矿床地球化学国家重点实验室知识库

It's a key problem to recognize the kinds of sediments in the ocean bottom during an acoustic survey or seismic exploration. In this paper, an ultrasonic rock physics experiment was introduced in the flume, which simulated different sedimentary types of ocean bottom, such as stone, fine sand, coarse sand, silt and cement. After processing the simulated acoustic data, some physical attributes, which are sensitive to different types of sediment, was found. In which, the weighted average frequency attribute can distinguish the coarse sand, silt and stone substrate if combined with sweetness attribute. The instantaneous quality factor (Q) attribute highlights the cement restrained with the weighted average frequency attribute. Through analyzing the relationships between porosity, density and these sensitive acoustic attributes, the types of sediment in the flume can be deduced and inversed by artificial neural network method.