Geostatistical Simulations

Geostatistical Simulations
Author: M. Armstrong
Publisher: Springer Science & Business Media
Total Pages: 258
Release: 2013-06-29
Genre: Mathematics
ISBN: 940158267X

When this two-day meeting was proposed, it was certainly not conceived as a celebration, much less as a party. However, on reflection, this might have been a wholly appropriate gesture because geostatistical simulation came of age this year: it is now 21 years since it was first proposed and implemented in the form of the turning bands method. The impetus for the original development was the mining industry, principally the problems encountered in mine planning and design based on smoothed estimates which did not reflect the degree of variability and detail present in the real, mined values. The sustained period of development over recent years has been driven by hydrocarbon applications. In addition to the original turning bands method there are now at least six other established methods of geostatistical simulation. Having reached adulthood, it is entirely appropriate that geostatistical simulation should now be subjected to an intense period of reflection and assessment. That we have now entered this period was evident in many of the papers and much of the discussion at the Fontainebleau meeting. Many questions were clearly articulated for the first time and, although many ofthem were not unambiguously answered, their presentation at the meeting and publication in this book will generate confirmatory studies and further research.

Geostatistical Simulation

Geostatistical Simulation
Author: Christian Lantuejoul
Publisher: Springer Science & Business Media
Total Pages: 262
Release: 2013-06-29
Genre: Mathematics
ISBN: 3662048086

This book deals with the estimation of natural resources using the Monte Carlo methodology. It includes a set of tools to describe the morphological, statistical and stereological properties of spatial random models. Furthermore, the author presents a wide range of spatial models, including random sets and functions, point processes and object populations applicable to the geosciences. The text is based on a series of courses given in the USA and Latin America to civil, mining and petroleum engineers as well as graduate students in statistics. It is the first book to discuss the geostatistical simulation techniques in such a specific way.

Spatial and Spatio-Temporal Geostatistical Modeling and Kriging

Spatial and Spatio-Temporal Geostatistical Modeling and Kriging
Author: José-María Montero
Publisher: John Wiley & Sons
Total Pages: 400
Release: 2015-08-18
Genre: Mathematics
ISBN: 1118762436

Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R. This book includes: Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods. The most innovative developments in the different steps of the kriging process. An up-to-date account of strategies for dealing with data evolving in space and time. An accompanying website featuring R code and examples

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.

Geostatistics

Geostatistics
Author: Jean-Paul Chilès
Publisher: John Wiley & Sons
Total Pages: 750
Release: 2012-02-08
Genre: Mathematics
ISBN: 1118136179

Praise for the First Edition ". . . a readable, comprehensive volume that . . . belongs on the desk, close at hand, of any serious researcher or practitioner." Mathematical Geosciences The state of the art in geostatistics Geostatistical models and techniques such as kriging and stochastic multi-realizations exploit spatial correlations to evaluate natural resources, help optimize their development, and address environmental issues related to air and water quality, soil pollution, and forestry. Geostatistics: Modeling Spatial Uncertainty, Second Edition presents a comprehensive, up-to-date reference on the topic, now featuring the latest developments in the field. The authors explain both the theory and applications of geostatistics through a unified treatment that emphasizes methodology. Key topics that are the foundation of geostatistics are explored in-depth, including stationary and nonstationary models; linear and nonlinear methods; change of support; multivariate approaches; and conditional simulations. The Second Edition highlights the growing number of applications of geostatistical methods and discusses three key areas of growth in the field: New results and methods, including kriging very large datasets; kriging with outliers; nonse??parable space-time covariances; multipoint simulations; pluri-gaussian simulations; gradual deformation; and extreme value geostatistics Newly formed connections between geostatistics and other approaches such as radial basis functions, Gaussian Markov random fields, and data assimilation New perspectives on topics such as collocated cokriging, kriging with an external drift, discrete Gaussian change-of-support models, and simulation algorithms Geostatistics, Second Edition is an excellent book for courses on the topic at the graduate level. It also serves as an invaluable reference for earth scientists, mining and petroleum engineers, geophysicists, and environmental statisticians who collect and analyze data in their everyday work.

