|Dictionary entry for Deconvolution (edit)|
(de kon vō’ lū sh∂n) 1. A process designed to restore a waveshape to the form it had before it underwent a linear filtering action (convolution); inverse filtering. The objective of deconvolution is to nullify objectionable effects of an earlier filter action and thus improve the recognizability and resolution of reflected events. May mean (a) system deconvolution to remove the filtering effect of the recording system; (b) dereverberation or deringing to remove the filtering action of a water layer; see also Backus filter and gapped deconvolution; (c) predictive deconvolution to attenuate multiples that involve the surface or near-surface reflectors; (d) deghosting to remove the effects of energy that leaves the source in the upward direction; (e) whitening or equalizing to make all frequency components within a band-pass equal in amplitude; (f) shaping the amplitude-frequency and/or phase response to match that of adjacent channels; or (g) wavelet processing (q.v.). Deconvolution results may vary markedly with different phase assumptions, gate locations or widths, or operator lengths. Often involves Wiener filtering (q.v.). Also called decomposition. See Sheriff and Geldart (1995, 285 and 292–303). 2. Potential maps, well logs, and other data sets besides time series may be deconvolved. </translate>
Typically, prestack deconvolution is aimed at improving temporal resolution by compressing the effective source wavelet contained in the seismic trace to a spike (spiking deconvolution). Predictive deconvolution (optimum Wiener filters and predictive deconvolution in practice) with a prediction lag (commonly termed gap) that is equal to the first or second zero crossing of the autocorrelation function also is used commonly. Although deconvolution usually is applied to prestack data trace by trace, it is not uncommon to design a single deconvolution operator and apply it to all the traces on a shot record. Deconvolution techniques used in conventional processing are based on optimum Wiener filtering.
Figure 1.5-6 shows the common-shot gathers after spiking deconvolution. By examining some of the individual reflections and comparing them with those in Figure 1.5-5, note how the wavelet associated with the significant reflections is compressed and reverberatory energy that trails behind each reflection is largely attenuated by deconvolution. Because both low- and high-frequency noise and signal are boosted, the data often need filtering with a wide band-pass filter after deconvolution. In addition, some kind of trace balancing (gain applications) often is applied after deconvolution to bring the data to a common root-mean-squared (rms) level (Figure 1.5-7).
- CMP sorting
- Velocity analysis
- Normal-moveout correction
- Multiple attenuation
- Dip-moveout correction
- CMP stacking
- Poststack processing
- Residual statics corrections
- Quality control in processing
- Parsimony in processing