Structural imaging using body-wave energy present in ambient seismic data remains a challenging task, largely because these wave modes are commonly much weaker than surface wave energy. In a number of situations body-wave energy has been extracted successfully; however, (nearly) all successful body-wave extraction and imaging approaches have focused on cross-correlation processing. While this is useful for interferometric purposes, it can also lead to the inclusion of unwanted noise events that dominate the resulting stack, leaving body-wave energy overpowered by the coherent noise. Conversely, wave-equation imaging can be applied directly on non-correlated ambient data that has been preprocessed to mitigate unwanted energy (i.e., surface waves, burst-like and electromechanical noise) to enhance body-wave arrivals. Following this approach, though, requires a significant preprocessing effort on often Terabytes of ambient seismic data, which is expensive and requires automation to be a feasible approach. In this work we outline an automated processing workflow designed to optimize body wave energy from an ambient seismic data set acquired on a large-N array at a mine site near Lalor Lake, Manitoba, Canada. We show that processing ambient seismic data in the recording domain, rather than the cross-correlation domain, allows us to mitigate energy that is inappropriate for body-wave imaging. We first develop a method for window selection that automatically identifies and removes data contaminated by coherent high-energy bursts. We then apply time- and frequency-domain debursting techniques to mitigate the effects of remaining strong amplitude and/or monochromatic energy without severely degrading the overall waveforms. After each processing step we implement a QC check to investigate improvements in the convergence rates - and the emergence of reflection events - in the cross-correlation plus stack waveforms over hour-long windows. Overall, the QC analyses suggest that automated preprocessing of ambient seismic recordings in the recording domain successfully mitigates unwanted coherent noise events in both the time and frequency domain. Accordingly, we assert that this method is beneficial for direct wave-equation imaging with ambient seismic recordings.