Novel Optical Sensors based on Nonlinear Effects in Few-mode Fibers

Size: px

Start display at page:

Download "Novel Optical Sensors based on Nonlinear Effects in Few-mode Fibers"

Christopher Floyd
6 years ago
Views:

1 Novel Optical Sensors based on Nonlinear Effects in Few-mode Fibers Zhongqi Pan; Yi Weng Dept. of Electrical and Computer Engineering, University of Louisiana at Lafayette, Lafayette, LA OSA Technical Group Webinar Monday, February 1st, 2016 Time: 11:00 AM Eastern (10:00 AM Central)

2 Outline 1. Introduction 1.1 Capacity Crunch & Space Division Multiplexing (SDM) Systems 1.2 Nonlinear Effects in Few-mode Fibers (FMF) 1.3 Different Scattering Mechanism for Sensors 2. Key Components of SDM Technique 2.1. Spatial Light Modulators 2.2. Mode Multiplexers 2.3. Detection Methods 2.4. Multi-input Multi-output (MIMO) Schemes 2.5. Performance Limitations 3. Spatial-Division Multiplexing based Fiber-Optic Sensors 3.1. Distributed sensors based on mode-division multiplexing (MDM) 3.2. Distributed sensors based on core multiplexing 3.3. Fiber Bragg grating (FBG) sensors based on core multiplexing 4. Prospective Outlook 4.1. Fiber Deployment 4.2. Big Data Analytics 4.3. New Opportunities Page 2

3 Capacity Crunch Fueled by emerging bandwidth-hungry applications, such as: Cloud Computing Internet of Things High-definition Video Streaming Online Gaming Dynamic Allocation Network Virtualization Programmable Control Flow Prioritization Mobile Networking Multimedia File Sharing Followed by Moore s Law And Other Information Technologies The internet traffic is growing exponentially; The trend is expected to continue in the future. Page 3

multiplexing (SDM) has emerged as a promising technology to overcome

4 Space Division Multiplexing (SDM) In order to keep up with the future of Internet bandwidth requirements, Space-division multiplexing (SDM) has emerged as a promising technology to overcome the next capacity crunch. D. J. Richardson, Nature Photonics 7, (2013). Page 4

Space Division Multiplexing (SDM) SDM is including Mode-division Multiplexing using few-mode fiber and Core Multiplexing using multicore fiber.

5 Space Division Multiplexing (SDM) SDM is including Mode-division Multiplexing using few-mode fiber and Core Multiplexing using multicore fiber. Multicore fiber (MCF): a fiber with many cores to pass through. Few-mode fiber (FMF): a single-core large-area fiber that allows several spatial modes to travel inside; J. Fini, Optics Express 18, (2010). R. Ryf, ECOC PDP Th.13.C.1 (2011). L. Gruner Nielsen, OFC PDP5A (2012). M. Salsi, OFC PDPB9 (2011). Page 5

6 Outline 1. Introduction 1.1 Capacity Crunch & Space Division Multiplexing (SDM) Systems 1.2 Nonlinear Effects in Few-mode Fibers (FMF) 1.3 Different Scattering Mechanism for Sensors 2. Key Components of SDM Technique 2.1. Spatial Light Modulators 2.2. Mode Multiplexers 2.3. Detection Methods 2.4. Multi-input Multi-output (MIMO) Schemes 2.5. Performance Limitations 3. Spatial-Division Multiplexing based Fiber-Optic Sensors 3.1. Distributed sensors based on mode-division multiplexing (MDM) 3.2. Distributed sensors based on core multiplexing 3.3. Fiber Bragg grating (FBG) sensors based on core multiplexing 4. Prospective Outlook 4.1. Fiber Deployment 4.2. Big Data Analytics 4.3. New Opportunities Page 6

Issue: Fiber Nonlinearity in FMF Nonlinear effects in MDM systems have recently gain great interest. Nonlinearities between MDM channels can lead to performance degradation.

