用振幅变化长短时均值比实现地震预警中P波自动拾取

地震P波到时快速、精确的自动拾取是实现地震预警的第一步。目前所有P波到时自动拾取方法都需要进一步考虑准确度问题,据此提出用"振幅变化"长短时均值比方法拾取P波到时。研究表明引进"振幅变化"作为特征函数比Allen的"振幅变化平方"更能突显地震波初至时刻的"突变"特征。对"振幅变化长短时均值比方法"和Allen的"振幅变化平方长短时均值比方法"进行抗噪音分析表明,在较低信噪比条件下,Allen方法不能准确地拾取P波到时,而新方法依然能较准确地拾取P波到时。在较高信噪比条件下,用两种方法拾取的160个M_S4.0地震P波到时,其误差大都在允许范围内,但新方法拾取的准确度略高。新方法可以看做是对长短时均值比方法的拓展。     

Characteristics of the Seismic Waves from a New Active Source Based on Methane Gaseous Detonation

Active seismic sources are critical for obtaining high resolution images of the subsurface. For active imaging in urban areas, environment friendly and green seismic sources are required. In present work, we introduce a new type of green active source based on the gaseous detonation of methane and oxygen. When fired in a closed container, the chemical reaction, i.e. gaseous detonation, will produce high pressure air over 150MPa. Seismic waves are produced when high pressure air is quickly released to impact the surroundings. The first field experiment of this active source was carried out in December, 2017 in Jingdezhen, Jiangxi Province, where a series of active sources were excited to explore their potential in mine exploration. In current work, we analyzed the seismic waves recorded by near-field accelerators and a dense short-period seismic array and compared them with those from a mobile airgun source, another kind of active source by releasing high pressure air into water. The results demonstrate that it can be used for high resolution near surface imaging. Firstly, the gaseous detonation productions are harmless CO₂ and water, making it a green explosive source. Secondly, the dominant seismic frequencies are 10-80Hz and a single shot can be recorded up to 15km, making it suitable for local structure investigations. Thirdly, it can be excited in vertical wells, similar to traditional powder explosive sources. It can also act as an additional on-land active source to airgun sources, which requires a suitable water body as intermediate media to generate repeating signals. Moreover, the short duration and high frequency signature of the source signals make it safe with no damage to nearby buildings. These make it convenient to excite in urban areas. As a new explosive source, the excitation equipment and conditions, such as gas ratio, sink depth and air-releasing directions, need further investigation to improve seismic wave generation efficiency.     

基于专家知识的神经元网络方法及其在潜在震源区定量划分中的应用

将专家知识和神经元网络方法结合起来，利用专家知识和规则构造规则样本的方法来提高神经元网络学习样本的质量，通过神经元网络对规则样本的学习，形成基于专家知识的神经元网络模型。在潜在震源区划分专家系统中有关规则的基础上，将基于专家知识的神经元网络方法引入到潜在震源区定量划分中，并以首都圈地区为例，对其潜在震源区作了定量划分，结果表明，规则样本能较好的反映专家的知识和规则，利用构造规则样本的方法，可以提高     

峰度和AIC方法在区域地震事件和直达P波初动自动识别方面的应用

提出了一种基于直达P波信号的峰度和Kurtosis-AIC方法进行区域地震事件实时检测和直达P波初动精细识别的新方法,并应用于山东地震台网记录的地震波资料处理.结果表明:(1)应用峰度方法能够有效识别出地震事件,可有效减低地震事件的错误报警率和漏报率;(2)与人工识别震相到时的结果相比,根据Kurtosis-AIC震相自动识别方法得到的震相到时的平均绝对值误差为(0.09±0.08)s。     

活动推覆构造区潜在震源的边界和震级上限——以1902年阿图什8(1/4)级地震构造区为例

1902年阿图什81/4级地震发生在西南天山山前推覆构造体中,逆冲推覆构造由推覆体的根部断裂、推覆体、滑脱断层和前缘逆断裂-褶皱等组成,大地震的发震断裂往往是推覆构造的根部断裂,而地震地表破裂和同震褶皱隆起则位于山前逆断层-褶皱带内。高震级的潜在震源区(MU7.5)对应于低速的天山地块和高速的塔里木地块之间的根带断裂,其长度对应于推覆体根带断裂的长度,宽度对应于根带隐伏逆冲断裂在地表的投影宽度。推覆体前缘的每个活动逆断裂-背斜对应于一个潜在震源(MU≤7.5),其长度与活动逆断裂-背斜的长度相等,宽度应覆盖活动褶皱的两翼。潜在震源的矩震级上限由W-C统计关系式确定,其中发震断裂的面积为活动褶皱的长度与隐伏断坡宽度的乘积。     

