AI fault prediction for ultra-deepwater OBN seismic data: advancing structural interpretation in carbonate reservoirs
Zeyu Wang
Accurate interpretation of complex fault networks is crucial for ultra-deepwater hydrocarbon exploration, yet traditional towed-streamer (TS) seismic systems frequently fail to image subtle faults due to environmental noise and complex topographies. This study develops an AI-driven fault prediction framework specifically tailored for high-fidelity Ocean Bottom Node (OBN) seismic data. The proposed methodology uses structure-oriented filtering for data preprocessing and an enhanced High-Resolutio