Coding and Decoding: Seismic Data
, by Ikelle
- ISBN: 9780080451596 | 0080451594
- Cover: Hardcover
- Copyright: 5/11/2010
This cutting-edge handbook and guide on surveying techniques on Coding and Decoding: Seimic Date investigates how to collect, stimulate, and process multishooting data, as well as address what improvements in seismic characterzation and resolution one can expect.
| Preface | p. ix |
| Introduction to Multishooting: Challenges and Rewards | p. 1 |
| Dimensions and Notation Conventions | p. 3 |
| Coordinate systems | p. 3 |
| Dimensions of heterogeneous media | p. 4 |
| Notation conventions | p. 4 |
| The f-x and f-k domains | p. 5 |
| Scattering Experiments in Petroleum Seismology | p. 6 |
| Principles of seismic acquisition | p. 8 |
| Seismic data | p. 16 |
| Shot, receiver, midpoint, and offset gathers | p. 17 |
| Multiazimuthal data | p. 22 |
| An Illustration of the Concept of Multishooting | p. 25 |
| An example of multishot data | p. 25 |
| The principle of superposition in multishooting | p. 32 |
| The Rewards of Multishooting | p. 34 |
| Seismic acquisition | p. 38 |
| Simulation of seismic surveys | p. 39 |
| Seismic data processing | p. 40 |
| Seismic data storage | p. 41 |
| The Challenges of Multishooting | p. 41 |
| Decoding of Multishot data | p. 42 |
| Source encoding | p. 47 |
| Processing of muitishot data without decoding | p. 48 |
| Scope and Content of This Book | p. 52 |
| Mathematics of Statistical Decoding: Instantaneous Mixtures | p. 55 |
| Seismic Data Representation as Random Variables | p. 57 |
| Examples of random variables | p. 57 |
| From seismic signals to seismic random variables | p. 64 |
| Probability-density function (PDF) of seismic random variables | p. 65 |
| Moments and cumulants of seismic random variables | p. 70 |
| Negentropy: A measurement of non-Gaussianity | p. 77 |
| Uncorrelatedness and Independence | p. 83 |
| Joint probability-density functions and Kullback-Leibler divergence | p. 85 |
| Joint moments and joint cumulants | p. 91 |
| Uncorrelatedness and whiteness of random variables | p. 96 |
| Independence of random variables | p. 98 |
| Analysis of uncorrelatedness and independence with scatterplots | p. 101 |
| Whitening | p. 113 |
| ICA Decoding | p. 120 |
| Decoding by maximizing contrast functions | p. 121 |
| Decoding by cumulant-tensor diagonalization | p. 140 |
| ICA decoding by negentropy maximizing | p. 146 |
| Decoding Methods of Noisy Mixtures | p. 153 |
| Special cases | p. 153 |
| General case | p. 154 |
| Problems | p. 154 |
| Mathematics of Statistical Decoding: Convolutive Mixtures | p. 169 |
| Motivation and Foundation for Working in the T-F-X Domain | p. 179 |
| Convolutive mixtures in the T-X domain | p. 180 |
| Convolutive mixtures in the F-X domain | p. 184 |
| Convolutive mixtures in the T-F-X domain | p. 186 |
| Statistics of Complex Random Variables and Vectors | p. 188 |
| The complex-valued gradient and the Hessian matrix | p. 189 |
| Statistics of complex random variables | p. 195 |
| Statistics of complex random vectors | p. 211 |
| An analysis of the statistical independence of seismic data in the T-F-X domain | p. 226 |
| Decoding in the T-F-X Domain: The MICA Approach | p. 233 |
| Whiteness of complex random variables | p. 235 |
| Decoding by negentropy maximization of complex random vectors | p. 236 |
| Permutation inconsistency problem | p. 245 |
| A cascaded ICA approach | p. 251 |
| Numerical examples | p. 251 |
| Decoding in Other Domains | p. 273 |
| Decoding in the F-X domain | p. 273 |
| Decoding in the T-X domain | p. 277 |
| Problems | p. 283 |
| Decoding Methods for Underdetermined Mixtures | p. 293 |
