Deconvolution of multicomponent seismic data by means of quaternions: Theory and preliminary results‡

Multicomponent seismic data are acquired by orthogonal geophones that record a vectorial wavefield. Since the single components are not independent, the processing should be performed jointly for all the components. In this contribution, we use hypercomplex numbers, specifically quaternions, to implement the Wiener deconvolution for multicomponent seismic data. This new approach directly derives from the complex Wiener filter theory, but special care must be taken in the algorithm implementation due to the peculiar properties of quaternion algebra. Synthetic and real data examples show that quaternion deconvolution, either spiking or predictive, generally performs superiorly to the standard (scalar) deconvolution because it properly takes into account the vectorial nature of the wavefields. This provides a better wavelet estimation and thus an improved deconvolution performance, especially when noise affects differently the various components.     

Deghosting by echo‐deblending

A marine source generates both a direct wavefield and a ghost wavefield. This is caused by the strong surface reflectivity, resulting in a blended source array, the blending process being natural. The two unblended response wavefields correspond to the real source at the actual location below the water level and to the ghost source at the mirrored location above the water level. As a consequence, deghosting becomes deblending (‘echo‐deblending’) and can be carried out with a deblending algorithm. In this paper we present source deghosting by an iterative deblending algorithm that properly includes the angle dependence of the ghost: It represents a closed‐loop, non‐causal solution. The proposed echo‐deblending algorithm is also applied to the detector deghosting problem. The detector cable may be slanted, and shot records may be generated by blended source arrays, the blending being created by simultaneous sources. Similar to surface‐related multiple elimination the method is independent of the complexity of the subsurface; only what happens at and near the surface is relevant. This means that the actual sea state may cause the reflection coefficient to become frequency dependent, and the water velocity may not be constant due to temporal and lateral variations in the pressure, temperature, and salinity. As a consequence, we propose that estimation of the actual ghost model should be part of the echo‐deblending algorithm. This is particularly true for source deghosting, where interaction of the source wavefield with the surface may be far from linear. The echo‐deblending theory also shows how multi‐level source acquisition and multi‐level streamer acquisition can be numerically simulated from standard acquisition data. The simulated multi‐level measurements increase the performance of the echo‐deblending process. The output of the echo‐deblending algorithm on the source side consists of two ghost‐free records: one generated by the real source at the actual location below the water level and one generated by the ghost source at the mirrored location above the water level. If we apply our algorithm at the detector side as well, we end up with four ghost‐free shot records. All these records are input to migration. Finally, we demonstrate that the proposed echo‐deblending algorithm is robust for background noise.     

地震预警系统模拟测试方法比较研究

地震预警系统作为一种减轻地震灾害的有效手段,其必须具有两个性能：可靠性和时效性.可靠性要求有低的误报率、漏报率;而时效性要求系统的计算时间短、反应速度快.系统的可靠性和时效性需要反复测试.在特定区域,地震是小概率事件,对于5级以上的破坏性地震更是极其罕见,因此只有通过模拟地震的方式才能对地震预警系统进行有效的测试.目前还没有文献系统地介绍地震预警系统的模拟测试方法.本文提出了振动台模拟、信号发生板卡模拟和软件模拟三种测试方法,并对每种方法的优缺点进行了对比研究.研究表明,软件模拟的优点最多,唯一的缺点是不能测试系统的抗震能力.通过分析,本文建议首先在振动台上做少量几次大幅度地震波输入测试;之后使用软件模拟测试方法,将所有收集到的地震波序列和干扰波形输入地震预警系统,对其进行功能测试,以得到全面且经济的测试效果.     

Full‐waveform based microseismic event detection and signal enhancement: An application of the subspace approach

Microseismic monitoring has proven invaluable for optimizing hydraulic fracturing stimulations and monitoring reservoir changes. The signal to noise ratio of the recorded microseismic data varies enormously from one dataset to another, and it can often be very low, especially for surface monitoring scenarios. Moreover, the data are often contaminated by correlated noises such as borehole waves in the downhole monitoring case. These issues pose a significant challenge for microseismic event detection. In addition, for downhole monitoring, the location of microseismic events relies on the accurate polarization analysis of the often weak P‐wave to determine the event azimuth. Therefore, enhancing the microseismic signal, especially the low signal to noise ratio P‐wave data, has become an important task. In this study, a statistical approach based on the binary hypothesis test is developed to detect the weak events embedded in high noise. The method constructs a vector space, known as the signal subspace, from previously detected events to represent similar, yet significantly variable microseismic signals from specific source regions. Empirical procedures are presented for building the signal subspace from clusters of events. The distribution of the detection statistics is analysed to determine the parameters of the subspace detector including the signal subspace dimension and detection threshold. The effect of correlated noise is corrected in the statistical analysis. The subspace design and detection approach is illustrated on a dual‐array hydrofracture monitoring dataset. The comparison between the subspace approach, array correlation method, and array short‐time average/long‐time average detector is performed on the data from the far monitoring well. It is shown that, at the same expected false alarm rate, the subspace detector gives fewer false alarms than the array short‐time average/long‐time average detector and more event detections than the array correlation detector. The additionally detected events from the subspace detector are further validated using the data from the nearby monitoring well. The comparison demonstrates the potential benefit of using the subspace approach to improve the microseismic viewing distance. Following event detection, a novel method based on subspace projection is proposed to enhance weak microseismic signals. Examples on field data are presented, indicating the effectiveness of this subspace‐projection‐based signal enhancement procedure.     

