利用序列反演研究南海细粒沉积物的地声参数

Wang Hao, Rui Duan, Kunde Yang
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引用次数: 0

摘要

与深海细粒沉积物相互作用的宽带信号是形成几何阴影区声场的关键。这些信号通过海底反射路径和折射路径传播。本文采用了一种顺序反演方案来估算深海粘土沉积物中的地质声学参数。该反演基于不同频率的海底反射损耗数据,以及2018年南海试验获得的折射与反射之间的旅行时差数据。地质声学参数随深度变化的剖面采用伯恩斯坦多项式计算。利用自适应单纯形模拟退火法和一种称为变异贝叶斯蒙特卡洛的近似变异推理技术,对多项式系数及其后验概率密度函数进行了有效估计。该技术与马尔可夫链蒙特卡罗采样法相比,效率更高,精度也相当。反演结果表明,该区域的深海粘土沉积物表现出正声速梯度和相对较低的衰减,两者的概率都很高。推导出的海底模型准确预测了传输损耗,与实验数据十分吻合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of Geoacoustic Parameters of Fine-Grained Sediment in the South China Sea Using Sequential Inversion
Broadband signals interacting with deep ocean fine-grained sediment are crucial in shaping the acoustic field of the geometric shadow zone. These signals travel through both the seabed reflected path and the refracted path. In this article, a sequential inversion scheme is employed to estimate the geoacoustic parameters in abyssal clay sediments. This inversion is based on seabed reflection loss data at different frequencies, as well as travel time difference data between refractions and reflections obtained from the South China Sea Experiment in 2018. Depth-dependent profiles of geoacoustic parameters are formulated using Bernstein polynomials. The polynomial coefficients and their posterior probability density functions are efficiently estimated using the adaptive simplex simulated annealing method and an approximate variational inference technique known as Variational Bayesian Monte Carlo. This technique demonstrates superior efficiency and comparable accuracy to Markov Chain Monte Carlo sampling. The inversion results indicate that the abyssal clay sediments in this area exhibit a positive sound speed gradient and relatively low attenuation, both with high probabilities. The deduced seabed model accurately predicts the transmission loss, aligning well with the experimental data.
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