地震背景噪声成像技术研究进展与展望

背景噪声成像技术是21世纪以来地震学研究最为重要的突破性进展之一.该方法不依赖于天然地震事件的发生,利用连续地震记录中普遍存在的"背景噪声",通过不同台站对间连续时间信号的互相关来提取经验格林函数并用以进行地下介质结构成像研究.与传统的天然源地震探测手段相比,背景噪声成像技术从随机场源信号中提取介质结构的信息,具有成像...     

中国大陆背景噪声成像研究及应用前景

对长时间序列的背景地震噪声进行互相关计算可以得到台站间的经验格林函数,这种方法不依赖天然地震及人工震源,仅利用台站记录的背景噪声就能得到地下结构,该方法可以更为便捷地获得地震活动性较低地区的地下构造.随着背景噪声层析成像技术的发展应用,该方法会进一步提高地壳上地幔速度模型的分辨率.本文综述了背景噪声成像技术及其在中国大...     

利用背景噪声研究壳幔结构发展综述

利用背景噪声研究地下结构即对两个台站长时间的地震噪声记录进行互相关计算提取台站间的格林函数,获取面波频散特征,并进一步层析成像或测量面波走时变化.通过该方法可获得壳幔速度结构和对地下介质监测.近些年,该方法在理论上和实践上都有长足进展.首先介绍地震背景噪声应用的发展历史,进而重点论述利用背景噪声对壳幔进行群速度和相速度结构成像、三维剪切波速度结构成像、与其他方法联合成像和对地下介质监测的应用.最后分析了目前背景噪声应用面临的问题,并展望了其发展前景.     

基于染色算法的宽频带地震照明及分辨率分析（英文）

偏移成像是将由地下目标产生的地震数据归位到反射界面从而产生地下结构的像。但由于受到采集系统孔径、复杂上覆介质和成像目标倾角等因素的影响,成像结果常常是地下结构的畸变了的像。地震照明和分辨率分析为上述因素对地震成像结果的影响提供了定量的描述方法。点弥散函数中包含地震照明和分辨率分析的全部信息。染色算法建立地下某一特定结构与地震波场和地震数据之间的对应关系。本文利用染色算法计算点弥散函数并进一步获得角度域照明信息,同时通过点弥散函数与原始成像结果反卷积的方法对成像结果予以校正。展示了SEG盐丘模型的相关计算结果。染色算法为点弥散函数的计算及进行宽频带地震照明与分辨率分析提供了一种高效的计算工具。     

辽宁地区低频背景噪声特征分析及模型建立

低频背景噪声是地震数据的重要组成部分,在地下介质成像和地质构造探测等研究中发挥重要作用。区域性背景噪声研究不仅会得出该区域背景噪声特性,还可以针对地域性特征进行更适合的应用。辽宁地区低频背景噪声对本区域背景噪声研究有重要意义,基于辽宁省6个台站连续多年的宽频带地震背景噪声数据,利用地震计观测的位移值研究辽宁地区低频背景噪声特征,并采用数学函数模型构建了辽宁地区低频背景噪声模型。通过计算背景噪声位移分析发现,辽宁地区低频背景噪声（1 Hz以下）具有明显季节性变化,通常在冬季达到最大值,在夏季达到最小值。基于三角函数关系拟合得到辽宁地区背景噪声年变公式,建立辽宁地区低频背景噪声模型,并采用ADF法验证了该模型可靠性。     

地震背景噪声成像研究综述

地震背景噪声成像方法已成为21世纪地震学的伟大突破之一,其原理是,对2个台站记录的连续背景噪声信号进行互相关计算,得到台站间的格林函数,利用经验格林函数得到面波速度函数,获取面波频散特性,用地震层析成像方法对面波速度进行反演,得到地球内部的速度结构。其应用近年来日益广泛,涉及各向同性和各向异性的速度结构成像、大地震前后速度结构变化监测、体波联合成像、衰减结构成像、地震定位精度提高、噪声源分布和物理起源探究、强地面运动评估等。其优点是不需要等待天然地震或使用对环境构成威胁的人工爆破,所有台阵都可以当作源,拓宽了频带范围,可以获得较多短周期频散数据,提高反演分辨率。     

密集台阵背景噪声双聚束成像化龙断裂精细结构

双聚束成像法(Double beamforming,简称DBF)是利用地震背景噪声进行地下速度结构成像的新方法,该方法通过对环境噪声场中能量相干部分的叠加达到提高信号信噪比的目的,识别和提取不同类型的地震波信号及其入射方位角(微弱体波、反射面波等),从而进行地下速度结构成像研究等.特别是进行背景噪声面波成像时,DBF能...     

