Composition of high frequency ambient noise from cross-correlation:A case study using a small aperture array

Long-time cross correlation of ambient noise has been proved as a powerful tool to extract Green's function between two receivers.The study of composition of ambient noise is important for a better understanding of this method.Previous studies confirm that ambient noise in the long period (3 s and longer) mostly consists of surface wave,and 0.25-2.5 s noise consists more of body waves.In this paper,we perform cross correlation processing at much higher frequency (30-70 Hz) using ambient noise recorded by a small aperture array.No surface waves emerge from noise correlation function (NCF),but weak P waves emerge.The absence of surface wave in NCF is not due to high attenuation since surface waves are strong from active source,therefore probably the high ambient noise mostly consists of body wave and lacks surface wave.Origin of such high frequency body waves in ambient noise remains to be studied.     

CRPN: A cascaded classification and regression DNN framework for seismic phase picking*

Current deep neural networks (DNN) used for seismic phase picking are becoming more complex, which consumes much computing time without significant accuracy improvement. In this study, we introduce a cascaded classification and regression framework for seismic phase picking, named as the classification and regression phase net (CRPN), which contains two convolutional neural network (CNN) models with different complexity to meet the requirements of accuracy and efficiency. The first stage of the CRPN are shallow CNNs used for rapid detection of seismic phase and picking P and S arrival times for earthquakes with magnitude larger than 2.0, respectively. The second stage of CRPN is used for high precision classification and regression. The regression is designed to reduce the time difference between the probability maximum and the real arrival time. After being trained using 500,000 P and S phases, the CRPN can process 400 hours’ seismic data per second, whose sampling rate is 1 Hz and 25 Hz for the two stages, respectively, on a Nvidia K2200 GPU, and pick 93% P and 89% S phases with the error being reduced by 0.1s after regression correction.     

Application of Machine Learning Methods in Arrival Time Picking of P Waves from Reservoir Earthquakes

Reservoir earthquake characteristics such as small magnitude and large quantity may result in low monitoring efficiency when using traditional methods. However, methods based on deep learning can discriminate the seismic phases of small earthquakes in a reservoir and ensure rapid processing of arrival time picking. The present study establishes a deep learning network model combining a convolutional neural network (CNN) and recurrent neural network (RNN). The neural network training uses the waveforms of 60 000 small earthquakes within a magnitude range of 0.8-1.2 recorded by 73 stations near the Dagangshan Reservoir in Sichuan Province as well as the data of the manually picked P-wave arrival time. The neural network automatically picks the P-wave arrival time, providing a strong constraint for small earthquake positioning. The model is shown to achieve an accuracy rate of 90.7% in picking P waves of microseisms in the reservoir area, with a recall rate reaching 92.6% and an error rate lower than 2%. The results indicate that the relevant network structure has high accuracy for picking the P-wave arrival times of small earthquakes, thus providing new technical measures for subsequent microseismic monitoring in the reservoir area.     

基于自适应阈值的地基云自动检测方法

云的高精度检测是云量计算的基础,利用晴朗天空下天空呈蓝色、云呈白色的属性, 该文提出一种基于最大类间方差的自适应阈值云检测方法, 并分别基于蓝红波段比值、差值和归一化差值处理进行试验。相比固定阈值的云检测方法, 自适应阈值具有更大的通用性, 且定量的评估结果表明:归一化差值处理在云检测的正确率和精确度方面都获得了令人满意的检测效果。     

人工震源地下介质变化动态监测

成像地球内部介质结构及其动态变化是地球物理学家的主要任务.相对于对地球介质静态结构的认识,对于地下介质性质随时间变化的了解明显不足.近年来随着观测资料的增加,已经开始利用重复地震和噪声等震源研究地下介质变化.受到源位置和时间等因素制约,基于地震和噪声等被动震源的观测结果的时间和空间分辨率有限.利用人工震源主动向地下发射...     

Three-dimensional velocity structure around the focal area of the 2021 MS6.4 Yangbi earthquake

