Recent advances in the processing and interpretation of sonic imaging surveys warrant a fresh look at the performance of active acoustic ranging for locating wellbores. The interpretation of results from sonic imaging surveys typically has been done in workflows similar to classic seismic interpretation, where the data are projected into a 2D plane and reflective features are picked. These sonic imaging workflows require significant time and expertise to execute. The reflected arrival events typically are obscured by higher amplitude borehole modes, and the migration workflow needs numerous critical parameter choices that require interpreting the raypath type and azimuth of the reflected arrivals. When used for acoustic ranging, additional challenges are present, particularly in situations where the logging tool rotates and the relative position of the target well changes with depth. This may occur when the logging or target well trajectories have a curved shape, since determining the direction and distance to the target well then requires careful interpretation of migration image amplitudes. We demonstrate how a newly developed automated approach to the interpretation of sonic imaging data helps improve accuracy and removes interpreter bias while simplifying the processing chain and reducing turnaround time. We compare our results to what has been obtained previously by using the same data set. We achieve a marked improvement in accuracy and consistency using this new technique.