Analysis of earthquake ground motions using an improved Hilbert–Huang transform

Some limitations of the Hilbert–Huang transform (HHT) for nonlinear and nonstationary signal processing are remarked. As an enhancement to the HHT, a time varying vector autoregressive moving average (VARMA) model based method is proposed to calculate the instantaneous frequencies of the intrinsic mode functions (IMFs) obtained from the empirical mode decomposition (EMD) of a signal. By representing the IMFs as time varying VARMA model and using the Kalman filter to estimate the time varying model parameters, the instantaneous frequencies are calculated according to the time varying parameters, then the instantaneous frequencies and the envelopes derived from the cubic spline interpolation of the maxima of IMFs are used to yield the Hilbert spectrum. The analysis of the length of day dataset and the ground motion record El Centro (1940, N–S) shows that the proposed method offers advantages in frequency resolution, and produces more physically meaningful and readable Hilbert spectrum than the original HHT method, short-time Fourier transform (STFT) and wavelet transform (WT). The analysis of the seismic response of a building during the 1994 Northridge earthquake shows that the proposed method is a powerful tool for structural damage detection, which is expected as the promising area for future research.     

Study on attribute characterization for reservoir dynamic monitoring by seismic

Study on characterizing reservoir parameters dynamic variations by time-lapse seismic attributes is the theoretical basis for effectively distinguishing reservoir parameters variations and conducting time-lapse seismic interpretation,and it is also a key step for time-lapse seismic application in real oil fields. Based on the rock physical model of unconsolidated sandstone,the different effects of oil saturation and effective pressure variations on seismic P-wave and S-wave velocities are calculated and analyzed. Using numerical simulation on decoupled wave equations,the responses of seismic amplitude with different offsets to reservoir oil saturation variations are analyzed,pre-stack time-lapse seismic attributes differences for oil saturation and effective pressure variations of P-P wave and P-S converted wave are calculated,and time-lapse seismic AVO (Amplitude Versus Offset) response rules of P-P wave and P-S converted wave to effective pressure and oil saturation variations are compared. The theoretical modeling study shows that it is feasible to distinguish different reservoir parameters dynamic variations by pre-stack time-lapse seismic information,including pre-stack time-lapse seismic attributes and AVO information,which has great potential in improving time-lapse seismic interpreta-tion precision. It also shows that the time-lapse seismic response mechanism study on objective oil fields is especially important in establishing effective time-lapse seismic data process and interpreta-tion scheme.     

南海北缘海啸波高对潜在海啸源震级偏差的敏感性

本文假设马尼拉海沟北段为潜在海啸源,基于中国地震台网对马尼拉海沟地区震级测定偏差,采用COMCOT(comell Multi-grid Coupled Tsunami Model)海啸数值模型,模拟南海海啸波传播.选取南海北缘3个特定地点,其中两个位于华南近海区域,另一个位于台湾岛南端近海区域,此外还在临近马尼拉海沟北段的深海地区选取了1个特定地点.分析这些特定地点最大海啸波以及最大海啸波到时对于震级测定偏差的敏感性.结果表明:马尼拉海沟北段地震如触发海啸,华南近海区域以及台湾岛南部近海区域最大海啸波振幅对震级偏差敏感,但最大海啸波振幅到时对于震级测定偏差不敏感;振幅最大的海啸波,二十几分钟即可波及台湾岛南端近岸区域,大约1小时后波及大陆华南近海北部区域.     

2008年3月21日新疆于田7.3级地震发震构造与震前地震活动特征研究

2008年3月21日新疆于田发生7.3级地震,打破了中国大陆6年多的7级地震平静,成为我国近期较为显著的一次地震事件.综合分析MS≥4.0余震分布、震区断裂性质以及等震线长轴方向等资料,认为郭扎错断裂是这次地震的发震构造;据Harvard震源机制解分析,这次地震是在近NS向力的作用下,郭扎错断裂发生略带走滑分量的拉张破裂所致.通过地震前震区附近地震活动特征分析发现,于田地震发生在1996年以来新疆南部及邻区7级地震有序分布的空段;震前震区附近有4级地震空区形成,空区持续91个月后发生了2006年9月12日皮山5.8级"信号震",其后1.5年发生于田7.3级地震.     

Classification of seismic signals at Villarrica volcano (Chile) using neural networks and genetic algorithms

Each volcano has its own unique seismic activity. The aim of this work is to construct a system able to classify seismic signals for the Villarrica volcano, one of the most active volcanoes in South America. Since seismic signals are the result of particular processes inside the volcano's structure, they can be used to forecast volcanic activity. This paper describes the different kinds of seismic signals recorded at the Villarrica volcano and their significance. Three kind of signals were considered as most representative of this volcano's activity: the long-period, the tremor, and the energetic tremor signals. A classifier is implemented to read the seismic registers at 30-second intervals, extract the most relevant features of each interval, and classify them into one of the three kinds of signals considered as most representative of this particular volcano. To do so, 1033 different kinds of 30-s signals were extracted and classified by a human expert. A feature extraction process was applied to obtain the main characteristics of each of them. This process was developed using criteria which have been shown by others to effectively classify seismic signals, based on the experience of a human expert. The classifier was implemented with a Multi-Layer Perceptron (MLP) artificial neural network whose architecture and training process were optimized by means of a genetic algorithm. This technique searched for the most adequate MLP configuration to improve the classification performance, optimizing the number of hidden neurons, the transfer functions of the neurons, and the training algorithm. The optimization process also performed a feature selection to reduce the number of signal features, optimizing the number of network inputs. The results show that the optimized classifier reaches more than 93% exactitude. identifying the signals of each kind. The amplitude of the signals is the most important feature for its classification, followed by its frequency content. The described methodology can be used to classify more seismic signals to improve the study of the activity of this volcano or to extend the study to other active volcanoes of the region.     

