Microseismic phase detection and arrival picking are critical steps in the processing of hydraulic fracturing microseismic monitoring data. As the signal-to-noise ratios of P- and S-waves differ because of the influence of focal mechanisms, geometry, and background noise, difficulties are introduced in the effective discrimination of seismic phases and the accurate acquisition of arrivals in conventional processing methods. In this paper, we propose a method for identifying microseismic phase arrival time by comprehensively analyzing the variation of moveout curves and combining the intra-event waveform similarities with the energy ratio of multitrace signals. First, a curve-fitting formula is constructed with perforation arrivals, and event detection is achieved by adopting an energy-weighted similarity coefficient that seeks plausible fitting curves with a sliding time window in continuous microseismic recordings. Then, the P- and S-waves are separated by the fitting parameters. The known arrival time trend of the microseismic phase is employed to calculate residual time corrections. Finally, the accurate arrival results of the microseismic phases can be obtained by picking the arrivals of stacked traces. The reliability and effectiveness of the proposed method for microseismic phase detection and arrival picking were determined through tests using field data. Arrival results indicate that the proposed method can improve accuracy compared with the traditional energy ratio method.