Karsted carbonates of the Ordovician Yingshan Formation represent significant hydrocarbon reservoirs in the Tarim Basin, China. Due to the geologic complexity of the formation, realistically predicting and modeling karst zones and rock properties is challenging. This drives the need to apply diverse techniques for building a suitable geologic model. We have developed a static model approach that uses fully automated seismic facies classification processes for predicting and modeling patterns associated with karst elements. Our method uses a seismic attribute and well logs as input data. We initially processed a seismic facies volume using the hierarchical clustering technique. This is based on seismic attribute values that take into account an optimal number of classes. The outcome reveals various patterns illustrated with low amplitudes highlighting the geomorphology of paleokarst elements. Simultaneously, a seismic traces map of the karsted interval was processed using the hybrid clustering technique conducted on seismic trace shape. In this case, the karst facies was extracted from the output and used as secondary input data in trend analysis of the model. Both outputs obtained from clustering techniques are processed in a volume of the most probable facies, which delineate the karst patterns. The results of the modeling process are visualized in various time slices and cross sections, appropriately recognizing the relationship of estimated patterns with karst zones. We have evaluated the karstification thickness and porosity map obtained from the 3D model that detail a reasonable connectivity between karst elements. This is based on the paleogeographic location and type of filling, as well as the dissolution development along the main striking faults. Finally, our method outputs a logical model of karst zones located within the host rock, which reduces the uncertainty and identify nonperforated segments.