LAUSR

Abstract The characterization and modeling of fractures in karsted carbonate reservoirs are challenging due to the mechanical interactions between fractures and irregular karst elements. This study proposes an integrated approach for characterizing and modeling large-scale fractures within deeply buried fractured karst carbonates of the Yingshan Formation (Ordovician in age) located at the Tahe oilfield, Tarim Basin (western China). This investigation implements a promising workflow to stochastically model the fracture sets interpreted from borehole image logs and compute both fracture porosity and permeability tensor in karsted carbonates. For this case study, we have constructed a Discrete Fracture Network (DFN) by combining two structural seismic attributes (i.e. local structural dip and ant-tracking). We have also applied the automatic fault extraction (AFE) algorithm. The results indicate that this method detects a greater number of discontinuities associated with fractures compared to the conventional methods employed in this kind of reservoir (e.g. seismic coherence and curvature). The fracture set with higher values of fracture porosity and permeability coincided with the orientation of maximum horizontal stress, WSW-ENE. In the model, the highest values of fracture intensity correspond to the most productive oil wells. Finally, this study highlights the importance of fracture modeling for evaluating the distribution of the most favorable production areas, so-called sweet-spots, in karsted carbonates reservoirs.