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Record Nr. |
UNINA9911006576403321 |
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Autore |
Remy Nicolas <1975-> |
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Titolo |
Applied geostatistics with SGeMS : a user's guide / / Nicolas Remy, Alexandre Boucher and Jianbing Wu |
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Pubbl/distr/stampa |
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Cambridge : , : Cambridge University Press, , 2009 |
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ISBN |
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1-139-15437-0 |
1-107-19010-X |
1-139-23479-X |
1-283-34099-2 |
9786613340993 |
1-139-15997-6 |
1-139-16097-4 |
1-139-15541-5 |
1-139-15716-7 |
1-139-15892-9 |
1-139-15001-4 |
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Descrizione fisica |
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1 online resource (xix, 264 pages) : digital, PDF file(s) |
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Disciplina |
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Soggetti |
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Geological modeling - Computer simulation |
Geological modeling - Statistical methods |
Geology - Computer simulation |
Geology - Statistical methods |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- General overview -- Geostatistics : a recall of concepts -- Data sets and SGeMS EDA tools -- Variogram computation and modeling -- Common parameter input interfaces -- Estimation algorithms -- Stochastic simulation algorithms -- Utilities -- Scripting, commands and plug-ins. |
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Sommario/riassunto |
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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 |
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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. |
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