Logging Evaluation of Carboniferous Visean Marlstone Reservoir in the Southern Margin of Pre-caspian Basin

Taking the Carboniferous Visean marlstone in the southern margin of the Pre-Caspian Basin as the research target, this study establishes a customized logging evaluation methodology and classifies reservoir types through comprehensive consideration of organic matter abundance, mineral composition, porosity, and fracture development. GR, DT, and RD curves were prioritized to predict total organic carbon (TOC) content using the K-Nearest Neighbors (KNN) machine learning method. Considering the development of bitumen in the reservoir, the multi-mineral logging interpretation model is optimized, and the accurate lithology and porosity profile are inverted. Using the DT and DTS logging curves, the mechanical parameters such as Young’s modulus and Poisson’s ratio are calculated, and then the fracture development index (FI) is constructed to evaluate the fracture development of the reservoir. Finally, the reservoir comprehensive index (ICF) of multi-parameter weight method is constructed, and the I-III reservoirs are divided. This work innovatively establishes a systematic logging evaluation framework for marlstone reservoirs, providing quantitative criteria for unconventional reservoir characterization. The methodology offers significant guidance for exploration and development of marlstone reservoirs in the Pre-Caspian Basin and analogous geological settings, demonstrating substantial theoretical and practical implications for emerging unconventional reserviors.