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In the framework of massive sensing and smart sustainable cities, this work presents an urban distributed acoustic sensing testbed in the vicinity of the School of Technology and Telecommunication Engineering of the University of Granada, Spain. After positioning the sensing technology and the state of the art of similar existing approaches, the results of the monitoring experiment are described. Details of the sensing scenario, basic types of events automatically distinguishable, initial noise removal actions and frequency and signal complexity analysis are provided. The experiment, used as a proof-of-concept, shows the enormous potential of the sensing technology to generate data-driven urban mobility models. In order to support this fact, examples of preliminary density of traffic analysis and average speed calculation for buses, cars and pedestrians in the testbed’s neighborhood are exposed, together with the accidental presence of a local earthquake. Challenges, benefits and future research directions of this sensing technology are pointed out.

11 pags., 8 figs., Distributed acoustic sensing (DAS) delivers real-time observation ofphysical perturbations such as vibrations or strain variations in conventional optical fibers with high sensitivity. The high density of sensing points and large network footprint provided by a single DAS system, along with the availability of a vast optical fiber network already deployed both in land and in oceanic regions, contrast with the high deployment and maintenance cost of conventional instrumentation networks for seismology. This situation has triggered a rapid growth of DAS deployments for seismic monitoring in recent years. Photonic engineers and geophysicists have joined efforts to prove the value of optical fibers as distributed seismometers, which has resulted in a wide panoply of tests demonstrating diverse applicability across the geosciences. For example, DAS has been successfully applied recording local to teleseismic earthquakes, monitoring glacial icequakes, and observing oceanographic phenomena at the sea floor. Most of the realized tests have been performed using commercially available optical fiber interrogators based on phase-sensitive optical time-domain reflectometry. Among them, DAS based on chirped pulse distributed acoustic sensing have provided optimized performance in terms of both range and sensitivity, particularly at low frequencies. In this communication, we provide a comprehensive review of the current situation of DAS for seismology applications, focusing on near surface monitoring, where already deployed optical fibers can be repurposed as sensor networks., Z.Z. acknowledges support from the Moore Foundation and NSF under CAREER Award 1848166.

This research describes a method of using distributed acoustic sensing to noninvasively measure volumetric flow rate via multiple unique sensor styles. This work modifies previously used methods of flow detection via fiber optic acoustic sensors affixed onto the exterior body of a flow apparatus. Flow rate measurement methods for two unique sensor styles are described. Weak trends are additionally observed as a function of flow temperature that may represent opportunity for future optimization. A discussion of current noninvasive flow rate measurement methods is given as well as their limitations. A background of distributed acoustic sensing is presented along with a summary of its fundamentals as well as its functionality in noninvasive flow rate measurement. A description of previous techniques that utilized distributed acoustic sensing in conjunction with fiber optic acoustic sensing is shown. The acoustic properties of the fluid-induced vibrations are measured as a function of flow rate and flow temperature utilizing a special type of fiber optic sensor. Numerically smoothed frequency domain acoustic peaks are evaluated by intensity, area, central frequency, and full width at half maximum as flow conditions vary. All tested sensors were found to yield a strong dependence between peak intensity and flow rate. A dependence between central frequency and flow temperature was observed in some cases. The sensor system developed was able to measure fluid-induced vibration intensity and vibrational central frequency and offers potential uses in a myriad of vibrational applications. Master of Science This research provides a method of measuring fluid-induced vibrations caused by internal pressure fluctuations stemming from a variety of flow conditions. In this case, a specially fabricated optical fiber is applied to the external surface of the pipe. As water flows at a known volumetric flow rate and temperature, the acoustic signal generated is detected by the optical sensor signal demodulation system. The fiber used is a silicate material designed to transmit optical signals over long distances with minimal loss. Modifications to the fiber can be made to differentiate the measured optical signal loss by frequency band, as well as to designate the spatial position on a fiber sensor to locate where loss is occurring. By measuring optical loss of distinct fiber spatial positions at high sampling frequencies, an abundance of sensing opportunities become available. In knowing optical signal travel time of select wavelengths to corresponding strain characteristics amongst a section of fiber, optoelectronic devices with strong computing power called interrogators can powerfully measure the intensity and rate of fiber strain at a significantly high sampling frequency. Fiber optic sensors have been used in many areas where monitoring of changes in positional microstrain is desired. Such sensors are embedded in-ground for seismic monitoring, as well as on the ocean floor for submarine structural characterization with long singular fibers. Flow rate measurement is performed with fiber coils and various other geometries for active oil wells, fission reactors, and other areas. Improving the performance and applicational flexibility of these sensors allows for greater opportunity for scientific advancement in an array of fields. This research was completed to offer a new method of flow rate measurement while also gauging if flow temperature was able to be measured via a single fiber optic sensor. Fiber strain was observed to be strongly dependent on flow rate, whereas the rate at which strain occurred suggests simultaneous flow and temperature measurement is possible in certain types of fiber arrangements. The work produced in this research is a step towards singular-fiber flow rate and temperature sensing.

