Fiber-optic vibration sensing ‒ II: Intrinsic sensing with scattered or transmitted light and their seismological applications
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摘要: 本征光纤振动传感通过在光纤一端重复发射探测激光，在光纤同端或另外一端接收散射光或透射光并解调它们的变化，测量光纤上的动态应变（即振动）. 本征传感以光纤为传感器，具有结构简单，布设灵活，运维方便的优点，能应用于流体、高温、高压或强电磁干扰等恶劣环境，可以大幅度延伸可监测的区域，并实现相对廉价的长期连续监测. 此外，光纤传感还可以利用全球城市内、城际间和跨洋等已有光缆中的冗余光纤资源，快速构建振动监测网络，改善振动监测能力. 目前基于散射光的振动传感，单台仪器可以实现沿光纤米级间隔、近百千米的密集分布式监测；而基于透射光的传感，尚缺乏分布式观测能力，但可检测上万千米长光纤上的强烈振动. 本文介绍这两类本征光纤振动传感相关的基本原理、应用实例和发展前景.Abstract: The intrinsic vibration sensing of optical fiber measures the dynamic strain (i.e., vibration) along with the fiber by repeatedly emitting detection lasers at one end of the fiber, receiving scattered or transmitted light at the same or another end, and demodulating its changes. The sensing system takes the fiber as sensors and has the advantages of being flexible and straightforward to build, and being easy to operate and maintain. It can be used in harsh environments with fluid, high temperature, high pressure, or strong electromagnetic interference. As a result, it can significantly expand the monitorable area while also achieving relatively low-cost and long-term continuous monitoring. Furthermore, many redundant fiber resources already present in fiber optic cables of cities, intercity, and across oceans around the world. Utilizing these fiber optic resources can be quickly converted to vibration monitoring networks, significantly improving vibration monitoring capabilities in these areas.Today, a single instrument can achieve intensive distributed monitoring along with the nearly 100 kilometers fiber with meter-level intervals based on vibration sensing of scattered light. At the same time, sensing based on transmission light lacks distributed observation capability but can detect strong vibration along optical fibers tens of thousands of kilometers long. This paper describes the fundamental principles, application scenarios and prospects of these two types of fiber-optic vibration sensing.
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图 1 光纤几种散射光的频率和强度分布示意图. T：温度；ε：应变
Figure 1. The diagram of frequency and intensity distributions of scattered lights in optical fiber. T: temperature; ε: strain
图 2 分布式光纤振动传感（DAS）系统示意图. 背向瑞利散射光能够测量光纤应变和温度的变化，振动是通过高频测量应变（或应变率）而获得. L0表示DAS的空间分辨率，是光脉冲在光纤内的光柱长度. 散射在光柱内是随机分布的；c是光纤光速，A和B为t1和t2两个时刻光柱所在位置；深红色和浅红色箭头分别指示透射光和背向散射光的传播方向
Figure 2. The diagram of the fiber-optic distributed acoustic sensing (DAS) system. The Rayleigh back-scattering lights can sense the changes of strain and temperature in fiber, and the vibration is obtained from high frequent strain (or strain rate) measurements. L0 is spatial resoltuion of DAS, which is the length of light plus in the fiber. The scattering is random distributed. c is light speed in fiber-optic; A and B are locations of fiber sections for light in the time of t1 and t2; the dark and light red arrows indicate the direction of transmitted light and back-scattering light respectively
图 3 （a）背向瑞利散射光信号的振幅—时间序列. （b）将时间序列按快慢轴重排后的二维时间序列. 红点和黑点分别对应光纤上的两个采样区段（修改自Masoudi and Newson, 2016）
Figure 3. (a) Amplitude-time series of the RBSs. (b) Rearranged the time series into 2D time series according to the fast and slow axis. The red dot and the black dot correspond to the two sampling sections on the fiber (modified from Masoudi and Newson, 2016)
图 4 P和S波DAS响应函数. （a）平面入射波以一定角度交汇于光纤；（b）P波和（c）S波的DAS响应函数. 其中标距L=10 m，VP=2 500 m/s，VS=1 560 m/s（修改自https://motionsignaltechnologies.com/what-is-das-and-what-is-it-measuring/）
Figure 4. DAS response functions for P and S waves. (a) Waves incident into optical fiber with angle; and the DAS responses for P wave (b) and S wave (c). Where gauge length L=10 m, VP=2 500 m/s, VP =1 560 m/s (modified from https://motionsignaltechnologies.com/what-is-das-and-what-is-it-measuring/)
