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the relative moment of all events in the sequence. To implement this, we will  separate the matched filter detections out into sequences based first on detecting  template, and then on waveform similarity and hypocentral location. As each template  event generally represents the largest was detected and processed automatically, a local  magnitude event in has already been assigned to  each of these sequences,  they are likely the best candidate for waveform-based moment tensor inversion. event.  We propose calculating seismic moment of these template events following the technique  outlined by both Jiao et al. \cite{Jiao_2014} and Guilhem et al. \cite{Guilhem_2014}  and to can  use these moment tensors pre-assigned magnitudes  to calibrate the relative moment calculations from the SVD method. This will work method,  provided each sequence contains  onlyfor sequences which contain at least  one template event for  which event. In this way  wecan calculate a reliable moment tensor solution but  will provide be left with  accurate moment local  magnitude values within these sequences down to potentially very small values.  Using the method of Guilhem and others \cite{Guilhem_2014} to calculate the focal  mechanisms for the templates will allow us to investigate the non-double-couple  components of these events which can account for large percentages of seismic moment  in a geothermal environment \cite{Guilhem_2014}. Furthermore, non-double-couple components of the  moment tensor offer extremely valuable information about the cause of seismicity.  For instance, we might expect to see an increase in the  non-double-couple component of the calculations based on relative  moment tensor near injection wells, transitioning  to largely double-couple events away from calculations via  the well or after well shut-in reflecting  a mechanism which contains parts shear failure and tensile opening in areas where  fluid movement is occurring \cite{Guilhem_2014}. SVD method.  \subsection{Focal Mechanisms}  Calculation of the focal mechanisms for the matched filter-detected events in this study will be done using the approach outlined in \cite{Pugh_2016} which expresses the first motion of a given phase arrival as the probability of both negative and positive polarities instead of the standard, binary "up or down" approach. This approach can also be fully automated which is useful when dealing with datasets of the size of matched filter detection catalogs.