7 Issue: Fiber Nonlinearity in FMF Nonlinear effects in MDM systems have recently gain great interest. Nonlinearities between MDM channels can lead to performance degradation. The ultimate limitation of MDM systems is determined by nonlinearities. Meanwhile, they also show attractive features that SMFs do not possess. Z. Pan et al., ICOCN 2014, S42.1 (2014). G. Rademacher et al., PTL 24 (21), 1929 (2012). R.-J. Essiambre, Nonlinear Optics, NTu2A.3 (2015). Page 7

8 Origin of Dispersion and Nonlinearities The effective refractive index of the fiber depends upon the frequency, modes (including different states of polarizations), and the power of the signal. n(, Mode (Pol.), P) Dispersion Effects (1) Chromatic (CD) (2) Polarization (PMD) (3) Intermodal (DMGD) Nonlinearities (1) Self-phase Modulation (SPM) (2) Cross-phase Modulation (XPM) (3) Four-wave Mixing (FWM) (4) Stimulated scattering Page 8

Kerr-effects & Four-wave Mixing (FWM) The most common nonlinear effect in optical fibers is the Kerr effect, also called the quadratic electro-optic effect,

9 Kerr-effects & Four-wave Mixing (FWM) The most common nonlinear effect in optical fibers is the Kerr effect, also called the quadratic electro-optic effect, including: Page 9 Self-phase modulation (SPM) Cross-phase modulation (XPM) Four-wave mixing (FWM) G. P. Agrawal, Nonlinear Fiber Optics, 4th ed. Academic Press (2007).

Example: Intermodal Four-wave Mixing (IM-FWM) ZDW: zero-dispersion wavelength CD: chromatic dispersion GVD: group velocity delay PMC: phase matching condition OSP: Optical Signal Processing In SMF,

10 Example: Intermodal Four-wave Mixing (IM-FWM) ZDW: zero-dispersion wavelength CD: chromatic dispersion GVD: group velocity delay PMC: phase matching condition OSP: Optical Signal Processing In SMF, it is required that the pump wavelength coincides with ZDW. In FMF, IM-FWM can be fully phase matched in the presence of large CD. PMCs depend on the intermodal dispersion and fiber birefringence. By carefully balancing GVD in FMFs, IM-FWM can be controlled for OSP. Z. Pan et al., ICOCN 2014, S42.1 (2014). Y. Weng et al., SPPCOM 2014, SW2C.2, (2014). Y. Weng et al., Opt. Commun. 348, 7-12 (2015). Page 10

11 Outline 1. Introduction 1.1 Capacity Crunch & Space Division Multiplexing (SDM) Systems 1.2 Nonlinear Effects in Few-mode Fibers (FMF) 1.3 Different Scattering Mechanism for Sensors 2. Key Components of SDM Technique 2.1. Spatial Light Modulators 2.2. Mode Multiplexers 2.3. Detection Methods 2.4. Multi-input Multi-output (MIMO) Schemes 2.5. Performance Limitations 3. Spatial-Division Multiplexing based Fiber-Optic Sensors 3.1. Distributed sensors based on mode-division multiplexing (MDM) 3.2. Distributed sensors based on core multiplexing 3.3. Fiber Bragg grating (FBG) sensors based on core multiplexing 4. Prospective Outlook 4.1. Fiber Deployment 4.2. Big Data Analytics 4.3. New Opportunities Page 11

12 DTS: Distributed Temperature Sensing Distributed Temperature Sensing (DTS) There are a number of distributed fiber sensing techniques that rely on different nonlinear scattering mechanisms. O. Hoes, Water Research 43, (2009). Page 12

13 DTS: Distributed Temperature Sensing Mechanism: Raman scattering The interaction with molecular vibrations in the fiber Frequency: Stokes and Anti-Stokes shifts Pros: Can measure absolute value of temperature. Simple configuration, earliest approach. Cons: It can only measure temperature, insensitive to strain or pressure. Intensity much lower than Brillouin/Rayleigh, so it needs higher power source and averaging for many seconds or even minutes to get reasonable results. Only suitable for measuring slowly varying temperatures, thus might not be completely suitable for monitoring oil/gas drilling. Page 13

