Solved Problems in Geostatistics

Solved Problems in Geostatistics
Author: Oy Leuangthong
Publisher: John Wiley & Sons
Total Pages: 145
Release: 2011-09-20
Genre: Mathematics
ISBN: 1118210514

This unique book presents a learn-by-doing introduction to geostatistics. Geostatistics provides the essential numerical tools for addressing research problems that are encountered in fields of study such as geology, engineering, and the earth sciences. Illustrating key methods through both theoretical and practical exercises, Solved Problems in Geostatistics is a valuable and well-organized collection of worked-out problems that allow the reader to master the statistical techniques for modeling data in the geological sciences. The book's scope of coverage begins with the elements from statistics and probability that form the foundation of most geostatistical methodologies, such as declustering, debiasing methods, and Monte Carlo simulation. Next, the authors delve into three fundamental areas in conventional geostatistics: covariance and variogram functions; kriging; and Gaussian simulation. Finally, special topics are introduced through problems involving utility theory, 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 be established in the section. Next, the background and assumptions are outlined, supplying the comprehensive foundation that is necessary to begin work on the problem. A solution plan demonstrates the steps and considerations that have to be taken when working with the exercise, and the solution allows the reader to check their work. Finally, a remarks section highlights the overarching principles and noteworthy aspects of the problem. Additional exercises are available via a related Web site, which also includes data related to the book problems and software programs that facilitate their resolution. Enforcing a truly hands-on approach to the topic, Solved Problems in Geostatistics is an indispensable supplement for courses on geostatistics and spatial statistics a the upper-undergraduate and graduate levels.It also serves as an applied reference for practicing professionals in the geosciences.

Geostatistics for Environmental Scientists

Geostatistics for Environmental Scientists
Author: Richard Webster
Publisher: John Wiley & Sons
Total Pages: 330
Release: 2007-10-22
Genre: Mathematics
ISBN: 9780470517260

Geostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes – such as the distribution of pollution – vary. The techniques used in geostatistics are ideally suited to the needs of environmental scientists, who use them to make the best of sparse data for prediction, and top plan future surveys when resources are limited. Geostatistical technology has advanced much in the last few years and many of these developments are being incorporated into the practitioner’s repertoire. This second edition describes these techniques for environmental scientists. Topics such as stochastic simulation, sampling, data screening, spatial covariances, the variogram and its modeling, and spatial prediction by kriging are described in rich detail. At each stage the underlying theory is fully explained, and the rationale behind the choices given, allowing the reader to appreciate the assumptions and constraints involved.

Geostatistical Reservoir Modeling

Geostatistical Reservoir Modeling
Author: Michael J. Pyrcz
Publisher: Oxford University Press
Total Pages: 449
Release: 2014-04-16
Genre: Mathematics
ISBN: 0199358834

Published in 2002, the first edition of Geostatistical Reservoir Modeling brought the practice of petroleum geostatistics into a coherent framework, focusing on tools, techniques, examples, and guidance. It emphasized the interaction between geophysicists, geologists, and engineers, and was received well by professionals, academics, and both graduate and undergraduate students. In this revised second edition, Deutsch collaborates with co-author Michael Pyrcz to provide an expanded (in coverage and format), full color illustrated, more comprehensive treatment of the subject with a full update on the latest tools, methods, practice, and research in the field of petroleum Geostatistics. Key geostatistical concepts such as integration of geologic data and concepts, scale considerations, and uncertainty models receive greater attention, and new comprehensive sections are provided on preliminary geological modeling concepts, data inventory, conceptual model, problem formulation, large scale modeling, multiple point-based simulation and event-based modeling. Geostatistical methods are extensively illustrated through enhanced schematics, work flows and examples with discussion on method capabilities and selection. For example, this expanded second edition includes extensive discussion on the process of moving from an inventory of data and concepts through conceptual model to problem formulation to solve practical reservoir problems. A greater number of examples are included, with a set of practical geostatistical studies developed to illustrate the steps from data analysis and cleaning to post-processing, and ranking. New methods, which have developed in the field since the publication of the first edition, are discussed, such as models for integration of diverse data sources, multiple point-based simulation, event-based simulation, spatial bootstrap and methods to summarize geostatistical realizations.

Introduction to Geostatistics

Introduction to Geostatistics
Author: P. K. Kitanidis
Publisher: Cambridge University Press
Total Pages: 276
Release: 1997-05-13
Genre: Science
ISBN: 9780521587471

Engineers and applied geophysicists routinely encounter interpolation and estimation problems when analysing data from field observations. Introduction to Geostatistics presents practical techniques for the estimation of spatial functions from sparse data. The author's unique approach is a synthesis of classic and geostatistical methods with a focus on the most practical linear minimum-variance estimation methods, and includes suggestions on how to test and extend the applicability of such methods. The author includes many useful methods (often not covered in other geostatistics books) such as estimating variogram parameters, evaluating the need for a variable mean, parameter estimation and model testing in complex cases (e.g. anisotropy, variable mean, and multiple variables), and using information from deterministic mathematical models. Well illustrated with exercises and worked examples taken from hydrogeology, Introduction to Geostatistics assumes no background in statistics and is suitable for graduate-level courses in earth sciences, hydrology, and environmental engineering, and also for self-study.

