A Python-based platform for processing and analyzing data from core CT scans will be presented. This dataset is a high resolution 3D dataset of compositional and textural information. In raw form, this data contains artifacts and is in a form unsuitable for analysis. Once the data has been cleaned, it can be processed to detect features such as beds, laminae and dip angle. It can be combined with high resolution core photographs and well logs. Machine learning algorithms can use the CT data as a feature set to perform facies classification.