地震频发区域背景噪声提取格林函数的反褶积方法研究

针对云南这一地震频发区域记录到的地震背景噪声数据,设计了一种"最大值均一化"算法,该算法能有效地消除背景噪声中的地震信号、畸变信号及其它干扰信号。应用此算法对记录到的背景噪声数据进行预处理,对处理后的数据利用多窗谱反褶积计算方法可获得其具有较高信噪比和保留了相对幅值信息的格林函数。     

基于局部优化粒子群算法的背景噪声反演

从背景噪声中提取瑞雷波频散曲线并通过反演获得地下横波速度结构已被广泛应用于大尺度的地下结构探测和小尺度的工程勘探中.基于频散函数的反演目标函数可以有效解决多阶模频散曲线联合反演的模式误判问题,然而其广泛分布的局部极值导致更为严重的多解性,在大范围的参数搜索空间下很难获得最优解,需要搭配全局搜索性能强的优化算法.本文提出局部优化粒子群算法(PSOG),通过粒子迭代过程中引入局部优化方法提高种群多样性,避免陷入局部极值并加快收敛速度.为验证新算法的有效性,结合基于久期函数的目标函数对理论合成数据进行反演,结果表明,局部优化粒子群算法比传统算法的稳定性与准确性都有显著提高.处理了上海苏州河地区的背景噪声数据,成功地对古河道切割造成的软弱层进行成像.PSOG算法与新型反演目标函数的结合在背景噪声勘探的工程应用上具有巨大潜力.     

海洋活动对云南地震观测台网的影响

1 研究背景 地震的孕育和发生通常伴随着应力场变化、地下流体迁移、地壳浅层破坏等事件的发生,从而导致地下介质物理性质(如波速)的变化.由于背景噪声监测方法的独特优势,背景噪声互相关函数在监测地震孕育过程中展现了巨大潜力(Brenguier et al,2008),也为地震预测预报工作提供了有用的参考信息.然而,噪声源季节性变化,对以背景噪声互相关方法测量的地震波速度的精度存在影响.因此,利用背景噪声监测地震波速度变化,必须对噪声源机制有清晰认识.     

利用背景噪声进行地震成像的新方法

利用背景地震噪声提取格林函数，即通过一对台站记录的地震噪声进行互相关计算，来近似台站间的格林函数，并进一步通过地震成像获取地下结构的认识，成为最近跨学科研究的热点问题之一.本文首先叙述了其发展背景及过程，然后分别从四个角度，简要介绍了目前对其物理原理的解释.如果该方法能得到进一步的发展，将不再依赖于天然地震以及人工地震，而仅仅利用地震台站记录的地震噪声便可获取高分辨率的地下成像.该方法将会大大促进地震学的发展.     

Directional‐oriented wavefield imaging: a new wave‐based subsurface illumination imaging condition for reverse time migration

The key objective of an imaging algorithm is to produce accurate and high‐resolution images of the subsurface geology. However, significant wavefield distortions occur due to wave propagation through complex structures and irregular acquisition geometries causing uneven wavefield illumination at the target. Therefore, conventional imaging conditions are unable to correctly compensate for variable illumination effects. We propose a generalised wave‐based imaging condition, which incorporates a weighting function based on energy illumination at each subsurface reflection and azimuth angles. Our proposed imaging kernel, named as the directional‐oriented wavefield imaging, compensates for illumination effects produced by possible surface obstructions during acquisition, sparse geometries employed in the field, and complex velocity models. An integral part of the directional‐oriented wavefield imaging condition is a methodology for applying down‐going/up‐going wavefield decomposition to both source and receiver extrapolated wavefields. This type of wavefield decomposition eliminates low‐frequency artefacts and scattering noise caused by the two‐way wave equation and can facilitate the robust estimation for energy fluxes of wavefields required for the seismic illumination analysis. Then, based on the estimation of the respective wavefield propagation vectors and associated directions, we evaluate the illumination energy for each subsurface location as a function of image depth point and subsurface azimuth and reflection angles. Thus, the final directional‐oriented wavefield imaging kernel is a cross‐correlation of the decomposed source and receiver wavefields weighted by the illuminated energy estimated at each depth location. The application of the directional‐oriented wavefield imaging condition can be employed during the generation of both depth‐stacked images and azimuth–reflection angle‐domain common image gathers. Numerical examples using synthetic and real data demonstrate that the new imaging condition can properly image complex wave paths and produce high‐fidelity depth sections.     

Direct migration of ambient seismic data

Utilising ambient seismic energy naturally propagating in the Earth as an alternative approach to active body-wave seismic investigations has been a topic of interest for a number of decades. However, because ambient surface-wave arrivals typically are of much greater amplitude than ambient body-wave energy, significant data signal processing and long recording times are required to mitigate this and other coherent noise sources, and to correlate sufficient reflected body-wave energy to converge to a stable image. Even for these scenarios, identifying and validating imaged body-wave reflection events remain challenging. In active-source investigations, extended imaging condition gathers are used to examine velocity (in)accuracy. Herein, we develop an ambient direct migration approach that uses a novel ambient (deconvolution) extended imaging condition. We simulate synthetic ambient-wavefield seismic data for two different models and use a field data set from Lalor Lake in Manitoba, Canada, to conduct a series of numerical experiments to demonstrate the velocity sensitivity and long-term stationarity of ambient-wavefield seismic data in the migration image domain. Tests with varying global velocity perturbations show a characteristic reflector moveout in deconvolution extended imaging condition gathers that can serve as a diagnostic of reflected ambient body-wave energy. We illustrate that this imaging formalism, under idealised circumstances, gives comparable results to conventional seismic methods, which extends the use of extended imaging condition gather-based image validation to ambient-wavefield seismic data scenarios. We assert that this may be a valuable tool for the validation of ambient migration techniques that to date have yielded largely inconclusive results.     

Simultaneous Denoising and Interpolation of Seismic Data via the Deep Learning Method

Utilizing data from controlled seismic sources to image the subsurface structures and invert the physical properties of the subsurface media is a major effort in exploration geophysics. Dense seismic records with high signal-to-noise ratio (SNR) and high fidelity helps in producing high quality imaging results. Therefore, seismic data denoising and missing traces reconstruction are significant for seismic data processing. Traditional denoising and interpolation methods rarely occasioned rely on noise level estimations, thus requiring heavy manual work to deal with records and the selection of optimal parameters. We propose a simultaneous denoising and interpolation method based on deep learning. For noisy records with missing traces, we adopt an iterative alternating optimization strategy and separate the objective function of the data restoring problem into two sub-problems. The seismic records can be reconstructed by solving a least-square problem and applying a set of pre-trained denoising models alternatively and iteratively.We demonstrate this method with synthetic and field data.     

Steered migration in hard rock environments

Hard rock seismic exploration normally has to deal with rather complex geological environments. These types of environments are usually characterized by a large number of local heterogeneity (e.g., faults, fracture zones, and steeply dipping interfaces). The seismic data from such environments often have a poor signal‐to‐noise ratio because of the complexity of hard rock geology. To be able to obtain reliable images of subsurface structures in such geological conditions, processing algorithms that are capable of handling seismic data with a low signal‐to‐noise ratio are required for a reflection seismic exploration. In this paper, we describe a modification of the 3D Kirchhoff post‐stack migration algorithm that utilizes coherency attributes obtained by the diffraction imaging algorithm in 3D to steer the main Kirchhoff summation. The application to a 3D synthetic model shows the stability of the presented steered migration to the presence of high level of the random noise. A test on the 3D seismic volume, acquired on a mine site located in Western Australia, reveals the capability of the approach to image steep and sharp objects such as fracture and fault zones and lateral heterogeneity.     

