Digital Sedimentology
Development of tools based on deep learning algorithms for complex analysis of petrographic section images
WEB solution deployed in the client’s office
Automated calculation of parameters of the void space
Displaying contacts with color indications by type
Automated segmentation by grain size, roundness, mineralogy
Additional core sections analysis using Shutov, sphericity and roundness diagrams
Automated analysis of directional angle distribution of the grain’s main axis
Creation of structured data base of marked core sections
Implementation of model optimization algorithms for new incoming data
Testing and execution of the algorithm of synthetic cut images generation
Testing and execution of the algorithm of automated segmentation of structured classes in core sections
