Long-Lived Microbursts in the Decimetric Wavelength Range and Their Connection with Noise Storms

In the present work a statistical analysis of long-lived microbursts (MBs) in the decimetric wavelength range was performed for the first time. Long-lived microbursts at decimetric wavelengths were observed with one-dimensional scans on the RATAN-600 radio telescope in intensity and circular polarization with a sensitivity of about 5 – 10 Jy. MBs have fluxes in the range of 0.001 – 0.1 s.f.u. and polarization degrees of 10 – 100%, and the duration of individual bursts is about 1 – 2 s. Microbursts and background sources exist for several days and appear at the sites of prolonged energy release. In this work MBs were compared with noise storms (NSs) in the metric wavelength range. Our analysis shows with high confidence that MBs are manifestation of NSs in the decimetric wavelength range. The reason for the significant difference in flux between MBs and NSs could be because MBs (unlike NSs) are related to incoherent generation of Langmuir waves. The nature of the MB emission is similar to the smoothly varying (background) emission of the NSs, butthe MB emission is impulsive because of the high rate of pitch-angle diffusion.     

基于匹配追踪和遗传算法的大地电磁噪声压制

针对匹配追踪计算量大、大地电磁数据处理效率低的问题,提出基于匹配追踪和遗传算法的大地电磁噪声压制方法.首先,利用Gabor原子构建过完备原子库,并对过完备原子库集合进行划分.然后,借助遗传算法的自适应性,快速搜寻最优匹配原子及所在位置.最后,运用最优匹配原子对待处理信号进行稀疏分解,重构有用信号.通过对计算机模拟的典型强干扰和矿集区实测大地电磁数据进行分析处理,实验结果表明,相对于匹配追踪和正交匹配追踪,文中所提方法能从过完备原子库中快速、自适应地选取最优匹配原子与不同噪声干扰类型高精度的匹配,极大地提升了计算效率;大地电磁时间域序列中的大尺度强干扰被有效剔除,视电阻率曲线更为光滑、连续,低频段的数据质量得到明显改善.     

基于参考台的盲源分离法在抑制地磁场近场噪音中的应用研究

随着城市建设的不断发展,地磁场观测受到的人文干扰越来越严重.汽车、地铁、高铁等产生的近场噪音造成了地磁脉动等空间场源信号难以被精确观测,严重影响了地磁观测资料的实际使用价值.因此抑制这些近场噪音、提取空间场源信号具有科学意义和应用价值.本研究将远场参考法和盲源信号分离法相结合,提出了一种能有效分离空间场源信号和近场噪音的方法.首先,基于仿真分析,我们准确分离了不同特征的源信号,阐明了此方法的有效性.然后,我们将该方法应用于日本千叶地区受电车干扰较为严重的实际磁场观测数据,并选用数据质量较高的KAK国际基准台作为远场参考,实现了地磁脉动和电车干扰信号的分离,并在此基础上对观测台站的近场噪音进行了抑制.这些结果表明基于参考台的盲源信号分离法在抑制近场噪音、提取地磁场信号中是有效的,可能在电磁法勘探中具有潜在的应用价值.     

淮河流域洪涝灾害时间对称性研究

准确判断重大自然灾害发生趋势对于防灾减灾意义重大.基于时间对称性理论,本文构建“可公度降噪—对称性趋势判断—信息结构系稳定性检验”研究模式,判断了淮河流域(HRB)洪涝灾害发生趋势.结果表明:(1)通过可公度降噪处理去除了噪声元素,提高了预测的精确性;(2)运用三元可公度、蝴蝶结构图、信息结构系等方法判断,2019年HRB发生洪涝灾害的信号较强,该年发生洪涝灾害的随机性概率为66.7%,不漏报置信水平为57.1%;(3)通过洪涝灾害与太阳黑子活动的相关性分析可知,HRB在太阳黑子活动谷年附近易发生洪涝灾害,进一步提高了预测结果的可信度.“可公度降噪—对称性趋势判断—信息结构系稳定性检验”研究模式是对现有时间对称性方法的补充和完善,以期为中国灾害预测起到一定的推动作用.     

Prestack data enhancement with phase corrections in time-frequency domain guided by local multidimensional stacking

We present a new approach to enhancing weak prestack reflection signals without sacrificing higher frequencies. As a first step, we employ known multidimensional local stacking to obtain an approximate ‘model of the signal’. Guided by phase spectra from this model, we can detect very weak signals and make them visible and coherent by ‘repairing’ corrupted phase of original data. Both presented approaches – phase substitution and phase sign corrections – show good performance on complex synthetic and field data suffering from severe near-surface scattering where conventional processing methods are rendered ineffective. The methods are mathematically formulated as a special case of time-frequency masking (common in speech processing) combined with the signal model from local stacking. This powerful combination opens the avenue for a completely new family of approaches for multi-channel seismic processing that can address seismic processing of land data with nodes and single sensors in the desert environment.     

The Gravity Module Assembly used in airborne full tensor gradiometry surveys

In airborne gravity gradiometry, the Gravity Module Assembly is an optional gravimeter unit that is mounted on the same stabilized platform as the Full Tensor Gradiometer. Direct measurements of the gravity field are needed from this device to constrain the long wavelengths when gradient data are integrated mathematically to form high-resolution gravity fields. The Gravity Module Assembly is, however, capable of providing independent gravity data with a specification approaching that expected from a dedicated airborne gravity system. Presented here is an error analysis of data from this instrument collected alongside the Full Tensor Gradiometer during an airborne survey. By having both gradiometry and gravity datasets, comparisons of the information content in these two types of measurement are made.     