Applied Geostatistics with SGeMS

Applied Geostatistics with SGeMS
Author: Nicolas Remy
Publisher: Cambridge University Press
Total Pages: 302
Release: 2011-04-14
Genre: Science
ISBN: 1139473468

The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying theory, demonstrates their implementation, discusses their potential limitations, and helps the user make an informed decision about the choice of one algorithm over another. Users can complete complex tasks using the embedded scripting language, and new algorithms can be developed and integrated through the SGeMS plug-in mechanism. SGeMS was the first software to provide algorithms for multiple-point statistics, and the book presents a discussion of the corresponding theory and applications. Incorporating the full SGeMS software (now available from www.cambridge.org/9781107403246), this book is a useful user-guide for Earth Science graduates and researchers, as well as practitioners of environmental mining and petroleum engineering.

Basic Steps in Geostatistics: The Variogram and Kriging

Basic Steps in Geostatistics: The Variogram and Kriging
Author: Margaret A. Oliver
Publisher: Springer
Total Pages: 106
Release: 2015-03-30
Genre: Technology & Engineering
ISBN: 3319158651

This brief will provide a bridge in succinct form between the geostatistics textbooks and the computer manuals for `push-button' practice. It is becoming increasingly important for practitioners, especially neophytes, to understand what underlies modern geostatistics and the currently available software so that they can choose sensibly and draw correct conclusions from their analysis and mapping. The brief will contain some theory, but only that needed for practitioners to understand the essential steps in analyses. It will guide readers sequentially through the stages of properly designed sampling, exploratory data analysis, variography (computing the variogram and modelling it), followed by ordinary kriging and finally mapping kriged estimates and their errors. There will be short section on trend and universal kriging. Other types of kriging will be mentioned so that readers can delve further in the substantive literature to tackle more complex tasks.

Practical geostatistics

Practical geostatistics
Author: Simon Houlding
Publisher: Springer Science & Business Media
Total Pages: 180
Release: 2000-06-08
Genre: Mathematics
ISBN: 9783540668206

Presents a set of linked HTML documents on the application of geostatistical theory, designed to be viewed and navigated with an Internet browser.

Geostatistics

Geostatistics
Author: M. Armstrong
Publisher: Springer Science & Business Media
Total Pages: 1059
Release: 2013-12-11
Genre: Science
ISBN: 9401568448

ACKNOWLEDGEMENTS xvii LIST OF PARTICIPANTS xix PLENARY SESSIQNS KRIGE D.G., GUARASCIO M. and CAMISANI-CALZOLARI F.A. Early South African qeostatistical techniques in today's perspective ... 1 MATHERON G. The internal consistency of models in qeostatistics ... 21 MONESTIEZ P., HABIB R. and AUDERGON J.M. Estimation de la covariance et du varioqramme pour une fonction aleatoire a support arborescent : application a l'etude des arbres fruitiers ... 39 CHILES J.P. Modelisation qeostatistique de reseaux de fractures ... 57 BRUNO R. and RASPA G. Geostatistical characterization of fractal models of surfaces 17 RIVOIRARD J. Models with orthoqonal indicator residuals ... 91 OMRE H., HALVORSEN K.B. and BERTEIG V.A Bayesian approach to kriqinq ... 109 THEQRY I SWITZER P. Non-stationary spatial covariances estimated from monitorinq data ... 127 CHAUVET P. Quelques aspects de l'analyse structurale des FAI-k a 1 dimension ... 139 vi TABLE OF CONTENTS DOWD P.A. Generalised cross-covariances ... 151 CRESSIE N. The many faces of spatial prediction ..-- ... - ... --.-.-..-. 163 OBLED C. & BRAUD I. Analogies entre geostatistique et analyse en composantes principales de processus ou analyse EOFs ... 177 THEORY II JEULIN D. Sequential random functions models ... 189 CHAUTRU J.M. The use of Boolean random functions in geostatistics -.--.-- ... 201 SOARES A.O. Use of a mathematical morphology tool in characterizing covariance & of indicator data ... 213 ALLISON H.J. Regularization in geostatistics and in ill-posed inversed problems ... - . . - . - . . - ... - - ... 225 DONG A.

Statistics for Spatial Data

Statistics for Spatial Data
Author: Noel Cressie
Publisher: John Wiley & Sons
Total Pages: 931
Release: 2015-03-18
Genre: Mathematics
ISBN: 1119115183

The Wiley Classics Library consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. Spatial statistics — analyzing spatial data through statistical models — has proven exceptionally versatile, encompassing problems ranging from the microscopic to the astronomic. However, for the scientist and engineer faced only with scattered and uneven treatments of the subject in the scientific literature, learning how to make practical use of spatial statistics in day-to-day analytical work is very difficult. Designed exclusively for scientists eager to tap into the enormous potential of this analytical tool and upgrade their range of technical skills, Statistics for Spatial Data is a comprehensive, single-source guide to both the theory and applied aspects of spatial statistical methods. The hard-cover edition was hailed by Mathematical Reviews as an "excellent book which will become a basic reference." This paper-back edition of the 1993 edition, is designed to meet the many technological challenges facing the scientist and engineer. Concentrating on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, revealing how design, inference, and diagnostics are an outgrowth of that link. It then explores new methods to reveal just how spatial statistical models can be used to solve important problems in a host of areas in science and engineering. Discussion includes: Exploratory spatial data analysis Spectral theory for stationary processes Spatial scale Simulation methods for spatial processes Spatial bootstrapping Statistical image analysis and remote sensing Computational aspects of model fitting Application of models to disease mapping Designed to accommodate the practical needs of the professional, it features a unified and common notation for its subject as well as many detailed examples woven into the text, numerous illustrations (including graphs that illuminate the theory discussed) and over 1,000 references. Fully balancing theory with applications, Statistics for Spatial Data, Revised Edition is an exceptionally clear guide on making optimal use of one of the ascendant analytical tools of the decade, one that has begun to capture the imagination of professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology.