This paper will present preliminary results and status in development of an automated tracking algorithm for whale signals using the Comprehensive Test Ban Treaty (CTBT) sensor network. The data from the CTBT stations is being made available for academic work, and the stations are also detecting bioacoustics sounds as well as seismic activity. We present an approach used to process several channels of the acoustic data collected off Cape Leeuwin, Australia, and automatically search for biologic activity using cross-correlation and Time-Difference-of-Arrival methods. After developing a graph of locations for peak correlation amplitude, the locations are mapped and grouped using location and proximity, in order to develop motion tracks and compare coherence of the signals within a grouping and between groupings, thus identify individual whales based on the differences in location and coherence levels.