沙漠地区地震勘探随机噪声建模及其在噪声压制中的应用

随机噪声是影响地震勘探有效信号的主要因素,其存在大大降低了地震记录的信噪比.在噪声压制方法不断被改进的同时,对随机噪声特性进行研究,了解噪声的产生机制是对其进行压制的先决条件,目前对噪声的研究主要是特性研究以寻找规律性,对其进行定性定量的分析还比较少.本文根据塔里木沙漠地区实际采集环境,考虑到噪声的连续性给计算带来的不便,假设各类噪声源以点源的形式分布在检波器周围,依据相应理论确定各类噪声源的源函数,其激发的噪声经由波动方程传播,将随机噪声作为各类噪声源共同作用的综合波场,建立随机噪声的理论模型.通过分析不同种噪声对地震记录的影响,选取合适的滤波方法对其进行压制,实验结果表明,通过建立沙漠地区随机噪声的理论模型,为选择有效的滤波方法,提高地震记录信噪比起到理论指导作用.     

基于能量运算的磁共振信号尖峰噪声抑制方法

磁共振探测信号微弱,使用高灵敏度的核磁共振地下水探测仪,极易受到环境噪声干扰.其中,工频谐波噪声和尖峰噪声,是影响信号质量最严重的两类噪声.国内外研究表明,通过参考线圈的布设,依据探测线圈和参考线圈中噪声相关性,利用自适应参考对消算法,能够有效抑制工频谐波噪声.然而,尖峰噪声的存在严重影响了主通道与参考道的数据相关性,成为了参考对消算法应用的难题与障碍.为解决这一问题,本文提出磁共振信号中尖峰噪声的抑制方法,推导了能量域磁共振信号表达式,通过计算信号能量,可有效检测尖峰噪声并突出不易识别的小幅度尖峰噪声,采用基于中位数的绝对偏差法确定阈值,进而剔除尖峰噪声.为了验证去噪效果,与应用较广的统计叠加法进行对比研究.仿真结果表明,对于干扰幅度较大、持续时间较长的尖峰噪声,能量运算法和统计叠加法均能识别并剔除,且不损失有效的磁共振信号,标准差偏差控制在0.3%以内,可以满足实际应用的要求;对于小于信号幅度1.5倍的尖峰噪声,能量运算法可有效识别并剔除,而统计叠加法无法实现.针对多通道探测系统,使用能量运算法剔除尖峰噪声后,可明显提高主通道和参考道的数据相关性,为后续自适应参考对消算法的应用奠定了基础.实测数据处理结果进一步证明了本文方法的实用性.     

The utilization of the double focal transformation for sparse data representation and data reconstruction

In many cases, seismic measurements are coarsely sampled in at least one dimension. This leads to aliasing artefacts and therefore to problems in the subsequent processing steps. To avoid this, seismic data reconstruction can be applied in advance. The success and reliability of reconstruction methods are dependent on the assumptions they make on the data. In many cases, wavefields are assumed to (locally) have a linear space–time behaviour. However, field data are usually complex, with strongly curved events. Therefore, in this paper, we propose the double focal transformation as an efficient way for complex data reconstruction. Hereby, wavefield propagation is formulated as a transformation, where one‐way propagation operators are used as its basis functions. These wavefield operators can be based on a macro velocity model, which allows our method to use prior information in order to make the data decomposition more effective. The basic principle of the double focal transformation is to focus seismic energy along source and receiver coordinates simultaneously. The seismic data are represented by a number of localized events in the focal domain, whereas aliasing noise spreads out. By imposing a sparse solution in the focal domain, aliasing noise is suppressed, and data reconstruction beyond aliasing is achieved. To facilitate the process, only a few effective depth levels need to be included, preferably along the major boundaries in the data, from which the propagation operators can be calculated. Results on 2D and 3D synthetic data illustrate the method's virtues. Furthermore, seismic data reconstruction on a 2D field dataset with gaps and aliased source spacing demonstrates the strength of the double focal transformation, particularly for near‐offset reflections with strong curvature and for diffractions.     

GNMF小波谱分离在地震勘探噪声压制中的应用

地震勘探资料噪声压制及信噪比提高是整个地震勘探信号处理过程中的重要任务,随着地震勘探深度的增加及其复杂性,人们对地震数据质量的要求越来越高.勘探环境的复杂化使得采集到的地震资料中有效信号被大量噪声淹没,无法清晰辨识,严重影响后续的数据处理与解释.小波去噪是地震勘探中常用且发展较成熟的一种方法,但是其涉及到的阈值函数选取问题一直令人困扰,虽然已有多种阈值函数被提出,但仍存在各自的缺陷.本文利用小波分解在时域及频域良好的信号细节体现特性,引入模式识别中的非负矩阵分解(NMF)谱分离思想,针对小波系数阈值优化问题,提出了一种小波域图非负矩阵分解(GNMF)消噪算法.该方法首先在小波分解基础上,利用GNMF算法实现小波分解系数谱中信号分量与噪声分量的谱分离,然后通过反变换重构各分离子谱对应的子信号,最后利用K均值聚类算法将得到的多个子信号划分为信号类及噪声类,最终得到重构信号及分离噪声.合成记录和实际地震资料的消噪结果验证了新方法在提高信号与噪声分离准确性和精度方面的有效性,同时新方法避免了阈值选取造成的噪声压制不理想或有效成分损失问题.与小波消噪结果的对比及数值分析也说明了新方法在噪声压制及有效成分保持方面的优势.