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Seismic Inversion Methods: A Practical Approach


Seismic Inversion Methods: A Practical Approach


Springer Geophysics

von: S. P. Maurya, N. P. Singh, K. H. Singh

117,69 €

Verlag: Springer
Format: PDF
Veröffentl.: 28.05.2020
ISBN/EAN: 9783030456627
Sprache: englisch

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Beschreibungen

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.
1. Fundamental of seismic inversion.- 2. Seismic data handling.- 3. Post-stack seismic inversion.- 4. Pre-stack inversion.- 5. Amplitude variation with offset (AVO) inversion.- 6. Optimization Methods for Nonlinear Problems.- 7. Geostatistical inversion.
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.
<div>Explains all popular seismic inversion methods and their mathematical backgrounds&nbsp;</div><div><br></div><div>Describes inversion based on global optimization, together with its application to both synthetic and real data&nbsp;</div><div><br></div><div>Discusses artificial neural network techniques, which are used to predict various petrophysical parameters in the seismic section away from the boreholes&nbsp;</div><div><br></div>

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