图 5 水压致裂操作过程中监测井DAS记录到的低频响应（修改自Jin and Roy, 2017）
Figure 5. Low-frequency DAS response at an offset well during hydraulic-fracturing operation (modified from Jin and Roy, 2017)
图 6 日本四国岛Muroto光缆DAS实验. （a）50 km长光缆接收到的气枪信号（在光缆20.8km附近），其中小图显示地震（五角星）、OBS（三角）和光缆（红线）的相对位置；（b）气枪源附近DAS信号放大；（c）20.8 km处单道DAS气枪信号和频谱；（d）附近OBS接收的气枪信号和频谱；（e）DAS接收到的地震信号；（f）20.8 km处单道DAS地震信号和频谱（修改自Matsumoto et al., 2021）
Figure 6. The DAS experiments on "Muroto cable" in Shikoku Island, Japan. (a) The airgun (near the location of cable length at 20.8 km) signals received by the 50 km fiber cable section. The inset shows the locations of earthquakes (star), OBS (triangle) and cable (red line); (b) The enlarged signals near the source; (c) Airgun signal and its time-frequency spectra of single DAS channel at 20.8 km; (d) Airgun signal recorded by nearby OBS and its time-frequency spectra; (e) Signals from M1.7 earthquake nearby received the 50 km fiber cable section; (f) Earthquake signal and time-frequency spectra of single DAS channel at 20.8 km (modified from Matsumoto et al., 2021)
图 7 斯坦福大学DAS-2实验. （a） DAS光纤路线（黑线）分布图；（b）DAS记录的交通轨迹. 波形被0.1~1 Hz带通滤波以便突出车辆经过时高质量的路基变形响应. 每辆车辆均被编号（修改自Lindsey et al., 2020b）
Figure 7. Stanford DAS-2 experiment Array. (a) Map of optical fiber path used for DAS (black line); (b) Vehicle observations from Stanford DAS-2 experiment. Waveforms are bandpassed around 0.1~1 Hz to highlight the high-quality geodetic strain responses of the roadbed due to vehicle loading. Individual vehicles are numbered (modified from Lindsey et al., 2020b)
图 8 美国加州Monterey湾区的MARS DAS实验. （a）MW3.4 Gilory地震的DAS波形记录和预测的地震震相到时（不同颜色线条）. 海岸在距离为0处. （b）B区已知断裂波形的放大. （c）MARS光缆、已知断层和Gilroy地震分布图. DAS只有其中20 km光缆（粉色）. （d）叠加VS反演和反向散射Scholte 波偏移的综合结果. 背景灰度图显示自然偏移结果；正面彩色图像为VS结果；蓝色虚线代表Kirchof 偏移结果. 黑色虚线表示从自相关图像观察到的水平不连续性. 注意此图海岸在左边[（a~c）修改自Lindsey et al., 2019；（d）修改自Cheng et al., 2021]
Figure 8. MARS DAS experiment in Monterey Bay, CA. (a) Full array observation (0 indicates the shore) with predicted seismic phase arrivals (colored lines). (b) Inset shows scattering with recently mapped submarine fault locations (white arrows). (c) The map shows MARS cable (DAS, pink portion), mapped faults, Gilroy earthquake. (d) Integrated results using VS inversion and backscattered Scholte wave migration. The gray background image shows the natural migration result; the front color image shows the VS inversion profile; the blue dashed line represents the Kirchhoff migration result. The black dashed lines indicate the observed horizontal discontinuity from the autocorrelation image. The shore is at the left side of the figlet [ (a~c) modified from Lindsey et al., 2019; (d) modified from Cheng et al., 2021]
图 9 DAS系统（离震源1.75 km）的监测结果. （a）由垂向震源得到的转换函数（左边）和617道的时间变化（中间和右边）；（b）10月10日至11月4日615～650道的P波速度变化，以10月22日为零. （c）615～650道平均速度变化（黑色）和降雨量（蓝色）. Oct：十月；Nov：十一月（修改自Tsuji et al., 2021）
Figure 9. Monitoring results derived from the DAS system ~1.75 km from the source system. (a) Transfer functions at all receiver channels derived from vertical source motion (left) and temporal variation of channel 617 (middle and right). (b) Temporal variation of P-wave velocity for channels #615～#650 from 10 October to 4 November. The velocity change is defined by using the velocity on 22 October as zero. (c) The velocity change averaged from channel #615～#650 results (black), and the precipitation from rain events (blue) (modified from Tsuji et al., 2021)
图 10 光纤透射光的振动传感. （a）基于透射光偏振状态（SOP）的振动传感（修改自Zhan et al., 2021）. 输入端的SOP是稳定的，接收端会一直监视SOP，正常情况下输入和输出SOP关系是稳定的（A）. 但当光缆受到来自地震和海浪产生的振动和应力（B），输出端的SOP会出现异常（C），从中可以检测出地震或海浪. SOP通常被旋转到北极以便于分析. （b）基于透射光相位变化的振动传感（修改自Marra et al., 2018）. 稳定的1 Hz激光被注入光纤，并通过回路从另外一根光纤中返回，进行干涉相位测量
