Statistical and Transform Methods in Geophysical Signal Processing
Statistical and Transform Methods in Geophysical Signal Processing
Statistical and Transform Methods in Geophysical Signal Processing
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vi CONTENTS<br />
5.1.5 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153<br />
5.1.6 Non-l<strong>in</strong>ear events: Chirps <strong>in</strong> ¢¡¤£ ? . . . . . . . . . . . . . . . . . . . 157<br />
5.1.7 Gap fill<strong>in</strong>g <strong>and</strong> recovery of near offset traces . . . . . . . . . . . . . . 157<br />
5.1.8 Pre-stack surface consistent FX filters . . . . . . . . . . . . . . . . . 161<br />
5.2 £¥¤ Projection Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162<br />
5.2.1 Wavenumber doma<strong>in</strong> formulation . . . . . . . . . . . . . . . . . . . 162<br />
5.2.2 Space doma<strong>in</strong> formulation . . . . . . . . . . . . . . . . . . . . . . . . 163<br />
5.2.3 Wrong formulation of the problem . . . . . . . . . . . . . . . . . . . 165<br />
5.3 ARMA formulation of Projection filters . . . . . . . . . . . . . . . . . . . . . 165<br />
5.3.1 Estimation of the ARMA prediction error filter . . . . . . . . . . . . 166<br />
5.3.2 Noise estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168<br />
5.3.3 ARMA <strong>and</strong> Projection Filters . . . . . . . . . . . . . . . . . . . . . . . 169<br />
5.4 FX Process<strong>in</strong>g Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176<br />
5.4.1 Prediction of harmonic models us<strong>in</strong>g AR filters . . . . . . . . . . . . 176<br />
5.4.2 £ ¤ algorithm, Canales (1984) . . . . . . . . . . . . . . . . . . . . . . 176<br />
5.4.3 L<strong>in</strong>ear prediction us<strong>in</strong>g AR filters . . . . . . . . . . . . . . . . . . . . 178<br />
5.4.4 ARMA filter<strong>in</strong>g . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178<br />
5.4.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180<br />
6 The KL transform <strong>and</strong> eigenimages 181<br />
6.1 Mathematical framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182<br />
6.2 Eigenimage analysis of common offset sections . . . . . . . . . . . . . . . . 188<br />
6.2.1 Eigenimages <strong>and</strong> application to Velocity Analysis . . . . . . . . . . . 194<br />
6.3 A Matlab Code for Eigenimage Analysis . . . . . . . . . . . . . . . . . . . . 199<br />
6.3.1 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200<br />
7 Radon <strong>Transform</strong>s 201<br />
7.1 Slant Stacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201<br />
7.1.1 The slant stack operator (conventional def<strong>in</strong>ition) . . . . . . . . . . 202<br />
7.1.2 The <strong>in</strong>verse slant stack operator . . . . . . . . . . . . . . . . . . . . . 205