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

• Published in: Applied geophysics Vol. 14; no. 2; pp. 225 - 235
• Main Authors: Li, Chang-Zheng, Yang, Yong, Wang, Rui, Zheng, Jun
• Format: Journal Article
• Language: English
• Published: Beijing Chinese Geophysical Society 01.06.2017; Springer Nature B.V; The Yellow River Institute of Hydraulic Research, Zhengzhou 450003, China
• Subjects: Acoustic data; Bottom sediments; Density; Earth and Environmental Science; Earth Sciences; Experimental data; Fluvial sediments; Geophysics; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Grain size; Mathematical models; Particle size; Permeability; Physical properties; Porosity; Profiling; Propagation velocity; Reflectance; Reservoirs; Rivers; Sediment; Sediments; Seismic velocities; Size distribution; Soil properties; Spatial variations; Wave propagation; Wave reflection; Wave velocity; density; inversion; subbottom profiling; river sediment; mechanical sampling
• ISSN: 1672-7975; 1993-0658
• DOI: 10.1007/s11770-017-0621-1

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.