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分布式声传感井中地震信号检测数值模拟方法

马国旗1,2 曹丹平1,2 尹教建3 朱兆林1,2

(1.中国石油大学(华东)地球科学与技术学院, 山东青岛 266580)
(2.海洋国家实验室海洋矿产资源评价与探测技术功能实验室, 山东青岛 266071)
(3.中国石油大学(华东)理学院, 山东青岛 266580)

【摘要】分布式声传感(DAS)基于光纤中瑞利散射效应获取地震波振动信号,光纤在探测地震波的同时实现信号的传输,适用于井中地震信号采集,具有成本低、分辨率高、抗电磁干扰强等优点。基于离散光纤瑞利散射干涉模型,在不考虑背景压力、温度和井壁光纤耦合的条件下,采用数值模拟方法模拟了井中DAS系统地震信号特征,详细探讨了震源强度、脉冲宽度以及光纤空间采样间隔对DAS光纤信号波形特征以及信噪比的影响。模拟结果表明:①不同震源强度对DAS光纤信号的影响不同,而且震源强度过大可能导致DAS光纤信号波形畸变或旁瓣增多而影响信号保真度。②较小的脉冲宽度常伴有较强的噪声,较大的脉冲宽度在一定程度上可以压制高频噪声、提高信噪比,但不可避免地降低分辨率。③通过相邻道叠加增大的光纤空间采样间隔有利于提高信噪比,因此选择合适的光纤空间采样间隔可以有效地提高信噪比、提升信号质量; DAS信号频率通常略高于原始地震信号频率,同时附带系统本身的高频噪声。

【关键词】 分布式声传感;瑞利散射;震源强度;脉冲宽度;光纤空间采样间隔;数值模拟;

【DOI】

Numerical simulation of detecting seismic signals in DAS wells

MA Guoqi1,2 CAO Danping1,2 YIN Jiaojian3 ZHU Zhaolin1,2

(1.School of Geosciences, China University of Petroleum (East China), Qingdao, Shandong Province, China 266580)
(2.Functional Laboratory for Marine Mineral Resources Assessment and Prospecting, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong Province, China 266071)
(3.College of Science, China University of Petroleum (East China), Qingdao, Shandong Province, China 266580)

【Abstract】Owing to the Rayleigh scattering, distributed acoustic sensing (DAS) could detect seismic vibrations in optical fibers, which meanwhile also functions as the carrier for signal transmission. Thus, this system is suitable for borehole seismic acquisition with low cost, high resolution, and high performance of anti-electromagnetic interference. Based on the discrete Rayleigh scattering interference model, we use numerical simulation to model borehole seismic signals in the DAS system; we also discuss the impacts of source strength, pulse width, and spatial fiber sampling interval on the waveform and signal to noise ratio of DAS signals. In this process, we do not consider the influence of ambient pressure, temperature, and borehole wallfiber coupling. The results show that (1) DAS signals vary with source strength. A strong source may cause waveform distortion or increased side lobes; this may lead to signal distortion. (2) Small pulse width is usually associated with strong noises. In contrast, large pulse width may facilitate high-frequency noise suppression and improve signal to noise ratio; but the resolution will be inevitably sacrificed to some extent; (3) increased fiber sampling interval by multi-trace stacking may be useful to the improvement of signal to noise ratio. Thus, we may choose a proper sampling interval to improve signal to noise ratio and signal quality. DAS signals usually exhibit slightly higher frequencies than the original seismic signals; there are also inherent high-frequency noises.

【Keywords】 distributed acoustic sensing; Rayleigh scattering; source strength; pulse width; spatial fiber sampling interval; numerical simulation;

【DOI】

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    References

    [1] Mateeva A, Lopez J, Potters H, et al. Distributed acoustic sensing for reservoir monitoring with vertical seismic profiling [J]. Geophysical Prospecting, 2014, 62 (4): 679–692.

    [2] Spikes K T, Tisato N, Hess T E, et al. Comparison of geophone and surface-deployed distributed acoustic sensing seismic data [J]. Geophysics, 2019, 84 (2): A25–A29.

    [3] Mestayer J, Cox B, Wills P, et al. Field trials of distributed acoustic sensing for geophysical monitoring [C]. SEG Technical Program Expanded Abstracts, 2011, 30, doi: 10.1190/1.3628095.

    [4] Parker T R, Shatalin S V, Farhadiroushan M, et al. Distributed acoustic sensing: recent field data and performance validation [C]. Second EAGE Workshop on Permanent Reservoir Monitoring 2013-Current and Future Trends, Stavanger, Norway, 2013, doi: 10.3997/2214-4609.20131303.

