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Seismic Inversion Methods: A Practical Approach

  • Book
  • © 2020

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Authors:
  1. S. P. Maurya

    1. Department of Geophysics, Institute of Sciences, Banaras Hindu University, Varanasi, India

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  2. N. P. Singh

    1. Department of Geophysics, Institute of Sciences, Banaras Hindu University, Varanasi, India

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  3. K. H. Singh

    1. Department of Earth Sciences, Indian Institute of Technology Bombay, Mumbai, India

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  • Explains all popular seismic inversion methods and their mathematical backgrounds
  • Describes inversion based on global optimization, together with its application to both synthetic and real data
  • Discusses artificial neural network techniques, which are used to predict various petrophysical parameters in the seismic section away from the boreholes

Part of the book series: Springer Geophysics (SPRINGERGEOPHYS)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-vii
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  2. Fundamental of Seismic Inversion

    • S. P. Maurya, N. P. Singh, K. H. Singh
    Pages 1-18

  3. Seismic Data Handling

    • S. P. Maurya, N. P. Singh, K. H. Singh
    Pages 19-37

  4. Post-stack Seismic Inversion

    • S. P. Maurya, N. P. Singh, K. H. Singh
    Pages 39-80

  5. Pre-stack Inversion

    • S. P. Maurya, N. P. Singh, K. H. Singh
    Pages 81-105

  6. Amplitude Variation with Offset (AVO) Inversion

    • S. P. Maurya, N. P. Singh, K. H. Singh
    Pages 107-143

  7. Optimization Methods for Nonlinear Problems

    • S. P. Maurya, N. P. Singh, K. H. Singh
    Pages 145-176

  8. Geostatistical Inversion

    • S. P. Maurya, N. P. Singh, K. H. Singh
    Pages 177-216
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Keywords

About this book

This book introduces readers to seismic inversion methods and their application to both synthetic and real seismic data sets. Seismic inversion methods are routinely used to estimate attributes like P-impedance, S-impedance, density, the ratio of P-wave and S-wave velocities and elastic impedances from seismic and well log data. These attributes help to understand lithology and fluid contents in the subsurface. There are several seismic inversion methods available, but their application and results differ considerably, which can lead to confusion. This book explains all popular inversion methods, discusses their mathematical backgrounds, and demonstrates their capacity to extract information from seismic reflection data. The types covered include model-based inversion, colored inversion, sparse spike inversion, band-limited inversion, simultaneous inversion, elastic impedance inversion and geostatistical inversion, which includes single-attribute analysis, multi-attribute analysis, probabilistic neural networks and multi-layer feed-forward neural networks. In addition, the book describes local and global optimization methods and their application to seismic reflection data. Given its multidisciplinary, integrated and practical approach, the book offers a valuable tool for students and young professionals, especially those affiliated with oil companies.

Authors and Affiliations

  • Department of Geophysics, Institute of Sciences, Banaras Hindu University, Varanasi, India

    S. P. Maurya, N. P. Singh

  • Department of Earth Sciences, Indian Institute of Technology Bombay, Mumbai, India

    K. H. Singh

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