Geostatistical Methods for Reservoir Geophysics

  • Leonardo Azevedo
  • Amílcar Soares

Part of the Advances in Oil and Gas Exploration & Production book series (AOGEP)

Table of contents

  1. Front Matter
    Pages i-xxvii
  2. Leonardo Azevedo, Amílcar Soares
    Pages 5-35
  3. Leonardo Azevedo, Amílcar Soares
    Pages 37-49
  4. Leonardo Azevedo, Amílcar Soares
    Pages 91-107
  5. Leonardo Azevedo, Amílcar Soares
    Pages 109-129
  6. Leonardo Azevedo, Amílcar Soares
    Pages 131-131
  7. Back Matter
    Pages 133-141

About this book


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.


Geostatistics Stochastic Simulation Reservoir Modeling Seismic Reservoir Characterization Geophysical Data Integration Seismic reflection data

Authors and affiliations

  • Leonardo Azevedo
    • 1
  • Amílcar Soares
    • 2
  1. 1.Instituto Superior TecnicoCERENALisboaPortugal
  2. 2.Instituto Superior TecnicoCERENALisboaPortugal

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Earth and Environmental Science
  • Print ISBN 978-3-319-53200-4
  • Online ISBN 978-3-319-53201-1
  • Series Print ISSN 2509-372X
  • Series Online ISSN 2509-3738
  • Buy this book on publisher's site