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7th Middle East Geosciences Conference and Exhibition
Manama, Bahrain
March 27-29, 2006
Geophysical Institute, University of Karlsruhe, Hertzstr. 16, 761 87 Karlsruhe, Germany
Summary. In the current situation of rapidly growing demand in oil and gas, on-shore exploration, even under
difficult conditions, becomes again more and more important. Unfortunately, rough top-surface topography
and a strongly varying weathering layer often result in poor data quality, which makes conventional
data processing
very difficult to apply.
As recent case studies demonstrated, the Common-Reflection-Surface (CRS) stack produces reliable stack
sections with high resolution and superior signal-to-noise ratio compared to conventional methods. Particularly
for land data, the increased computational expense required by the generalized high-density velocity
analysis preceding the CRS stacking process may be worthwhile. In order to define optimal spatial stacking
operators, the CRS stack extracts for every sample of the zero offset (ZO) section an entire set of physically
interpretable stacking parameters. These so-called kinematic wavefield attributes, obtained as a by-product
of the data-driven stacking process, can be applied to solve various dynamic and kinematic stacking, modeling,
and inversion problems. By this means, a very flexible CRS-stack-based seismic reflection imaging
workflow can be established. Besides the CRS stack itself, the main steps of this processing
workflow are
residual static correction, the determination of a macrovelocity model via tomographic inversion and limited
aperture Kirchhoff migration.
The presented extension of the CRS-stack-based imaging workflow provides support for arbitrary top-surface
topography. Both CRS stack and also CRS-stack-based residual static correction are applied to
the original prestack data without the need of any elevation statics
. Finally, a redatuming procedure relates
the CRS-stacked ZO section, the kinematic wavefield attribute sections, and the quality control sections to
a chosen planar measurement level. Thus, an ideal input for a preliminary interpretation and subsequent
CRS-stack-based
processing
steps is provided.