Conventional seismographic networks sparsely sample the wavefields excited by earthquakes. Thus, standard event detection is conducted by analyzing separate stations and merging their results. Emerging distributed acoustic sensing recording technologies allow for unbiased spatial sampling of the wavefield and, as a result, array‐based processing of the recorded signals. Using a cemented fiber in the San Andreas Fault Observatory at Depth main hole, 800 virtual receivers are sampled at a 1 m interval from the surface to 800 m depth. Recorded earthquakes are approximated as plane waves reaching the bottom of the array first. Following this assumption, the relative travel times of the recorded event depend on the local velocity at the array location and the angle of incidence at which the planar wavefront reaches it. Given the seismic velocity, a newly proposed detection algorithm amounts to a single‐parameter scan of the incidence angle and measurement of data coherency along the different possible travel‐time curves. Using the entire recording array, a much higher effective signal‐to‐noise ratio can be obtained when compared to individual channel processing. About 20 days of recorded seismic activity from the San Andreas Fault is analyzed. Using a downhole single array, the majority of cataloged events in the area are detected. In addition, a previously unknown event is unveiled. We estimate its magnitude at roughly .