华北地区强震前的信号震及其预测意义

根据对华北地区1970年以来M_S≥6地震以前中小地震活动空间图像变化特征的分析, 研究了“信号震”发生的时空特征及其地震活动背景, 由“场-源”关系特征对一般地震进行严格的筛选识别, 从而得出信号震的有关预测指标。 信号震一般发生在强震前的2年之内, 多数发生在15个月内; 信号震与强震的距离不超过200 km, 多数在100 km之内; 震级强度一般为M_L4.0～5.3。 信号震一般发生在局部的M_L≥4.0地震平静区内, 一般发生在中小地震条带上或条带附近, 在其周围或附近存在中小地震空区。 检验结果表明, 信号震发生后的9个月之内, 其预测概率P_t即超过0.5, R_t值达到0.27; 预测区域半径在距信号震震中100 km之内时, 其发生概率P_d可以达到0.73; 预测强震震级一般为M_S≥6.0。 研究表明, 信号震的环境应力值τ₀明显高于其他地震, 显示了高应力背景的异常显著性, 它所辐射的地震波中很可能含有未来强震孕震区的大量的本质性信息。     

利用P波和S波的初动和振幅比计算中小地震的震源机制解

应用Snoke最新发展的利用P波、 SV波、 SH波的初动和振幅比联合计算地震震源机制解的程序, 使用一些省地震局数字台网得到的数字波形资料, 尝试计算了中小地震的震源机制解, 并与原来仅用P波初动得到的结果进行对比研究。 结果表明, 这种方法是可行的。 该方法为数字地震资料在地震预测中的应用提供了一种新的可能。     

塔中古溶洞见证晚奥陶世抬升幅度

塔中隆起区上奥陶统良里塔格组灰岩与桑塔木组砂—粉砂岩之间为不整合接触,昭示着这两个组沉积期之间存在一次历时约百万年的区域性构造抬升事件。中古31井良里塔格组三段的4 125.6～4 133.9 m井段为垮塌型溶洞沉积,洞顶距良里塔格组二段顶部190.6 m,溶洞中角砾状充填物主要来自良里塔格组洞壁本身的礁相灰岩,且见数厘米厚的暗河流水沉积纹层,未发现源于其它时代的颗粒混杂其间。这一事实指证了溶洞的形成和充填时代均为良里塔格组沉积之后、桑塔木组覆盖之前的晚奥陶世凯迪中期。具溶蚀力的淡水潜流带的深度一般不低于周围的海平面,由此可推断出该井区这次抬升出海平面之上的高度,即使忽略良里塔格组顶部可能经地表剥蚀的良里塔格组一段,抬升出水面部分至少也应该有190 m,藉生态地层学恢复洞壁礁灰岩沉积时的海水深度约为30 m±,因此总抬升幅度至少能达到220 m。     

基于加密探空资料对不同海拔高度台站边界层大气的对比分析

本文利用中国气象局成都高原气象研究所西南涡加密观测试验获取的探空资料及地面台站资料,对比分析了高原东侧的四川省境内不同海拔高度台站的边界层特征,结果表明:高海拔地区地表大气受陆面的影响更为剧烈,日变化幅度更大,且极值出现时间更早。温度/比湿/风速的差异都主要体现在低层边界层大气中,越靠近地面,差异越显著。其中,温度递减率在02:00（北京时,下同）最小,14:00最大,高海拔测站受陆面影响的大气层厚度比低海拔测站大,低海拔测站在近地层300 m以下大气中存在明显的逆温现象。14:00近地层大气的比湿最小,午夜02:00近地层大气的比湿最大,高海拔地区低层大气的平均比湿递减率小于低海拔地区。高海拔地区风速日变化幅度大,4个时次的风速廓线形态差异也大;低海拔地区风速变化幅度小,4个时次的风速廓线形态也比较一致。高海拔台站地表大气的日变化幅度大,极值出现时间略早。     

风廓线雷达估算大气返回信号功率方法研究

基于风廓线雷达大气返回信号功率谱中噪声电平的估算方法,统计分析了北京延庆对流层风廓线雷达（CFL-08）2006年10～12月的探测数据。对该频段风廓线雷达环境噪声的空间和时间变化进行了分析,观测期间环境噪声在5km以下随高度递减,10月的平均环境噪声大于11月、12月的平均分布。给出目前风廓线雷达用信噪比估算大气返回信号功率的两种方法,并对两种方法进行了环境噪声的剔除,经过修正后的大气返回信号功率输出结果趋于一致。