SEISMIC FACIES ANALYSIS BASED ON 3D MULTI-ATTRIBUTE VOLUME CLASSIFICATION, DARIYAN FORMATION, SE PERSIAN GULF
*Department of Earth Science, University of Bergen, Allegt. 41, N-5007, Bergen, Norway. email: firstname.lastname@example.org
Interpretation of recently-acquired 3D seismic data from two adjacent oilfields in the SE Persian Gulf indicates that a 3D interpretation of seismic facies is crucial to resolve the internal stratal geometries of the Aptian Dariyan Formation. This carbonate formation passes southward into the Shu’aiba Formation, a prolific reservoir rock of similar facies in the UAE. Lack of exposures and limited cored intervals have forced reliance on the seismic data for evidence of the depositional environment and the internal architecture of potential reservoir rocks. The progradational nature of the Dariyan Formation and the occurrence of carbonate build-ups within it make this stratal geometry complex. The complex internal heterogeneity of the build-ups and presence of seismic noise make mapping of the build-ups in 3D space using conventional seismic interpretation tools difficult, despite the availability of high-quality 3D seismic data covering the area.
The high quality seismic and limited well data from this field is one of the few datasets of this kind presented in the literature. A procedure for the hierarchical multi-attribute analysis of seismic facies using Paradigm’s SeisFacies software is used in this study to provide a 3D interpretation of the stratal patterns. Principal component analysis reduces the noise and redundant data by reducing the main data variances to a few vector components in a transformed coordinate system. Cluster analysis is performed using those components which have the greatest contribution to the maximum spread of the data variability. Six seismic attribute volumes are used in this study and the result is a single 3D classified volume.
Important new information obtained from within the Dariyan Formation gives new insights into its stratigraphic distribution and internal variability. This method of processing seismic data is a step towards exploring for subtle stratigraphic traps in the study area, and may help to identify exploration targets.
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