Modern Singular Spectral-Based Denoising and Filtering Techniques for 2D and 3D Reflection Seismic Data

Modern Singular Spectral-Based Denoising and Filtering Techniques for 2D and 3D Reflection Seismic Data\nThis book discusses the latest advances in singular spectrum-based algorithms for seismic data processing, providing an update on recent developments in this field. Over the past few decades, researchers have extensively studied the application of the singular spectrum-based time and frequency domain eigen image methods, singular spectrum analysis (SSA) and multichannel SSA for various geophysical data. This book addresses seismic reflection signals, which represent the amalgamated signals of several unwanted signals/noises, such as ground roll, diffractions etc. Decomposition of such non-stationary and erratic field data is one of the multifaceted tasks in seismic data processing. This volume also includes comprehensive methodological and parametric descriptions, testing on appropriately generated synthetic data, as well as comparisons between time and frequency domain algorithms and their applications to the field data on 1D, 2D, 3D and 4D data sets. Lastly, it features an exclusive chapter with MATLAB coding for SSA.\nModern Singular Spectral-Based Denoising and Filtering Techniques for 2D and 3D Reflection Seismic Data is written by R. K. Tiwari; R. Rekapalli and published by Springer. ISBNs for Modern Singular Spectral-Based Denoising and Filtering Techniques for 2D and 3D Reflection Seismic Data are 9783030193041, 3030193047 and the print ISBNs are 9783030193034, 3030193039.