Systems and methods include a computer-implemented method for suggesting changes in wellbore operations based on the reservoir quality predictions, three-dimensional (3D) reservoir modeling, and volume estimations. Correlated geoscience datasets are generated for a set of oil and gas drilling operations. Integrated Diagenetic-Depositional Facies (IDDF) classifications are performed using genetic and analytic criteria and using the correlated geoscience datasets. A training dataset is prepared using the IDDF classifications and well data including core, petrographic, and routine core analyses (RCA) data. The training dataset includes correlations of porosity-permeability (poro-perm) and log properties. Automated machine learning is performed using the training dataset to provide IDDF estimation in uncovered wells. Reservoir quality predictions, 3D reservoir modeling, and volume estimations are performed based on the automated machine learning. Suggested changes to make in wellbore operations are provided in a user interface based on the reservoir quality predictions, the 3D reservoir modeling, and the volume estimations.