On May 21, 2021, an M_S6.4 earthquake occurred in Yangbi, Yunnan province, China, which exhibited typical foreshock-mainshock-aftershock characteristics. To better understand the velocity structure of the focal area and adjacent fault zones, Pg/Sg travel times at 12 seismic stations for the local earthquakes with M_L ≥ 1.5 from 2009–2019 and the Yangbi sequence in May of 2021 were used to invert the three-dimensional (3D) structures for both v_P and v_P/v_S. The obtained structure extends deeply to 15 km for area (25°N–26.5°N, 99.5°E–101°E) at a horizontal resolution of 10× 10 km, and the accuracy of the v_P velocity was verified using airgun signals excited by the Binchuan Airgun Transmitting Seismic Station (BATSS). The resulting v_P and v_P/v_S images correlate with existing fault zones and the Yangbi sequence, including: (1) The shallow velocity structure at 0 km agrees with local topography, where the Binchuan basin exhibits low-v_P and high-v_P/v_S values. From 3–15 km, v_P and v_P/v_S show variations, and the boundaries are consistent with the main faults (e.g., the Weixi-Qiaohou-Weishan, Honghe, and Chenghai faults). (2) The largest foreshock (M_S5.6), mainshock (M_S6.4), and largest aftershock (M_S5.2) occurred near the boundaries where both v_P and v_P/v_S have clear contrasts. (3) Small earthquakes are also concentrated in the transition zone between high- and low-v_P and v_P/v_S anomalies, and are biased toward low-v_P/v_S zones. (4) Boundaries in v_P and v_P/v_S are observed at 20 km west of the Weixi-Qiaohou-Weishan fault, indicating that there may exist one hidden fault.     

贵州省1:5万敬南等三幅区域地质调查新进展

为了查明黔西南地区的地层、岩石、古生物及卡林型金矿分布等特征,充分应用了数字地质填图新方法和现代地质理论及测试手段,开展1:5万敬南幅、巴结幅、坡脚幅区域地质调查。结果表明: 依据岩石组合、生物组合等特征,厘清和划分了研究区地层填图单元,并新建了18个非正式填图单位; 首次发现右江盆地北西侧早三叠世晚期产于陆棚相区的海生爬行动物(鱼龙)化石; 首次发现中三叠世台缘礁相带海生爬行动物(幻龙)化石; 新发现矿化点11处,其中金矿化点9处、钼矿化点1处、胶磷矿化点1处,共圈出了卡林型金矿的3个找矿远景区和1个找矿靶区。该研究为区内开展相关地质矿产调查和研究提供参考。     

High-resolution 3D crustal S-wave velocity structure of the MiddleLower Yangtze River Metallogenic Belt and implications for its deep geodynamic setting

The Middle-Lower Yangtze River Metallogenic Belt(MLYMB) is an important mineral resource region in China.High-resolution crustal models can provide crucial constraints to understand the ore-forming processes and geodynamic setting in this region. Using ambient seismic noise from 107 permanent and 82 portable stations in the MLYMB and the adjacent area,we present a new high-resolution 3D S-wave velocity model of this region. We first extract 5–50 s Rayleigh wave phase velocity dispersion data by calculating ambient noise cross-correlation functions(CFs) and then use the surface wave direct inversion method to invert the mixed path travel times for the 3D S-wave velocity structure. Checkerboard tests show that the horizontal resolution of the 3D S-wave velocity model is approximately 0.5°–1.0° and that the vertical resolution decreases with increasing noise and depth. Our high-resolution 3D S-wave velocity model reveals:(1) AV-shaped high-velocity zone(HVZ) is located in the lower crust and the uppermost mantle in the study region. The western branch of the HVZ passes through the Jianghan Basin,the Qinling-Dabie orogenic belt and the Nanxiang Basin. The eastern branch, which almost completely covers the main body of the MLYMB, is located near the Tanlu Fault. The low-velocity anomalies between the western and eastern branches are located in the area of the Qinling-Dabie orogenic belt.(2) High-velocity uplifts(HVUs) are common in the crust of the MLYMB,especially in the areas near the Tanlu Fault, the Changjiang Fault and the Yangxin-Changzhou Fault. The intensities of the HVUs gradually weaken from west to east. The V-shaped HVZ in the lower crust and uppermost mantle and the HVUs in the middle and lower crust likely represent cooled mantle intrusive rocks. During the Yanshanian period, fault systems formed in the MLYMB due to the convergence between the South China Plate and the North China Plate, the multiple-direction drifting of the PaleoPacific Plate and its subduction beneath the Eurasian Plate. The dehydration of the cold oceanic crust led to partial melting in the upper mantle. Temperature differences caused strong convection of the upper mantle material that underplated the lower crust and rose to near the surface along the deep fault systems. After mixing with the crustal materials, mineralization processes, such as assimilation and fractional crystallization, occurred in the MLYMB.     

三维激光扫描技术在建筑立面照明设计中的应用

建筑立面图是立面照明设计的基础数据,直接影响着设计精度和效果。本文针对传统立面测量效率低、还原度低等问题,提出了基于三维激光扫描技术的建筑立面测量方案;并结合实际案例,探讨了导线式三维激光扫描和点云图形绘制。应用案例表明,三维扫描技术更便捷、高效地为立面照明设计提供了精确详细的建筑立面图。