Titlebook: Geostatistics and Petroleum Geology; Michael Edward Hohn Book 1988 Springer Science+Business Media New York 1988 Kriging.geology.geoscienc

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CUMB

Linear Estimation,s, to drawing flat surfaces within triangulations, all requiring some criterion to be satisfied. The geologist working by hand interpolates between pairs of points, draws connecting contours, does some smoothing to make the map look “real,” and perhaps works in some trends derived from geological ex

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Nonlinear Estimation,he expected precision of the estimates. However, some applications may call for knowledge of local spatial distributions. Placing confidence intervals around local estimates; stating the probability that a regionalized variable lies below, between, or above some values; computing mean values of a va

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More Detail, Less Certainty: Conditional Simulation,ch to mapping lies in the modeling of spatial covariance that precedes interpolation; semivariogram models derived from this step can make the final estimates sensitive to directional anisotropics present in the data. On the other hand, the smoothing property of kriging can also mean that one throws

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Hectic

From Indicator Variables to Nonparametric Estimation,inuous variable can be converted to an indicator variable for a number of thresholds, yielding a new variable for each threshold chosen; this procedure forms the basis for nonparametric estimation, described in the second part of this chapter.

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Overview of Geostatistics,that observed in nearby wells. The assumption that a variable like thickness is correlated with itself in space—i.e., autocorrelated—lies at the heart of contour mapping, whether by computer or by hand.

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The Semivariogram,res methods, practitioners recommend actual inspection of the observed semivariogram and the fitted model. A properly fitted model then allows the computer program to calculate linear estimates that reflect the spatial extent and orientation of autocorrelation in the variable to be mapped.