14 DAS: Distributed Acoustic Sensing Mestayer, SEG 30, 4253 (2011). Page 14

15 Mechanism: Rayleigh scattering Small variations in the refractive index of the fiber. Frequency: Pros: DAS: Distributed Acoustic Sensing Same frequency as the transmitted light Highest intensity, so easy to detect at the same frequency. Very sensitive to strain, temperature and other variations. Cons: Lack of processing platform to interpret large quantities of acoustic data into understandable information. Cannot standalone, supported by other diagnostic tools i.e. DTS/DTSS, micro-seismic, etc. Only able to detect changes in temperature or strain rather than absolute values. Page 15

16 DTSS: Distributed Temperature & Strain Sensing Distributed Temperature & Strain Sensing (DTSS) X. Bao, Sensors 11, (2011). Page 16

17 DTSS: Distributed Temperature & Strain Sensing Mechanism: Brillouin scattering The interaction between the light and acoustic phonons travelling in the fiber. Frequency: Pros: Stokes and Anti-Stokes shifts Can measure absolute value of both temperature and strain. Suitable for a variety of applications, such as Oil/LNG pipeline monitoring. Cons: Intensity weaker than Rayleigh, so it needs to average a number of pulses with heterodyne detection to reduce noise. Challenging to discriminate between the effects caused by the temperature or strain. Page 17

18 Outline 1. Introduction 1.1 Capacity Crunch & Space Division Multiplexing (SDM) Systems 1.2 Nonlinear Effects in Few-mode Fibers (FMF) 1.3 Different Scattering Mechanism for Sensors 2. Key Components of SDM Technique 2.1. Spatial Light Modulators 2.2. Mode Multiplexers 2.3. Detection Methods 2.4. Multi-input Multi-output (MIMO) Schemes 2.5. Performance Limitations 3. Spatial-Division Multiplexing based Fiber-Optic Sensors 3.1. Distributed sensors based on mode-division multiplexing (MDM) 3.2. Distributed sensors based on core multiplexing 3.3. Fiber Bragg grating (FBG) sensors based on core multiplexing 4. Prospective Outlook 4.1. Fiber Deployment 4.2. Big Data Analytics 4.3. New Opportunities Page 18

Spatial Light Modulators A spatial light modulator (SLM) is a device that imposes some form of spatially varying modulation upon a beam of light.

19 Spatial Light Modulators A spatial light modulator (SLM) is a device that imposes some form of spatially varying modulation upon a beam of light. An SLM can modulate both the intensity and the phase of the beam simultaneously. The spiral beam parameters can be changed dynamically. Page 19 E. Ip, Th.13.C, 2011 ECOC. M. Salsi, Th.3.A.6, 2012 ECOC C. Koebele, PTL, Vol. 23, No. 18, 2011 K.-P. Ho, Optics Express 19(17), 2012

Mode Multiplexers The multiplexing/demultiplexing of spatial modes is crucial for SDM systems. The mode combination/separation can be achieved through mode-selective evanescent coupling.

20 Mode Multiplexers The multiplexing/demultiplexing of spatial modes is crucial for SDM systems. The mode combination/separation can be achieved through mode-selective evanescent coupling. So far the low-loss photonic lanterns are considered the best mode multiplexers. Page 20 R. Ryf, OFC 2014, W4J.2 M. Salsi, Th.3.A.6, 2012 ECOC H. Bulow, OECC 2012, (2012). N. Riesen, PTL 25, (2013).

Detection Methods Page 21 In coherent detection, decoder complexity depends mainly on the total data rate, so decoder can be implemented jointly to reduce complexity.

21 Detection Methods Page 21 In coherent detection, decoder complexity depends mainly on the total data rate, so decoder can be implemented jointly to reduce complexity. Coefficient adaptation can be achieved with LMS algorithm and data-aided training, and joint carrier recovery can be used in spatial superchannels. S. Randel et al., Opt. Express (2011). M. Feuer et al., PTL (2012).