利用噪声研究地下介质速度结构及其变化在中国大陆的应用

背景噪声层析成像技术已被广泛应用于地壳和上地幔速度结构的研究,这种方法不依靠地震的发生和人工源爆破,只需记录连续的噪声信号而无需产生信号,因为噪声穿过地下介质时会携带信息,然后通过利用台站记录到的连续背景噪声数据进行互相关计算和叠加,即可得到台站间的经验格林函数,从而获取对地下结构的认识。这种方法已经很好地应用于中国的东北地区、华北克拉通、青藏高原以及华南地区,并成功地揭示了这些地区地壳与上地幔顶部的速度结构。此外近年来,一些学者还利用噪声互相关技术研究地下介质地震波速度随时间的变化,通过对汶川大地震前后连续噪声记录的研究发现,大震发生后呈现同震波速降低和震后波速逐渐恢复的特点,这表明可以通过观测地震波特性的变化来监测地下应力的变化,从而为大震的预测预防工作提供科学依据。本文主要综述了近些年来背景噪声技术及其在中国大陆地区的应用。     

CONVOLUTIONAL BACK-PROJECTION IMAGING OF PHYSICAL MODELS WITH CROSSHOLE SEISMIC DATA1

The development of crosshole seismic tomography as an imaging method for the subsurface has been hampered by the scarcity of real data. For boreholes in excess of a few hundred metres depth, crosshole seismic data acquisition is still a poorly developed and expensive technology. A partial solution to this relative lack of data has been achieved by the use of an ultrasonic seismic modelling system. Such ultrasonic data, obtained in the laboratory from physical models, provide a useful test of crosshole imaging software. In particular, ultrasonic data have been used to test the efficacy of a convolutional back-projection algorithm, designed for crosshole imaging. The algorithm is described and shown to be less susceptible to noise contamination than a Simultaneous Iterative Reconstruction Technique (SIRT) algorithm, and much more computationally efficient.     

流动地震观测背景噪声的台基响应

大规模流动地震台阵技术发展为高分辨率深部结构成像提供了重要基础,背景噪声是影响流动地震观测质量的关键因素. 为掌握流动地震观测噪声规律,发展流动地震观测降噪技术, 编制流动地震观测技术规范, 我们开展了针对不同台基流动地震观测背景噪声的观测实验与分析. 其中,山西省临汾市五个地点架设了共22个对比观测台站, 进行了超过一年半的连续观测. 通过计算不同频段范围内背景噪声记录的加速度功率谱密度, 研究了不同场地条件和环境噪声下流动地震观测台站的噪声特征及其台基响应,分析了不同台基处理方式对噪声的抑制效果. 结果表明:(1)高频人为噪声和长周期自然噪声是影响流动地震观测质量的主要噪声, 可以通过增加台基深度和改善台基处理方式等方法降低其影响; (2)增加台基深度能有效地降低长周期噪声和高频噪声, 2 m深坑能使高人为噪声台站各分量的高频频段和长周期频段分别降低5 dB和10 dB; (3)由于其不稳定性, 沙子台基的水平分量在长周期频段一般要高于摆墩台基5 dB, 流动地震观测中推荐使用摆墩台基; (4) 台站位置、台站内部温度和空气流动都是影响台站噪声的重要因素. 在此基础上提出了不同场地条件和噪声环境下的台基处理建议和适合国情的移动地震台阵台站建设参考方案, 有助于流动地震观测野外工作的标准化和规范化.     

高铁地震数据干涉成像技术初探

高铁运行会引起铁轨的震动,从而产生地震波向地下介质中传播,通过研究该地震波可对高铁沿线的地质情况进行持续监测.与常规地震勘探中的震源相比,高铁地震中的震源较为复杂,为移动震源,而地震干涉技术可以通过地震记录间的相互干涉,消除震源的影响,因此可利用地震干涉技术对高铁地震信号进行处理并成像.本文通过分析研究,总结出地震干涉方法在处理高铁地震数据时的关键技术问题:不同于常规地震干涉中先干涉后叠加的干涉成像方式,高铁地震移动源的特点使得干涉顺序变为先叠加后干涉,由此带入了大量震源串扰噪声;初步提出两种解决高铁地震干涉成像的思路:通过对高铁地震信号的处理,使高铁变相"提速"或"降速",给出了"提速"或"降速"后各自的成像思路,并给出了数据处理的技术设想.