3D seismic data has the potential to provide an enormous amount of detailed information about karst<br>and dissolution features. However, horizon based interpretation is not well suited to the analysis of<br>such features and, in addition to being very time consuming, reveals little or no information on the<br>paleokarst network and connectivity between karsts within a carbonate target. Without a good<br>understanding of karst distribution it is difficult to compile a comprehensive geological model and<br>appreciate the impact such structures will have on porosity evolution and reservoir quality (Budd et al.,<br>1995; Neuhaus et al., 2004).<br>Although karst and dissolution features may be extensive, they can be hard to identify in reflectivity<br>data due to their variable seismic character. The application of Image Processing and Analysis (IPA)<br>workflows enables a rapid and detailed examination of Carbonate features, including karsts, as well as<br>reefs / buildups and clinoforms. The IPA workflow employs attribute analysis to highlight the location<br>and extent of these features, and then 3D geobody delineation techniques are applied to allow the 3D<br>geometry of the highlighted features to be examined in detail. A major strength of these workflows is<br>the built-in capability to detect karsts and dissolution features across a wide range of scales and with<br>diverse morphologies.<br>This paper describes the IPA workflow and illustrates its application to the interpretation of upper<br>Palaezoic carbonates in the Loppa High area of the Norwegian Barents Sea. Here it is estimated that<br>some 300-500 m of uplift, erosion and karstification of a mixed carbonate-evaporite succession<br>occurred during c. 20 million years of subaerial exposure (i.e. Roadian-Induan times). Major drainage<br>systems can be traced across basement rocks and into and through the karstified carbonate<br>succession. The carbonates are cut by steep km-scale canyons and penetrative sinkholes. The dataset<br>shows a range of contrasting paleokarst features, so that some of the key seismic attributes and<br>spectral decomposition methods used to delimit contrasting genetic elements of paleokarst systems<br>can be illustrated. Results from the seismic data analysis have been quality-controlled against well data<br>and horizon-based interpretations.


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