As crucial transportation hubs and economic nodes, the underwater security and infrastructure maintenance of harbors are of paramount importance. Harbors are characterized by high vessel traffic and complex underwater environments, where traditional underwater inspection methods, such as diver operations, face challenges of low efficiency, high risk, and limited operational range. This paper introduces a collaborative survey and disposal system that integrates a deformable unmanned surface vehicle (USV) with a lightweight remotely operated vehicle (ROV). The USV is equipped with a side-scan sonar (SSS) and a multibeam echo sounder (MBES), enabling rapid, large-area searches and seabed topographic mapping. The ROV, equipped with an optical camera system, forward-looking sonar (FLS), and a manipulator, is tasked with conducting close-range, detailed observations to confirm and dispose of abnormal objects identified by the USV. Field trials were conducted at an island harbor in the South China Sea, where simulated underwater objects, including an iron drum, a plastic drum, and a rubber tire, were deployed. The results demonstrate that the USV-ROV collaborative system effectively meets the demands for underwater environmental measurement, object localization, identification, and disposal in complex harbor environments. The USV acquired high-resolution (0.5 m × 0.5 m) three-dimensional topographic data of the harbor, effectively revealing its topographical features. The SSS accurately localized and preliminarily identified all deployed simulated objects, revealing their acoustic characteristics. Repeated surveys revealed a maximum positioning deviation of 2.2 m. The lightweight ROV confirmed the status and location of the simulated objects using an optical camera and an underwater positioning system, with a maximum deviation of 3.2 m when compared to the SSS locations. The study highlights the limitations of using either vehicle alone. The USV survey could not precisely confirm the attributes of the objects, whereas a full-area search of 0.36 km² by the ROV alone would take approximately 20 h. In contrast, the USV-ROV collaborative model reduced the total time to detect all objects to 9 h, improving efficiency by 55%. This research offers an efficient, reliable, and economical practical solution for applications such as underwater security, topographic mapping, infrastructure inspection, and channel dredging in harbor environments.

Recently, shallow gas fields and hydrate-bearing sand in the deepwater area of the northern South China Sea have been successively discovered, and the accurate prediction of shallow sands is an important foundation. However, most of the current prediction methods are mainly for deep oil and gas reservoirs. Compared with those reservoirs with high degree of consolidation, shallow sandy reservoirs are loose and unconsolidated, whose geophysical characteristics are not well understood. This paper analyzes the logging data of shallow sandy reservoirs recovered in the South China Sea recently, which show that the sand content has a significant influence on Young’s modulus and Poisson’s ratio of the sediments. Therefore, this paper firstly constructs a new petrophysical model of unconsolidated strata targeting sandy content and qualitatively links the mineral composition and the elastic parameters of the shallow marine sediments and defines a new indicator for sandy content: the modified brittleness index (MBI). The effectiveness of MBI in predicting sandy content is then verified by measured well data. Based on pre-stack seismic inversion, the MBI is then inverted, which will identify the sandy deposits. The method proposed provides technical support for the subsequent shallow gas and hydrate exploration in the South China Sea.