Cepstrum analysis of seismic source characteristics

This paper introduces the concept of cepstrum.By investigating the difference in source characteristics between earthquakes and explosions the paper infers the manifestation of source difference in various variable domains,and seeks for effective means to express such source difference.Extending the approach of source discrimination from time and frequency domain to the cepstrum domain,the paper proposes a method of cepstrum analysis for recognizing the characteristics of seismic sources and establishes criteria for identifying the type of seismic sources.Cepstrum analysis on some recent earthquakes and explosions has been made,and the result shows that the method is quite effective in practice.     

基于线性预测倒谱系数的地震相分析

本文借鉴语音识别技术中的线性预测倒谱系数(LPCC系数)特征参数提取方法对地震数据进行分解,这种方法的优点是:可以获得将子波和反射系数信息分离的地震语音特征参数,对地质现象边界具有较好的描述能力,使我们可以从不同维度更细致地观察隐藏在地震数据中的地质特征.理论模型分析表明,基于LPCC系数的地震分析具有较高的地震相划分能力.实际地震资料应用表明,LPCC系数对储层特征的描述比常规三瞬属性更为细致,不同阶次LPCC系数在描述储层不同特征时也保持了内在的联系.采用K均值聚类方法对提取的12阶和24阶LPCC系数进行聚类分析,聚类结果与目的层段古地形较为吻合,较好地反映了研究区的断裂、礁滩相带、深水扇和储层的分布特征,说明在地震相分析中采用LPCC系数作为特征参数是可行和有效的.     

小震级地震事件的倒谱差异

从数学、几何及物理方面,简要介绍了地震事件震源倒谱分析和震源性质判别的基本原理和方法。将该方法应用于小震级的地震与爆炸事件的分析,结果表明,朝鲜半岛6次较小地震与爆炸的震源倒谱具有显著的峰值差异,倒谱差异的定量描述C值参量分别大于和小于1。     

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朝鲜半岛2次不同震源类型地震事件的倒谱特征

简要介绍地震事件震源倒谱分析的基本原理和方法,分析发生在朝鲜半岛的2006年核爆炸(M_L4.3)与2007年M_L5.1地震事件的倒谱特征。结果表明,倒谱判据在朝鲜半岛具有判识效能。     

只测天然水平电场提取地下各深度信息的一种可能方案

一、引言 对于探测深度大于几十米的地下的电波传播理论研究,从电磁感应的原理出发是最方便的.由于有了无噪声情况下地电反演的唯一性定理,从地面通过测量天然宽频带电场和磁场探测地下较细微的电性结构并不是不可能的.现行的地下电磁探测的主要问题之一是需要提高分辨力.一种可能的思路是试图将以前测不到的弱信息测出来.利用精密电子技术,先将微弱信息与强信息分离,再通过信号检测技术（例如多次叠加）将弱信息从各种干扰噪声中提取出来.在地电探测领域,关键之一是要解决弱信息与强信息分离的方法.本文就是探索分离水平电场中各层次信息的方法.假如水平磁场也同时测量,并也采用本文的方案进行处理,则可能得到改进的大地电磁法. 二、输入阻抗模值的模拟反演公式 弱信息与强信息的分离,相当于用模拟电路完成通常用数字处理完成的反演处理,因而需要简易的反演公式.只测电场的反演需要输入阻抗模值的简易反演公式,这里只给出结果,推导见文献1). 类似于地震学中的Goupilloud方法,可以建立起一种导电介质反演的理论公式,在这些公式基础上,可以推导出输入阻抗模值的反演的倒谱公式,从倒谱公式出发便得到适合于模拟反演的公式. 设地面所测输入阻抗为 ρ（ω）=E_x（ω,0）/H_y（ω,0）,（1） 第一层波阻抗为 ρ₁（ω）=(     

震源性质的倒谱分析ht

介绍了倒谱的概念．从天然地震与人工爆炸的震源差异入手，推断震源差异在各域的反映形式，探索表征这种震源差异的有效途径．将震源识别的研究方法从时间域、频率域扩展到倒谱域，提出了识别震源性质的倒谱分析方法，建立了一个震源类型的识别判据．对近年来发生的一些地震及爆炸事件进行了倒谱分析，结果表明该方法具有良好的效能．      

Source characterisation of low frequency events at Stromboli and Vulcano Islands (Isole Eolie Italy)

The discussion about the source of low frequency events generally wrecorded on active volcanoes is still open and needs deeper understanding of the phenomena involved in their generation. Most of the models view such a phenomenon as a source effect (oscillation of volcanic fluids in conduits or cracks), although a different explanation as a path or site effect exists. In the present paper we analysed 26 seismic signals recorded at Vulcano and 60 at Stromboli in order to put some constraints on the functional shape of the recorded signals. They evidence all the characteristics of the low frequency events. The spectral analysis reveals sharp peaks in the range 0.5–4 Hz, while the cepstra suggest that the signals are composed by a two-sine kind function. This suggestion is confirmed by the two-dimensional projections of the reconstructed phase space. The correlation dimension of the attractor is very close to 3 for both the volcanoes confirming the existence of a toroidal structure in the phase space. This implies that we can suggest as a model for the low frequency events source a physical mechanism very similar to a Duffing oscillator or any other quasiperiodic one. In particular in the cases of the analysed volcanoes we recognise two independent oscillations.     

Initial Experimental Result of Accurately Controlled Routinely Operated Signal System （ACROSS）

The principle of Accurately Controlled Routinely Operated Signal System (ACROSS) is introduced in this paper, A sample machine is made and tested. The experiment shows that the signal-stacking technique is effective in improving signal-to-noise ratio and the sompi cepstrum method is applicable to deconvolute a set of travel times of wave elements from accurate transfer function data in frequency domain.     

识别震源性质的一种新方法

提出了利用地震事件的震源差异在倒谱域所呈现的不同特征识别震源性质的新方法。识别结果表明新方法是有效的 ,展示出良好的应用前景