Seismic Inversion Methods A Practical Approach
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Seismic Inversion Methods: A Practical Approach
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.
A Practical Guide to Seismic Reservoir Characterization
Author: Timothy Tylor-Jones
language: en
Publisher: Springer Nature
Release Date: 2023-01-11
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 allows the reader to get a comprehensive insight of the most common and advanced workflows. It aims at graduate students related to energy (hydrocarbons), CO2 geological storage, and near surface characterization as well as professionals in these industries. The reader benefits from the strong and coherent theoretical background of the book, which is accompanied with real case examples.
Recent Developments in Earthquake Seismology
The book presents earthquake source, wave propagation, site amplification, and other seismological studies including earthquake simulation, application of Artificial Neural Network (ANN) in seismology, earthquake early warning system, waveform inversion, moment tensor analysis, receiver function analysis, earthquake prediction, and earthquake early warning system applications. To minimize the losses due to an earthquake, it is better to understand the source properties, medium characteristics, site condition, and amplitude of a probable earthquake at a particular site. The evolutions of earthquake source models make it possible to understand the source dynamics. However, analysis of the source using a single-domain method does not provide a better understanding of the source dynamics. Therefore, this book combines methods from the earthquake spectrum to waveform inversion and joint inversion. The book also discusses earthquake prediction methods and their reliability around the globe, and techniques of simulation viz. stochastic, empirical, semi-empirical, and hybrid, along with their limitations and application. Seismology is an interdisciplinary subject. Therefore, the information presented in the book will appeal to a wider readership from students, teachers, researchers, planners engaged in developmental work, and people concerned with earthquake awareness.