论文标题
使用能量可能函数的表面波散分散反演
Surface wave dispersion inversion using an energy likelihood function
论文作者
论文摘要
地震表面波散分散反演被广泛用于研究地球的地下结构。分散性能通常是通过使用频率速度（F-C）分析和从获得的F-C频谱挑选相速度的。但是，由于潜在的污染，F-C频谱通常在每种模式下在每个频率下都具有多模式。这些引入了采摘相速度中的不确定性和错误，因此获得的剪切速度结构是偏差的。为了克服这个问题，在本研究中，我们引入了一种直接使用频谱作为数据的新方法。我们通过解决贝叶斯框架中的反问题并定义了新的似然函数，即能量可能性函数，该功能使用频谱能量来定义数据拟合，从而实现了这一目标。我们将新方法应用于密集接收器阵列记录的土地数据集，并将结果与使用传统方法获得的结果进行比较。结果表明，新方法会产生更准确的结果，因为它们更好地匹配了折射断层扫描的独立数据。该真实数据应用程序还表明，它可以有效地应用，因为它消除了选择相速度的需求，并且对当前实践的调整相对较少，因为它使用标准的F-C面板来定义了可能性。因此，我们建议使用能量可能性功能，而不是在表面波分散反演中明确选择相位速度。
Seismic surface wave dispersion inversion is used widely to study the subsurface structure of the Earth. The dispersion property is usually measured by using frequency-phase velocity (f-c) analysis and by picking phase velocities from the obtained f-c spectrum. However, because of potential contamination the f-c spectrum often has multimodalities at each frequency for each mode. These introduce uncertainty and errors in the picked phase velocities, and consequently the obtained shear velocity structure is biased. To overcome this issue, in this study we introduce a new method which directly uses the spectrum as data. We achieve this by solving the inverse problem in a Bayesian framework and define a new likelihood function, the energy likelihood function, which uses the spectrum energy to define data fit. We apply the new method to a land dataset recorded by a dense receiver array, and compare the results to those obtained using the traditional method. The results show that the new method produces more accurate results since they better match independent data from refraction tomography. This real-data application also shows that it can be applied efficiently since it removes the need to pick phase velocities, and with relatively little adjustment to current practice since it uses standard f-c panels to define the likelihood. We therefore recommend using the energy likelihood function rather than explicitly picking phase velocities in surface wave dispersion inversion.
