新疆尼勒克、巩留县交界6.0级地震测震应急流动台站架设及经验探讨

对新疆尼勒克、巩留交界6.0级地震测震应急流动台站的架设工作进行总结,针对应急流动台站的台址勘选、仪器设备的安装架设形式及数据实时传输等方面进行分析,总结经验,发现不足.期望对今后的地震现场应急流动测震台站的安装架设起到一定的参考作用.     

Water‐bottom multiple attenuation by Kirchhoff extrapolation

Despite being less general than 3D surface‐related multiple elimination (3D‐SRME), multiple prediction based on wavefield extrapolation can still be of interest, because it is less CPU and I/O demanding than 3D‐SRME and moreover it does not require any prior data regularization. Here we propose a fast implementation of water‐bottom multiple prediction that uses the Kirchhoff formulation of wavefield extrapolation. With wavefield extrapolation multiple prediction is usually obtained through the cascade of two extrapolation steps. Actually by applying the Fermat’s principle (i.e., minimum reflection traveltime) we show that the cascade of two operators can be replaced by a single approximated extrapolation step. The approximation holds as long as the water bottom is not too complex. Indeed the proposed approach has proved to work well on synthetic and field data when the water bottom is such that wavefront triplications are negligible, as happens in many practical situations.     

An automated cross‐correlation based event detection technique and its application to a surface passive data set

In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running‐window energy ratio of the short‐term average to the long‐term average of the passive seismic data for each trace. We show that for the common case of a low signal‐to‐noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross‐correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal‐to‐noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.     

A new Likelihood Ratio for supervised classification of fully polarimetric SAR data: An application for sea ice type mapping

One of the potential applications of polarimetric Synthetic Aperture Radar (SAR) data is the classification of land cover, such as forest canopies, vegetation, sea ice types, and urban areas. In contrast to single or dual polarized SAR systems, full polarimetric SAR systems provide more information about the physical and geometrical properties of the imaged area. This paper proposes a new Bayes risk function which can be minimized to obtain a Likelihood Ratio (LR) for the supervised classification of polarimetric SAR data. The derived Bayes risk function is based on the complex Wishart distribution. Furthermore, a new spatial criterion is incorporated with the LR classification process to produce more homogeneous classes. The application for Arctic sea ice mapping shows that the LR and the proposed spatial criterion are able to provide promising classification results. Comparison with classification results based on the Wishart classifier, the Wishart Likelihood Ratio Test Statistic (WLRTS) proposed by Conradsen et al. (2003) and the Expectation Maximization with Probabilistic Label Relaxation (EMPLR) algorithm are presented. High overall classification accuracy of selected study areas which reaches 97.8% using the LR is obtained. Combining the derived spatial criterion with the LR can improve the overall classification accuracy to reach 99.9%. In this study, fully polarimetric C-band RADARSAT-2 data collected over Franklin Bay, Canadian Arctic, is used.     

庐枞矿集区大地电磁探测及电性结构初探

在庐枞矿集区开展大地电磁测深(Magnetotelluric,MT)工作,有助于研究庐枞矿集区区域地质结构、构造,同时,对强干扰地区大地电磁下扰信号规律的研究和MT数据的处理与解释水平的提高有着重要的理论意义.论文首先阐述了庐枞盆地的地质概况及深部MT探测的研究现状,接着介绍了庐枞矿集区大地电磁测深数据采集及相关实验研...     

甘肃嘉峪关地震台大地电场观测数据干扰分析

文章对甘肃嘉峪关地震台2001年至2009年以来大地电场分钟值资料做了全面的分析和整理。对造成观测资料相关性低的电暴（磁暴）、人类活动、雷电、降水、观测系统本身变化（包括更换电极）、电阻率测量、公用接地网等干扰因素进行分析,并做出相关的解释。这将对分析和运用地电场资料进行地震预报有一定的意义。     

Seismic random noise attenuation by time-frequency peak filtering based on joint time-frequency distribution

Time-Frequency Peak Filtering (TFPF) is an effective method to eliminate pervasive random noise when seismic signals are analyzed. In conventional TFPF, the pseudo Wigner–Ville distribution (PWVD) is used for estimating instantaneous frequency (IF), but is sensitive to noise interferences that mask the borderline between signal and noise and detract the energy concentration on the IF curve. This leads to the deviation of the peaks of the pseudo Wigner–Ville distribution from the instantaneous frequency, which is the cause of undesirable lateral oscillations as well as of amplitude attenuation of the highly varying seismic signal, and ultimately of the biased seismic signal. With the purpose to overcome greatly these drawbacks and increase the signal-to-noise ratio, we propose in this paper a TFPF refinement that is based upon the joint time-frequency distribution (JTFD). The joint time-frequency distribution is obtained by the combination of the PWVD and smooth PWVD (SPWVD). First we use SPWVD to generate a broad time-frequency area of the signal. Then this area is filtered with a step function to remove some divergent time-frequency points. Finally, the joint time-frequency distribution JTFD is obtained from PWVD weighted by this filtered distribution. The objective pursued with all these operations is to reduce the effects of the interferences and enhance the energy concentration around the IF of the signal in the time-frequency domain. Experiments with synthetic and real seismic data demonstrate that TFPF based on the joint time-frequency distribution can effectively suppress strong random noise and preserve events of interest.     

首都圈数字地震台网对微弱爆破信号的检测能力

利用首都圈数字地震台网接收人工地震信号,进行地下结构研究具有重要意义.但人工震源释放的能量小,激发的地震波以短周期为主,因此本文较全面地研究了地震台网对短周期微弱信号（1～20 Hz）的检测能力：(1) 分析了台网的背景噪声,结果表明基岩台址的地震台噪声比沉积盖层台址的地震台噪声低约13 dB,这相当于近1个震级的检测阈值;夜间的噪声比白天低约5 dB;噪声有逐年增高的趋势,2006年比2001年噪声提高约4 dB.(2 )分析了在台网内进行的药量为25 kg的陆地井下爆破实验,一次爆破相当于0.69级（M_L）的天然地震,有18个地震台可辨认爆炸产生的Pg、Pm或Pc波;离爆破点218 km的基岩台,仍可以接收到振幅只有1.6 nm 的Pm波,这个结果可为地震勘探实际工作提供参考.(3) 研究了台网外核爆试验的信号特征,2006年发生在朝鲜的地下核试验是一次检验台网检测微弱信号能力的好机会.波形记录经1～5Hz滤波后,台网中噪声小的18个基岩台可以清晰辨认核爆破产生的P波或Lg波,P波平均振幅为16 nm,计算的平均震级为m_b4.3,和NEIC给出的震级相同;分析还表明背景噪声是影响台站信号检测能力的主要因素之一.     

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.     

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.