Figure 10. Principles of fiber sensing of transmitted lights. (a) Polarization-based on transmitted light sensing (modified from Zhan et al., 2021). The state of polarization (SOP) at the receiver is monitored routinely while the input SOP stays stable. The output SOP is generally robust, owing to relatively minimal perturbations along most of its path in the deep ocean (A). The SOP anomalies (C) produce by shaking or pressuring the cable are used to detect earthquakes or ocean waves (B). The SOPs are rotated to the north pole for analyzing (D). (b) Phase-based of transmitted light sensing (modified from Marra et al., 2018). Stable lasers are injected into one fiber, and then returned to sender from another fiber for Interferometric phase measurement
图 11 （a）地震预警的时间进程、不同台间距强振动到达时间和预警盲区. 假设P波和S波速度分布为5.8 km/s和3.4 km/s，tP 和 tS 分别是P波（蓝线）与S波（红线）的到达时间，tA是预警发出时间，介于tP 和 tS 之间. 虚竖线表示台间距，不同灰色区对应预警盲区，它和台间距与系统处理时间有关. 离震中台站越远，发出预警所需时间越长；此外，预警盲区内的振动和破坏往往比外围区域更大（修改自Tajima and Hayashida, 2018）. （b）由6C台站、DAS系统组成的断裂带光纤振动传感网络. 3C台站6C升级、沿断裂带铺设分布式传感光纤（黄线和红点）、数据传输光缆中冗余光纤转变为传感光纤，将对活断裂带形成密集监测网络（修改自http://www.seismo.ethz.ch/en/research-and-teaching/fields_of_research/earthquake-early-warning/）
Figure 11. (a) Diagram showing the time course of earthquake warnings, the arrival time of strong vibrations at different station spacing, and blind warnings areas. The blue line(tP) and red line(tS) are travel time curves for P- and S-waves, assuming 5.8 km/s for P-wave velocity and 3.4 km/s for S-wave velocity for the uppermost layer. tA is the warning alert time which is between tP and tS. Gray zones are the EEW shadow zones that failed to alert, and their sizes depend on the network station interval (Δx, vertical dash line) and system processing time. The further the site is from the epicenter, the longer the warning time is. On the other hand, the ground shaking is stronger and more damage may be caused in the gray zone than outside the zone (modified from Tajima and Hayashida, 2018). (b) Fiber vibrating sensing network composed of 6C stations and DAS systems. 6C stations updated from 3C stations, sensing fibers laid along the faults (yellow line and red dots) and sensing fibers converted from dark fiber in data transmission cables, will build a denser monitoring network for activate faults (modified from http://www.seismo.ethz.ch/en/research-and-teaching/fields_of_research/earthquake-early-warning/)
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[1] Ajo-Franklin J B, Dou S, Lindsey N J, et al. 2019. Distributed acoustic sensing using dark fiber for near-surface characterization and broadband seismic event detection[J]. Scientific Reports, 9(1): 1328. doi: 10.1038/s41598-018-36675-8 [2] Alajmi M S, Pevzner R, Alkhalifah T, et al. 2019. Trialling distributed acoustic sensing in a sand dune environment[J]. ASEG Extended Abstracts, 2019(1): 1–3. [3] Bakku S K. 2015. Fracture characterization from seismic measurements in a borehole[D]. Cambridge, Massachusetts: Massachusetts Institute of Technology. [4] Bakulin A, Silvestrov I, Pevzner R. 2020. Surface seismics with DAS: An emerging alternative to modern point-sensor acquisition[J]. The Leading Edge, Society of Exploration Geophysicists, 39(11): 808–818. [5] Bashilov I P, Volosov S G, Korolev S A, et al. 2018. A family of seismometers with capacitive transducers[J]. Seismic Instruments, 54(5): 543–550. doi: 10.3103/S0747923918050055 [6] Becker M W, Ciervo C, Cole M, et al. 2017. Fracture hydromechanical response measured by fiber optic distributed acoustic sensing at milliHertz frequencies[J]. Geophysical Research Letters, 44(14): 7295–7302. doi: 10.1002/2017GL073931 [7] Becker M W, Coleman T I. 2019. Distributed acoustic sensing of strain at Earth tide frequencies[J]. Sensors, 19(9): E1975. doi: 