Optical fiber distributed acoustic sensing (DAS) based on phase sensitive optical time domain reflectometry (ϕ-OTDR) has a great demand in many application fields with large signals, such as railway safety monitoring, cable vibration detection, etc. However, due to the inherent limits of phase unwrapping algorithm, the large signal whose phase change exceeds π cannot be recovered correctly by DAS. In this work, the differential-unwrapping-integral (DUI) algorithm is proposed and demonstrated to replace the traditional unwrapping algorithm for large signal recovery. By utilizing differential operation to compress the signal amplitude, the large phase signal can be converted into small signal which can be recovered through unwrapping. Then, multiple integral operations and polynomial fitting compensation algorithm are applied onto the differential signal to recover the original phase signal without any signal-to-noise ratio(SNR) sacrificed. In theory, the maximum measurable phase of DUI can be improved 1390 times compared with traditional DUI algorithm. Further, the experimental results demonstrate that the dynamic range of DAS with DUI can reach up to 131.7 dB. Moreover, DUI algorithm has been tested and verified in the field test for recording the digging signals with large amplitude. This scheme can be applicable for all phase-demodulation-based sensing techniques without increasing the system complexity.

To maintain pipeline transportation’s optimal efficiency and safety, pipelines must be regularly inspected and cleaned by the pipeline inspection gauge (PIG). Since the PIG passes through the whole pipeline, which is generally tens of kilometers, observing where the PIG is working in real-time is necessary. When the PIG passes through the pipe joint, the vibration signal will generate by the collision between the PIG and the girth weld, which can transmit along the fiber cable besides the pipeline. In this paper, we demonstrate that the optical fiber distributed acoustic sensing (DAS) can acquire the collision vibration in terms of the V pattern in the waterfall diagram, whose vertex is the collision position of PIG. The vertex will not exist when the cable positions are far away from the pipeline, which is relatively common in practice. We proposed an algorithm based on the clustering algorithm and the Hough transform to detect the position of the PIG even when the vertex of the V pattern does not exist. A field experiment shows that the proposed positioning algorithms applied to the DAS can effectively track the PIG online.

Distributed acoustic sensing (DAS) is a novel seismic observation system developed in recent years that can realize ultrahigh density observations and has attracted extensive attention in the field of seismology. DAS uses fiber-optic cables as sensing units, which are easy to incorporate with urban telecommunication fiber-optic cables for seismological observations. Compared with seismometers, DAS has the advantages of being rapidly deployed and recyclable, being able to acquire dense observations at low cost, and convenient data collection. In this study, a 5.2 km long telecom fiber-optic internet cable was utilized as a DAS array in an urban area to record ambient noise, and the noise cross-correlation function (NCF) was calculated. There are two different distribution types of ambient noise sources along the cable, regular along-road trucks (Taihe Road) and complex ambient noise, including human activities and traffic sources along and across the Jinniu road. In the first case, we constructed a 2D S-wave velocity model down to 100 m depth and a low-velocity zone was revealed. The S-wave model well explained the traffic signal along the Taihe road and the low-velocity zone is also consistent with the results obtained from co-located geophone arrays. In the second case, due to the complexity of the traffic noise distribution, empirical Green’s functions were barely achieved. Therefore, we performed a synthetic test obtaining different NCFs with different source distributions, and two specific cases that dominate the NCF results were matched. Finally, we obtained the traffic noise distribution along the road, which is consistent with the power spectra density of the ambient noise. In conclusion, by combining DAS and urban fiber-optic internet cables with urban traffic noise, we can effectively reveal the traffic activities and image shallow structures with high resolution, which could offer a reference for urban construction and disaster prevention. Article Highlights DAS turns the urban fiber-optic internet cables into ultra-dense permanent seismic observation arraysWe revealed a high-resolution shallow structure using urban fiber-optic internet cablesWe obtained the distribution of traffic activities along the road

