Geosciences Barcelona, GEO3BCN-CSIC, C/Lluis Solé i Sabarís s/n, 08028 Barcelona, Spain.
Department of Chemistry and Physics, University of Almería, Carretera de Sacramento s/n, La Cañada de San Urbano, 04120 Almería, Spain.
Sensors (Basel). 2021 Sep 4;21(17):5946. doi: 10.3390/s21175946.
Horizontal-to-Vertical Spectral Ratios (HVSR) and Rayleigh group velocity dispersion curves (DC) can be used to estimate the shallow S-wave velocity (VS) structure. Knowing the VS structure is important for geophysical data interpretation either in order to better constrain data inversions for P-wave velocity (VP) structures such as travel time tomography or full waveform inversions or to directly study the VS structure for geo-engineering purposes (e.g., ground motion prediction). The joint inversion of HVSR and dispersion data for 1D VS structure allows characterising the uppermost crust and near surface, where the HVSR data (0.03 to 10s) are most sensitive while the dispersion data (1 to 30s) constrain the deeper model which would, otherwise, add complexity to the HVSR data inversion and adversely affect its convergence. During a large-scale experiment, 197 three-component short-period stations, 41 broad band instruments and 190 geophones were continuously operated for 6 months (April to October 2017) covering an area of approximately 1500km2 with a site spacing of approximately 1 to 3km. Joint inversion of HVSR and DC allowed estimating VS and, to some extent density, down to depths of around 1000m. Broadband and short period instruments performed statistically better than geophone nodes due to the latter's gap in sensitivity between HVSR and DC. It may be possible to use HVSR data in a joint inversion with DC, increasing resolution for the shallower layers and/or alleviating the absence of short period DC data, which may be harder to obtain. By including HVSR to DC inversions, confidence improvements of two to three times for layers above 300m were achieved. Furthermore, HVSR/DC joint inversion may be useful to generate initial models for 3D tomographic inversions in large scale deployments. Lastly, the joint inversion of HVSR and DC data can be sensitive to density but this sensitivity is situational and depends strongly on the other inversion parameters, namely VS and VP. Density estimates from a HVSR/DC joint inversion should be treated with care, while some subsurface structures may be sensitive, others are clearly not. Inclusion of gravity inversion to HVSR/DC joint inversion may be possible and prove useful.
水平-垂直谱比 (HVSR) 和瑞利群速度频散曲线 (DC) 可用于估计浅层 S 波速度 (VS) 结构。了解 VS 结构对于地球物理数据解释很重要,无论是为了更好地约束 P 波速度 (VP) 结构的反演,例如旅行时层析成像或全波形反演,还是为了直接研究 VS 结构以进行地质工程目的(例如,地面运动预测)。HVSR 和频散数据的联合反演可用于一维 VS 结构,从而描述最上层地壳和近地表,其中 HVSR 数据(0.03 到 10 秒)最敏感,而频散数据(1 到 30 秒)约束较深的模型,否则,这将增加 HVSR 数据反演的复杂性,并对其收敛性产生不利影响。在一次大规模实验中,197 个三分量短周期台站、41 个宽带仪器和 190 个检波器连续运行了 6 个月(2017 年 4 月至 10 月),覆盖了大约 1500km2 的区域,站点间距约为 1 到 3km。HVSR 和 DC 的联合反演可用于估计 VS,在某种程度上还可以估计密度,深度可达 1000m 左右。宽带和短周期仪器的性能统计优于检波器节点,因为后者在 HVSR 和 DC 之间存在灵敏度差距。可以使用 HVSR 数据与 DC 进行联合反演,从而提高浅层的分辨率和/或缓解短周期 DC 数据的缺失,后者可能更难获得。通过将 HVSR 纳入 DC 反演,可以将 300m 以上各层的置信度提高两到三倍。此外,HVSR/DC 联合反演对于大规模部署中的 3D 层析成像反演生成初始模型可能很有用。最后,HVSR 和 DC 数据的联合反演可能对密度敏感,但这种敏感性是特定情况的,并且强烈依赖于其他反演参数,即 VS 和 VP。应谨慎对待 HVSR/DC 联合反演的密度估计,而一些地下结构可能敏感,其他则不敏感。将重力反演纳入 HVSR/DC 联合反演可能是可能的,并可能证明有用。