    [5] Parker T, Shatalin S, Farhadiroushan M. Distributed acoustic sensing-a new tool for seismic applications [J]. First Break, 2014, doi: 10.3997/1365-2397.2013034.

    [6] Miller D, Parker T, Kashikar S, et al. Vertical seismic profiling using a fibre-optic cable as a distributed acoustic sensor [C]. Extended Abstracts of 74th EAGE Conference & Exhibition, 2012, doi: 10.3997/2214-4609.20148799.

    [7] Madsen K N, Thompson M, Parker T, et al. A VSP field trial using distributed acoustic sensing in a producing well in the North Sea [J]. First Break, 2013, doi: 10.3997/1365-2397.2013027.

    [8] Mateeva A, Mestayer J, Yang Z, et al. Dual-well 3D VSP in deepwater made possible by DAS [C]. SEG Technical Program Expanded Abstracts, 2013, 32, doi: 10.1190/segam2013-0667.1.

    [9] Cox B E, Lehner R, Webster P, et al. Keynote presentation: microseismic data integration: how connecting the dots can help solve the unconventionals puzzle [C]. Fifth EAGE Passive Seismic Workshop, 2014, doi: 10.3997/2214-4609.20142154.

    [10] Molenaar M M, Hill D, Webster P, et al. First downhole application of distributed acoustic sensing for hydraulic-fracturing monitoring and diagnostics[J]. SPE Drilling & Completion, 2012, 27 (1): 32–38.

    [11] Bakku S K, Fehler M, Wills P, et al. Vertical seismic profiling using distributed acoustic sensing in a hydrofrac treatment well [C]. SEG Technical Program Expanded Abstracts, 2014, 33, doi: 10.1190/segam2014-1559. 1.

    [12] Barberan C, Allanic C, Avila D, et al. Multi-offset seismic acquisition using optical fiber behind tubing [C]. Extended Abstracts of 76th EAGE Conference & Exhibition, 2014, doi: 10. 3997/2214-4609. 20148798.

    [13] Harris K, White D, Melanson D, et al. Feasibility of time-lapse VSP monitoring at the Aquistore CO2 storage site using a distributed acoustic sensing system [J]. International Journal of Greenhouse Gas Control, 2016, 50 (4): 248–260.

    [14] Correa J, Pevzner R, Popik S, et al. Application of 3D VSP acquired with DAS and 3C geophones for site characterization and monitoring program design: preliminary results from stage 3 of the CO2CRC Otway project [C]. SEG Technical Program Expanded Abstracts, 2018, 37, doi: 10. 1190/segam2018-2996035.1.

    [15] Hornman K, Kuvshinov B, Zwartjes P, et al. Field trial of a broadside-sensitive distributed acoustic sensing cable for surface seismic [C]. Extended Abstracts of 75th EAGE Conference & Exhibition, 2013, doi: 10. 3997/2214-4609.20130383.

    [16] Kuvshinov B N. Interaction of helically wound fibre-optic cables with plane seismic waves [J]. Geophysical Prospecting, 2016, 64 (3): 671–688.

    [17] Hornman J C. Field trial of seismic recording using distributed acoustic sensing with broadside sensitive fibre-optic cables [J]. Geophysical Prospecting, 2017, 65 (1): 35–46.

    [18] Wang H, Fratta D, Lord N, et al. Distributed acoustic sensing (DAS) field trials for near-surface geotechnical properties, earthquake seismology and mine monitoring [C]. SEG Technical Program Expanded Abstracts, 2018, 37: 4953–4957.

    [19] Yu G, Chen Y Z, Wu J, et al. 3D-VSP survey using a DAS system and downhole geophone array in southwest China [C]. Extended Abstracts of 81st EAGE Conference & Exhibition, 2019.

    [20] Yu G, Sun Q, Ai F, et al. Microstructured fiber distributed acoustic sensing system for borehole seismic survey [C]. SEG Technical Program Expanded Abstracts, 2018, 37: 4669–4673.

    [21] Sun Z, Liu X, Zhang F, et al. High sensitivity fiber laser geophone array and field test analysis [J]. Measurement, 2015, doi: 10.1016/j. measurement. 2015. 09. 043.

    [22] Shang Y, Yang Y, Wang C, et al. Optical fiber distributed acoustic sensing based on the self-interference of Rayleigh backscattering [J]. Measurement, 2016, doi: 10. 1016/j. measurement. 2015. 09. 042.

