--> Abstract: Improving the Imaging Capability and Interpretability of Seismic Data Through Proper Parameter Selection, by W. B. Pramik; #90088 (2009)

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Improving the Imaging Capability and Interpretability of Seismic Data Through Proper Parameter Selection

W. B. Pramik
Petroleum Geo-Services, Houston, TX, [email protected]

There have been many recent advances with respect to seismic acquisition technology and each of these, in their own right, has contributed to the continual improvement we see in seismic data quality. There is, however, one technology area that if properly applied can have a greater impact on seismic data quality than almost anything else we do. That technology is seismic acquisition parameter selection.

The seismic wavefield that we record during acquisition contains a large number of events. Events that have traveled down into the earth, reflected one time from a lithologic interface and returned to the surface are called signal. Everything else we put into a category called noise. The problem with much of this noise is that it can often overwhelm the signal, generally does not decay in amplitude as fast as the signal, and travels with a significantly slower velocity. To be able to address the noise in data processing, acquisition parameters designed for the noise, rather than the signal, need to be considered.

Seismic noise generally travels with a slower velocity than our desired seismic signals and, because of this, requires more stringent acquisition parameters. Smaller bins, higher fold, and improved distribution of offsets and azimuths are usually the results of a noise based survey design. Fortunately, the same types of parameter modifications required to address the noise issues also result in improved sampling and imaging of our desired signal events.

These principals have been applied to a number of 3D surveys with excellent results. Data examples from the Wichita Mountain front in Oklahoma and the deep Bossier trend in East Texas demonstrate significant improvements in data quality, both in the reduction of noise, and the imaging of complex structure. The results are data sets that are significantly more interpretable.

AAPG Search and Discovery Article #90088©2009 Pacific Section Meeting, Ventura, California, May 3-5, 2009