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  • Cited by 655
      • Per Avseth, Norwegian University of Science and Technology, Trondheim, and Odin Petroleum, Bergen, Tapan Mukerji, Stanford University, California, Gary Mavko, Stanford University, California
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    • Publisher:
      Cambridge University Press
      Publication date:
      January 2010
      February 2005
      ISBN:
      9780511600074
      9780521151351
      Dimensions:
      Weight & Pages:
      Dimensions:
      (247 x 174 mm)
      Weight & Pages:
      0.68kg, 408 Pages
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    Book description

    Quantitative Seismic Interpretation demonstrates how rock physics can be applied to predict reservoir parameters, such as lithologies and pore fluids, from seismically derived attributes. The authors provide an integrated methodology and practical tools for quantitative interpretation, uncertainty assessment, and characterization of subsurface reservoirs using well-log and seismic data. They illustrate the advantages of these new methodologies, while providing advice about limitations of the methods and traditional pitfalls. This book is aimed at graduate students, academics and industry professionals working in the areas of petroleum geoscience and exploration seismology. It will also interest environmental geophysicists seeking a quantitative subsurface characterization from shallow seismic data. The book includes problem sets and a case-study, for which seismic and well-log data, and MATLAB® codes are provided on a website (http://www.cambridge.org/9780521151351). These resources will allow readers to gain a hands-on understanding of the methodologies.

    Reviews

    '… a book that has a little something for everyone.'

    Source: EOS, Transactions, American Geophysical Union

    'The authors provide very useful guidelines … by highlighting important points and pitfalls within the text and bulleted conclusions at the end of each chapter. … The reference list is quite extensive and very current … I recommend this book to geophysicists involved with reservoir property estimation from seismic data and well log formation evaluation.'

    Source: The Leading Edge

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    Contents

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