22 MIMO Frequency-domain Equalization (FDE) Key difference to spectral superchannel architecture is the use of MIMO. To equalize for mode coupling, mitigate nonlinear effects and enable denser constellations, the adaptive multi-input multi-output (MIMO) FDE has been proposed and demonstrated, to de-multiplex the signals subject to multimode interference in optical transport networks. E. Ip, ECOC Th.1.C.2 (2013). E. Ip, OFC Th4A.5 (2014). Page 22

23 Approach: Ultrafast Optical Signal Processing (OSP) Various nonlinear interactions can be utilized for Ultrafast OSP. Nonlinear interactions can mix amplitudes, phases, frequencies, polarizations and modes. OSP Functions: Wavelength Conversion Mux/Demux Equalization FFT/DFT D/A and A/D Converter Mode Conversion Advantages over Electronics: High-speed Processing Encoding in Multiple Domains No Need for O-E-O Conversion Benefit to Optical Networks: Buffering & Routing Multiplexing & Synchronization P. J. Winzer, Opt. Express 19 (17), (2011). A. E. Willner et al., J. Lightw. Technol. 32(4), (2013). S. O. Arık, et al., Proc. of SPIE Vol. 9388, (2015). Page 23

24 Performance Limitations for SDM Systems The MIMO-SDM technique might be increasingly difficult to proceed beyond four mode groups, due to imperfections in the laydown process. Scaling to more modes is challenging, but would be assisted by designing novel low-loss SLMs and Mode Multiplexers with a smaller ratio of cladding to core diameter. Services Srvc 1 Srvc 2 Srvc 3 Central Nodes C[1] C[2] C[3] E E E O O O R[1] O E BS R[2] O Page 24 E R[3] R[4] O O E E Srvc N s C[m] Electrical Switch E O optical switch + fiber Central office R[n-1] O E BS R[n] O E BS Remote Nodes

25 Outline 1. Introduction 1.1 Capacity Crunch & Space Division Multiplexing (SDM) Systems 1.2 Nonlinear Effects in Few-mode Fibers (FMF) 1.3 Different Scattering Mechanism for Sensors 2. Key Components of SDM Technique 2.1. Spatial Light Modulators 2.2. Mode Multiplexers 2.3. Detection Methods 2.4. Multi-input Multi-output (MIMO) Schemes 2.5. Performance Limitations 3. Spatial-Division Multiplexing based Fiber-Optic Sensors 3.1. Distributed sensors based on mode-division multiplexing (MDM) 3.2. Distributed sensors based on core multiplexing 3.3. Fiber Bragg grating (FBG) sensors based on core multiplexing 4. Prospective Outlook 4.1. Fiber Deployment 4.2. Big Data Analytics 4.3. New Opportunities Page 25

Point Sensor such as Fiber Bragg Gratings Distributed Sensor such as Brillouin optical time-domain

26 Distributed Fiber-Optic Sensors There are two different types of optical fiber sensors. One distributed sensing system can replace thousands of point sensors! Point Sensor such as Fiber Bragg Gratings Distributed Sensor such as Brillouin optical time-domain reflectometer Oil & Gas Pipeline Monitoring Fire & Earthquake Disaster Alerts vs. Dam, Bridge & Building Health Review Damage Detection in Concrete Structures Page 26

27 Examples of Explosive / Accidents Mitsubishi Chemical Explosion China Qingdao Oil Pipeline Explosion Taiwan Gas Pipe Explosion Manhattan East Harlem Explosion Page 27

Summary: Back-scattering mechanism in FMF There are a number of distributed fiber sensing techniques that rely on different back-scattering mechanisms.