With new developments of fiber-optic sensing and rotary sources, continuous active seismic monitoring for onshore applications has now the opportunity to be fully realized and applied to enhance subsurface resource extraction and use. To date, conventional seismic monitoring deployments have primarily consisted of receiver arrays, either fixed or not, with periodic data acquisition campaigns using temporarily deployed sources, resulting in time-lapse data with poor temporal resolution. Only a few niche efforts have demonstrated continuous acquisition using fixed source-receiver networks. We have evaluated the initial results of a network of fixed rotary seismic sources, referred to as surface orbital vibrators (SOVs), coupled with a permanent distributed acoustic sensing (DAS) network at the CO2CRC Otway Field Site. Although rotary seismic sources are not new, our development of the SOV focused on simplifying the cost and complexity of the source hardware while delivering broad frequency spectrum of the source signal. The upgraded hardware is aligned with a robust methodology for autonomous operation and data processing. At the Otway Site, we deployed SOVs at nine locations, monitoring seismic response in seven DAS instrumented wells. Baseline operation of the DAS/SOV sensor array and source system demonstrates its capability with near offsets attaining a signal-to-noise ratio approaching 100 dB with a normalized root mean square of 10%. Furthermore, analyses of traveltime repeatability indicate that the DAS/SOV system can deliver time resolution of ±500 μs.

Distributed acoustic sensing (DAS) is an emerging technology that repurposes a fiber-optic cable as a dense array of strain sensors. This technology repeatedly pings a fiber with laser pulses, measuring optical phase changes in Rayleigh backscattered light. DAS is beneficial for studies of fine-scale processes over multi-kilometer distances, long-term time-lapse monitoring, and deployment in logistically challenging areas (e.g., high temperatures, power limitations, land access barriers). These benefits have motivated a decade of applications in subsurface imaging and microseismicity monitoring for energy production and carbon sequestration. DAS arrays have recorded microearthquakes, regional earthquakes, teleseisms, and infrastructure signals. Analysis of these wavefields is enabling earthquake seismology where traditional sensors were sparse, as well as structural and near-surface seismology. These studies improved understanding of DAS instrument response through comparison with traditional seismometers. More recently, DAS has been used to study cryosphere systems, marine geophysics, geodesy, and volcanology. Further advancement of geoscience using DAS requires several community efforts related to instrument access, training, outreach, and cyberinfrastructure. ▪ DAS is a seismic acquisition technology repurposing fiber optics as arrays of dynamic strain sensors at 1- to 10-m spacing over kilometers. ▪ Easy DAS installations have availed time-lapse geophysical sensing in formerly inaccessible sites: urban, icy, and offshore areas. ▪ High-frequency wavefields recorded by DAS are analyzed with array-based methods to characterize seismic sources and image the subsurface. ▪ DAS has shown low-frequency sensitivity in the laboratory and field, for slow hydrodynamic and geodynamic processes.

Maintenance of wind turbine towers is currently a manual process that requires visual inspection and bolt tightening yearly. This process is costly to energy companies and its necessity is not well-defined. In this study, two Rayleigh-based distributed fiber optic sensing technologies are evaluated and compared for their ability to monitor the dynamic structural behavior of a model wind turbine tower subject to free and forced vibration. They are further tested for their ability to detect structural phenomena associated with loose bolts and material damage within the tower. The two technologies examined are optical frequency domain reflectometry (OFDR) and phase-based optical time domain reflectometry ($$\phi$$ ϕ -OTDR), which is a technology used in distributed acoustic sensing (DAS). OFDR is a tested and proven strain measurement technology commonly used for structural health monitoring but can only make strain measurements over short distances (10 s of meters). OFDR was used to validate the measurements made with $$\phi$$ ϕ -OTDR which can measure over much longer distances (several kilometers). Due to its sensing distance capability, $$\phi$$ ϕ -OTDR is a promising technology for monitoring many wind turbines networked together with a single fiber optic cable. This study presents a first-of-its-kind use of $$\phi$$ ϕ -OTDR for structural health monitoring to demonstrate its capabilities.

We derive fundamental thermodynamic limits on the strain resolution of a class of fiber optic distributed acoustic sensing (DAS) techniques based on optical time domain reflectometry. The results indicate a lower limit of around $10^{-14}$ strain/ $\sqrt{\mathrm{Hz}}$ for a 2 m long (10 ns) optical pulse. These limits indicate that interrogation of unmodified fiber optic cable is unlikely to achieve sensing performance approaching that of engineered acoustic sensors.