基于BP-CCA法的福建春季降水因子分析

利用BP-CCA方法,分析了1961-2005年间500 hPa高度场和北太平洋海温场与福建春季降水量之间的关系,结果表明:这一方法为寻找降水预测的前兆信号提供了一条可行的途径,同时得出前兆因子对福建春雨都有不同程度的影响,其中以西太平洋副热带高压、ENSO现象以及太平洋西风漂流区影响最大.     

暴雨信号发布思路

深圳2000年4月份出现了4次暴雨和大暴雨，其中“4.14”为打破历史纪录的特大暴雨。深圳市气象台所发布的黄、红、蓝色暴雨信号是历史上次数最多，最频繁之一。本文通过对这几次不同量级的暴雨过程中暴雨信号发布情况以及短期天气预报和云图、雷达和自动站等中尺度资料在暴雨预警信号发布中所发挥作用的分析，总结发布暴雨信号的发布思路；并得到十分有益的经验。     

激光荧光技术用于地物遥感的可能性研究

本文从植被、土壤的荧光光谱特征和系统的信噪比等出发.分析讨论了激光荧光技术用于地物遥感的可能性。     

Separation of multi-mode surface waves by supervised machine learning methods

Logistic regression, neural networks and support vector machines are tested for their effectiveness in isolating surface waves in seismic shot records. To distinguish surface waves from other arrivals, we train the algorithms on three distinguishing features of surface-wave dispersion curves in the domain: spectrum coherency of the trace's magnitude spectrum, local dip and the frequency range for a fixed wavenumber k in the spectrum. Numerical tests on synthetic data show that the kernel-based support vector machines algorithm gives the highest accuracy in predicting the surface-wave window in the domain compared to neural networks and logistic regression. This window is also used to automatically pick the fundamental dispersion curve. The other two methods correctly pick the low-frequency part of the dispersion curve but fail at higher frequencies where there is interference with higher-order modes.     

Trial of earthquake prediction in Japan and a statistical test of time-shift

Earthquake prediction was practiced in Japan to examine the hypothesis that “a pair of earthquakes with similar magnitudes may be a signal of an impending larger earthquake”. In the present study, predictions were announced with expected probabilities of 20–30% (rank A) or 10–20% (rank B). In 2001–2002, excepting the Ogasawara region, 26 and 6 cases among 61 and 30 predictions of ranks A and B, respectively, were successful. Based on a statistical test of time-shift, i.e., one-year shift in this paper, and averaged activity in 1990–1999, the success rate of 43% for rank A was shown to be greater than that expected by chance with a confidence level more than 99%. The success rate of 20% for rank B gave a corresponding confidence level of only about 40%, suggesting that the predictions of rank B were not confident in this period. According to the results, a statistical test of time-shift was found to be useful to evaluate the significance of prediction methods of this type.     

Seismic demands and analysis of site effects in the Marmara region during the 1999 Kocaeli earthquake

The characteristics of the strong ground motion accelerograms from the 1999 Kocaeli earthquake are investigated in detail in this study. The emphasis is on the comparison of the response spectra for the fault normal (FN) and fault parallel (FP) components of the ground motions. The results show that the near-fault records with directivity effects characterize themselves with increased base shear demands rather than increased displacement demands for both the FN and FP components and a narrower velocity sensitive region for the FN component. This study also shows that the effectiveness of base isolation may vary from site to site and for a given site, from component to component. The site effects in the Marmara region during the 1999 Kocaeli earthquake are examined. Site amplifications are predicted by the classical spectral ratio (CSR) and the receiver function (RF) methods. The CSR method gives higher estimates for the site amplifications compared to the RF method and is in better conformity with the observed damage during the Kocaeli earthquake. The districts of Istanbul that are especially susceptible to site amplification hazard are determined. It is apparent from the results that the site amplification hazard risk is the highest for Avcilar and Bakirkoy districts. This study also shows that for sites which have the risk of soil amplification for long-period structures, liquefaction may not be beneficial as a natural base isolator, and may result in shifting the eigenperiod of the low- and mid-rise structures to the critical periods with high site amplifications. This may be especially the case for Avcilar and Bakirkoy districts. In Fatih, Bakirkoy, and Cekmece districts, the predominant period of the ground motion is calculated to be very close to the eigenperiods of the typical residential buildings. Therefore, these three districts are expected to experience heavier damages in future earthquakes due to resonance effects.