分布式光纤地震传感技术在成像研究中的应用进展

分布式光纤地震传感技术是新一代密集台阵观测技术,其利用光纤在地震波场作用下产生的光时程变化,探测地下介质的动态应变信号.其具有空间采样率高、恶劣条件耐受性强、运维成本低等优势,适用于城市、海洋、深井、冰川等传统地震学观测手段较难开展工作的环境.本文围绕该技术在地球内部结构成像研究中的应用,调研了从浅表数米到莫霍面深度等不同尺度成像的研究进展,其利用信号为从地脉动到高频交通噪声等多频段被动源和不同级别的主动源.文章同时分析了该技术面临的一些挑战,包括信号质量和信号保真度、海量数据处理和波场信息挖掘、海量数据存储和共享分析等,由此建议,须开展主被动源高分辨率动态成像、仪器传递函数计算及其校正方法、大数据有效信息挖掘等研究,从而更好地服务于高密度、高精度的光纤传感地震成像研究.     

分布式光纤声波传感器及其在天然地震学研究中的应用

分布式光纤声波传感器(Distributed Acoustic Sensing, DAS)是近年来兴起的超密集地震观测系统,具有一系列观测密度高、观测成本低、耐受恶劣环境等优势,在油气行业得到了广泛应用,也引起了天然地震学界的关注.本文简要回顾了DAS系统的测量原理、发展历程、技术方案、介绍了测量原理及其响应特性,然后围绕多个观测实验,介绍浅部结构成像、深部结构探测和地震监测三个方向的典型应用实例,最后讨论了DAS系统在天然地震学研究中应用面临的挑战和发展趋势.     

分布式光纤声波传感系统在近地表成像中的应用Ⅱ:背景噪声成像

随着城市化的发展,城市地球物理日益成为地球物理研究的重要方向,地震成像是构建城市地下空间三维/四维图像的重要手段,但面临观测成本高的困难.近年来国际上新发展的分布式光纤声波传感器作为高密度地震观测系统已经在地震层析成像方面得到了应用,在提高成像分辨率的同时,又降低了观测成本.本研究使用国产分布式光纤声波传感器开展了观测实验,利用480 m埋地光缆记录了13 h背景噪声,计算得到噪声互相关函数,获得了高频Rayleigh面波信号.采用多道面波分析方法提取相速度频散曲线,其结果与传统检波器记录和主动源结果较为一致.采用遗传算法反演得到了研究区内二维S波速度剖面,获得了下方沉积物横向变化特征.通过本次实验,初步验证了国产设备开展地震背景噪声成像研究、构建地下浅层结构模型的可行性.

     

分布式光纤声波传感微振动响应特征

分布式光纤声波传感技术(Distributed Acoustic Sensing, DAS)利用光纤中的瑞利散射来获取振动信息, 具有高密度、低成本、可长时监测等优点, 目前已经广泛应用于地震勘探领域.DAS系统可用于采集沿光纤轴向的应变或应变率, 且DAS响应与地震波传播方向和偏振方向有关.本文推导获得了不同震源模型的应变辐射花样, 并通过数值模拟获得了不同震源机制和不同布设条件下的分布式光纤微振动数据.理论合成算例结果表明, P波的应变辐射花样和速度辐射花样在各类震源机制条件下都具有较为相似的形态, 而S波的两种辐射花样在某些震源机制条件下具有较为明显的形态差异.此外, 包含DC(Double Couple, 双力偶)成分震源的S波DAS响应记录与常规速度检波器记录相比, 极性反转的位置具有较大差异.

     

利用分布式光纤声波传感器监测大容量气枪震源信号

近年来出现的新型高密度地震观测系统——分布式光纤声波传感器(Distributed Acoustic Sensing,DAS)有望提高地震成像的空间分辨率。为探索该技术在监测介质动态变化方面的应用,在云南省宾川县布设了长约180m的传感光缆,对9.6km外的宾川大容量气枪震源的激发信号进行了监测。在为期2d的实验期间,对气枪震源进行了24次高重复激发,采用时频域加权相位叠加算法对多炮和多道记录进行叠加处理,得到了高质量的地震波信号,与共址观测的地震仪记录具有较高的一致性。通过此次观测实验,初步验证了利用DAS监测大容量气枪震源信号的可行性,未来有望将其推广应用于高分辨率4D地震成像研究中。     

