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GCWhat Is Previous HitDeconvolutionNext Hit?*

By

Robert E. Sheriff1

 

Search and Discovery Article #40132 (2004)

 
*Adapted from the Geophysical Corner column in AAPG Explorer, April, 2004, entitled “A Demystifying of Previous HitDeconvolutionNext Hit” and prepared by the author. Appreciation is expressed to the author, to Alistar R. Brown, editor of Geophysical Corner, and to Larry Nation, AAPG Communications Director, for their support of this online version. 
1Professor, University of Houston ([email protected])

 

General Statement 

Previous HitDeconvolutionNext Hit is a process universally applied to seismic data, but is one that is mysterious to many geoscientists. Previous HitDeconvolutionNext Hit compresses the basic wavelet in the recorded seismogram and attenuates reverberations and short-period multiples. Hence, it increases resolution and yields a more interpretable seismic section. 

Note the differences in the Figure 1. The quality of modern seismic data owes a great deal to the success of Previous HitdeconvolutionNext Hit. Seismic processing often involves several stages of Previous HitdeconvolutionNext Hit, each of a different type and with a different objective. 

Previous HitDeconvolutionNext Hit usually involves convolution with an inverse filter. The idea is that this will undo the effects of a previous filter, such as the earth or the recording system. The difficulty in designing an inverse filter is that we hardly ever know the properties of the filter whose effects we are trying to remove.

 

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uTypes of Previous HitdeconvolutionNext Hit

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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uTypes of Previous HitdeconvolutionNext Hit

 

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Types of Previous HitDeconvolutionNext Hit 

Different kinds of Previous HitdeconvolutionNext Hit are generally described by the different adjectives. They usually designate the type of assumptions made in the process.  

Deterministic Previous HitdeconvolutionNext Hit can be used to remove the effects of the recording system, if the system characteristics are known. This type also can be used to remove the ringing that results from waves undergoing multiple bounces in the water layer, if the travel time in the water layer and the reflectivity of the seafloor are known. 

In the case of the earth, the previous filtering that was applied is not known, and thus the Previous HitdeconvolutionNext Hit takes on a statistical nature. In this situation the needed information comes from an autocorrelation of the seismic trace. Because the embedded wavelet from the source is repeated at each reflecting interface, this repetition is captured by the autocorrelation and used to design the inverse filter. 

The embedded wavelet ordinarily dominates the early part of an autocorrelation, whereas multiples dominate the later part. Hence different parts of the autocorrelation are used to determine different filters for different types of Previous HitdeconvolutionNext Hit. The embedded wavelet then can be recovered from the early part of the autocorrelation, but, because the autocorrelation contains amplitude information only, an assumption about phase is required. Minimum phase in the recorded data is usually assumed, and normally this is a good assumption. The output of the Previous HitdeconvolutionNext Hit, however, is normally zero phase. The enormous interpretive benefits of zero phase data have been discussed in previous Geophysical Corner columns ("Seismic/Geology Links Critical," AAPG Explorer November 1996, also Search and Discovery Article #40130 (2004), and "Zero Phase Can Aid Interpretation," AAPG Explorer April 1997, also in “Understanding the Seismic Wavelet,” by Steven G. Henry, Search and Discovery Article #40028 (2001)).  

Autocorrelations may be calculated over several time windows in an attempt to allow for changes in the shape of the embedded wavelet as it travels through the earth. This is called adaptive Previous HitdeconvolutionNext Hit. 

Spiking Previous HitdeconvolutionNext Hit shortens the embedded wavelet and attempts to make it as close as possible to a spike. The frequency bandwidth of the data limits the extent to which this is possible. This is also called whitening Previous HitdeconvolutionNext Hit, because it attempts to achieve a flat, or white, spectrum. This kind of Previous HitdeconvolutionNext Hit may result in increased noise, particularly at high frequencies. 

Previous HitPredictiveNext Hit Previous HitdeconvolutionNext Hit uses the later portions of the autocorrelation to remove the effects of some multiples. Predictability means that the arrival of an event can be predicted from knowledge of earlier events. Different formulations are used, including maximum and minimum entropy, a measure of disorder. 

Sparse-spike Previous HitdeconvolutionTop attempts to minimize the number of reflections, thus emphasizing large amplitudes.

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