28 Summary: Back-scattering mechanism in FMF There are a number of distributed fiber sensing techniques that rely on different back-scattering mechanisms. DTS is based on Raman scattering using intensity change ratio for temperature measurement. DTSS is based on Brillouin scattering using frequency shift for strain and temperature measurement. DAS is based on Rayleigh scattering using local phase change for acoustic wave and vibration measurement. Each mechanism has its pros and cons. Raman is only related to temperature. Rayleigh has no Stokes & anti-stokes waves. Distributed temperature & strain sensing (DTSS) Distributed acoustic sensing (DAS) Distributed temperature sensing (DTS) X. Bao, Sensors 11, (2011). O. Hoes, Water Research 43, (2009). Mestayer, SEG 30, 4253 (2011). Page 28

29 Simultaneous Temperature & Strain Monitoring How to separate temperature and strain effects? Rely on Brillouin frequency shift (BFS) BFS proportional to both temperature and strain Hard to separate two effects by only measuring one BFS Related Previous Work: SMF: plus the Brillouin power measurement o Poor spatial resolution o Imprecise power measurement LEAF: multiple BFS in single core o Poor spatial resolution o Limited sensing accuracy Raman + Brillouin: using two systems o Additional noise o Extra cost and complexity Page 29 T. R. Parker et al, Optics Letters 22, (1997). Y. Sakairi et al, Proc. SPIE 4920, (2002). G. Bolognini et al, PTL 21, (2009).

30 Few-mode Brillouin Sensors BDGs and BOTDA using stimulated Brillouin scattering in FMFs have been proposed for sensing purposes. S. Li et al., Opt. Lett. 37(22), (2012). K. Y. Song et al., Opt. Lett. 38(22), (2013). Page 30

If part of the FUT cracks, the measurement can no longer be performed, which could lead to pipeline leakage and explosion. Pros: S. Li et al.

31 Challenges for Few-mode Brillouin Sensors This might cause a big issue for geotechnical and petroleum applications, such as the automated monitoring of oil or gas pipelines. If part of the FUT cracks, the measurement can no longer be performed, which could lead to pipeline leakage and explosion. Pros: S. Li et al., Opt. Lett. 37(22), (2012). A. Li et al., Opt. Lett. 39(11), (2014). Good Sensing Performance Multi-parameter Discriminative Capability Cons: Two light-waves Must be injected into Both Ends of the FMF Complicated Setup High Cost Page 31

32 Distributed Fiber-optic Sensors We have purposed a single-end FMF-based distributed sensing system that allows simultaneous temperature and strain measurement by Brillouin optical time-domain reflectometry (BOTDR) and heterodyne detection. Z. Pan et al., Photonic Netw Commun. (2015). Y. Weng et al., CLEO 2015, SM2O.5 (2015). Y. Weng et al., Optics & Photonics News 26, 59 (2015). Page 32

33 Approach: Multi-parameter Discriminative Measurement Y. Weng et al., Opt. Express. 23(7), (2015). Y. Weng et al., CLEO SM2O.5 (2015). Page 33

34 Intermodal Spontaneous Brillouin Scattering Brillouin scattering depends on the correlation between acoustic and optical modes. For LP01 mode, the optical and acoustic profiles match well. For LP11 mode, the overlap integral of optical/acoustic profiles is much smaller. This explains why each spatial mode in FMF has slightly different Brillouin properties. Z. Pan et al., Photonic Netw Commun. (2015). Y. Weng et al., Opt. Express. 23(7), (2015). Y. Weng et al., CLEO SM2O.5 (2015). Page 34

35 Experimental Setup Z. Pan et al., Photonic Netw Commun. (2015). Y. Weng et al., Opt. Express. 23(7), (2015). Y. Weng et al., CLEO SM2O.5 (2015). Page 35

36 Results and Discussion Each spatial mode in FMF may have different Brillouin properties. The BFS is then determined from the differential spectrum and used to decide the effects of strain or temperature along the sensing fiber. Y. Weng et al., Opt. Express. 23(7), (2015). Y. Weng et al., Sensors SeS3C.3 (2015). Page 36

37 Simultaneous Temperature and Strain Sensing Y. Weng et al., Opt. Express. 23(7), (2015). Y. Weng et al., CLEO SM2O.5 (2015). Page 37

38 Simultaneous Temperature and Strain Sensing Y. Weng et al., Opt. Express. 23(7), (2015). Y. Weng et al., CLEO SM2O.5 (2015). Page 38

