Understanding fracture density and orientation is key to producing many carbonate reservoirs. Over the years many methods have been used to extract this information from seismic data. These methods include shear wave birefringence and velocity variations of P-wave data resulting from the anisotropy due to the fracturing. We want to investigate the class of geometrical attributes and the class of spectral attributes as a means of detecting fractures. This will avoid the time consuming process of picking P-wave data and the expense of multi-component data for shear wave analysis. To conduct a controlled experiment, we constructed a fracture model and acquired a various sets of data employing differing offsets and azimuths. Some of the geometrical attributes were able to identify the fractures while others were not. Of the spectral attributes, the dominant frequency was used to identify the fractures.