10.3390/s19091975 [8] Booth A D, Christoffersen P, Schoonman C, et al. 2020. Distributed acoustic sensing of seismic properties in a borehole drilled on a fast-flowing Greenlandic outlet glacier[J]. Geophysical Research Letters, 47(13): e2020GL088148. [9] Borodin I, Segal A. 2020. Real-time hydraulic fracture monitoring and wellbore characterization with distributed acoustic sensing of pumping noise[J]. The Leading Edge, 39(11): 785–792. doi: 10.1190/tle39110785.1 [10] Cedilnik G, Lees G, Schmidt P E, et al. 2019. Pushing the reach of fiber distributed acoustic sensing to 125 km without the use of amplification[J]. IEEE Sensors Letters, 3(3): 1–4. [11] 陈颙, 陈龙生, 于晟. 2003. 城市地球物理学发展展望[J]. 大地测量与地球动力学, 23(4): 1-4Chen Y, Chen L S, Yu S. 2003. Urban geophysics: A new discipline of Earth science[J]. Journal of Geodesy and geodynamics, 23 (4): 1-4(in Chinese). [12] Cheng F, Chi B, Lindsey N J, et al. 2021. Utilizing distributed acoustic sensing and ocean bottom fiber optic cables for submarine structural characterization[J]. Scientific Reports, 11(1): 5613. doi: 10.1038/s41598-021-84845-y [13] Cole S, Karrenbach M. 2019. Multi-well DAS observations for hydraulic fracture monitoring[C]. European Association of Geoscientists & Engineers, 2019(1): 1–4. [14] Daley T M, Freifeld B M, Ajo-Franklin J, et al. 2013. Field testing of fiber-optic distributed acoustic sensing (DAS) for subsurface seismic monitoring[J]. The Leading Edge, 32(6): 699–706. doi: 10.1190/tle32060699.1 [15] Dou S, Lindsey N, Wagner A M, et al. 2017. Distributed acoustic sensing for seismic monitoring of the near surface: A traffic-noise interferometry case study[J]. Scientific Reports, 7(1): 11620. doi: 10.1038/s41598-017-11986-4 [16] Fan X. 2018. Distributed Rayleigh Sensing[M]//Peng G-D. Handbook of Optical Fibers. Singapore: Springer, 1–50. [17] Fang G, Li Y E, Zhao Y, et al. 2020. Urban near-surface seismic monitoring using distributed acoustic sensing[J]. Geophysical Research Letters, 47(6): e2019GL086115. [18] Fernández-Ruiz M R, Soto M A, Williams E F, et al. 2020. Distributed acoustic sensing for seismic activity monitoring[J]. APL Photonics, 5(3): 030901. [19] Freifeld B M, Dou S, Ajo Franklin J B, et al. 2017. Using DAS for reflection seismology-lessons learned from three field studies[C]. AGU Fall Meeting Abstracts, 33. [20] Grandi S, Dean M, Tucker O. 2017. Efficient containment monitoring with distributed acoustic sensing: Feasibility studies for the former peterhead CCS Project[J]. Energy Procedia, 114: 3889–3904. doi: 10.1016/j.egypro.2017.03.1521 [21] Hartog A H, Payne D N. 1982. A fibre-optic temperature-distribution sensor[C]//IEE Colloquium on Optical Fibre Sensors, London, IEE, Digest 1982/60: 2/1–2/2 [22] Hartog A. 2000. Distributed fiber-optic sensors: Principles and applications[C]//Grattan K, Meggitt B T. Optical fiber sensor technology : Advanced applications-bragg gratings and distributed sensors. Springer US, 241–301. [23] Hartog A H. 2018. An Introduction to Distributed Optical Fibre Sensors[M]. CRC Press. [24] He H, Yan L, Qian H, et al. 2020. Enhanced range of the dynamic strain measurement in phase-sensitive OTDR with tunable sensitivity[J]. Optics Express, 28(1): 226. doi: 10.1364/OE.378257 [25] Hunziker J, Greenwood A, Minato S, et al. 2020. Bayesian full-waveform inversion of tube waves to estimate fracture aperture and compliance[J]. Solid Earth, 11(2): 657–668. doi: 10.5194/se-11-657-2020 [26] Ichikawa M, Uchida S, Katou M, et al. 2020. Case study of hydraulic fracture monitoring using multiwell integrated analysis based on low-frequency DAS data[J]. The Leading Edge, 39(11): 794–800. doi: 10.1190/tle39110794.1 [27] Ide S, Araki E, Matsumoto H. 2021. Very broadband strain-rate measurements along a submarine fiber-optic cable