Few-mode Fiber-optic Sensors In Thethis system project, can achieve we present goodasensitivity single-end andfmf-based requires light distributed injection sensing into only system one endthat of

39 Few-mode Fiber-optic Sensors In Thethis system project, can achieve we present goodasensitivity single-end andfmf-based requires light distributed injection sensing into only system one endthat of the allows fiber, simultaneous because it s temperature based on spontaneous and strain measurement Brillouin scattering. by Therefore, Brillouin itoptical can prevent time-domain catastrophic reflectometry failures in (BOTDR) many applications. and heterodyne detection. Z. Pan et al., Photonic Netw Commun. (2015). Y. Weng et al., CLEO 2015, SM2O.5 (2015). Y. Weng et al., Optics & Photonics News 26, 59 (2015). Page 39

40 Outline 1. Introduction 1.1 Capacity Crunch & Space Division Multiplexing (SDM) Systems 1.2 Nonlinear Effects in Few-mode Fibers (FMF) 1.3 Different Scattering Mechanism for Sensors 2. Key Components of SDM Technique 2.1. Spatial Light Modulators 2.2. Mode Multiplexers 2.3. Detection Methods 2.4. Multi-input Multi-output (MIMO) Schemes 2.5. Performance Limitations 3. Spatial-Division Multiplexing based Fiber-Optic Sensors 3.1. Distributed sensors based on mode-division multiplexing (MDM) 3.2. Distributed sensors based on core multiplexing 3.3. Fiber Bragg grating (FBG) sensors based on core multiplexing 4. Prospective Outlook 4.1. Fiber Deployment 4.2. Big Data Analytics 4.3. New Opportunities Page 40

41 Distributed sensors based on core multiplexing The experimental setup for Brillouin measurement for investigating the BFS dependence on strain and temperature in the multicore fiber (MCF) is shown below. Using a silica-based, 7-core multi-core fiber (MCF) with incident light of 1.55 μm wavelength across the C-band. Y. Mizuno, Appl. Phys. Lett. 104, (2014). Y. Mizuno, Sci. Rep. 5, (2015). Page 41

Distributed sensors based on core multiplexing (a) cross-sectional micrograph of the 7-core MCF and the structures of the fiber under test for detecting Brillouin scattering.

42 Distributed sensors based on core multiplexing (a) cross-sectional micrograph of the 7-core MCF and the structures of the fiber under test for detecting Brillouin scattering. (b) When the Stokes light returned from the central core of the MCF. (c) When the Stokes light returned from one of the outer cores. Y. Mizuno, Appl. Phys. Lett. 104, (2014). Y. Mizuno, Sci. Rep. 5, (2015). Page 42

43 Simultaneous Temperature and Strain Sensing BFS dependence on strain (0, 0.067, 0.135, 0.202, and 0.270%) BFS dependence on temperature (28, 40, 50, 60, 70, 80, 90 C) Y. Mizuno, Sci. Rep. 5, (2015). Page 43

44 Outline 1. Introduction 1.1 Capacity Crunch & Space Division Multiplexing (SDM) Systems 1.2 Nonlinear Effects in Few-mode Fibers (FMF) 1.3 Different Scattering Mechanism for Sensors 2. Key Components of SDM Technique 2.1. Spatial Light Modulators 2.2. Mode Multiplexers 2.3. Detection Methods 2.4. Multi-input Multi-output (MIMO) Schemes 2.5. Performance Limitations 3. Spatial-Division Multiplexing based Fiber-Optic Sensors 3.1. Distributed sensors based on mode-division multiplexing (MDM) 3.2. Distributed sensors based on core multiplexing 3.3. Fiber Bragg grating (FBG) sensors based on core multiplexing 4. Prospective Outlook 4.1. Fiber Deployment 4.2. Big Data Analytics 4.3. New Opportunities Page 44

45 FBG sensors based on core multiplexing Multi-core fiber with fiber Bragg gratings (MC-FBG) can be used for bending & shaping measurements. S. G. Leon-Saval, Opt. Lett. 30, 2545 (2005) R. R. Thomson, FiO 2010, PDPA3 (2010). Page 45

