Leuangthong / Khan / Deutsch Solved Problems in Geostatistics

1. Auflage 2011
ISBN: 978-1-118-21051-2
Verlag: John Wiley & Sons
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 216 Seiten, E-Book

This unique book presents a learn-by-doing introduction togeostatistics.
Geostatistics provides the essential numerical tools foraddressing research problems that are encountered in fields ofstudy such as geology, engineering, and the earth sciences.Illustrating key methods through both theoretical and practicalexercises, Solved Problems in Geostatistics is a valuableand well-organized collection of worked-out problems that allow thereader to master the statistical techniques for modeling data inthe geological sciences.
The book's scope of coverage begins with the elements fromstatistics and probability that form the foundation of mostgeostatistical methodologies, such as declustering, debiasingmethods, and Monte Carlo simulation. Next, the authors delve intothree fundamental areas in conventional geostatistics: covarianceand variogram functions; kriging; and Gaussian simulation. Finally,special topics are introduced through problems involving utilitytheory, loss functions, and multiple-point geostatistics.
Each topic is treated in the same clearly organized format.First, an objective presents the main concepts that will beestablished in the section. Next, the background and assumptionsare outlined, supplying the comprehensive foundation that isnecessary to begin work on the problem. A solution plandemonstrates the steps and considerations that have to be takenwhen working with the exercise, and the solution allows the readerto check their work. Finally, a remarks section highlights theoverarching principles and noteworthy aspects of the problem.
Additional exercises are available via a related Web site, whichalso includes data related to the book problems and softwareprograms that facilitate their resolution. Enforcing a trulyhands-on approach to the topic, Solved Problems inGeostatistics is an indispensable supplement for courses ongeostatistics and spatial statistics a the upper-undergraduate andgraduate levels.It also serves as an applied reference forpracticing professionals in the geosciences.

Autoren/Hrsg.

Leuangthong, Oy

Khan, K. Daniel

Deutsch, Clayton V.

Inhaltsverzeichnis

Preface and Acknowledgments.
1. Introduction.
1.1 Plan of this Book.
1.2 The Premise of Geostatistics.
1.3 Nomenclature.
2. Getting Comfortable with Probabilities.
2.1 Parametric Probability Distributions.
2.2 Variance of Linear Combinations.
2.3 Standardization and Probability Intervals.
3. Obtaining Representative Distributions.
3.1 Basic Declustering.
3.2 Debiasing with Bivariate Glaussian Distribution.
3.3 Comparison of Declustering Methods.
4. Monte Carlo Simulation.
4.1 Impact of the Central Limit Theorem.
4.2 Bootstrap and Spatial Bootstrap.
4.3 Transfer of Uncertainty.
5. Variograms and Volume Variance.
5.1 Geometric Anisotropy.
5.2 Variogram Calculation.
5.3 Variogram Modeling and Volume Variance.
6. Kriging.
6.1 Stationary Kriging.
6.2 Nonstationary Kriging.
6.3 Screening Effect of Kriging.
7. Gaussian Simulation.
7.1 Bivariate Gaussian Distribution.
7.2 Conditioning by Kriging.
7.3 Gaussian Simulation.
8. Indicators.
8.1 Variogram of Objects.
8.2 Indicator Variograms and the Gaussian Distribution.
8.3 Indicator Simulation for Categorical Data.
9. Multiple Variables.
9.1 Linear Model of Coregionalization.
9.2 Gaussian Cosimulation.
9.3 Multiscale Cokriging.
10. Special Topics.
10.1 Decision Making in the Presence of Uncertainty.
10.2 Trend Model Construction.
10.3 Multiple Point Statistics.
11. Closing Remarks.
Bibliography.
Index.

Über Autor(innen)

Oy Leuangthong, PhD, is Assistant Professor in theDepartment of Civil and Environmental Engineering at the Universityof Alberta, Canada. Dr. Leuangthong conducts extensive research onthe use of geostatistical methods for improving mineral resourcesand petroleum reservoirs.
K.Daniel Khan, PHD, is an Earth Scientist with ChevronCorporation, specializing in reservoir modeling. Dr. Khan's workfocuses on modeling heterogeneity and fluid flow processes usinggeostatistical and inverse techniques.
Clayton V. Deutsch, PHD, is Professor in the Departmentof Civil and Environmental Engineering at the University ofAlberta, where he is also Director of the School of Mining andPetroleum Engineering. He has over twenty years of experience inboth academia and industry. Dr. Deutsch has published over 100articles in his areas of research interest, which include modelingheterogeneity and uncertainty in petroleum reservoirs and mineraldeposits.