Information-based inversion and processing with applications

This book 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), elementar...

Full description

Saved in:
Bibliographic Details
Main Author Ulrych, Tadeusz J.
Other Authors Sacchi, Mauricio D.
Format Electronic eBook
LanguageEnglish
Published Amsterdam ; Boston : Elsevier, 2005.
Edition1st ed.
SeriesHandbook of geophysical exploration. Seismic exploration ; v. 36.
Subjects
Inversion (Geophysics)
elektronické knihy
electronic books
Online AccessFull text
ISBN0080461344
9780080461342
9780080447216
008044721X
1280641045
9781280641046
9786610641048
6610641048
Physical Description1 online resource (xxvii, 405 pages) : illustrations.

Cover

Table of Contents:
  • Cover
  • Contents
  • Some Basic Concepts
  • Introduction
  • Probability Distributions, Stationarity & Ensemble Statistics
  • Properties of Estimators
  • Orthogonality
  • Orthogonal Vector Space
  • Fourier Analysis
  • Expectations etc.,
  • Lagrange Multipliers
  • Linear Time Series Modelling
  • Introduction
  • The Wold Decomposition Theorem
  • The Moving Average. MA, Model
  • The Autoregressive, AR, Model
  • The Autoregressive Moving Average, ARMA, Model
  • MA, AR and ARMA Models in Seismic Modelling and Processing
  • Extended AR Models and Applications
  • A Few Words About Nonlinear Time Series
  • Levinson's Recursion and Reflection Coefficients
  • Minimum Phase Property of the PEO
  • Information Theory and Relevant Issues
  • Introduction
  • Entropy in Time Series Analysis
  • The Kullback-Lciblcr Information Measure
  • MaxEnt and the Spectral Problem
  • The Akaike Information Criterion, AIC
  • Mutual Information and Conditional Entropy
  • The Inverse Problem
  • Introduction
  • The Linear (or Linearized) Inverse Formulation
  • Probabilistic Inversion
  • Minimum Relative Entropy Inversion
  • Bayesian Inference
  • Signal to Noise Enhancement
  • Introduction
  • f
  • x Filters
  • Principal Components, Eigenimages and the KL Transform
  • Radon Transforms
  • Time variant Radon Transforms
  • Discussion
  • Deconvolution with Applications to Seismology
  • Introduction
  • Layered Earth Model
  • Deconvolution of the Reflectivity Series
  • Sparse Deconvolution and Bayesian Analysis
  • ID Impedance Inversion
  • Nonminimum Phase Wavelet Estimation
  • Blind, Full Band Deconvolution
  • Discussion
  • A Potpourri of Some Favorite Techniques
  • Introduction
  • Physical Wavelet Frame Dcnoising
  • Stein Processing
  • The Bootstrap and the EIC
  • The Extended Information Criterion
  • Summary
  • Last Page.

Similar Items