分布式光纤声波传感系统在近地表成像中的应用Ⅰ：主动源高频面波

近年来发展的新型地震观测系统--分布式光纤声波传感器(DAS,Distributed Acoustic Sensing)可以实现低成本高密度观测,有望提高浅层结构成像的精度以及分辨率.最近国内研发了一系列具有自主知识产权的DAS设备,为验证国产设备在浅层结构研究中的可行性以及应用效果,2018年7月我们开展了一次DAS观测实验.实验采集了50kg落锤震源激发的地震信号,并采用多道面波分析方法提取了8~20Hz频段的主动源Rayleigh波相速度频散曲线,得到了实验区浅层30m的S波速度结构.获得的主动源面波频散曲线与共址检波器的结果吻合,也与背景噪声提取的结果具有较好的一致性,表明国产设备的可靠性和DAS在浅层结构主动源面波成像研究中的可行性.     

分布式光纤声波传感系统在西部已开发气田井下断层活动性监测中的试验研究与应用

克拉2气田是塔里木盆地储量最大的整装超高压干气气藏,也是西气东输的主力气田,经过近20年的开发已进入开发中后期,23口生产井中11口井不同程度见水.为查明该气田的水侵运移通道,在一口观察井中下入高灵敏度的分布式光纤声波传感系统,长期监测井下微地震信号.本文介绍了分布式光纤传感系统的仪器选择、监测方案设计和定位算法研究等,通过对井下微地震信号的采集、降噪、滤波、识别和定位等,研究微地震事件集中发生的区域和频率,分析气田断层的活动性与水侵的关系.井下监测和数据分析结果表明,分布式光纤声波传感系统长期监测可以为断层活动性评价提供更丰富的数据,克拉2气田西南方向断层破碎带附近有大量微地震事件,断层的稳定性较差,是导致克拉2气田气井出水的主要原因之一.     

基于孪生网络的人工震源分布式光纤传感数据噪声压制

受耦合效应和其他诸多因素的影响,野外实际采集的分布式光纤声波传感(Distributed Fiber-optic Acoustic Sensing,DAS)数据的信噪比通常较低.因此,在后续处理之前,需要首先对DAS数据进行去噪处理.传统的基于人工智能监督学习的去噪方法能够对DAS数据中的噪声进行压制,但它需要大量含噪声和无噪声数据进行成组标记,人工标记工作量巨大.为此,本文提出了基于自监督学习孪生网络的DAS地震数据去噪方法.该方法基于自监督学习中的孪生网络结构,采用U-Net网络建立深度学习框架.所提框架通过对输入的含噪声数据进行数据自我特征学习,迭代获取去噪目标函数的最优解,从而实现自监督高精度深度学习去噪网络构建.合成数据和实际资料处理结果表明,本文方法可以有效抑制人工震源DAS采集数据中的随机噪声,显著提高去噪结果的信噪比和同相轴的连续性.此外,本文方法能够避免常规监督学习方法需要进行数据标记的人工工作量,有效提高实际地震数据去噪处理效率.

     

分布式光纤振动传感系统中数据采集及信号处理系统设计

本文主要介绍了一套分布式光纤振动传感系统中的数据采集及信号处理系统,该系统设计采用高性能的运算放大电路完成光电信号调理,以高精度差动模数转换器AD9246完成模数转换工作,并选用高性能FPGA作为核心逻辑控制器,并以低功耗的OMAP-L137作为CPU负责振动数据计算、网络通讯等工作,从而使该-OTDR分布式光纤振动传感系统测量范围扩展到25 km范围。本文通过计算相邻测点振动增量方法检测是否发生了振动入侵,提高了分布式光纤振动入侵检测的灵敏度。该设计方法提高分布式光纤振动传感系统的信噪比,使得该系统振动检测灵敏度提高、抗干扰能力增强,因此该分布式光纤振动传感系统可以用于实际工程的振动监控。     

基于应变率的分布式光纤声波传感全波形反演研究

分布式光纤声波传感系统(Distributed Acoustic Sensing, DAS)是近年来迅速发展的新型地震数据采集系统.与传统地震检波器相比,DAS具有耐受恶劣环境,易实现大区域高密度观测等优点.传统地震检波器测量质点速度,而DAS接收沿光纤的轴向应变率(或应变)信号,传统基于速度—应力场弹性波方程全波形反演无法直接用于DAS数据反演.在前人DAS数据全波形反演研究中,将DAS数据转换为沿光纤的质点速度,但会放大低波数噪声,在低信噪比条件下影响反演精度.本文提出了直接基于应变率数据的DAS信号全波形反演方法.首先推导实现了直接基于应变率参数的DAS数据全波形反演理论.其次通过典型模型测试和DAS实测数据验证了直接基于应变率的全波形反演方法在DAS数据速度反演中的可行性和有效性.     

