Difference between revisions of "Basic data processing sequence"

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==See also==
==See also==
* [[Introduction to fundamentals of signal processing]]
* [[Preprocessing]]
* [[The 1-D Fourier transform]]
* [[Deconvolution]]
* [[The 2-D Fourier transform]]
* [[CMP sorting]]
* [[Worldwide assortment of shot records]]
* [[Velocity analysis]]
* [[Gain applications]]
* [[Normal-moveout correction]]
* [[Multiple attenuation]]
* [[Dip-moveout correction]]
* [[CMP stacking]]
* [[Poststack processing]]
* [[Migration]]
* [[Residual statics corrections]]
* [[Quality control in processing]]
* [[Parsimony in processing]]
* [[Fundamentals of signal processing exercises|Exercises]]
* [[A mathematical review of the Fourier transform]]

Revision as of 14:55, 5 August 2014

Seismic Data Analysis
Series Investigations in Geophysics
Author Öz Yilmaz
DOI http://dx.doi.org/10.1190/1.9781560801580
ISBN ISBN 978-1-56080-094-1
Store SEG Online Store

Since the introduction of digital recording, a routine sequence in seismic data processing has evolved. This basic sequence now is described to gain an overall understanding of each step. There are three primary steps in processing seismic data — deconvolution, stacking, and migration, in their usual order of application. Figure 1.5-1 represents the seismic data volume in processing coordinates — midpoint, offset, and time. Deconvolution acts along the time axis. It removes the basic seismic wavelet (the source time function modified by various effects of the earth and recording system) from the recorded seismic trace and thereby increases temporal resolution. Deconvolution achieves this goal by compressing the wavelet. Stacking also is a process of compression (velocity analysis and statics corrections). In particular, the data volume in Figure 1.5-1 is reduced to a plane of midpoint-time at zero offset (the frontal face of the prism) first by applying normal moveout correction to traces from each CMP gather (velocity analysis and statics corrections), then by summing them along the offset axis. The result is a stacked section. (The terms stacked section, CMP stack, and stack often are used synonymously.) Finally, migration commonly is applied to stacked data. It is a process that collapses diffractions and maps dipping events on a stacked section to their supposedly true subsurface locations. In this respect, migration is a spatial deconvolution process that improves spatial resolution.

Figure 1.5-1  Seismic data volume represented in processing coordinates — midpoint-offset-time. Deconvolution acts on the data along the time axis and increases temporal resolution. Stacking compresses the data volume in the offset direction and yields the plane of stacked section (the frontal face of the prism). Migration then moves dipping events to their true subsurface positions and collapses diffractions, and thus increases lateral resolution.

All other processing techniques may be considered secondary in that they help improve the effectiveness of the primary processes. For example, dip filtering may need to be applied before deconvolution to remove coherent noise so that the autocorrelation estimate is based on reflection energy that is free from such noise. Wide band-pass filtering also may be needed to remove very low- and high-frequency noise. Before deconvolution, correction for geometric spreading is necessary to compensate for the loss of amplitude caused by wavefront divergence. Velocity analysis, which is an essential step for stacking, is improved by multiple attenuation and residual statics corrections.

Many of the secondary processes are designed to make data compatible with the assumptions of the three primary processes. Deconvolution assumes a stationary, vertically incident, minimum-phase source wavelet and white reflectivity series that is free of noise. Stacking assumes hyperbolic moveout, while migration is based on a zero-offset (primaries only) wavefield assumption. A pessimist could claim that none of these assumptions is valid. However, when applied to field data, these techniques do provide results that are close to the true subsurface image. This is because these three processes are robust and their performance is not very sensitive to the underlying assumptions in their theoretical development.

Keep in mind that the success of a process depends not only on the proper choice of parameters pertinent to that particular process, but also on the effectiveness of the previous processing steps.

We shall use a 2-D seismic line from the Caspian Sea to demonstrate the basic processing sequence. Table 1-14 provides the processing parameters for the line. The water depth at one end of the line is approximately 750 m and decreases along the line traverse to approximately 200 m at the other end.

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