46 Multi-core Fiber with Fiber Bragg Gratings UV power inside a sideilluminated 7-core fiber. Photograph of 7-core fiber and polished capillary tube J. Bland-Hawthorn, Nat. Commun. 2, 581 (2011). E. Lindley, Opt. Express 22(25), (2014). Page 46

47 Simultaneous Temperature and Strain Sensing Transmission profiles of individual cores of an MC-FBG written without any compensation for lensing by the cladding. J. Bland-Hawthorn, Nat. Commun. 2, 581 (2011). E. Lindley, Opt. Express 22(25), (2014). Page 47

48 Outline 1. Introduction 1.1 Capacity Crunch & Space Division Multiplexing (SDM) Systems 1.2 Nonlinear Effects in Few-mode Fibers (FMF) 1.3 Different Scattering Mechanism for Sensors 2. Key Components of SDM Technique 2.1. Spatial Light Modulators 2.2. Mode Multiplexers 2.3. Detection Methods 2.4. Multi-input Multi-output (MIMO) Schemes 2.5. Performance Limitations 3. Spatial-Division Multiplexing based Fiber-Optic Sensors 3.1. Distributed sensors based on mode-division multiplexing (MDM) 3.2. Distributed sensors based on core multiplexing 3.3. Fiber Bragg grating (FBG) sensors based on core multiplexing 4. Prospective Outlook 4.1. Fiber Deployment 4.2. Big Data Analytics 4.3. New Opportunities Page 48

Fiber Deployment and Data Acquisition Fiber

49 Fiber Deployment and Data Acquisition Fiber location has significant impact on DAS data, because different spots may have very different sound fields and pressure wave characteristics. A. Kumar, J. Lightwave Technol. 19(3), 358 (2001). A. Li, Opt. Express 23(2), 1139 (2015). Page 49

Big Data Analytics for Oil & Gas Data Plane Control Plane Services Srvc 1 Srvc 2 Srvc 3 Srvc N s C[1] C[2] C[3] C[4] C[5] C[m] Electrical Switch E λ1 E λ2 E λ3 E λ4 E λ5 λ m OLT λ: central node ONU:

50 Big Data Analytics for Oil & Gas Data Plane Control Plane Services Srvc 1 Srvc 2 Srvc 3 Srvc N s C[1] C[2] C[3] C[4] C[5] C[m] Electrical Switch E λ1 E λ2 E λ3 E λ4 E λ5 λ m OLT λ: central node ONU: remote node E WDM λ1 λ2 λ4 λ m-2 λ m-1 λ m E λ3 λ4 λ5 ONUs λ m-2 λ m E RX E λ3 λ5 λ1 λ5 E RX E λ2 R[1] RX E E RX RX R[n] R[2] RX RX R[3] R[n-1] R[4] R[5] Service table Central node table Remote node table service 2 service 3 service N s -1 Candidate group map Flow table Request table Waiting list table service 1 service N s Services Electrical fabric Controller CN CN CN CN Central Nodes Deterministic method Optical fabric Main frame RN RN RN RN RN RN Optimization method RN RN RN RN RN RN RN Remote Nodes RN RN RN The combination of optical sensing systems, data processing platforms with big data analytics can help the oil & gas company executives acquire subsurface trends and geographic characteristics more accurately. Page 50

51 New Opportunities for SDM Sensors In conclusion, the SDM sensors, including FMF, MCF and MC-FBG, have great potential for both research and commercial applications. Z. Pan et al., Photonic Netw Commun. (2015). Y. Weng et al., Optics & Photonics News 26, 59 (2015). Page 51

52 Page 52

Sensing Technology. A company of the BRUGG Group

Sensing Technology. A company of the BRUGG Group Sensing Technology. Applications. 2 Basic_Sensing_e.ppt / ad Laser. LASER λ 0 [nm] Intensity λ [nm] λ 0 3 Basic_Sensing_e.ppt / ad Rayleigh, Brillouin, Raman Scattering. LASER λ 0 [nm] Rayleigh Intensity