This study investigates the formation mechanism of natural gas hydrates in the deep-water Qiongdongnan Basin, with particular emphasis on the controlling role of sandy reservoirs in the hydrate accumulation system. On the basis of geological observations of sand bodies inside and outside the gas hydrate stability zone (GHSZ), including locally continuous hydrate-bearing sand bodies within the stability zone, the sealing effect of overlying mudstones, and sandy reservoirs near the base of the stability zone that provide pathways for the migration of underlying free gas, a new conceptual model for hydrate accumulation is proposed. A Transformer-encoder-based artificial intelligence algorithm was applied to three-dimensional seismic data and associated well-log data to predict the spatial distribution of sandy reservoirs and gas hydrate enrichment zones in the study area. The prediction results indicate high-saturation hydrate enrichment within high-quality sandy reservoirs inside the stability zone, and also suggest the sealing efficiency of overlying mudstones and the possible connectivity between sand bodies beneath the stability zone and deeper gas sources. This study supports the proposed accumulation mechanism and illustrates the application of artificial intelligence methods for hydrate reservoir prediction under complex geological conditions, providing an integrated interpretation and technical reference for selecting natural gas hydrate exploration targets in the deep-water northern South China Sea.
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Liu et al. (2026) studied this question.
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