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用于海底地声剖面及不确定性的反射数据联合时频域反演

Joint time/frequency-domain inversion of reflection data for seabed geoacoustic profiles and uncertainties.

作者信息

Dettmer Jan, Dosso Stan E, Holland Charles W

机构信息

School of Earth and Ocean Sciences, University of Victoria, Victoria, BC V8W 3P6, Canada.

出版信息

J Acoust Soc Am. 2008 Mar;123(3):1306-17. doi: 10.1121/1.2832619.

Abstract

This paper develops a joint time/frequency-domain inversion for high-resolution single-bounce reflection data, with the potential to resolve fine-scale profiles of sediment velocity, density, and attenuation over small seafloor footprints (approximately 100 m). The approach utilizes sequential Bayesian inversion of time- and frequency-domain reflection data, employing ray-tracing inversion for reflection travel times and a layer-packet stripping method for spherical-wave reflection-coefficient inversion. Posterior credibility intervals from the travel-time inversion are passed on as prior information to the reflection-coefficient inversion. Within the reflection-coefficient inversion, parameter information is passed from one layer packet inversion to the next in terms of marginal probability distributions rotated into principal components, providing an efficient approach to (partially) account for multi-dimensional parameter correlations with one-dimensional, numerical distributions. Quantitative geoacoustic parameter uncertainties are provided by a nonlinear Gibbs sampling approach employing full data error covariance estimation (including nonstationary effects) and accounting for possible biases in travel-time picks. Posterior examination of data residuals shows the importance of including data covariance estimates in the inversion. The joint inversion is applied to data collected on the Malta Plateau during the SCARAB98 experiment.

摘要

本文针对高分辨率单反射数据开发了一种联合时频域反演方法,该方法有潜力在小海底覆盖范围(约100米)内解析沉积物速度、密度和衰减的精细尺度剖面。该方法利用时域和频域反射数据的顺序贝叶斯反演,采用射线追踪反演来确定反射走时,并采用层包剥离法进行球面波反射系数反演。走时反演的后验可信度区间作为先验信息传递给反射系数反演。在反射系数反演中,参数信息以旋转到主成分的边际概率分布的形式从一个层包反演传递到下一个层包反演,提供了一种有效方法来(部分)考虑一维数值分布中的多维参数相关性。通过采用全数据误差协方差估计(包括非平稳效应)并考虑走时拾取中可能存在的偏差的非线性吉布斯采样方法,给出了定量的地质声学参数不确定性。对数据残差的后验检验表明了在反演中纳入数据协方差估计的重要性。该联合反演方法应用于SCARAB98实验期间在马耳他高原收集的数据。

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