Cover of: Plurigaussian Simulations in Geosciences | Margaret Armstrong

Plurigaussian Simulations in Geosciences

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Springer-Verlag Berlin Heidelberg , Berlin, Heidelberg
Mathematical geography, Geog
Statementby Margaret Armstrong, Alain Galli, Hélène Beucher, Gaelle Loc"h, Didier Renard, Brigitte Doligez, Rémi Eschard, Francois Geffroy
ContributionsGalli, Alain, Beucher, Hélène, Loc"h, Gaelle, Renard, Didier, Doligez, Brigitte, Eschard, Rémi, Geffroy, François, SpringerLink (Online service)
The Physical Object
Format[electronic resource] /
ID Numbers
Open LibraryOL25546306M
ISBN 139783642196065, 9783642196072

About this book 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). 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 : Hardcover. Plurigaussian Simulations in Geosciences - Kindle edition by Margaret Armstrong, Alain Galli, Hélène Beucher, Gaelle Loc'h, Didier Renard, Brigitte Doligez, Rémi Eschard, Francois Geffroy.

Download it once and read it on your Kindle device, PC, phones or tablets. 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. Buy Plurigaussian Simulations in Geosciences () (): NHBS - Margaret Armstrong, Alain Galli, Hélène Beucher, Gaëlle Le Loc'h, Didier Renard, Brigitte Doligez, Rémi Eschard, François Geffroy, Springer NaturePrice Range: £ - £ Plurigaussian Simulations in Geosciences focuses on the last type of simulation.

It presents the theory required to understand the method, along with the practical examples of applications in mining and and the oil industry as well as tutorial examples. 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 : Springer Berlin Heidelberg.

Simulation is the fastest developing branch in geostatistics, and simulating the facies inside reservoirs and orebodies is the most exciting part of this. Several methods have been developed to do this (sequential indicator simulations, Boolean methods, Markov chains and plurigaussian simulations).

This book focuses on the last type of simulation. Main Plurigaussian Simulations in Geosciences Plurigaussian Simulations in Geosciences Dr. Margaret Armstrong, Dr. Alain G. Galli, Dr. Gaëlle Le Loc’h, Dr. François Geffroy, Dr. Rémi Eschard (auth.). The plurigaussian model is currently used for simulating geological domains (facies) in petroleum reservoirs and mineral deposits, with the aim of assessing the uncertainty in the domain boundaries and of improving the geological controls in the characterization of quantitative attributes.

Plurigaussian Simulation Method (Le Loc'h et al., ; Armstrong et al., ) is an extension of the Truncated Gaussian Method but based on the simultaneous truncation of several multigaussian variables thus allowing the simulation of different facies displaying different spatial anisotropies.

Plurigaussian Simulations in Geosciences. Springer, Berlin. Google Scholar; Betzhold and Roth, Characterizing the mineralogical variability of a Chilean copper deposit using plurigaussian simulations. Journal of the South African Institute of Mining and Metallurgy.

v i2. Google Scholar; Beucher et al,   The plurigaussian model is currently used for simulating geological domains (facies) in petroleum reservoirs and mineral deposits, with the aim of assessing the uncertainty in the domain boundaries and of improving the geological controls in the characterization of quantitative attributes.

This paper discusses the main aspects of the model and provides a set of computer programs to perform. 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. PluriGaussian simulation aims at constructing realizations of a categorical variable (a rock type in the present case), represented by the truncation of one or more Gaussian random fields.

Plurigaussian simulations in geosciences. [Margaret Armstrong] -- Simulation is the fastest developing branch of geostatistics and simulating facies inside reservoirs.

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. Truncated plurigaussian simulation is a useful method for simulating spatial categorical variables, such as facies, in a geological context. The method is an extension of the truncated Gaussian method that retains the main advantages of the latter (mainly that it produces permissible sets of indicator semi-variograms and cross-semi-variograms) but overcomes its limitations (the truncated Cited by: simulation.