off Cape Muroto, Nankai subduction zone, Japan[J]. Earth, Planets and Space, 73(1): 63. [28] Isaenkov R, Pevzner R, Glubokovskikh S, et al. 2021. An automated system for continuous monitoring of CO2 geosequestration using multi-well offset VSP with permanent seismic sources and receivers: Stage 3 of the CO2CRC Otway Project[J]. International Journal of Greenhouse Gas Control, 108: 103317. doi: 10.1016/j.ijggc.2021.103317 [29] Jakkampudi S, Shen J, Li W, et al. 2020. Footstep detection in urban seismic data with a convolutional neural network[J]. The Leading Edge, 39(9): 654–660. doi: 10.1190/tle39090654.1 [30] Jin G, Roy B. 2017. Hydraulic-fracture geometry characterization using low-frequency DAS signal[J]. The Leading Edge, 36(12): 975–980. doi: 10.1190/tle36120975.1 [31] Jin G, Mendoza K, Roy B, et al. 2019. Machine learning-based fracture-hit detection algorithm using LFDAS signal[J]. The Leading Edge, 38(7): 520–524. [32] Jousset P, Reinsch T, Ryberg T, et al. 2018. Dynamic strain determination using fibre-optic cables allows imaging of seismological and structural features[J]. Nature Communications, 9(1): 2509. doi: 10.1038/s41467-018-04860-y [33] Jousset P. 2019. Illuminating Earth’s faults[J]. Science, 366(6469): 1076–1077. doi: 10.1126/science.aaz7750 [34] Karrenbach M, Cole S, Ridge A, et al. 2019. Fiber-optic distributed acoustic sensing of microseismicity, strain and temperature during hydraulic fracturing[J]. Geophysics, Society of Exploration Geophysicists, 84(1): D11–D23. [35] Lellouch A, Horne S, Meadows M A, et al. 2019a. DAS observations and modeling of perforation-induced guided waves in a shale reservoir[J]. The Leading Edge, 38(11): 858–864. [36] Lellouch A, Yuan S, Ellsworth W L, Biondi B. 2019b. Velocity-based earthquake detection using downhole distributed acoustic sensing—Examples from the San Andreas fault observatory at depth[J]. Bulletin of the Seismological Society of America, 109(6): 2491–2500. doi: 10.1785/0120190176 [37] Lellouch A, Yuan S, Spica Z, et al. 2019c. Seismic velocity estimation using passive downhole distributed acoustic sensing records: Examples from the San Andreas fault observatory at depth[J]. Journal of Geophysical Research: Solid Earth, 124(7): 6931–6948. doi: 10.1029/2019JB017533 [38] Lellouch A, Lindsey N J, Ellsworth W L, et al. 2020a. Comparison between distributed acoustic sensing and geophones: Downhole microseismic monitoring of the FORGE geothermal experiment[J]. Seismological Research Letters, 91(6): 3256–3268. doi: 10.1785/0220200149 [39] Lellouch A, Meadows M A, Nemeth T, et al. 2020b. Fracture properties estimation using distributed acoustic sensing recording of guided waves in unconventional reservoirs[J]. Geophysics, 85(5): M85–M95. doi: 10.1190/geo2019-0793.1 [40] Lellouch A, Biondi B L. 2021. Seismic applications of downhole DAS[J]. Sensors, 21(9): 2897. doi: 10.3390/s21092897 [41] Li Z, Shen Z, Yang Y, et al. 2021. Rapid response to the 2019 ridgecrest earthquake with distributed acoustic sensing[J]. AGU Advances, 2(2): e2021AV000395. [42] 林融冰, 曾祥方, 宋政宏, 等. 2020. 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[J]. 地球物理学报, 63(4): 1622–1629 doi: 10.6038/cjg2020N0272Lin R B, Zeng X F, Song Z H, et al. 2020. Distributed acoustic sensing for imaging shallow structureⅡ: Ambient noise tomography[J]. Chinese Journal of Geophysics, 63(4): 1622-1629(in Chinese). doi: 10.6038/cjg2020N0272 [43] Lindsey N J, Martin E R, Dreger D S, et al. 2017. Fiber-optic network observations of earthquake wavefields[J]. Geophysical Research Letters, 44(23): 11792-11799. [44] Lindsey N J, Dawe T C, Ajo-Franklin J B. 2019. Illuminating seafloor faults and ocean dynamics with dark fiber distributed acoustic sensing[J]. Science, 366(6469): 1103–1107. doi: 10.1126/science.aay5881 [45] Lindsey N J, Rademacher H, Ajo-Franklin J B. 2020a. On the broadband instrument response of fiber-optic DAS Arrays[J]. Journal of Geophysical Research: Solid Earth, 125(2): e2019JB018145. [46] Lindsey N J, Yuan S, Lellouch A, et al. 2020b. City-scale dark fiber DAS measurements of infrastructure use during the COVID-19 pandemic[J]. Geophysical Research Letters, 47(16): e2020GL089931. [47] Lindsey N J, Martin E R. 2021. Fiber-optic seismology[J]. Annual Review of Earth and Planetary Sciences, 49(1), 309–336. doi: 10.1146/annurev-earth-072420-065213 [48] Lior I, Sladen A, Rivet D, et al. 2021. On the detection capabilities of underwater distributed acoustic sensing[J]. Journal of Geophysical Research: Solid Earth, 126(3): e2020JB020925. [49] Luo B, Trainor-Guitton W, Bozdağ E, et al. 2020a. Horizontally orthogonal distributed acoustic sensing array for earthquake- and ambient-noise-based multichannel analysis of surface waves[J]. Geophysical Journal International, 222(3): 2147–2161. doi: 10.1093/gji/ggaa293 [50] Luo B, Jin G, Lellouch A. 2020b. Estimation of seismic velocity and layer thickness of Eagle Ford Formation using microseismic guided waves in downhole distributed acoustic sensing records[R]. SEG Technical Program Expanded Abstracts 2020, Society of Exploration Geophysicists, 535–539. [51] Marra G, Clivati C, Luckett R, et al. 2018. Ultrastable laser interferometry for earthquake detection with terrestrial and submarine cables[J]. Science, 361(6401): 486–490. [52] Martin E R, Castillo C M, Cole S, et al. 2017. Seismic monitoring leveraging existing telecom infrastructure at the SDASA: Active, passive, and ambient-noise analysis[J]. The Leading Edge, 36(12): 1025–1031. [53] Masoudi A, Newson T P. 2016. Contributed review: Distributed optical fibre dynamic strain sensing[J]. Review of Scientific Instruments, 87(1): 011501. doi: 10.1063/1.4939482 [54] Mateeva A, Lopez J, Potters H, et al. 2014. Distributed acoustic sensing for reservoir monitoring with vertical seismic profiling[J]. Geophysical Prospecting, 62: 679–692. doi: 10.1111/1365-2478.12116 [55] Mateeva A, Lopez J, Chalenski D, et al. 2017. 4D DAS VSP as a tool for frequent seismic monitoring in deep water[J]. The Leading Edge, 36(12): 995–1000. doi: 10.1190/tle36120995.1 [56] Matsumoto H, Araki E, Kimura T, et al. 2021. Detection of hydroacoustic signals on a fiber-optic submarine cable[J]. Scientific Reports, 11(1): 2797. doi: 10.1038/s41598-021-82093-8 [57] Molenaar M M, Hill D, Webster P, et al. 2012. First downhole application of distributed acoustic sensing for hydraulic-fracturing monitoring and diagnostics[J]. SPE Drilling & Completion, 27(1): 32–38. [58] Molteni D, Williams M J, Wilson C. 2017. Detecting microseismicity using distributed vibration[J]. First Break, 35, 51–55. [59] Nakata N, Nakata R, Xue Z. 2019. Estimation of scatterer locations and subsurface velocities using scattered tube waves observed during a crosswell survey[C]//SEG Technical Program Expanded Abstracts 2019. San Antonio, Texas: Society of Exploration Geophysicists, 869–874. [60] Ning I L C, Sava P. 2017. Multicomponent distributed acoustic sensing: concept and theory[J]. Geophysics, 82(2): 1–49. [61] Ning I L C, Sava P. 2018. High-resolution multi-component distributed acoustic sensing[J]. Geophysical Prospecting, 66(6): 1111–1122. doi: 10.1111/1365-2478.12634 [62] Nishimura T, Emoto K, Nakahara H, et al. 2021. Source location of volcanic earthquakes and subsurface characterization using fiber-optic cable and distributed acoustic sensing system[J]. Scientific Reports, 11(1): 6319. doi: 10.1038/s41598-021-85621-8 [63] Ourabah A, Crosby A. 2020. A 184 million traces per km2 seismic survey with nodes-acquisition and processing[C]//SEG Technical Program Expanded