Abstract:
In recent years, major hydrocarbon discoveries have been made by exploring subsalt hydrocarbon plays. Finding a proper model for identifying the salt deposits is great importance for identifying salt-related drilling hazards. To simplify the process of salt body extraction from seismic data and better assess the quality of the extracted salt bodies, an automated system is needed. In this work, we deal with detecting salt bodies in seismic data by using very limited number of features that used for texture-based segmentation along with presenting a hybrid semi-supervised clustering technique. Experiment results have shown that the presented technique provides remarkable accuracy.
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