Geostatistics for Natural Resources EvaluationThis text fulfills a need for an advanced-level work covering both the theory and application of geostatistics. It covers the most important areas of geostatistical methodology, introducing tools for description, quantitative modeling of spatial continuity, spatial prediction, and assessment of local uncertainty and stochastic simulation. It also details the theoretical background underlying most GSLIB programs. The tools are applied to an environmental data set, but the book includes a general presentation of algorithms intended for students and practitioners in such diverse fields as soil science, mining, petroleum, remote sensing, hydrogeology, and the environmental sciences. |
Contents
Introduction | 3 |
Inference and modeling | 75 |
Accounting for a single attribute | 125 |
Accounting for secondary information | 185 |
Assessment of spatial uncertainty | 369 |
Summary | 437 |
Appendixes | 443 |
The Jura data | 457 |
465 | |
477 | |
Common terms and phrases
1.6 Distance km algorithms anisotropy Argovian attribute bottom graph ccdf ccdf models ccdf values Cd concentration ppm Cd data Cd values cokriging estimator cokriging system cokriging weights colocated computed contaminated correlogram covariance function covariance model cross covariance cross semivariogram cumulative distribution function dashed line data locations data values datum example experimental Figure Gaussian geostatistics h-scattergram i(ua indicator data indicator kriging indicator semivariograms Journel Kimmeridgian kriging estimate kriging system kriging weights linear combination linear model location ua matrix mean measure model of coregionalization NE-SW transect normal score OK estimates ordinary cokriging ordinary kriging positive semi-definite posterior probabilities prior probabilities random realizations rock types sample secondary data secondary information secondary variables semivari semivariogram model simple cokriging simple kriging simulated annealing simulated values statistics study area threshold values top graph transform trend component trend estimate u₁ uncertainty variogram z-values z(ua zero
Popular passages
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Page 470 - Voltz. 1992. Linear coregionalization model: Tools for estimation and choice of cross-variogram matrix. Mathematical Geology, 24(3):269-286.
Page 468 - Galli, A. and Meunier, G. (1987). Study of a gas reservoir using the external drift method. In: G. Matheron and M. Armstrong (eds.), Geostatistical Case Studies, 105-120.
Page 470 - P., 1993. Study of spatial and temporal variations of hydrogeochemical variables using factorial kriging analysis. In: Scares, A.
Page 470 - Haldorsen, HH, PJ Brand, and CJ Macdonald. 1988. Review of the stochastic nature of reservoirs. In S. Edwards and PR King, editors, Mathematics in Oil Production, pages 109-209. Clarendon Press, Oxford.
Page 473 - C., 1987, Conditional simulation of the geometry of fluvio-deltaic reservoirs: SPE Paper 16753, presented at the 62nd Annual Technical Conference and Exhibition of the SPE, Dallas.
Page 470 - Isaaks, EH 1984. Risk Qualified Mappings for Hazardous Waste Sites: A Case Study in Distribution-free Geostatistics.