The basin-scale distribution of gas hydrates and methane migration pathways in the western Black Sea remains enigmatic, owing to the region's complex geological history. Characterizing the abundant gas hydrate accumulations across temporal scales poses significant challenges. In this study, we developed and applied a 3D large-scale numerical model to study the formation, development, and fate of natural gas hydrate systems in the western Black Sea sub-basin. Our model enables us to simulate the dynamic evolution of basin geometry and facies distribution over the last 98 million years and under dynamically changing boundary conditions, e.g. due to sea-level changes. Our study estimates the total volume of gas hydrates stored within western Black Sea sediments at ∼14,607 MtC, equivalent to ∼30,073 × 1011 m3 of CH4 (at STP conditions) which is about 5 times higher than average gas hydrate density at continental margins. Our findings reveal three distinct mechanisms driving gas hydrate reservoir formation within the reconstructed sub-basin: gas hydrate recycling zones, chimney-like structure formation, and gas hydrate deposits associated with paleo-deep sea fans. We identified and simulated key controlling parameters, related to methane migration pathways and regional geomorphology, governing each type of hydrate formation. Subsequently, we conduct a detailed analysis of regional gas hydrate systems, focusing on the Dniepr paleo-fan system, the Danube paleo-fan region, multiple offshore locations near Turkey, and the central Black Sea area. Furthermore, we investigate various biogenic methane formation kinetics and their impact on basin-scale methane generation. Our sensitivity studies enable us to predict the optimal temperature range for microbial activity driving methanogenesis in the Black Sea sediments at 30 °C–40 °C. Overall, our study provides a novel understanding and quantitative correlation between methane generation, migration, and storage in the form of gas hydrates on a basin-scale in the western Black Sea.
Read full abstract