淮南深地实验室分布式光纤地震立体台阵观测数据分析

在淮南深地实验室布设了水泥固结的传感光缆,结合竖井中已有通信光缆,利用分布式光纤地震传感技术(DAS)构建了高密度的三分量立体台阵,开展了为期一年的连续观测.通过分析地下870 m的背景噪声记录,发现其日间变化幅度较小,这表明深地实验室受气压、温度和人类活动等的影响较小.然而,在低频段观测到明显增强的噪声,这给低频信号研究带来了一定困难.在连续记录中,识别出了多个地方震和区域震信号,尤其是获得了高质量的玛多地震P波信号.与共址地震仪数据的一致性表明DAS波形记录的可靠性.通过三分量DAS记录识别了Rayleigh面波信号,并利用多重滤波技术测量得到其群速度频散曲线;利用DAS应变率记录与共址宽频带地震仪的速度记录比值获得了相速度信息.两种方法测得的面波频散数据可用于研究速度结构.这些初步结果展现了深地实验室提供的超静环境以及三分量立体DAS台阵观测的优势,为后续进一步研究提供参考.

     

Imaging shallow structure with active-source surface wave signal recorded by distributed acoustic sensing arrays

Distributed acoustic sensing (DAS) is one recently developed seismic acquisition technique that is based on fiber-optic sensing. DAS provides dense spatial spacing that is useful to image shallow structure with surface waves. To test the feasibility of DAS in shallow structure imaging, the PoroTomo team conducted a DAS experiment with the vibroseis truck T-Rex in Brady’s Hot Springs, Nevada, USA. The Rayleigh waves excited by the vertical mode of the vibroseis truck were analyzed with the Multichannel Analysis of Surface Waves (MASW) method. Phase velocities between 5 and 20 Hz were successfully extracted for one segment of cable and were employed to build a shear-wave velocity model for the top 50 meters. The dispersion curves obtained with DAS agree well with the ones extracted from co-located geophones data and from the passive source Noise Correlation Functions (NCF). Comparing to the co-located geophone array, the higher sensor density that DAS arrays provides help reducing aliasing in dispersion analysis, and separating different surface wave modes. This study demonstrates the feasibility and advantage of DAS in imaging shallow structure with surface waves.     

Convolutional neural networks for automated microseismic detection in downhole distributed acoustic sensing data and comparison to a surface geophone array

Distributed acoustic sensing is a growing technology that enables affordable downhole recording of strain wavefields from microseismic events with spatial sampling down to ∼1 m. Exploiting this high spatial information density motivates different detection approaches than typically used for downhole geophones. A new machine learning method using convolutional neural networks is described that operates on the full strain wavefield. The method is tested using data recorded in a horizontal observation well during hydraulic fracturing in the Eagle Ford Shale, Texas, and the results are compared to a surface geophone array that simultaneously recorded microseismic activity. The neural network was trained using synthetic microseismic events injected into real ambient noise, and it was applied to detect events in the remaining data. There were 535 detections found and no false positives. In general, the signal-to-noise ratio of events recorded by distributed acoustic sensing was lower than the surface array and 368 of 933 surface array events were found. Despite this, 167 new events were found in distributed acoustic sensing data that had no detected counterpart in the surface array. These differences can be attributed to the different detection threshold that depends on both magnitude and distance to the optical fibre. As distributed acoustic sensing data quality continues to improve, neural networks offer many advantages for automated, real-time microseismic event detection, including low computational cost, minimal data pre-processing, low false trigger rates and continuous performance improvement as more training data are acquired.     

