Geostatistical Methods for Reservoir Geophysics

This book PDF is perfect for those who love Science genre, written by Leonardo Azevedo and published by Springer which was released on 07 April 2017 with total hardcover pages 141. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Geostatistical Methods for Reservoir Geophysics books below.

Geostatistical Methods for Reservoir Geophysics
Author : Leonardo Azevedo
File Size : 53,9 Mb
Publisher : Springer
Language : English
Release Date : 07 April 2017
ISBN : 9783319532011
Pages : 141 pages
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Geostatistical Methods for Reservoir Geophysics by Leonardo Azevedo Book PDF Summary

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.

Geostatistical Methods for Reservoir Geophysics

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

Get Book
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Earth science is becoming increasingly quantitative in the digital age. Quantification of geoscience and engineering problems underpins many of the applications of big data and artificial intelligence. This book presents quantitative geosciences in three parts. Part 1 presents data analytics using probability, statistical and machine-learning methods. Part 2 covers reservoir characterization using

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This book covers in detail the entire workflow for quantitative seismic interpretation of subsurface modeling and characterization. It focusses on each step of the geo-modeling workflow starting from data preconditioning and wavelet extraction, which is the basis for the reservoir geophysics described and introduced in the following chapters. This book

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