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Adaptive Dip Estimations on Post-Stack Seismic Data

Abstract

A robust dip estimate is essential in many calculations performed on post stack seismic including dip steered seismic attribute calculations. According to Chopra and Marfurt (Seismic attributes for prospect identification and reservoir characterization, 2007) there are several methods to estimate dip and they fall into three main categories; spatial and temporal derivatives, dip scan of most coherent reflector and eigenvectors of gradient structure tensors. All these methods have a limitation of assuming static operators throughout the entire calculation, which is what our method attempts to resolve. We propose a new approach to a robust dip Previous HitestimationNext Hit that involves adaptive filtering techniques that are better suited to the nature of seismic data. The adaptive filtering approach accounts for seismic properties and tunes various parameters during calculations to better resolve dip estimations. This way the estimate accounts for attenuation of the seismic signal as well as changes in seismic texture. One of the key aspects to this adaptive filtering is the novel rotational transformation method developed. The dip Previous HitestimationNext Hit results are imaged using the illumination techniques discussed in (Aqrawi and Boe, Imaging structural geology with dip and directional dip, 2012) Preliminary testing of this method is done on a synthetic dataset consisting of spheres to see how robust the Previous HitestimationNext Hit is. This is done in a comparison study to other market leading dip Previous HitestimationTop techniques. We also test this method on data from the Gulf of Mexico with structural features such as folding, salt diapers, faults (both minor and major), and chaotic seismic textures. This gives more insight in real life examples and strengthens our findings from the synthetic data comparisons. The comparison results to market leading dip estimations show a sharper, more robust estimate that delineates structural features better in post stack seismic and is less sensitive to random noise.