承德地区形变资料前兆异常特征及映震能力分析

主要通过Nakai拟合、振幅因子以及非潮汐拟合常数3种方法对承德地区各个台站的各形变手段所得数据拟合处理,进行前兆异常分析,同时与该地区异常有效评价范围内的地震联系在一起,分析地震前兆异常与地震之间的关系.通过分台站、分手段、分拟合方法对各形变仪器映震能力进行R值评价,指出了形变异常观测在地震监测预报应用过程中存在的优...     

地震前兆异常识别技术的数值模拟实验研究

针对地震前兆观测数据可能含有异常信息的特点,为客观描述数据序列的正常背景,并且不失真地识别异常信号,本文通过模拟实验序列,论述了时间序列分析识别异常方法中建模样本序列遴选和经验预测序列估计的关键技术．实验序列分析结果表明,该方法是可行的有效的,所识别的异常信号清晰明确,与模拟假设的异常信号基本一致．      

昆明地震台形变观测资料降雨干扰

云南省地震频发,形变观测短临数据跟踪对地震工作具有较明显的指示意义。降雨干扰对形变观测多为缓慢变化影响,这些变化隐藏在众多地震前兆异常中,影响地震观测数据的使用。本文通过对昆明地震台历年降雨及形变观测数据的分析,总结降雨干扰规律,以便准确提取并有效识别地震前兆异常。     

2009年7月9日云南姚安6.0级地震预测回顾

基于2009年7月9日姚安6.0级地震发生之前形变观测前兆异常,给出该地震三要素,总结其前兆异常特点,反思运用单台前兆观测资料预报地震过程中存在的问题,为今后的地震预测积累经验.     

华北地区地震异常前兆信息场演化特征及其与地震关系的研究

在对地震异常前兆信息量先前研究的基础上,进一步给出了描述各种地震异常前兆信息量的普适性综合数学表达式.从大量震例资料入手,再次研究了地震异常延续有效性的问题,进而建立了地震异常持续有效时间与延续有效时间的数学关系式.收集整理了1980～1997年华北地区水化、形变、地磁、应力、水位、地电等371个观测项目、上百万个前兆观测数据,对每一观测项目逐一计算了它们的地震异常前兆信息量.研究了华北地区近20年的地震异常前兆信息场的演化特征及其与地震的关系,建立了华北地区Ms≥5地震的中短期综合预报指标体系,经R值评分检验,表明该地震综合预报指标体系在中短期地震预测中具有一定效果.     

小波变换在前兆观测资料分析中的应用

由于数字化前兆具有高精度特点，因此，如何分离数字化前兆中的高频与低频信息，以及如何识别地震前兆的趋势异常与短期异常，是数字化前兆资料分析应用中的一个重要问题。本文给出了小波变换应用于正常的数字化前兆资料高频与低频信息的分离方法，并实际应用于地震前兆观测资料的处理，结合实例给出了地震前兆的趋势异常与短期异常的识别思路，从而为数字化前兆的趋势异常与短期异常的识别提供了一种新的有效方法。     

基于地震对应概率谱分析的前兆异常识别研究

针对观测或分析资料曲线异常的定量化识别提取问题,研究提出了地震对应概率谱统计方法和累计滑动平均概率分析方法.通过地震对应谱分析可以得到不同值域数据异常信度属性.在不同考察时长的对应概率谱基础上,将原始数据时间序列转换成概率时间序列,并采用多点累计滑动平均方法得到滑动平均概率时间进程曲线,进而进行地震前兆异常的识别研究.以新疆北天山地区地震学参数η值时间进程序列为原始数据进行算例分析,结果显示,当考察时长为18个月时,利用滑动平均概率时间进程曲线可以较好地识别地震前兆异常,异常对应率为83%,有震报准率为86%,异常具有中期属性.分析认为,不同考察时长的地震对应概率谱和滑动平均概率序列,不仪可以用于单项资料的前兆异常识别研究,还可以为综合分析预报提供定量的单项因子数据.     

蒙城地电阻率数据异常变化的应对措施

当地震前兆观测数据出现异常变化,特别是电阻率出现下降变化(范莹莹,2010)时,及时进行相应的检查、巡视和数据分析,是前兆异常核实工作的重要内容.针对此次数据变化,我们通过一系列的检查工作,初步排除观测系统、观测环境等因素.同时指出,本次数据变化时间短、幅度较小,目前尚无充分证据证明该变化属于震兆异常.     

