We describe an automated short-period Rayleigh wave (Rg) detector designed to work on local (<2.5° epicentral distance) events recorded at three- component stations. The detector was modeled after an automatic 17- to 22-sec Rayleigh-wave detection method; however, we have modified the algorithms for local distance and short-period applications. We have tested the detector on a well-located cluster of mining events from central India and on a set of ground-truth events in the area. The Rg detector was also integrated into a semiautomatic event detection and location algorithm and applied on continuous data. Fourier and wavelet-based methods are evaluated for prefiltering. We observe that sample standard deviations of backazimuth estimates using the Rg detector, after wavelet prefiltering, are comparable to fk3C P backazimuth estimates from event clusters. Our results indicate that using the Rg-phase backazimuths for event location is a promising alternative to using small signal-to-noise ratio first-arrival backazimuths. We recommend wavelet prefiltering versus Fourier prefiltering because it is more consistent for the detection of low signal-to-noise ratio events at local distances.