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03360nam a22005295i 4500 |
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978-3-319-53201-1 |
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DE-He213 |
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20170408075150.0 |
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170408s2017 gw | s |||| 0|eng d |
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|a 9783319532011
|9 978-3-319-53201-1
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|a 10.1007/978-3-319-53201-1
|2 doi
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|a 526.1
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|a Azevedo, Leonardo.
|e author.
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|a Geostatistical Methods for Reservoir Geophysics
|h [electronic resource] /
|c by Leonardo Azevedo, Amílcar Soares.
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| 264 |
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1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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| 300 |
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|a XXVII, 141 p. 114 illus., 84 illus. in color.
|b online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
|b PDF
|2 rda
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| 490 |
1 |
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|a Advances in Oil and Gas Exploration & Production,
|x 2509-372X
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| 505 |
0 |
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|a Introduction -- Fundamental geostatistical tools for data integration -- Simulation Models of Physical Phenomena in Earth Sciences -- Integration of geophysical data for reservoir modeling and characterization -- Data integration into geostatistical seismic inversion methodologies -- Afterword.
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| 520 |
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|a This book presents a geostatistical framework for data integration into subsurface Earth modeling. It offers extensive geostatistical background information, including detailed descriptions of the main geostatistical tools traditionally used in Earth related sciences to infer the spatial distribution of a given property of interest. This framework is then directly linked with applications in the oil and gas industry and how it can be used as the basis to simultaneously integrate geophysical data (e.g. seismic reflection data) and well-log data into reservoir modeling and characterization. All of the cutting-edge methodologies presented here are first approached from a theoretical point of view and then supplemented by sample applications from real case studies involving different geological scenarios and different challenges. The book offers a valuable resource for students who are interested in learning more about the fascinating world of geostatistics and reservoir modeling and characterization. It offers them a deeper understanding of the main geostatistical concepts and how geostatistics can be used to achieve better data integration and reservoir modeling.
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| 650 |
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|a Earth sciences.
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| 650 |
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|a Economic geology.
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| 650 |
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|a Geology
|x Statistical methods.
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| 650 |
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|a Geophysics.
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| 650 |
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|a Statistics.
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| 650 |
1 |
4 |
|a Earth Sciences.
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| 650 |
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4 |
|a Geophysics/Geodesy.
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| 650 |
2 |
4 |
|a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
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| 650 |
2 |
4 |
|a Quantitative Geology.
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| 650 |
2 |
4 |
|a Economic Geology.
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| 700 |
1 |
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|a Soares, Amílcar.
|e author.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
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8 |
|i Printed edition:
|z 9783319532004
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| 830 |
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|a Advances in Oil and Gas Exploration & Production,
|x 2509-372X
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-319-53201-1
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-EES
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| 950 |
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|a Earth and Environmental Science (Springer-11646)
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