山西地区断层形变异常强度与地震关系

根据建立的数学模型,对山西地区跨断层观测资料进行整理计算,得到断层形变速率、异常强度值、异常强度等值线和区域性异常变化的时序曲线,并根据断层形变异常强度值及时空演化等特征,结合山西地区中、强地震,研究断层形变异常强度与地震的关系,发现在山西地区发生MS≥4.0地震前1年左右或稍长时间,断层形变异常强度均出现强烈异常,表现为R5,可以作为中、强地震孕育发生的前兆标志。     

赤峰地震台定点形变2021年短期大幅变化分析

2021年6月,赤峰地震台洞体应变和水管倾斜定点形变出现短期大幅变化现象,选取2017—2021年观测数据进行跟踪分析,发现2017年以来,该台定点形变观测曲线多次出现短时大幅变化现象,对变化因素进行归纳总结,使用年变形态、载荷和速率变化分析方法,剔除观测数据干扰因素,判定2021年6月数据变化为前兆异常。结合震例进行预测效能检验,认为该台定点形变短期大幅异常变化,对未来100天内台站周边600 km范围内4.5级及以上地震的发生具有一定指示意义。     

数字化台网的近震震相自动识别

首次提出了数字化台网对于近震震相自动识别的“波形变化值增长”算法和“无后续震相”判据 .前者根据波形变化值来描述近震波形的变化 ,用该值的增长捕捉地震波振幅或频率的突变 ;后者在识别到初动后考察后续波形的变化情况 ,如果没有其它震相 ,初动识别无效 .该判据使算法在初动震相振幅过小识别不清时 ,不会误将后续振幅较大的震相识别为初动震相 .该方法经实例检验表明精度符合地震速报的要求 ,并编制了相应的程序     

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.     

Local outlier factor as part of a workflow for detecting and attenuating blending noise in simultaneously acquired data

A number of deblending methods and workflows have been reported in the past decades to eliminate the source interference noise recorded during a simultaneous shooting acquisition. It is common that denoising algorithms focusing on optimizing coherency and weighting down/ignoring outliers can be considered as deblending tools. Such algorithms are not only enforcing coherency but also handling outliers either explicitly or implicitly. In this paper, we present a novel approach based on detecting amplitude outliers and its application on deblending based on a local outlier factor that assigns an outlier-ness (i.e. a degree of being an outlier) to each sample of the data. A local outlier factor algorithm quantifies outlier-ness for an object in a data set based on the degree of isolation compared with its locally neighbouring objects. Assuming that the seismic pre-stack data acquired by simultaneous shooting are composed of a set of non-outliers and outliers, the local outlier factor algorithm evaluates the outlier-ness of each object. Therefore, we can separate the data set into blending noise (i.e. outlier) and signal (i.e. non-outlier) components. By applying a proper threshold, objects having high local outlier factors are labelled as outlier/blending noise, and the corresponding data sample could be replaced by zero or a statistically adequate value. Beginning with an explanation of parameter definitions and properties of local outlier factor, we investigate the feasibility of a local outlier factor application on seismic deblending by analysing the parameters of local outlier factor and suggesting specific deblending strategies. Field data examples recorded during simultaneous shooting acquisition show that the local outlier factor algorithm combined with a thresholding can detect and attenuate blending noise. Although the local outlier factor application on deblending shows a few shortcomings, it is consequently noted that the local outlier factor application in this paper obviously achieves benefits in terms of detecting and attenuating blending noise and paves the way for further geophysical applications.     

Quality control and homogeneity of Turkish precipitation data

Outlier trimming and homogeneity checking/correction were performed on the monthly precipitation time series of various lengths from 267 stations in Turkey. Outlier values are usually found during dry summer months, and are concentrated mostly over the southern parts of the country, where the dry period is most pronounced, implying natural extremes rather than wrong measurements. Homogeneity analysis was done using the Standard Normal Homogeneity Test, on an individual monthly basis, which led to many non‐testable series due to lack of reference stations, especially during summer months. Yet, remaining testable months were usually helpful for the assessment of homogenity, revealing a well distributed set of stations that proved to be homogeneous. There were still a number of stations which either could not be tested efficiently, or were classified as inhomogeneous. Lack of metadata is argued to be largely responsible for inefficient homogeneity testing. Copyright © 2008 John Wiley & Sons, Ltd.     

Frequency‐ and angle‐dependent poroelastic seismic analysis for highly attenuating reservoirs

We extend the frequency‐ and angle‐dependent poroelastic reflectivity to systematically analyse the characteristic of seismic waveforms for highly attenuating reservoir rocks. It is found that the mesoscopic fluid pressure diffusion can significantly affect the root‐mean‐square amplitude, frequency content, and phase signatures of seismic waveforms. We loosely group the seismic amplitude‐versus‐angle and ‐frequency characteristics into three classes under different geological circumstances: (i) for Class‐I amplitude‐versus‐angle and ‐frequency, which corresponds to well‐compacted reservoirs having Class‐I amplitude‐versus‐offset characteristic, the root‐mean‐square amplitude at near offset is boosted at high frequency, whereas seismic energy at far offset is concentrated at low frequency; (ii) for Class‐II amplitude‐versus‐angle and ‐frequency, which corresponds to moderately compacted reservoirs having Class‐II amplitude‐versus‐offset characteristic, the weak seismic amplitude might exhibit a phase‐reversal trend, hence distorting both the seismic waveform and energy distribution; (iii) for Class‐III amplitude‐versus‐angle and ‐frequency, which corresponds to unconsolidated reservoir having Class‐III amplitude‐versus‐offset characteristic, the mesoscopic fluid flow does not exercise an appreciable effect on the seismic waveforms, but there exists a non‐negligible amplitude decay compared with the elastic seismic responses based on the Zoeppritz equation.     

