Covariance Analysis For Seismic Signal Processing

Rather than address one seismic data-processing problem and present several methods, this book presents one fundamental methodology - analysis of the sample covariance matrix - and many seismic data problems to which it applies, providing the geophysical signal analyst with sufficient material to understand the usefulness of this approach.

This book presents the proceedings of the 6th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA-2017), held in Bhubaneswar, Odisha. The event brought together researchers, scientists, engineers, and practitioners to exchange their new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. The book is divided into two volumes: Information and Decision Sciences, and Intelligent Engineering Informatics. This volume covers broad areas of Information and Decision Sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management & networks, sensor networks, signal processing, wireless networks, protocols & architectures etc. The book also offers a valuable resource for students at the post-graduate level in various engineering disciplines.

Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing cohesively combines contributions from field experts to deliver a comprehensive account of the latest developments in signal processing. These experts detail the results of their research related to audio and speech enhancement, acoustic image estimation, video compression, biometric recognition, hyperspectral image analysis, tensor decomposition with applications in communications, adaptive sparse-interpolated filtering, signal processing for power line communications, bio-inspired signal processing, seismic data processing, arithmetic transforms for spectrum computation, particle filtering in cooperative networks, three-dimensional television, and more. This book not only shows how signal processing theory is applied in current and emerging technologies, but also demonstrates how to tackle key problems such as how to enhance speech in the time domain, improve audio quality, and meet the desired electrical consumption target for controlling carbon emissions. Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing serves as a guide to the next generation of signal processing solutions for speech and video coding, hearing aid devices, big data processing, smartphones, smart digital communications, acoustic sensors, and beyond.

The Handbook of Poststack Seismic Attributes is a general reference for poststack seismic attributes. It discusses their theory, meaning, computation, and application, with the goal of improving understanding so that seismic attributes can be applied more effectively. The chapters of the book build upon each other and progress from basic attributes to more involved methods. The book introduces the ideas that underlie seismic attributes and reviews their history from their origins to current developments. It examines attribute maps and interval statistics; complex trace attributes; 3D attributes that quantify aspects of geologic structure and stratigraphy, primarily dip, azimuth, curvature, reflection spacing, and parallelism; seismic discontinuity attributes derived through variances or differences; spectral decomposition, thin-bed analysis, and waveform classification; the two poststack methods that purportedly record rock properties — relative acoustic impedance through recursive inversion, and Q estimation through spectral ratioing; and multiattribute analysis through volume blending, cross-plotting, principal component analysis, and unsupervised classification. The book ends with an overview of how seismic attributes aid data interpretation and discusses bright spots, frequency shadows, faults, channels, diapirs, and data reconnaissance. A glossary provides definitions of seismic attributes and methods, and appendices provide background mathematics. The book is intended for reflection seismologists engaged in petroleum exploration, including seismic data interpreters, data processors, researchers, and students.

Advances in Geophysics is a highly-respected publication in the field of geophysics. Since 1952, each volume has been eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. Now with over 50 volumes, the series contains much material still relevant today – truly an essential publication for researchers in all fields of geophysics. Provides high-level reviews of the latest innovations in geophysics Written by recognized experts in the field Presents an essential publication for researchers in all fields of geophysics

Information-Based Inversion and Processing with Applications examines different classical and modern aspects of geophysical data processing and inversion with emphasis on the processing of seismic records in applied seismology. Chapter 1 introduces basic concepts including: probability theory (expectation operator and ensemble statistics), elementary principles of parameter estimation, Fourier and z-transform essentials, and issues of orthogonality. In Chapter 2, the linear treatment of time series is provided. Particular attention is paid to Wold decomposition theorem and time series models (AR, MA, and ARMA) and their connection to seismic data analysis problems. Chapter 3 introduces concepts of Information theory and contains a synopsis of those topics that are used throughout the book. Examples are entropy, conditional entropy, Burg's maximum entropy spectral estimator, and mutual information. Chapter 4 provides a description of inverse problems first from a deterministic point of view, then from a probabilistic one. Chapter 5 deals with methods to improve the signal-to-noise ratio of seismic records. Concepts from previous chapters are put in practice for designing prediction error filters for noise attenuation and high-resolution Radon operators. Chapter 6 deals with the topic of deconvolution and the inversion of acoustic impedance. The first part discusses band-limited extrapolation assuming a known wavelet and considers the issue of wavelet estimation. The second part deals with sparse deconvolution using various 'entropy' type norms. Finally, Chapter 7 introduces recent topics of interest to the authors. The emphasis of this book is on applied seismology but researchers in the area of global seismology, and geophysical signal processing and inversion will find material that is relevant to the ubiquitous problem of estimating complex models from a limited number of noisy observations. Non-conventional approaches to data processing and inversion are presented Important problems in the area of seismic resolution enhancement are discussed Contains research material that could inspire graduate students and their supervisors to undertake new research directions in applied seismology and geophysical signal processing

Written by leaders in the field of remote sensing information processing, this book covers the frontiers of remote sensors, especially with effective algorithms for signal/image processing and pattern recognition with remote sensing data. Sensor and data fusion issues, SAR images, hyperspectral images, and related special topics are also examined. Techniques making use of neural networks, wavelet transforms, and knowledge-based systems are emphasized. A special set of three chapters is devoted to seismic analysis and discrimination. In summary, the book provides an authoritative treatment of major topics in remote sensing information processing and defines new frontiers for these areas. Contents: Data Mining; SAR Image Processing; Wavelet Analysis and Applications; Military Applications of Remote Sensing; Microwave Remote Sensing; Statistical Pattern Recognition; Automatic Target Segmentation; Neural Networks; Change Detection; Seismic Signal Processing; Time Series Prediction; Image Compression; Emerging Topics. Readership: Engineers and scientists dealing with remote sensing data in particular, and signals and images in general; computer scientists involved in software development on geophysical data analysis.