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Statistical and Transform Methods in Geophysical Signal Processing

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iv CONTENTS<br />

2.3.4 Least squares <strong>in</strong>version of a m<strong>in</strong>imum phase dipole . . . . . . . . . 43<br />

2.3.5 Inversion of M<strong>in</strong>imum Phase sequences . . . . . . . . . . . . . . . . 47<br />

2.4 MATLAB codes used <strong>in</strong> Chapter 2 . . . . . . . . . . . . . . . . . . . . . . . . 51<br />

2.4.1 Inversion of dipoles . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51<br />

2.4.2 Amplitude <strong>and</strong> phase . . . . . . . . . . . . . . . . . . . . . . . . . . . 51<br />

2.4.3 Least squares <strong>in</strong>version of a dipole . . . . . . . . . . . . . . . . . . . 52<br />

2.4.4 Eigenvalues of the Toeplitz matrix . . . . . . . . . . . . . . . . . . . 53<br />

2.4.5 Least square <strong>in</strong>verse filters . . . . . . . . . . . . . . . . . . . . . . . . 53<br />

2.5 The autocorrelation function . . . . . . . . . . . . . . . . . . . . . . . . . . 55<br />

2.5.1 The Toeplitz matrix <strong>and</strong> the autocorrelation coefficients . . . . . . . 56<br />

2.6 Inversion of non-m<strong>in</strong>imum phase wavelets: optimun lag Spik<strong>in</strong>g filters . . 59<br />

3 Discrete Fourier <strong>Transform</strong> 61<br />

3.1 The Z transform <strong>and</strong> the DFT . . . . . . . . . . . . . . . . . . . . . . . . . . 61<br />

3.1.1 Inverse DFT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63<br />

3.1.2 Zero padd<strong>in</strong>g . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65<br />

3.1.3 The Fast Fourier <strong>Transform</strong> (FFT) . . . . . . . . . . . . . . . . . . . . 67<br />

3.1.4 Work<strong>in</strong>g with the DFT/FFT . . . . . . . . . . . . . . . . . . . . . . . 69<br />

3.2 The 2D DFT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71<br />

3.3 On the Design of F<strong>in</strong>ite Impulse Response filters . . . . . . . . . . . . . . . 73<br />

3.3.1 Low Pass FIR filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73<br />

3.3.2 High Pass filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77<br />

4 Deconvolution of reflectivity series 79<br />

4.1 Model<strong>in</strong>g normal <strong>in</strong>cidence seismograms . . . . . . . . . . . . . . . . . . . 79<br />

4.1.1 Normal <strong>in</strong>cidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79<br />

4.1.2 Impulse response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81<br />

4.2 Deconvolution of reflectivity series . . . . . . . . . . . . . . . . . . . . . . . 85<br />

4.2.1 The autocorrelation sequence <strong>and</strong> the white reflectivity assumption 86<br />

4.2.2 What to do with the noise? . . . . . . . . . . . . . . . . . . . . . . . . 88

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