Geostatistical Simulation Models and Algorithms / [electronic resource] :
by Christian Lantuejoul.
- 1st ed. 2002.
- XIII, 256 p. 232 illus., 76 illus. in color. online resource.
1. Introduction -- 2. Investigating stochastic models -- 3. Variographic tools -- 4. The integral range -- 5. Basic morphological concepts -- 6. Stereology: some basic notions -- 7. Basics about simulations -- 8. Iterative algorithms for simulation -- 9. Rate of convergence of iterative algorithms -- 10. Exact simulations -- 11. Point processes -- 12. Tessellations -- 13. Boolean model -- 14. Object based models -- 15. Gaussian random function -- 16. Gaussian variations -- 17. Substitution random functions.
Within the geoscience community the estimation of natural resources is a challenging topic. The difficulties are threefold: Intitially, the design of appropriate models to take account of the complexity of the variables of interest and their interactions. This book discusses a wide range of spatial models, including random sets and functions, point processes and object populations. Secondly,the construction of algorithms which reproduce the variability inherent in the models. Finally, the conditioning of the simulations for the data, which can considerably reduce their variability. Besides the classical algorithm for gaussian random functions, specific algorithms based on markovian iterations are presented for conditioning a wide range of spatial models (boolean model, Voronoi tesselation, substitution random function etc.) This volume is the result of a series of courses given in the USA and Latin America to civil, mining and petroleum engineers, as well as to gradute students is statistics. It is the first book to discuss geostatistical simulation techniques in such a systematic way.
9783662048085
10.1007/978-3-662-04808-5 doi
Statistics . Environmental monitoring. Mineralogy. Geophysics. Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. Environmental Monitoring. Mineralogy. Geophysics.