Abstract
The semivariogram is the basic geostatistical tool for visualizing, modeling, and exploiting the spatial autocorrelation of a regionalized variable. As the name implies, a semivariogram is a measure of variance. Although procedures exist for modeling the semivariogram through iterative or least-squares 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.
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References
Cressie, N., and D. M. Hawkins, 1980, Robust Estimation of the Variogram: I, Math. Geol. 12:115–125.
Danza Errico, J. C., 1986, Geostatistical Applications Using APL on Bauxite Deposits at Pogos de Caldas, Minas Gerais State, Brazil, 19th APCOM, 265–267.
Gumati, Y. D., and W. H. Kanes, 1985, Early Tertiary Subsidence and Sedimentary Facies—Northern Sirte Basin, Libya, Am. Assoc. Pet. Geol. Bull. 69:39–52.
Hawkins, D. M., 1980, Identification of Outliers, Chapman and Hall, London, 188p.
Hohn, M. E., and M. V. Fontana, 1986, Geostatistics and artificial intelligence applied to stratigraphic correlation, Am. Assoc. Pet. Geol. Bull. 70:601.
Huber, P. J., 1978, Robust Estimates of Location: Symmetry and Asymmetric Contamination, Ann. Math. Stat. 42:1020–1034.
Journel, A. G., and C. J. Huijbregts, 1978, Mining Geostatistics, Academic Press, London, 600 p.
Journel, A. G., 1983, Nonparametric Estimation of Spatial Distributions, Math Geol. 15:445–468.
Journel, A. G., and R. Froidevaux, 1982, Anisotropic Hole-Effect Modeling, Math. Geol. 14:217–247.
Krige, D. G., and E. J. Magri, 1982, Studies of the Effects of Outliers and Data Transformations on Variogram Estimates for a Base Metal and Gold Ore Body, Math. Geol. 14:557–564.
Myers, D. E., C. L. Begovich, T. R. Butz, and V. E. Kane, 1982, Variogram Models for Regional Groundwater Geochemical Data, Math. Geol. 14:629–644.
Neal, D., and B. Price, 1986, Oil and Gas Report and Maps of Lincoln, Logan, and Mingo Counties, West Virginia. W.V. Geol. and Econ. Survey Bull. B-41, 68 p.
Sharp, W. E., 1982a, Stochastic Simulation of Semivariograms, Math. Geol. 14:445–456.
Sharp, W. E., 1982b, Estimation of Semivariograms by the Maximum Entropy Method, Math. Geol. 14:457–474.
Sharp, W. E., 1982c, A Statistical Test for Exponential Semivariograms, American Statistical Association, Abstracts:55.
Taneja, V. S., and L. A. Aroian, 1980, Time Series in M Dimensions, Autoregressive Models, Commun. Stat., Simul. Comput. B9:491–513.
Williamson, N. L., 1974, Depositional environments of the Pocono Formation in Southern West Virginia, West Virginia University, unpublished Ph.D. dissertation, 127 p.
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© 1988 Van Nostrand Reinhold
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Hohn, M.E. (1988). The Semivariogram. In: Geostatistics and Petroleum Geology. Computer Methods in the Geosciences. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-7106-3_2
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DOI: https://doi.org/10.1007/978-1-4615-7106-3_2
Publisher Name: Springer, Boston, MA
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