Abstracts 2020. Virtual: Society of Exploration Geophysicists, 41–45. [64] Pevzner R, Isaenkov R, Yavuz S, et al. 2021. Seismic monitoring of a small CO2 injection using a multi-well DAS array: Operations and initial results of Stage 3 of the CO2CRC Otway project[J]. International Journal of Greenhouse Gas Control, 110: 103437. doi: 10.1016/j.ijggc.2021.103437 [65] Poole A, Moldoveanu N, Sudhakar V, et al. 2020. "Faster-Denser-Better": Setting new standards for high-density seismic in Permian Basin[C]//SEG Technical Program Expanded Abstracts 2020. Virtual: Society of Exploration Geophysicists, 51–55. [66] Posey R, Johnson G A, Vohra S T. 2000. Strain sensing based on coherent Rayleigh scattering in an optical fibre[J]. Electronics Letters, 36(20): 1688–1689. doi: 10.1049/el:20001200 [67] Schumann H, Jin G. 2020. Inferring near-well conductivity from DAS-recorded tube waves generated by perforation shots[C]//SEG Technical Program Expanded Abstracts 2020. Society of Exploration Geophysicists, 455–459. [68] Shragge J, Yang J, Issa N, et al. 2021. Low-frequency ambient distributed acoustic sensing (DAS): Case study from Perth, Australia[J]. Geophysical Journal International, 226(1): 564–581. doi: 10.1093/gji/ggab111 [69] 宋政宏, 曾祥方, 徐善辉, 等. 2020. 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[J]. 地球物理学报, 63(2): 532–540 doi: 10.6038/cjg2020N0184Song Z H, Zeng X G, Xu S H, et al. 2020. Distributed acoustic sensing for imaging shallow structureⅠ: Active source survey[J]. Chinese Journal of Geophysics, 63(2): 532-540 (in Chinese). doi: 10.6038/cjg2020N0184 [70] Spica Z J, Perton M, Martin E R, et al. 2020. Urban seismic site characterization by fiber-optic seismology[J]. Journal of Geophysical Research: Solid Earth, 125(3): e2019JB018656. [71] Spikes K T, Tisato N, Hess T E, et al. 2019. Comparison of geophone and surface-deployed distributed acoustic sensing seismic data[J]. Geophysics, 84(2): A25–A29. doi: 10.1190/geo2018-0528.1 [72] Sukhovich A, Bonnieux S, Hello Y, et al. 2015. Seismic monitoring in the oceans by autonomous floats[J]. Nature Communications, 6(1): 8027. doi: 10.1038/ncomms9027 [73] Tajima F, Hayashida T. 2018. Earthquake early warning: what does “seconds before a strong hit” mean? [J]. Progress in Earth and Planetary Science, 5(1): 63. doi: 10.1186/s40645-018-0221-6 [74] Tsuji T, Ikeda T, Matsuura R, et al. 2021. Continuous monitoring system for safe managements of CO2 storage and geothermal reservoirs[J]. Scientific Reports, 11(1): 19120. doi: 10.1038/s41598-021-97881-5 [75] Trainor-Guitton W, Guitton A, Jreij S, et al. 2019. 3D Imaging of geothermalfaults from a vertical DAS fiber at Brady Hot Spring, NV USA[J]. Energies, 12(7): 1401. doi: 10.3390/en12071401 [76] Urosevic M, Bona A, Ziramov S, et al. 2018. Reflection seismic with DAS, why and where? [C]. European Association of Geoscientists & Engineers, 2018(1): 1–5. [77] van Putten L D, Masoudi A, Brambilla G. 2019. 100-km-sensing-range single-ended distributed vibration sensor based on remotely pumped Erbium-doped fiber amplifier[J]. Optics Letters, 44(24): 5925. doi: 10.1364/OL.44.005925 [78] Walter F, Gräff D, Lindner F, et al. 2020. Distributed acoustic sensing of microseismic sources and wave propagation in glaciated terrain[J]. Nature Communications, 11(1): 2436. doi: 10.1038/s41467-020-15824-6 [79] 王宝善, 曾祥方, 宋政宏, 等. 2021. 利用城市通信光缆进行地震观测和地下结构探测[J]. 科学通报, 66: 1–6 doi: 10.1016/j.scib.2020.10.007Wang B S, Zeng X F, Song Z H, et al. 2021. Seismic observation and subsurface imaging using an urban telecommunication optic-fiber cable[J]. Science Bulletin, 66: 1–6(in Chinese). doi: 10.1016/j.scib.2020.10.007 [80] Wang H F, Zeng X, Miller D E, et al. 2018. Ground motion response to an ML 4.3 earthquake using co-located distributed acoustic sensing and seismometer arrays[J]. Geophysical Journal International, 213(3): 2020–2036. doi: 10.1093/gji/ggy102 [81] 王伟君, 陈凌, 王一博, 彭菲. 2022. 