I am a sedimentologist specializing in carbonate sedimentology, with a primary focus on the depositional systems and diagenetic evolution of carbonate rocks. My research centers on paleo-depositional environment reconstruction, integrating sedimentological, stratigraphic, and petrographic datasets to interpret carbonate platform development and basin evolution. In addition to fundamental sedimentological research, I have conducted applied studies in carbonate reservoir geology. My work in this area involves detailed characterization of reservoir properties, emphasizing the geological controls on porosity and permeability distribution. I have extensive experience in reservoir zonation and rock typing, employing quantitative methods such as the Flow Unit Indicator (FZI) and the Stratigraphic Modified Lorenz Plot (SMLP) to define hydraulic flow units and improve reservoir predictability. More recently, my research has expanded into the application of machine learning techniques, particularly neural networks, for reservoir rock classification and petrophysical prediction. This interdisciplinary approach integrates geological insight with data-driven modeling to enhance reservoir characterization accuracy and reduce uncertainty in subsurface interpretation.