Automatic picking of P and S phases using a neural tree

The large amount of digital data recorded by permanent and temporary seismic networks makes automatic analysis of seismograms and automatic wave onset time picking schemes of great importance for timely and accurate event locations. We propose a fast and efficient P- and S-wave onset time, automatic detection method based on neural networks. The neural networks adopted here are particular neural trees, called IUANT2, characterized by a high generalization capability. Comparison between neural network automatic onset picking and standard, manual methods, shows that the technique presented here is generally robust and that it is capable to correctly identify phase-types while providing estimates of their accuracies. In addition, the automatic post processing method applied here can remove the ambiguity deriving from the incorrect association of events occurring closely in time. We have tested the methodology against standard STA/LTA phase picks and found that this neural approach performs better especially for low signal-to-noise ratios. We adopt the recall, precision and accuracy estimators to appraise objectively the results and compare them with those obtained with other methodologies.Tests of the proposed method are presented for 342 earthquakes recorded by 23 different stations (about 5000 traces). Our results show that the distribution of the differences between manual and automatic picking has a standard deviation of 0.064 s and 0.11 s for the P and the S waves, respectively. Our results show also that the number of false alarms deriving from incorrect detection is small and, thus, that the method is inherently robust.This paper has not been submitted elsewhere in identical or similar form, nor will it be during the first three months after its submission to Journal of Seismology.     

天然地震识别与震相自动拾取技术进展

震相拾取是地震数据处理过程中最基本的步骤之一。在传统的人工拾取技术不能满足庞大的地震数据处理需求的情况下,震相自动拾取技术从产生到发展至今经历了漫长的过程。本文回顾并总结了震相自动拾取技术的发展状况,重点介绍了长短时窗法、赤池准则法、模板匹配技术、基于自相关盲搜索的FAST法、S波偏振分析法、人工智能方法等,以及近年发展起来的多频率震相识别、全波形叠加、二次方自回归模型等方法,同时分析了每种方法的优势和局限性。     

The Acquisition Technique of High-resolution Seismic Data for the Prospecting of Active Faults

The high-resolution shallow seismic technique can be used for more accurately prospecting the position and property of faults and for the preliminary study of fault activity.The author obtains many high quality stack time sections through the prospecting methods of different seismic sources,different group intervals and different observation systems on the Xiadian fault.These sections clearly display the stratum structure and the structure characteristics from several meters to several hundred meters of the...     

地震事件自动识别技术及其在南岭流动台阵的应用?

地震事件识别是地震层析成像的重要组成部分。然而,在处理宽频带流动台阵天然地震记录中识别地震事件过程中,利用传统的人工识别方法耗时巨大,效率十分低。本文首先运用STA/LTA 对地震事件进行初步判断,并结合支持向量机信号检测算法和多台联合检验法来提高地震事件判别的准确度及抗干扰能力,达到天然地震事件的自动识别。南岭流动台阵数据的应用结果表明该综合识别算法可自动快速准确地判别地震事件,并可用于地震震相的拾取。     

智能化地震事件识别和定位系统研究现状及展望

数字地震观测技术的发展为提高台网信息处理能力、地震应急能力和台网服务功能提供了先决条件。智能化地震事件识别和快速地震定位是发挥台网社会效益的一个重要方面。文章对国内外基于现代信号处理技术的智能化地震事件识别和定位方法的研究现状进行了综合分析，针对该项研究存在的问题，对其发展趋势进行了探讨，初步提出了未来需要深入研究的课题。     

谈远震特别区域震相记录特征与震相识别——以大同国家测震台观测资料为例

以大同国家测震台观测资料为例,总结了震中距10~°50°范围内特别区域地震震相特征和震相识别的方法,对震相识别的难点进行了说明,以图例的形式为判读震相提供了依据。     

山西数字遥测地震台网震源机制解速报方法及结果分析

使用振幅比法计算地震的震源机制解软件，要求条件低、计算简便易行，可满足地震台网在地震速报中同时提供震源机制解参数的需要，利用山西数字遥测地震台网考核运行期间的数字记录资料。进行了震源机制解的速报与分析，结果表明，虽然山西数字遥测地震台网运行的时间很短，能够计算震源机制解的地震有限，但是结果仍可显示出受华北构造应力场一定的控制作用，半数中小地震的震源机制解和华北强震的震源机制解相同。     

Benchmark on the accuracy and efficiency of several neural network based phase pickers using datasets from China Seismic Network

