Comprehensive Seismic Data Conditioning of the Bioclastic Limestone in the Middle East

Abstract

Abstract The bioclastic limestone reservoirs of Cretaceous period occupy an important position in the petroleum industry of Middle East. It is the carbonate heterogeneity that is challenging the accuracy of the reservoir prediction, which brings forward higher requirements for the seismic data quality. Besides, some seismic data are processed more than 10 years ago, the signal to noise ratio (SNR) is relative low due to the random noise and coherent noise like acquisition footprint anomalies. The acquisition footprint artifacts caused by acquisition and processing seriously suppress the true stratigraphic features, which can result in pitfalls in seismic interpretation, seismic attribute analysis as well as seismic inversion. While the pre-stack seismic data is usually unavailable, which means that the noise can hardly be subtracted by conventional pre-stack seismic processing workflows, such as statics, high-resolution velocity analysis and ground roll attenuation. Consequently, a comprehensive post-stack seismic data conditioning workflow is necessary to solve the above problems. In order to improve the post-stack seismic data quality, a comprehensive data conditioning workflow are applied for noise suppression. Firstly, structural-oriented filtering is utilized to attenuate random noise and partial acquisition footprint artifacts. Then 2D waveform transform of seismic amplitude and filtered seismic attribute in x-y domain are calculated, to separate acquisition footprint anomalies (large wave number in kx-ky domain) from true structural signal (small wave number in kx-ky domain) by interactive analysis. The application of Laplace-Gaussian (LoG) filter deserves an obvious improvement in acquisition footprint suppression workflow. The comprehensive noise attenuation workflow in this paper can effectively remove both periodic and non-periodic noise to obtain higher signal to noise ratio (SNR) for post-stack seismic volume. In this way, the stratigraphic features (tidal-channel, reef-beach complex) can be more clearly depicted and some artifacts caused by noise will disappear in seismic attribute calculation, seismic inversion and reservoir prediction.