A rugged seabed signal compensation method based on W transform compressive sensing framework

The Qiongdongnan Basin, situated in the northern part of the South China Sea, is a geologically significant and resource-rich marine area, characterized by extremely complex seabed topography that transitions seamlessly across shallow coastal waters, gently sloping continental shelves, steep shelf break zones, and abyssal deep-sea basins. Within this basin, the vicinities of the rugged and uneven seabed-marked by abrupt topographic variations such as submerged ridges, fault scarps, and scattered seamounts-have emerged as key exploration zones, as geological surveys and preliminary prospecting have identified a multitude of potential hydrocarbon and mineral reserve targets in these sub-seabed formations. However, the amplitude and frequency of seismic data under the rugged seabed in deep water are distorted, and there is a large gap between the seismic data collected on land and that under the rugged seabed. Traditional signal compensation methods fail to effectively process such data. ObjectiveIn order to obtain high-quality seismic data and accurately evaluate targets under the rugged seabed, it is urgent to develop a reasonable and effective compensation method. MethodsInspired by time-frequency analysis and compressive sensing methods, this paper designed a compressive sensing compensation framework based on W transform. By constructing the compensation matrix between the reference trace and the target trace, the amplitude compensation of seismic data was rapidly achieved in a single step. The sparse transform regularization method was introduced to ensure the high signal-to-noise ratio of the compensation data and improve the quality of the seismic data. ResultsThis method was used to compensate the seismic data under complex rugged seabed conditions in the northern part of the South China Sea, and the consistency of the energy distribution of the seismic data profile after compensation was effectively improved. ConclusionThe successful application of the signal compensation processing demonstrates the feasibility of the method and provides a reference for the signal compensation processing of similar seismic data.