The Dynamic Network Experiment 2018 (DNE18) was a virtual experiment designed to quantitatively assess current capabilities for multi-modal data ingestion and processing for nuclear explosion monitoring at the local/regional scale. This assessment will allow us to identify and prioritize remaining challenges that need to be met to achieve desired monitoring capabilities. The experiment was a collaborative effort between Los Alamos National Laboratory, Lawrence Livermore National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratories. We describe efforts to test various velocity models for any bias or other recognizable patterns using two-week, analyst-built event (ABE) bulletin. The data set includes over 6000 events manually-built by the analyst using the Utah Seismic Network which includes about 182 seismo-acoustic stations, 152 of which have analyst arrival picks. There are active mines in the state of Utah, many of which are associated with clusters of events. The ABEs include mostly Pg and Lg arrivals for events within Utah and some just outside the state. Global events were also picked that included teleseismic P and S as well as core phases, etc. although these are not included in this study. We test local, regional, and global P and S velocity models (1-D, 2-D, 3-D) for their effect on the event locations, paying attention to overall epicenter shifts, residual reduction, and error ellipses. Many of the event clusters are good candidates for application of relative relocation techniques.