Correction of seabed layer thickness in processing subbottom profile data

The subbottom profiling is an important means of marine engineering survey, hazardous geology study and continental shelf scientific research. The accuracy of subbottom profile data interpretation has a direct impact on the research and investigation results. Because some of profilers’ transducer and hydrophone are separately installed, when the survey area is very shallow, distortion of shallow layers will be caused if it is seen as a self-excited and self-collected single-channel seismic system. According to the principle of subbottom profiler, the distortion correction formula is deduced and analyzed, providing actual value to using C-View software to interpret such subbottom profile data more accurately. In addition, the seabed sediments sound velocity is one of the key parameters when acquiring and processing the subbottom profile data. On the basis of comparing some sound velocity forecasting empirical equations, the LU Bo’s equation was considered the most appropriate to predict the seabed sediments, sound velocity at near-shore of China. In a survey of an artificial island site, the LU Bo’s equation and the porosity data obtained from geological drilling were utilized to predict the sediments sound velocity, and the sound velocity structure profile was plotted, which was applied in processing the subbottom profile data of the artificial island investigation. The method of using porosity data to predict sediments sound velocity in processing subbottom profile data can improve the interpretation accuracy and it’s of practical significance.

Inversion of river-bottom sediment parameters using mechanically sampled specimens and subbottom profiling data

The study of river dynamics requires knowledge of physical parameters, such as porosity, permeability, and wave propagation velocity, of river-bottom sediments. To do so, sediment properties are determined on mechanically sampled specimens and from subbottom profiling. However, mechanical sampling introduces disturbances that affect test results, with the exception of grain-size distribution. In this study, we perform inversion of acoustic data using the grain-size distribution of mechanically sampled specimens and the relation between porosity and permeability from the Kozeny-Carman equation as prior information. The wave reflection coefficient of the water-silt interface is extracted from the raw subbottom profile. Based on the effective density fluid model, we combine the Kozeny-Carman equation and the wave reflection coefficient. We use experimental data from two Yellow River reservoirs to obtain the wave velocity and density of multiple sections and their spatial variations, and find that the inversion and testing results are in good agreement.