Spatial autocorrelation method based on dense short-period seismic array and its application in the Guangdong-Hong Kong-Macao Greater Bay
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摘要: 基于空间自相关法从短周期密集地震台阵所记录的微动信号中提取了瑞雷波频散曲线，进而进行台阵下方的S波速度结构反演. 以布设在粤港澳大湾区的短周期密集台阵为例，选取21个观测点的实测数据，按照不同台间距对台站对进行组合，利用空间自相关法得到了广州市番禺区内布设的观测点下方1 km深度范围内的浅层S波速度结构。结果显示：台阵下方0.25 km深度以内的速度明显偏低，介于1.17 km/s到1.59 km/s之间；0.25—1 km深度之间的速度平稳增加至2.88 km/s，表明通过空间自相关法可以有效获取观测台阵下方稳定可靠的浅层速度结构。因此短周期密集台阵技术与空间自相关法结合是在人口稠密的城市群地区进行地下浅层精细结构探测的一种有效、经济、环保的手段，将在未来城市地区浅层结构探测中发挥重要作用。
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关键词:
- 短周期密集台阵 /
- 空间自相关（SPAC）法 /
- 频散曲线 /
- S波速度结构
Abstract: Based on the spatial autocorrelation （SPAC） method, the dispersion curves of Rayleigh wave have been extracted from the ambient noise recorded by the dense short-period seismic array, and then the inversion of S-wave velocity structure beneath the observation nodes were carried out. We used the SPAC method to process the records of 21 stations belong to the dense short-period seismic array in the Guangdong-Hong Kong-Macao Greater Bay area. The dispersion curves have been obtained by combining the station-pairs with different distances, and then the inversion for shallow S-wave velocity structures within a depth of 1 km beneath the Panyu district, Guangzhou city, have been performed. The results show that the velocity beneath the array is obviously low above 0.25 km, ranging from 1.17 km/s to 1.59 km/s, while the velocity increases steadily to 2.88 km/s between 0.25 km to 1 km. This indicates that the stability and the reliability of the method, which also implies that the SPAC is an effective, economical and environmentally method for detecting the shallow fine structures in densely populated urban areas, and it will play an increasingly important role in the detection of shallow structure in urban areas in the future. -
图 1 研究区台站分布示意图（图中黑色三角形示意短周期地震台站位置）
Figure 1. Distribution map of stations in the studied region （Black triangles denote the location of stations）
图 2 SPAC法台阵（a）及不同台间距（b−f）下的台站对组合示意图
Figure 2. Schematic diagram of the SPAC subarray （a） and the combinations of stations with different station spacing （b−f）
图 3 原始微动记录（a）和预处理后的微动记录（b）
Figure 3. Raw records of the original waveforms （a） and records of the microtremors after pretreatment （b）
图 4 五种台间距下的台站对的实测空间自相关系数（a）以及平滑后的空间自相关系数（b）
Figure 4. The SPAC coefficients of the station-pairs with five different interval distance （a） and corresponding coefficient after smoothing （b）
图 5 根据SPAC系数零极点计算得到的观测频散点及其拟合频散曲线
Figure 5. The observed dispersion points calculated according to the zero-pole of SPAC coefficients and their polynomial fitting curve
图 6 初始模型和反演所得的S波速度结构（a）及观测和反演的频散曲线（b）
Figure 6. Initial model and S-wave velocity structure from inversion （a） as well as the observed and predicted dispersion curves （b）
图 7 按照台间距排列的S波速度结构（以第一个速度结构作为剖面线的起始点）
Figure 7. S-wave velocity structure sorted by station spacing （Taking the first velocity structure as the initial point of the profile line）
图 8 S波速度结构（a）和标准差D （b）
Figure 8. Vertical sections of S-wave velocity obtained from different observation time periods （a） and standard deviation D （b）
表 1 研究区所用地震仪的主要性能指标
Table 1. Main parameters of the seismometers used in the studied region
地震仪 记录道数 ADC分辨率/bits 采样频率/ms 动态范围/dB 时间精度/μs SmartSolo IGU-16HR 3C 3 24 0.25，0.5，1，2，4，8，10，20 125 ±10，GPS驯服 Zland 3C 3 24 0.5，1，2，4 127 ±10，GPS驯服 
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