Fault seismic attribute volumes (such as volumetric coherence and curvature) represent an efficient and objective way to visualize and identify faults in seismic cubes. Fault geometric attributes such as length, height, and fault segmentation can be extracted from such fault seismic attribute volumes. We evaluate the strengths and pitfalls of using coherence volumes for characterization of fault geometry. The results are obtained using a database from the Barents Sea, which contains 35 3D seismic cubes, together with conceptual synthetic seismic models. A high signal-to-noise ratio is a requirement for the extraction of accurate fault geometric data. Noise attenuation methods improve fault visualization, but our results indicate that the effect of noise attenuation on the extracted fault geometric attributes is only clear in areas of low signal-to-noise ratios. The choice of coherence algorithm is important when extracting fault length data. Semblance-based coherence performs better than gradient structure tensor-based coherence in low-displacement areas near the fault tips, and it produces more accurate fault length data. Faults can appear segmented in coherence volumes if relatively similar reflectors are juxtaposed across a fault. In such areas, it is important that the interpreter does not overlook the fault. The size of the analysis window used in coherence calculations controls the resolution and continuity of the imaged faults. Our results support an optimal temporal window size of one to two times the dominant period of the seismic data (typically 7–17 samples in conventional 4 ms sampled 3D seismic data). Larger temporal window sizes can result in an overestimation of fault height, especially for small faults. A large spatial window can smear out segmentation along the fault and make the fault traces wider. Even though a large spatial window can have some positive effects, we recommend using a relatively small spatial window (five traces) when extracting subtle fault geometric attributes.