分布式声波传感VSP数据中的光缆耦合噪声局部稀疏优化压制方法

分布式声学传感系统在采用光纤采集垂直地震剖面（Vertical Seismic Profile,VSP）时,受到光缆与井壁耦合不良等因素影响,地震数据会受到能量较强的光缆耦合噪声干扰.全局稀疏优化方法在压制光缆耦合噪声时未考虑有效信号和光缆耦合噪声的时变特性,影响了噪声压制效果.本文提出了一种基于局部稀疏优化的光缆耦合噪声自适应压制方法.该方法针对每道地震数据在时窗长度选择范围内综合计算每个时窗长度下的有效信号和光缆耦合噪声的稀疏度,进而选择稀疏度最优下的时窗长度,最终采用形态成分分析方法在最优时窗内实现VSP数据中光缆耦合噪声的稀疏优化压制.模型算例和实际算例的结果均表明本文所提方法优于全局稀疏优化方法.

     

Seismic hazard analysis for a spatial linearly distributed system

The models currently used in the seismic evaluation of important projects, microzoning and seismic zonation are all for site. Although seismic hazard analysis have been done for many sites in seismic zonation and microzoning, relationship among sites is not considered in the final results. Studies show that it is impossible to get total hazard for specific area from the results of the hazard analysis of sites. So, when we consider the total seismic hazard of a specific spatial distributed system, methods for site are not enough. Author discussed the relation and the difference between system hazard and segments hazard which form the system and proposed a seismic hazard analysis model taking spatial linear distributed series and parallel system as an example. In aseismic design and earthquake disaster prevention decision, not only the seismic hazard of segments of the system but also the total seismic hazard of the system should be considered. The Chinese version of this paper appeared in the Chinese edition ofActa Seismologica Sinica,15, 347–352, 1993.     

Ambient noise as the new source for urban engineering seismology and earthquake engineering: a case study from Beijing metropolitan area

In highly populated urban centers, traditional seismic survey sources can no longer be properly applied due to restrictions in modern civilian life styles. The ambient vibration noise, including both microseisms and microtremor, though are generally weak but available anywhere and anytime, can be an ideal supplementary source for conducting seismic surveys for engineering seismology and earthquake engineering. This is fundamentally supported by advanced digital signal processing techniques for effectively extracting the useful information out from the noise. Thus, it can be essentially regarded as a passive seismic method. In this paper we first make a brief survey of the ambient vibration noise, followed by a quick summary of digital signal processing for passive seismic surveys. Then the applications of ambient noise in engineering seismology and earthquake engineering for urban settings are illustrated with examples from Beijing metropolitan area. For engineering seismology the example is the assessment of site effect in a large area via microtremor observations. For earthquake engineering the example is for structural characterization of a typical reinforced concrete high-rise building using background vibration noise. By showing these examples we argue that the ambient noise can be treated as a new source that is economical, practical, and particularly valuable to engineering seismology and earthquake engineering projects for seismic hazard mitigation in urban areas.     

1D System identification of a 54‐story steel frame building by seismic interferometry

A 54‐story steel, perimeter‐frame building in downtown Los Angeles, California, is identified by a wave method using records of the Northridge earthquake of 1994 (M_L = 6.4, R = 32 km). The building is represented as a layered shear beam and a torsional shaft, characterized by the corresponding velocities of vertically propagating waves through the structure. The previously introduced waveform inversion algorithm is applied, which fits in the least squares sense pulses in low‐pass filtered impulse response functions computed at different stories. This paper demonstrates that layered shear beam and torsional shaft models are valid for this building, within bands that include the first five modes of vibration for each of the North–South (NS), East–West (EW), and torsional responses (0–1.7 Hz for NS and EW, and 0–3.5 Hz for the torsional response). The observed pulse travel time from ground floor to penthouse level is τ ≈1.5 s for NS and EW and τ ≈ 0.9 s for the torsional responses. The identified equivalent uniform shear beam wave velocities are β_eq ≈ 140 m/s for NS and EW responses, and 260 m/s for torsion, and the apparent Q ≈ 25 for the NS and torsional, and ≈14 for the EW response. Across the layers, the wave velocity varied 90–170 m/s for the NS, 80–180 m/s for the EW, and 170–350 m/s for the torsional responses. The identification method is intended for use in structural health monitoring. Copyright © 2013 John Wiley & Sons, Ltd.