Multiple-point Geostatistics

Multiple-point Geostatistics
Author: Professor Gregoire Mariethoz
Publisher: John Wiley & Sons
Total Pages: 376
Release: 2014-10-16
Genre: Science
ISBN: 1118662938

This book provides a comprehensive introduction to multiple-point geostatistics, where spatial continuity is described using training images. Multiple-point geostatistics aims at bridging the gap between physical modelling/realism and spatio-temporal stochastic modelling. The book provides an overview of this new field in three parts. Part I presents a conceptual comparison between traditional random function theory and stochastic modelling based on training images, where random function theory is not always used. Part II covers in detail various algorithms and methodologies starting from basic building blocks in statistical science and computer science. Concepts such as non-stationary and multi-variate modeling, consistency between data and model, the construction of training images and inverse modelling are treated. Part III covers three example application areas, namely, reservoir modelling, mineral resources modelling and climate model downscaling. This book will be an invaluable reference for students, researchers and practitioners of all areas of the Earth Sciences where forecasting based on spatio-temporal data is performed.

Geostatistics for Seismic Data Integration in Earth Models

Geostatistics for Seismic Data Integration in Earth Models
Author: Olivier Dubrule
Publisher: SEG Books
Total Pages: 282
Release: 2003
Genre: Science
ISBN: 1560801212

Geostatistics is used not only in reservoir characterization but also in velocity analysis, time-to-depth conversion, seismic inversion, uncertainty quantification, and data integration in earth models. This book includes covariance and the variogram, interpolation, heterogeneity modelling, uncertainty quantification, and geostatistical inversion.

Model-based Geostatistics

Model-based Geostatistics
Author: Peter Diggle
Publisher: Springer Science & Business Media
Total Pages: 242
Release: 2007-05-26
Genre: Science
ISBN: 0387485368

This volume is the first book-length treatment of model-based geostatistics. The text is expository, emphasizing statistical methods and applications rather than the underlying mathematical theory. Analyses of datasets from a range of scientific contexts feature prominently, and simulations are used to illustrate theoretical results. Readers can reproduce most of the computational results in the book by using the authors' software package, geoR, whose usage is illustrated in a computation section at the end of each chapter. The book assumes a working knowledge of classical and Bayesian methods of inference, linear models, and generalized linear models.

Plurigaussian Simulations in Geosciences

Plurigaussian Simulations in Geosciences
Author: Margaret Armstrong
Publisher: Springer Science & Business Media
Total Pages: 182
Release: 2011-08-12
Genre: Science
ISBN: 3642196071

Simulation is the fastest developing branch of geostatistics and simulating facies inside reservoirs and orebodies is the most exciting part of this. Several methods have been developed to do this (sequential indicator simulations, Boolean simulations, Markov chains and plurigaussian simulations). This book focuses on the last type of simulations. It presents the theory required to understand the method, along practical examples of applications in mining and the oil industry as well as tutorial exercises. Demonstration software to illustrate how these simulations work is available on http://pluridemo.geosciences.mines-paristech.fr Since the publication of the first edition, enormous numbers of papers have appeared in the literature on the subject. Plurigaussian simulations are now the preferred method for simulating facies in both mining & the oil industry. The new edition contains new case studies in both mining & petroleum, together with an extensively updated theory section.

Geostatistics and Petroleum Geology

Geostatistics and Petroleum Geology
Author: Michael Hohn
Publisher: Springer Science & Business Media
Total Pages: 252
Release: 1998-11-30
Genre: Mathematics
ISBN: 9780412757808

This is an extensive revision of a book that I wrote over ten years ago. My purpose then has remained unchanged: to introduce the concepts and methods of spatial statistics to geologists and engineers working with oil and gas data. I believe I have accomplished more than that; just as I learned the basics of variography and kriging from books for mining engineers, this book could be used by scientists from many fields to learn the basics of the subject. I have tried to adopt an introductory and practical approach to the subject, knowing that books that detail the theory are available. What I say and write comes from my own experience. As a geologist working in the public sector, I have had the privilege of using geostatistics in funded research, in answering service requests from industry, and in short courses. I have taught geostatistics in the university classroom, and advised graduate students in theses and dissertations. I have attempted to anticipate the needs and questions of the enquiring scientist because I was there myself, and know the kind of questions and concerns I had at the time I was trying to learn the subject.