The commonly applied indicator kriging (IK) and sequential indicator simulation (SIS) algorithms are compared in a non-sedimentary gold deposit environment to the more computationally demanding and more complex plurigaussian simulation (PGS).

Comparisons between the three models are made by examining. Plurigaussian Simulations in Geosciences. Springer, Berlin. Google Scholar; Bahar and Kelkar, Journey from well logs/cores to integrated geological and petrophysical properties simulation: a methodology and application.

SPE Reservoir Evaluation and Engineering. v3 i5.

Description Plurigaussian Simulations in Geosciences FB2

Google Scholar; Chil$#;s and Delfiner, Author: EmeryXavier, A SilvaDaniel. Optimizing Thresholds in Truncated Pluri-Gaussian Simulation.

Samaneh Sadeghi and Jeff B. Boisvert. Truncated pluri-Gaussian simulation (TPGS) is an extension of truncated Gaussian simulation.

Plurigaussian Simulations in Geosciences, Berlin Heidelberg New York, pp. Deutsch, C.V., and Journel, A. J.,Geostatistical software File Size: KB. Truncated plurigaussian simulations The mathematical theory underlying the truncated gaussian (Matheron et al.

Details Plurigaussian Simulations in Geosciences EPUB

) and the truncated plurigaussian (Le Loc'h and Galli ) methods is described in detail in the book of Armstrong et al. () or in the. This paper focuses on the general work flow developed for the geological characterization and geocellular modeling of the Albian carbonate reservoirs (), and the application of this work flow in one of these important oil work flow is being used in a long term training program through an agreement between PETROBRAS and UNESP (São Paulo State University).

Books. Armstrong is the author of the textbook Basic Linear Geostatistics (Springer, ), and co-author of the book Plurigaussian Simulations in Geosciences (Springer, ; 2nd ed., ). With Matheron, she edited Geostatistical Case Studies (Springer, ).

Recognition. 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. Books > Earth Sciences. Plurigaussian Simulations In Geosciences. More Books by Margaret Armstrong See All. Murder in Stained Glass. Field Book of Western Wild Flowers.

Il mistero della vetreria. Plurigaussian Simulations in Geosciences. More ways to shop: Find an Apple Store or other retailer near you. Or call MY-APPLE. Choose your country or region. More Books by Margaret Armstrong See All. Field Book of Western Wild Flowers.

Il mistero della vetreria. Murder in Stained Glass. Plurigaussian Simulations in Geosciences. More ways to shop: Find an Apple Store or other retailer near you.

Or call MY-APPLE/5(26). Geosciences 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. All Books. Back to the front page of the bibliography. Geomodeling. GSLIB.

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Reservoir Simulation: History Matching and Forecasting. Fractured Vuggy Carbonate Reservoir Simulation. Plurigaussian Simulations in Geosciences. Reservoir Model Design. Geostatistical Reservoir Modeling. Simulation is the fastest developing branch in geostatistics, and simulating the facies inside reservoirs and orebodies is the most exciting part of this.

Several methods have been developed to do this (sequential indicator simulations, Boolean methods, Markov chains and plurigaussian simulations). This book focuses on the last type of simulation.

Several methods including sequential indicator simulation (SIS) [23,24], truncated Gaussian simulation (TGS) [25,26], plurigaussian simulation (PGS) [27,28] and multiple-point simulation (MPS) [29,30] are extensively employed in modeling domains.See all books authored by Margaret Armstrong, including Western Wild Flowers, and The Storyteller's Pack: A Frank R.

Stockton Reader, and more on Plurigaussian Simulations in Geosciences. Margaret Armstrong $ - $ Wanted -- A Chaperon. Margaret Armstrong $ - $ Sonnets from the Portuguese. A single non-conditional simulation, and a median of 10 non-conditional simulations of permeability A single 10% conditional simulation, and a median of 10, 10% conditional simulations of permeability A single 50% conditional simulation, and a median of 10, 50% conditional simulations of permeability.