrelation is important in classifying reservoirs or in modeling fluid flow in permeable media. However, our knowledge of autocorrelation is based on one-dimensional constructs derived from time-series analysis of geostatistics. Little is known about how well these tools apply to multidimensional fields. This work studies the bias and standard deviation of autocorrelation estimates using both analytical and numerical methods and then extends this information to multiple dimensions. The authors show that the bias of the sample autocovariance function is significant at high correlation. The reduced form of the autocovariance function estimate further under-estimates the correlation for highly correlated data. The variogram is more accurate when the correlation is high and separation distance is small. The dimensionless sample span, the total sample span divided by the correlation length, determines both the bias and the standard deviation of the autocorrelation estimates when data are highly correlated. At medium correlation length a higher dimensionality reduces both the bias and the standard deviation. The bias may still be significant, and various estimates should be used to obtain a more accurate function. When the correlation length is small, the reduced autocovariance function estimate offers a small standard deviation without increasing the bias." @default.
- W7266772 created "2016-06-24" @default.
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- W7266772 date "2007-12-01" @default.
- W7266772 modified "2023-10-16" @default.
- W7266772 title "The Accuracy of Autocorrelation Estimates" @default.
- W7266772 doi "https://doi.org/10.1142/9789812770851_0005" @default.
- W7266772 hasPublicationYear "2007" @default.
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