We improved two beamforming-based methodologies for seismological analysis. The first one is a new Three-Dimensional Phase-Weighted Relative Back Projection (3-D PWBP) method to improve the spatial resolution of Back Projection results. We exploit both phase and amplitude of the seismogram signal to enhance the distinction of correlated signals. Also, we implement a 3-D velocity model to provide more accurate travel times. We vindicate these refinements with several synthetic tests and an analysis of the 1997 Mw 7.2 Zirkuh (Iran) earthquake, which we show ruptured mainly unilaterally southwards at a rupture speed of ∼3.0 km/s along its ∼125 km- long, mostly single-stranded surface rupture. Then, we apply the new method to the more complex case of the 2016 Mw 7.8 Kaikoura (New Zealand) earthquake, which we demonstrate is divided into two major stages separated by a gap of ∼8 s and ∼30–40 km. The overall rupture speed is ∼1.7 km/s and the overall duration is ∼84 s, considerably shorter than some earlier estimates. We see no clear evidence for continuous failure of the subduction interface that underlies the known, surface-rupturing crustal faults, though we cannot rule out its involvement in the second major stage in the northern part of the rupture area. The late (∼80 s) peak in relative energy is likely a high-frequency stopping phase, and the rupture appears to terminate southwest of the offshore Needles fault. The second methodology is a novel workflow for earthquake detection and location, named Seismicity-Scanning based on Navigated Automatic Phase-picking (S-SNAP). By taking a cocktail approach that combines Source-Scanning, Kurtosis-based Phase-picking and the Maximum Intersection location technique into a single integrated workflow, this new method is capable of delineating complex spatiotemporal distributions of seismicity. It is automatic, efficiently providing earthquake locations with high comprehensiveness and accuracy. We apply S-SNAP to a dataset recorded by a dense local seismic array during a hydraulic fracturing operation to test this novel approach and to demonstrate the effectiveness of S-SNAP in comparison to existing methods. Overall, S-SNAP found nearly four times as many high-quality events as a template-matching based catalogue. All events in the previous catalogue are identi- fied with similar epicenter, depth and magnitude, while no false detections are found by visual inspection. / Graduate