We describe a novel system of categorizing rock samples using a branch of topology as means of extracting pertinent info. Previously, categorization of rock samples based on CT scans was something only possible by hand. By utilizing persistent homology, we aim to automate that process and describe here some of the challenges in doing so. If successful, we plan to apply persistent homology to other fields including intelligent thresholding, data analytics, and signal processing.