Author: Kerry D. SchutzPublisher:
ISBN:
Category : Seismic reflection method
Languages : en
Pages : 154
Book Description
Optimum Deconvolution of Seismic Transients
Author: Kerry D. SchutzPublisher:
ISBN:
Category : Seismic reflection method
Languages : en
Pages : 154
Book Description
Optimal Seismic Deconvolution
Author: Jerry M. MendelPublisher: Elsevier
ISBN: 148325819X
Category : Science
Languages : en
Pages : 269
Book Description
Optimal Seismic Deconvolution: An Estimation-Based Approach presents an approach to the problem of seismic deconvolution. It is meant for two different audiences: practitioners of recursive estimation theory and geophysical signal processors. The book opens with a chapter on elements of minimum-variance estimation that are essential for all later developments. Included is a derivation of the Kaiman filter and discussions of prediction and smoothing. Separate chapters follow on minimum-variance deconvolution; maximum-likelihood and maximum a posteriori estimation methods; the philosophy of maximum-likelihood deconvolution (MLD); and two detection procedures for determining the location parameters in the input sequence product model. Subsequent chapters deal with the problem of estimating the parameters of the source wavelet when everything else is assumed known a priori; estimation of statistical parameters when the source wavelet is known a priori; and a different block component method for simultaneously estimating all wavelet and statistical parameters, detecting input signal occurrence times, and deconvolving a seismic signal. The final chapter shows how to incorporate the simplest of all models—the normal incidence model—into the maximum-likelihood deconvolution procedure.
Deconvolution of Seismic Data
Author: V. K. AryaDigital Imaging and Deconvolution
Author: Enders A. RobinsonPublisher: SEG Books
ISBN: 1560801484
Category : Computers
Languages : en
Pages : 449
Book Description
Covering ideas and methods while concentrating on fundamentals, this book includes wave motion; digital imaging; digital filtering; visualization aspects of the seismic reflection method; sampling theory; the frequency spectrum; synthetic seismograms; wavelet processing; deconvolution; seismic attributes; phase rotation; and seismic attenuation.
Deconvolution 2
Author: Enders A. RobinsonPublisher:
ISBN:
Category : Nature
Languages : en
Pages : 740
Book Description
Journal
Author: Canadian Society of Exploration GeophysicistsPublisher:
ISBN:
Category : Prospecting
Languages : en
Pages : 792
Book Description
Processing of Seismic Reflection Data Using MATLAB
Author: Wail MousaPublisher: Springer Nature
ISBN: 3031025342
Category : Technology & Engineering
Languages : en
Pages : 81
Book Description
This short book is for students, professors and professionals interested in signal processing of seismic data using MATLABTM. The step-by-step demo of the full reflection seismic data processing workflow using a complete real seismic data set places itself as a very useful feature of the book. This is especially true when students are performing their projects, and when professors and researchers are testing their new developed algorithms in MATLABTM for processing seismic data. The book provides the basic seismic and signal processing theory required for each chapter and shows how to process the data from raw field records to a final image of the subsurface all using MATLABTM. The MATLABTM codes and seismic data can be downloaded here. Table of Contents: Seismic Data Processing: A Quick Overview / Examination of A Real Seismic Data Set / Quality Control of Real Seismic Data / Seismic Noise Attenuation / Seismic Deconvolution / Carrying the Processing Forward / Static Corrections / Seismic Migration / Concluding Remarks
Acquisition and Processing of Marine Seismic Data
Author: Derman DondururPublisher: Elsevier
ISBN: 0128114916
Category : Science
Languages : en
Pages : 610
Book Description
Acquisition and Processing of Marine Seismic Data demonstrates the main principles, required equipment, and suitable selection of parameters in 2D/3D marine seismic data acquisition, as well as theoretical principles of 2D marine seismic data processing and their practical implications. Featuring detailed datasets and examples, the book helps to relate theoretical background to real seismic data. This reference also contains important QC analysis methods and results both for data acquisition and marine seismic data processing. Acquisition and Processing of Marine Seismic Data is a valuable tool for researchers and students in geophysics, marine seismics, and seismic data, as well as for oil and gas exploration. Contains simple step-by-step diagrams of the methodology used in the processing of seismic data to demonstrate the theory behind the applications Combines theory and practice, including extensive noise, QC, and velocity analyses, as well as examples for beginners in the seismic operations market Includes simple illustrations to provide to the audience an easy understanding of the theoretical background Contains enhanced field data examples and applications
Maximum-Likelihood Deconvolution
Author: Jerry M. MendelPublisher: Springer Science & Business Media
ISBN: 1461233704
Category : Technology & Engineering
Languages : en
Pages : 233
Book Description
Convolution is the most important operation that describes the behavior of a linear time-invariant dynamical system. Deconvolution is the unraveling of convolution. It is the inverse problem of generating the system's input from knowledge about the system's output and dynamics. Deconvolution requires a careful balancing of bandwidth and signal-to-noise ratio effects. Maximum-likelihood deconvolution (MLD) is a design procedure that handles both effects. It draws upon ideas from Maximum Likelihood, when unknown parameters are random. It leads to linear and nonlinear signal processors that provide high-resolution estimates of a system's input. All aspects of MLD are described, from first principles in this book. The purpose of this volume is to explain MLD as simply as possible. To do this, the entire theory of MLD is presented in terms of a convolutional signal generating model and some relatively simple ideas from optimization theory. Earlier approaches to MLD, which are couched in the language of state-variable models and estimation theory, are unnecessary to understand the essence of MLD. MLD is a model-based signal processing procedure, because it is based on a signal model, namely the convolutional model. The book focuses on three aspects of MLD: (1) specification of a probability model for the system's measured output; (2) determination of an appropriate likelihood function; and (3) maximization of that likelihood function. Many practical algorithms are obtained. Computational aspects of MLD are described in great detail. Extensive simulations are provided, including real data applications.
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