Seismic phase pickers based on deep neural networks have been extensively used recently, demonstrating their advantages on both performance and efficiency. However, these pickers are trained with and applied to different data. A comprehensive benchmark based on a single dataset is therefore lacking. Here, using the recently released DiTing dataset, we analyzed performances of seven phase pickers with different network structures, the efficiencies are also evaluated using both CPU and GPU devices. Evaluations based on F₁-scores reveal that the recurrent neural network (RNN) and EQTransformer exhibit the best performance, likely owing to their large receptive fields. Similar performances are observed among PhaseNet (UNet), UNet++, and the lightweight phase picking network (LPPN). However, the LPPN models are the most efficient. The RNN and EQTransformer have similar speeds, which are slower than those of the LPPN and PhaseNet. UNet++ requires the most computational effort among the pickers. As all of the pickers perform well after being trained with a large-scale dataset, users may choose the one suitable for their applications. For beginners, we provide a tutorial on training and validating the pickers using the DiTing dataset. We also provide two sets of models trained using datasets with both 50 Hz and 100 Hz sampling rates for direct application by end-users. All of our models are open-source and publicly accessible.     

华北地区第三、 四活动期平静幕后期中强地震活动与未来强震

本文通过分析、 研究华北地区第三、 四活动期各平静幕后期的中强地震活动特征, 认为: ① 华北地区第三、 四活动期9个活跃幕中有7个在首发强震前3年内发生中强地震, 其中第四活动期1～4活跃幕首发强震前2年内都发生了中强地震, 未来第5活跃幕首发强震前, 以发生中强地震作为序幕的可能性较大; ② 华北地区平静幕后期的中强地震活动, 对其后活跃幕首发强震在时间和地点上有一定指示作用。 由于华北地区可能即将进入新的强震活跃幕, 该研究对判断华北地区未来强震趋势具有实用意义。     

阿坝州数字地震台网的动态范围与台网监控能力计算

本文从阿坝州数字地震台网布局入手,随机选取了一定数量的台站地脉动记录数据,利用Noise_psd011噪声功率谱密度测定程序对样本进行分析,得到各台站的台基地动噪声均值,进而计算出各台站观测系统动态范围和台网监控能力。     

基于开源WebGIS的测震台站运维管理系统的设计与实现

本文介绍了一套测震台站运维管理系统的设计与实现。在研发过程中,使用开源的WebGIS服务器GeoServer和前端技术Openlayers,实现了测震台站WebGIS、在线式台站运维信息管理、台站仪器状态监视和台站故障统计功能,对测震台站运维管理工作提供软件支持。系统在河北测震台网的应用效果良好,具有一定的推广应用价值。     

建设科学、有效的地震前兆监测台网提高捕捉地震前兆信息的能力--试论当前地震监测台网的三大弊病与三点建议

地震预报本质上是一门观测科学。本文分析了当前我国地震前兆监测台网存在的主要弊病,给出了建设具有中国特色、科学有效的地震前兆监测台网的建议。     

华北遥测地震台网联网中心信号系统设计与实现

根据世界银行贷款项目——国家部分的总体设计和实施方案的要求,建立华北遥测地震台网联网中心。本文概括介绍了华北联网中心信号汇集与分配系统的设计与实现。     

BP神经网络算法考虑激活函数后对强震路基塌陷变形预测研究

当前强震后铁路路基变形预测中,相关算法未能考虑激活函数的非线性属性,造成非线性变形特征数据提取不完整,且其特征数据存在偏差,陷入局部最优解。文章提出BP神经网络算法考虑激活函数后对强震路基塌陷变形预测方法,采用双极S因子补偿ReLU非线性激活函数,优化BP神经网络算法,解决非线性路基变形特征数提取问题。利用数据标准化归一方法,对已修正提取的全部变形特征数据进行偏差数据归一,得到路基变形特征数据集合,结合强震后路基变形连接权值计算路基变形预测值,完成强震路基塌陷变形预测。结合实测结果,在matlab下进行预测实验,结果表明所提混合方法可以有效地对水平地震作用下铁路路基塌陷变形程度进行预测,且预测值在误差允许范围内,为铁路的安全运行以及实时维护提供重要依据。     

利用祁连山主动源资料研究2016年门源6.4级地震前后波速变化

采用叠加、互相关、插值拟合等方法对祁连山气枪主动源台网数据进行处理,针对2016年1月21日青海门源6.4级地震前后气枪激发地震P波、S波震相的走时变化特征进行了分析,结果表明,地震前约6个月时,震中附近3个台站的相对走时出现下降变化（走时减少）,至震前约3个月时低值异常恢复正常,之后再次出现走时下降变化,地震即发生于走时变化恢复过程中。S波走时变化最大下降幅度达18ms,震后走时变化逐渐恢复正常,且3个台站变化趋势较为一致,其中,距震中最近的台站的S波走时变化最明显（ZDY38台）,较远台站的走时变化幅度较小,其变化特征与震源区位置有关。走时缩短意味着速度增加,可能与区域应力积累间存在一定的关系。