光纤振动传感之一: 旋转测量技术及其地震学应用[J]. 地球与行星物理论评, 53（1）: 1-16.Wang W J, Chen L, Wang Y B, Peng F. 2022. Fiber-optic vibration sensing—I: Rotation measurement technique and its seismological applications[J]. Reviews of Geophysics and Planetary Physics, 53(1): 1-16 (in Chinese). [82] Wang X, Williams E F, Karrenbach M, et al. 2020. Rose parade seismology: Signatures of floats and bands on optical fiber[J]. Seismological Research Letters, 91(4): 2395–2398. doi: 10.1785/0220200091 [83] Wang X, Zhan Z, Williams E F, et al. 2021. Ground vibrations recorded by fiber-optic cables reveal traffic response to COVID-19 lockdown measures in Pasadena, California[J]. Communications Earth & Environment, 2(1): 160. [84] Webster P, Molenaar M, Perkins C. 2016. DAS Microseismic fiber-optic locating DAS microseismic events and errors[J]. CSEG Recorder, 38–39. [85] Westbrook P S, Feder K S, Kremp T, et al. 2020. Enhanced optical fiber for distributed acoustic sensing beyond the limits of Rayleigh backscattering[J]. iScience, 23(6): 101137. doi: 10.1016/j.isci.2020.101137 [86] Wu H, Feder K S, Stolov A A, et al. 2020. High-temperature enhanced Rayleigh scattering optical fiber sensor for borehole applications[C]//Optical Components and Materials XVII. International Society for Optics and Photonics, 11276: 112760Y. [87] 吴伟, 汪忠德, 杨瑞娟, 等. 2015. 地震采集技术发展动态与展望[J]. 石油科技论坛, 33(5): 36–43Wu W, Wang Z D, Yang R J, et al. 2015. Outlook of seismic acquisition technological development[J]. Petroleum Science and Technology Forum, 33(5): 36-43. [88] Xu P, Dong Y, Zhou D, et al. 2016. 1200°C high-temperature distributed optical fiber sensing using Brillouin optical time domain analysis[J]. Applied Optics, 55(21): 5471–5478. doi: 10.1364/AO.55.005471 [89] Yavuz S, Tertyshnikov K, Pevzner R, et al. 2021. Repeatability analysis of time-lapse vertical seismic profiling data acquired using distributed acoustic sensing: Harvey, South-West Hub[C]//European Association of Geoscientists & Engineers, 1-5. [90] Yu C, Zhan Z, Lindsey N J, et al. 2019. The potential of DAS in teleseismic studies: Insights from the goldstone experiment[J]. Geophysical Research Letters, 46(3): 1320–1328. doi: 10.1029/2018GL081195 [91] Yuan S, Lellouch A, Clapp R G, et al. 2020. Near-surface characterization using a roadside distributed acoustic sensing array[J]. The Leading Edge, 39(9): 646–653. [92] Zeng X, Lancelle C, Thurber C, et al. 2017. Properties of noise cross-correlation functions obtained from a distributed acoustic sensing array at Garner Valley, California[J]. Bulletin of the Seismological Society of America, 107(2): 603–610. doi: 10.1785/0120160168 [93] Zhan Z. 2020. Distributed acoustic sensing turns fiber-optic cables into sensitive seismic antennas[J]. Seismological Research Letters, 91(1): 1–15. doi: 10.1785/0220190112 [94] Zhan Z, Cantono M, Kamalov V, et al. 2021. Optical polarization–based seismic and water wave sensing on transoceanic cables[J]. Science, 371(6532): 931–936. doi: 10.1126/science.abe6648 [95] 张旭苹. 2013. 全分布式光纤传感技术[M]. 北京: 科学出版社.Zhang X P. 2013. Fully Distributed Optical Fiber Sensing Technology [M]. Beijing: Science Press (in Chinese). [96] Zhu T, Stensrud D J. 2019. Characterizing thunder-induced ground motions using fiber-optic distributed acoustic sensing array[J]. Journal of Geophysical Research: Atmospheres, 124(23): 12810–12823. doi: 10.1029/2019JD031453 [97] Zhu T, Shen J, Martin E R. 2021. Sensing Earth and environment dynamics by telecommunication fiber-optic sensors: An urban experiment in Pennsylvania, USA[J]. Solid Earth, 12(1): 219–235. doi: 10.5194/se-12-219-2021 -
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