In this paper field measurements are carried out using a distributed acoustic sensing system (DAS) for the identification of horse gait. The DAS system has a spatial resolution of 1 m, frequency range of 1–5 kHz and the fiber length is of about 70 m. The optical fiber cable lays down into trench of 15 cm of depth. Several measurements are also carried out in order to fully understand the measuring capacity of the system, including a 2 kg calibrated impact hammer and a small controlled blast of 12.6 Pa of air pressure. Results demonstrate the capacity to measure soil mechanical waves speed of 171 m/s for the impact hammer tests and sound speeds in air of about 366 m/s for the controlled blast tests. The experiments involving horses allowed the identification of three distinct horse gait patterns: step, trot and gallop, as well the horse speed in each gait with SNR about 30 dB.

Phase-sensitive optical time domain reflectometry (Ф-OTDR) is an effective way to detect vibrations and acoustic waves with high sensitivity, by interrogating coherent Rayleigh backscattering light in sensing fiber. In particular, fiber-optic distributed acoustic sensing (DAS) based on the Ф-OTDR with phase demodulation has been extensively studied and widely used in intrusion detection, borehole seismic acquisition, structure health monitoring, etc., in recent years, with superior advantages such as long sensing range, fast response speed, wide sensing bandwidth, low operation cost and long service lifetime. Significant advances in research and development (R&D) of Ф-OTDR have been made since 2014. In this review, we present a historical review of Ф-OTDR and then summarize the recent progress of Ф-OTDR in the Fiber Optics Research Center (FORC) at University of Electronic Science and Technology of China (UESTC), which is the first group to carry out R&D of Ф-OTDR and invent ultra-sensitive DAS (uDAS) seismometer in China which is elected as one of the ten most significant technology advances of PetroChina in 2019. It can be seen that the Ф-OTDR/DAS technology is currently under its rapid development stage and would reach its climax in the next 5 years.

We modeled cross-well strain/strain rate responses of fiber optic sensing, including distributed strain sensing (DSS) and low-frequency distributed acoustic sensing (DAS), to hydraulic stimulation. DSS and low-frequency DAS have been used to measure strain or the strain rate to characterize hydraulic fractures. However, the current application of DSS/DAS is limited to acquisition, processing, and qualitative interpretations. The lack of geomechanical models hinders the development of the technology toward quantitative interpretation and inversion. We have developed a strategy to use the displacement discontinuity method to model the strain field around kinematically propagating fractures. For a horizontal monitoring well, modeling results were able to explain the heart-shaped extending pattern before a fracture hit, the polarity flip due to fracture interaction during stimulation, and the V-shaped pattern when a fracture does not intersect with the monitoring well. For a vertical monitoring well, modeling shows the different characters of strain rate responses when a fracture is near and far away from a vertical monitoring well. We also investigated the effects of fractures with various geometries such as elliptic and layered fractures. We compared and verified the modeling with field data from the Hydraulic Fracturing Test Site 2, a research experiment performed in the Permian Basin. Our modeling work can be used to identify patterns in field observations. The results also help to improve acquisition design and lay the groundwork for quantitative interpretation and inversion.

In this study, a novel method is proposed to detect and classify the threats for fiber optic distributed acoustic sensing (DAS) systems. In the study, phase-sensitive optical time-domain reflectometry (phase-OTDR) is realized for the sensing system. The proposed method is consisted of three main stages. In the first stage, Wavelet denoising method is applied for noise reduction in the measured signal, and difference in time domain approach is used to perform high-pass filtering. Autocorrelation is then used for comparing the signal with itself over time in each bin to remove uncorrelated signals. Next, the power of the correlated signals at each bin is calculated and sorted where maximum valued bins are considered as the event signal. In the second stage, Variational Mode Decomposition (VMD) technique is used to decompose the detected event signals into a series of band-limited modes from which the event signals are reconstructed. From the reconstructed event signals, higher order statistical (HOS) features including variance, skewness, and kurtosis are extracted. In the last stage, the threats are discriminated by implementing Linear Support Vector Machine (LSVM)-based classification approach to the extracted features. In order to evaluate the effects of proposed method on the classification performance, different types of activities such as digging with hammer, pickaxe, and shovel collected from various points of a buried fiber optic cable have been used under different Signal-to-Noise Ratio (SNR) levels (-4 to -18 dB). It has observed that the classification accuracy at high/moderate (-4 to -8 dB) and low (-8 to -18 dB) SNR levels are 79.5% and 75.2%, respectively. To the best of authors' knowledge, this research study is the first report to use VMD technique for threat classification in phase-OTDR-based DAS systems. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

