CRS-stack-based seismic imaging for rough top-surface topography

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. In recent years, many case studies demonstrated that the Common-Reflection-Surface (CRS) stack produces reliable stack sections with high resolution and superior signal-to-noise ratio compared to conventional methods. 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, so-called kinematic wavefield attributes. As will be shown, these CRS attributes, obtained as a by-product of the data-driven stacking process, may be even more important than the stacked section itself. They can be applied to solve various dynamic and kinematic stacking, modeling, and inversion problems. CRS-stack-based seismic imaging makes use of these extended possibilities during the stack and in further processing. The presented extention of the CRS-stack-based imaging workflow provides support for arbitrary topsurface topography. Its implementation combines two different approaches of topography handling to a cascaded processing strategy demanding very little additional effort. Finally, the CRS stack and also CRS-stack-based residual static corrections can be applied to the original prestack data without the need of any elevation statics. By a redatuming procedure, the CRS-stacked ZO section, the kinematic wavefield attribute sections, and the quality control sections can be related to a chosen planar measurement level. Thus, an ideal input for a preliminary interpretation and subsequent CRS-stack-based processing steps is provided. INTRODUCTION Obtaining a sufficiently accurate image, either in time or in depth domain, is often a difficult task in regions governed by complex geological structure and/or complicated near-surface conditions. Under such circumstances where simple model assumptions may fail it is of particular importance to extract as much information as possible directly from the measured data. Fortunately, the ongoing increase in available computing power makes so-called data-driven approaches (e. g., Hubral, 1999) feasible which, thus, have increasingly gained in relevance, during the last years. The Common-Reflection-Surface (CRS) stack (e. g., Müller, 1999; Jäger et al., 2001; Mann, 2002) is one of these promising methods. Besides an improved zero-offset (ZO) simulation, its decisive advantage over conventional methods is that several so-called kinematic wavefield attributes are obtained as a by-product of the data-driven stacking process. As will be shown, they can be applied both to improve the stack itself and to support subsequent processing steps as, e.g., tomographic inversion or depth migration. With these CRS attributes an advanced data-processing workflow can be established leading from time to depth domain, covering a broad range of seismic reflection imaging issues in a consistent manner. The major steps of this workflow are displayed in Figure 1. 50 Annual WIT report 2004 Conventional processing e.g. NMO/DMO etc. Poststack depth migration Velocity updating Residual static Kinematic wavefield correction