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The 12 February 2013 nuclear test conducted by the Democratic People’s Republic of Korea stands out among other nuclear tests because it produced unusually large transversal motions. Previous studies found various percentages of isotropic components of the seismic moment tensor (MT), which opens up an important question about the reliability of the methods and assumptions we routinely use to recover the seismic MT in the point source approximation. Of particular interest is the data noise model that can be utilized to represent the uncertainty associated with the recorded data. If the noise is not accounted for, this may result in a range of unwanted effects such as overfitting waveform data, and, in turn, it may lead to erroneous conclusions. We thus scrutinize the analyses of the seismic MT of this explosion by performing a thorough analysis of the source depth and time utilizing newly developed Earth structure models to invert seismograms at regional distances at different frequency bands. In addition, we estimate the solution uncertainty within a hierarchical Bayesian framework that allows accounting for noise in the data. Our results show that the resulting MT of this event contains an expectedly large isotropic component (about 70%) and a dip-slip faulting.

Moment tensor (MT) inversion studies of events in The Geysers geothermal field mostly focused on microseismicity and found a large number of earthquakes with significant non‐double‐couple (non‐DC) seismic radiation. Here we concentrate on the largest events in the area in recent years using a hierarchical Bayesian MT inversion. Initially, we show that the non‐DC components of the MT can be reliably retrieved using regional waveform data from a small number of stations. Subsequently, we present results for a number of events and show that accounting for noise correlations can lead to retrieval of a lower isotropic (ISO) component and significantly different focal mechanisms. We compute the Bayesian evidence to compare solutions obtained with different assumptions of the noise covariance matrix. Although a diagonal covariance matrix produces a better waveform fit, inversions that account for noise correlations via an empirically estimated noise covariance matrix account for interdependences of data errors and are preferred from a Bayesian point of view. This implies that improper treatment of data noise in waveform inversions can result in fitting the noise and misinterpreting the non‐DC components. Finally, one of the analyzed events is characterized as predominantly DC, while the others still have significant non‐DC components, probably as a result of crack opening, which is a reasonable hypothesis for The Geysers geothermal field geological setting.