    [23] Wang J, Hu B, Li W, et al. Design and application of fiber Bragg grating (FBG) geophone for higher sensitivity and wider frequency range [J]. Measurement, 2016, doi: 10.1016/j. measurement.2015.09.041.

    [24] Xu T W, Fang G S, Yue J, et al. Distributed acoustic sensing: system and experiments [C]. 2017 Opto-electronics & Communications Conference, 2017, doi: 10.1109/OECC.2017.8114770.

    [25] Wang Z Y, Li L C, Zheng H R, et al. Smart distributed acoustics/vibration sensing with dual path network [C]. 26th International Conference on Optical Fiber Sensors, Lausanne, 2018, doi: 10.1364/OFS.2018.WF105.

    [26] Liang J J, Wang Z Y, Lyu Bin, et al. Distributed acoustic sensing for 2D and 3D acoustic source localization[J]. Optics Letters, 2019, 44 (7): 1690–1693.

    [27] Mateeva A, Mestayer J, Cox B, et al. Advances in distributed acoustic sensing (DAS) for VSP [C]. SEG Technical Program Expanded Abstracts, 2012, 31, doi: 10.1190/segam2012-0739.1.

    [28] Li M, Wang H, Tao G. Current and future applications of distributed acoustic sensing as a new reservoir geophysics tool [J]. The Open Petroleum Engineering Journal, 2015, 8 (1): 272–281.

    [29] Butter C D, Hocker G B. Fiber optics strain gauge [J]. Applied Optics, 1978, 17 (18): 2867–2869.

    [30] Masoudi A, Newson T P. Analysis of distributed optical fiber acoustic sensors through numerical modeling [J]. Optics Express, 2017, 25 (25): 32021–32040.

    [31] PENG Fei. Phase-Sensitive Optical Time Domain Reflectometry & Applications [D]. University of Electronic Science and Technology of China, Chengdu, Sichuan, 2015 (in Chinese).

    [32] YU Miao. Research and Application of Phase-Sensitive Optical Time-Domain Reflectometric System Based on Single-source Dual Heterodyne Detection Scheme [D]. Jilin University, Changchun, Jilin, 2017 (in Chinese).

    [33] WANG Youzhao, HUANG Jing. Optical Fiber Sensing Technology [M]. Xidian University Press, Xi'an, Shaanxi, 2015 (in Chinese).

    [34] Park J, Lee W, Taylor H F. Fiber optic intrusion sensor with the configuration of an optical time-domain reflectometer using coherent interference of Rayleigh backscattering [J]. Proceedings of SPIE, 1998, 3555 (1): 49–56.

    [35] Park J, Taylor H F. Fiber optic intrusion sensor using coherent optical time domain reflectometer [J]. Japanese Journal of Applied Physics, 2003, 42 (6): 3481–3482.

    [36] Chen L, Zhu T, Bao X Y, et al. Distributed vibration sensor based on coherent detection of phase-OTDR [J]. Journal of Lightwave Technology, 2010, 28 (22): 3243–3249.

    [37] Liokumovich L B, Ushakov N A,Kotov O I, et al. Fundamentals of optical fiber sensing schemes based on coherent optical time domain reflectometry: signal model under static fiber conditions [J]. Journal of Lightwave Technology, 2015, 33 (17): 3660–3671.

    [38] Howard R M. Statistics of coherently detected backscatter and range performance of coherent OTDRs [J]. Optical and Quantum Electronics, 1987, 19 (3): 145–168.

    [39] Bao X Y, Zhou D P, Baker C, et al. Recent development in the distributed fiber optic acoustic and ultrasonic detection [J]. Journal of Lightwave Technology, 2017, 35 (16): 3256–3267.

    [40] Martin E R. Passive Imaging and Characterization of the Subsurface with Distributed Acoustic Sensing [D]. Department of Computinal and Mathematical Engineering, Standford University, California, 2018.

    [41] Daley T M, Miller D E, Dodds K, et al. Field testing of modular borehole monitoring with simultaneous distributed acoustic sensing and geophone vertical seismic profiles at Citronelle, Alabama [J]. Geophysical Prospecting, 2015, 64 (5): 1318–1334.

This Article

ISSN:1000-7210

CN: 13-1095/TE

Vol 55, No. 02, Pages 311-320+229-230

April 2020

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Article Outline

Abstract

  • 0 Introduction
  • 1 Methodology
  • 2 Numerical simulation and analysis of borehole seismic DAS signal
  • 3 Conclusions
  • References