Abstract: Based on the data from the shared Cruise supported by the National Natural Science Foundation of China in Bohai and Yellow Sea in 2018, this study processed and analyzed a large amount of underway raw acoustic data acquired by a shipborne dual-frequency echo sounder (200 kHz and 12 kHz). By integrating synchronously measured temperature and salinity profiles for calibration, the common issue of inaccurate detection of ocean interface layers using acoustic data was effectively resolved. Through the fusion of the calibrated acoustic data from both frequencies, a new method was established to identify the thickness of seabed mud layers using dual-frequency echo sounder. The method leverages the high-resolution characteristics of the 200 kHz acoustic wave to identify the upper interface of the mud layer and the strong penetration capability of the 12 kHz’s to identify the lower interface, thereby enabling the calculation of mud layer thickness. The results were validated by in-situ standard penetration test data, demonstrating that the method is applicable for studying the temporal variation and spatial distribution of seabed mud layer thickness in the Yellow Sea. In the context of the current era of marine big data, this study also highlights the significance of further mining and efficiently utilizing historical data to promote breakthroughs in marine survey research.