Waveform Retrieval and Phase Identification for Seismic Data from the CASS Experiment

The little destruction to the deployment site and high repeatability of the Controlled Accurate Seismic Source (CASS) shows its potential for investigating seismic wave velocities in the Earth's crust. However, the difficulty in retrieving impulsive seismic waveforms from the CASS data and identifying the seismic phases substantially prevents its wide applications. For example, identification of the seismic phases and accurate measurement of travel times are essential for resolving the spatial distribution of seismic velocities in the crust. Until now, it still remains a challenging task to estimate the accurate travel times of different seismic phases from the CASS data which features extended wave trains, unlike processing of the waveforms from impulsive events such as earthquakes or explosive sources. In this study, we introduce a time-frequency analysis method to process the CASS data, and try to retrieve the seismic waveforms and identify the major seismic phases traveling through the crust. We adopt the Wigner-Ville Distribution (WVD) approach which has been used in signal detection and parameter estimation for linear frequency modulation (LFM) signals, and proves to feature the best time-frequency convergence capability. The Wigner-Hough transform (WHT) is applied to retrieve the impulsive waveforms from multi-component LFM signals, which comprise seismic phases with different arrival times. We processed the seismic data of the 40-ton CASS in the field experiment around the Xinfengjiang reservoir with the WVD and WHT methods. The results demonstrate that these methods are effective in waveform retrieval and phase identification, especially for high frequency seismic phases such as PmP and SmS with strong amplitudes in large epicenter distance of 80–120 km. Further studies are still needed to improve the accuracy on travel time estimation, so as to further promote applicability of the CASS for and imaging the seismic velocity structure.     

Utilizing spectral decomposition to determine the distribution of injected CO2 at the Snøhvit Field

Time‐lapse 3D seismic reflection data, covering the CO₂ storage operation at the Snøhvit gas field in the Barents Sea, show clear amplitude and time‐delay differences following injection. The nature and extent of these changes suggest that increased pore fluid pressure contributes to the observed seismic response, in addition to a saturation effect. Spectral decomposition using the smoothed pseudo‐Wigner–Ville distribution has been used to derive discrete‐frequency reflection amplitudes from around the base of the CO₂ storage reservoir. These are utilized to determine the lateral variation in peak tuning frequency across the seismic anomaly as this provides a direct proxy for the thickness of the causative feature. Under the assumption that the lateral and vertical extents of the respective saturation and pressure changes following CO₂ injection will be significantly different, discrete spectral amplitudes are used to distinguish between the two effects. A clear spatial separation is observed in the distribution of low‐ and high‐frequency tuning. This is used to discriminate between direct fluid substitution of CO₂, as a thin layer, and pressure changes that are distributed across a greater thickness of the storage reservoir. The results reveal a striking correlation with findings derived from pressure and saturation discrimination algorithms based on amplitude versus offset analysis.     

一种自适应增益限的反Q滤波

地层的Q吸收会造成地震波振幅衰减、相位畸变,分辨率和信噪比明显降低.反Q滤波可消除由于地层Q吸收造成的振幅衰减和相位畸变,从而提高地震资料的分辨率;但反Q滤波振幅补偿的数值不稳定性问题会严重降低地震资料的信噪比,并产生很多假象.截止频率法和稳定因子法反Q滤波振幅补偿方法虽可控制数值非稳定性问题,但振幅补偿函数的增益限为一个时不变的常数,且与地震数据动态范围无关,其经常会压制深层地震波的高频成分,反而降低地震资料的分辨率;因此,本文在研究截止频率法和稳定因子法的基础上,结合地震数据的动态范围对地震记录分辨率的影响,提出了一种自适应增益限的反Q滤波振幅补偿方法,其增益限和稳定因子都是时变的,且都自适应于地震数据有效频带的截止频率.合成数据和实际数据试算表明,本文的自适应增益限的反Q滤波方法可恢复地震信号有效频带范围内的能量,且能较好地控制数值非稳定性问题,最终获得高分辨率和高信噪比的地震数据.     

非轴对称套管井中声场的并行有限差分模拟

本文提出了一种用于模拟非轴对称套管井中扇区水泥胶结测井100 kHz 3维瞬态声场的并行算法.采用时域有限差分方法,以及非裂化的完全匹配层吸收边界条件,基于信息传递接口(MPI)并行环境,在计算机集群上实现并行计算.对内边界上的差分方程进行参数平均处理,提高了计算稳定性.通过在轴对称情况下将有限差分模拟结果与实轴积分法计算结果对比,验证了方法的正确性.使用并行有限差分算法,模拟了水泥环有不同大小和在不同方位缺失时非轴对称套管井中8扇区的扇区水泥胶结测井仪的测井波形,并分析了套管波幅度随水泥缺失-换能器夹角的变化.根据模拟和分析结果,得到了非轴对称套管井中新的声场传播规律,并建议了一种用于反演水泥缺失大小和方位的方法.