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首页> 外文期刊>Journal of Applied Geophysics >Marine rock physical flume experiment: The method of seafloor shallow sediment recognition by ultrasonic physical attributes
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Marine rock physical flume experiment: The method of seafloor shallow sediment recognition by ultrasonic physical attributes

机译:海岩石物理水槽实验:利用超声物理属性识别海床浅层沉积物的方法

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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. (C) 2015 Elsevier B.V. All rights reserved.
机译:在声学勘测或地震勘探过程中,识别海底沉积物的种类是一个关键问题。本文在水槽中引入了超声波岩石物理实验,模拟了海底不同沉积类型,如石头,细砂,粗砂,粉砂和水泥。处理模拟的声波数据后,发现了一些对不同类型的沉积物敏感的物理属性。其中,加权平均频率属性与甜度属性结合使用可以区分粗砂,粉砂和石材。瞬时品质因数(Q)属性突出显示了受加权平均频率属性约束的水泥。通过分析孔隙度,密度和这些敏感的声学属性之间的关系,可以通过人工神经网络方法推导和反演水槽中的沉积物类型。 (C)2015 Elsevier B.V.保留所有权利。

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