This study provides the assessment of site characterization and possible shallow shear-velocity structure from the study of the horizontal to vertical spectral ratio (HVSR) measurements using the ambient noise or microtremor (herein called classical HVSR), extracted Rayleigh wave from the ambient noise data (herein called standard HVSR) and earthquake (herein called earthquake HVSR) data at five stations in the Surat district of mainland Gujarat, India. These locations are the hub of many mining and industrial projects like oil and natural gas, which need to function safely within the seismic hazard and ground shaking limits. From the classical and standard HVSR datasets, estimates of the predominant resonant frequency of the soil are obtained, observed to be well matched, from which first order inversions are carried out around the predominant frequency to provide a fair estimate of thickness of the regimented layer over a hard seismic substratum up to a depth of 100 m. In the standard HVSR datasets, the Rayleigh wave ellipticity curves are extracted with time–frequency analysis using continuous wavelet transforms. This is followed by the Rayleigh wave ellipticity inversion approach to derive a first order approximate sedimentary shear velocity structure. We also compute HVSR measurements using earthquakes. The noise and earthquake HVSR curves are well-matched in terms of the predominant frequencies and range from 3.8 to 16.7 Hz and 3.2 to 16.5, respectively. The estimated V_S30 values (the average shear wave velocity (V_S) for the top 30 m of the soil) vary from 520 to 1350 m/s, matching well with some of the geotechnical studies conducted here. The study emphasizes the effectiveness of the single station HVSR method in determination of hitherto unknown soil structures as economical and non-invasive exploration viability and proving quite useful for critical centres of industrial establishments.

中文翻译：

---

古吉拉特邦南部大陆环境噪声和地震HVSR建模，用于现场表征

这项研究通过使用环境噪声或微震（此处称为经典HVSR），从环境噪声数据中提取瑞利波，通过研究水平与垂直光谱比（HVSR）的研究，提供了场地特征和可能的浅剪切速度结构的评估。印度古吉拉特邦苏拉特地区五个站的地震（此处称为标准HVSR）和地震（此处称为HVSR）数据。这些地点是许多采矿和工业项目（如石油和天然气）的枢纽，它们需要在地震危险和地面震动范围内安全运行。从经典和标准的HVSR数据集中，可以获得对土壤主要共振频率的估计值，观察到它们匹配得很好，从中，围绕主频进行一阶反演，以提供对直至100 m深度的坚硬地震基底上的整顿层厚度的合理估计。在标准的HVSR数据集中，使用连续小波变换通过时频分析提取瑞利波椭圆率曲线。其次是瑞利波椭圆率反演方法，以推导一阶近似沉积剪切速度结构。我们还使用地震计算HVSR测量值。噪声和地震HVSR曲线在主要频率方面具有很好的匹配性，范围分别为3.8至16.7 Hz和3.2至16.5。估计的V 在标准的HVSR数据集中，使用连续小波变换通过时频分析提取瑞利波椭圆率曲线。其次是瑞利波椭圆率反演方法，以推导一阶近似沉积剪切速度结构。我们还使用地震计算HVSR测量值。噪声和地震HVSR曲线在主要频率方面具有很好的匹配性，范围分别为3.8至16.7 Hz和3.2至16.5。估计的V 在标准的HVSR数据集中，使用连续小波变换通过时频分析提取瑞利波椭圆率曲线。其次是瑞利波椭圆率反演方法，以推导一阶近似沉积剪切速度结构。我们还使用地震计算HVSR测量值。噪声和地震HVSR曲线在主要频率方面具有很好的匹配性，范围分别为3.8至16.7 Hz和3.2至16.5。估计的V 噪声和地震HVSR曲线在主要频率方面具有很好的匹配性，范围分别为3.8至16.7 Hz和3.2至16.5。估计的V 噪声和地震HVSR曲线在主要频率方面具有很好的匹配性，范围分别为3.8至16.7 Hz和3.2至16.5。估计的V_S30的值（平均剪切波速（V_小号的土壤的顶部30米））变化从520至1350米/秒，与一些在这里进行的岩土研究的匹配良好。该研究强调了单站HVSR方法在确定迄今未知的土壤结构方面的经济性和非侵入性勘探可行性，并证明对工业设施的重要中心非常有用。