Geostatistics for Natural Resources EvaluationThis text fulfills a need for an advancedlevel 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. 
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geastatistics
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A good book for geostatistics
Contents
Introduction  3 
Exploratory data analysis  9 
The random function model  59 
Inference and modeling  75 
Accounting for a single attribute  125 
Accounting for secondary information  185 
Common terms and phrases
1.6 Distance km algorithms anisotropy Argovian bottom graph ccdf ccdf models ccdf values Cd data Cd values cokriging estimator cokriging system cokriging weights colocated computed constraint contaminated correlogram covariance function covariance model cross covariance cross semivariogram cumulative distribution function dashed line data locations data values datum error variance example experimental Figure Gaussian geostatistics hscattergram histogram indicator data indicator kriging indicator semivariograms interpolation Journel Kimmeridgian kriging estimate kriging system kriging weights linear combination linear model maps matrix mean measure metal concentrations model of coregionalization NESW transect normal score OK estimates ordinary cokriging ordinary kriging positive semidefinite posterior probabilities prior probabilities realizations relation rock types sample search neighborhood secondary data secondary information secondary variables semivari semivariogram model sequential simple cokriging simple kriging simulated annealing simulated values stationary statistics study area threshold values top graph transform trend component trend estimate uncertainty variogram zvalues z(ua zero
Popular passages
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Page 470  Voltz. 1992. Linear coregionalization model: Tools for estimation and choice of crossvariogram matrix. Mathematical Geology, 24(3):269286.
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, 105120.
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 109209. Clarendon Press, Oxford.
Page 473  C., 1987, Conditional simulation of the geometry of fluviodeltaic 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 Distributionfree Geostatistics.