| Identification: Estimation of the Mixing Matrix | p. 294 |
| Histograms of data-concentration directions | p. 297 |
| Expectation maximization | p. 306 |
| Cumulant matching methods | p. 318 |
| Some Background on Sparsity Optimization | p. 322 |
| Sparsity regularization methods: $0norm | p. 322 |
| Sparsity regularization methods: $1norm | p. 339 |
| Separation Based on ICA Decomposition | p. 350 |
| Data-driven transform | p. 353 |
| Single-shot separation | p. 363 |
| Separation Based on Phase Encoding | p. 369 |
| Decoding with reference single shots | p. 373 |
| Window-by-window decoding | p. 382 |
| A combination of phase encoding and reciprocity | p. 385 |
| Array-processing Decoding Methods | p. 394 |
| Simultaneous shooting of monopole and dipole sources | p. 394 |
| Beamforming-based decoding | p. 397 |
| MUSIC decoding | p. 401 |
| Decoding with Known Source Signatures | p. 403 |
| Decoding of single-mixture data in the F-X domain | p. 405 |
| Decoding of single- and multiple-mixture data in the T-F-X domain | p. 406 |
| Decoding with Unknown Source Signatures | p. 408 |
| Decoding of single-mixture data in the F-X domain | p. 408 |
| Decoding of single- and multiple-mixture data in the T-F-X domain | p. 409 |
| Problems | p. 414 |
| Modeling and Imaging of Multishot Data | p. 419 |
| Introduction to Multiple Attenuation | p. 420 |
| Some background on free-surface demultiple methods | p. 420 |
| Radon free-surface-multiple attenuation | p. 425 |
| Kirchhoff-Scattering Demultiple of Multishot Data | p. 432 |
| A brief review of Kirchhoff-based free-surface multiple attenuation | p. 432 |
| A reformulation of the Kirchhoff demultiple for multishot data | p. 442 |
| Denoising of the vertical component of the particle velocity | p. 454 |
| A reconstruction of primaries | p. 466 |
| The Sea-Level-Based Demultiple | p. 477 |
| The phenomenon of low and high tides in demultiples | p. 477 |
| Demultiples | p. 478 |
| Migration and Velocity Analysis | p. 488 |
| Formulation of migration of multishot data | p. 490 |
| Velocity-migration analysis | p. 494 |
| ICA for seismic imaging and monitoring | p. 513 |
| Numerical Modeling Using the Multishooting Concept | p. 518 |
| Perturbation theory in data decoding | p. 522 |
| Array-processing-based decoding of FDM data | p. 527 |
| The source-signature-based decoding of FDM data | p. 528 |
| Problems | p. 533 |
| Nonnegative Matrix Factorization | p. 539 |
| Lee-Seung Matrix Factorization Algorithm | p. 540 |
| Mathematical formulation | p. 540 |
| Numerical illustrations of the forward and inverse transform | p. 547 |
| Selecting the number of elements of a dictionary | p. 551 |
| Nonnegative matrix factorization with auxiliary constraints | p. 553 |
| Other Nonnegative Matrix Factorization Algorithms | p. 556 |
| Project-gradient algorithm | p. 556 |
| Alternating least-squares algorithm | p. 559 |
| Decoding Challenges | p. 567 |
| Nonnegative Tensor Factorization | p. 569 |
| Parafac Decomposition Model | p. 569 |
| Tucker Tensor Factorization | p. 575 |
| A Review of 3 D Finite-difference Modelling | p. 579 |
| Basic Equations for Elastodynamic Wave Motion | p. 579 |
| Discretization in Both Time and Space | p. 581 |
| Staggered-grid Implementation | p. 582 |
| Stability of the Staggered-grid Finite-difference Modelling | p. 587 |
| Grid Dispersion in Finite-difference Modelling | p. 587 |
| Boundary Conditions | p. 588 |
| Bibliography | p. 589 |
| Author Index | p. 597 |
| Subject Index | p. 601 |
| Table of Contents provided by Ingram. All Rights Reserved. |
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