Distributed acoustic sensing technology has unique advantage in diverse applications, such as seismology, mineral exploration, and so on. We explored the methods to increase measurement range, distance and speed, which are the most important requirement for field deployment. Heterogeneous sideband linear frequency modulated optical pulse with different frequency modulated bandwidth was used to realize simultaneous measurement of acoustic events in different dynamic ranges. Weak fiber Bragg gratings and phase of constructed single frequency were proposed for long distance sensing. Fast processing algorithm based on a graphics processing unit for a linear frequency modulation pulse demodulation was realized. The experiment results verified our methods well.

In this paper, we introduce Internet Photonic Sensing (IPS), a new framework for deformation and vibration measurement and monitoring based on signals that are available from standard fiber optic communication hardware deployed in the Internet. IPS is based on the hypothesis that atmospheric, seismic, anthropogenic and other natural activity cause deformations and vibrations in the earth that trigger detectable changes in standard optical signals that transmit data through Internet fiber. We assume a simple system component model for optical communication hardware and identify two candidate signals that may reflect deformation and vibrations and that can be measured through standard interfaces: Optical Signal Strength (OSS) and Bit Error Rate (BER). We investigate the efficacy of IPS through a series of controlled, laboratory experiments that consider how the candidate signals respond when fiber is subjected to a range of mechanical deformations. We believe that advancement of IPS offers the potential to transform the practice of scientific, commercial and public safety-related vibration monitoring applications by providing a highly-sensitive platform that is available at a global scale.

Distributed Acoustic Sensing (DAS) is a fiber optic sensing system that is used for vibration monitoring. At a minimum, DAS is composed of a fiber optic cable and an optic analyzer called an interrogator. The oil and gas industry has used DAS for over a decade to monitor infrastructure such as pipelines for leaks, and in recent years changes in DAS performance over time have been observed for DAS arrays that are buried in the ground. This dissertation investigates the effect that soil type, soil temperature, soil moisture, time in-situ, and vehicle loading have on DAS performance for fiber optic cables buried in soil. This was accomplished through a field testing program involving two newly installed DAS arrays. For the first installation, a new portion of DAS array was added to an existing DAS array installed a decade prior. The new portion of the DAS array was installed in four different soil types: native fill, sand, gravel, and an excavatable flowable fill. Soil moisture and temperature sensors were buried adjacent to the fiber optic cable to monitor seasonal environmental changes over time. Periodic impact testing was performed at set locations along the DAS array for over one year. A second, temporary DAS array was installed to test the effect of vehicle loading on DAS performance. Signal to Noise Ratio (SNR) of the DAS response was used for all the tests to evaluate the system performance. The results of the impact testing program indicated that the portions of the array in gravel performed more consistently over time. Changes in soil moisture or soil temperature did not appear to affect DAS performance. The results also indicated that time DAS performance does change somewhat over time. Performance variance increased in new portions of array in all material types through time. The SNR in portions of the DAS array in native silty sand material dropped slightly, while the SNR in portions of the array in sand fill and flowable fill material decreased significantly over time. This significant change in performance occurred while testing halted from March 2020 to August 2020 due to the Covid-19 pandemic. These significant changes in performance were observed in the new portion of test bed, while the performance of the prior installation remained consistent. It may be that, after some time in-situ, SNR in a DAS array will reach a steady state. Though it is unfortunate that testing was on pause while changes in DAS performance developed, the observed changes emphasize the potential of DAS to be used for infrastructure change-detection monitoring. In the temporary test bed, increasing vehicle loads were observed to increase DAS performance, although there was considerable variability in the measured SNR. The significant variation in DAS response is likely due to various industrial activities on-site and some disturbance to the array while on-boarding and off-boarding vehicles. The results of this experiment indicated that the presence of load on less than 10% of an array channel length may improve DAS performance. Overall, this dissertation provides guidance that can help inform the civil engineering community with respect to installation design recommendations related to DAS used for infrastructure monitoring.

Distributed acoustic sensing (DAS) in optical fibers detect dynamic strains or sound waves by measuring the phase or amplitude changes of the scattered light. This contrasts with other distributed (and more conventional) methods, such as distributed temperature (DTS) or strain (DSS), which measure quasi-static physical quantities, such as intensity spectrum of the scattered light. DAS is attracting considerable attention as it complements the conventional distributed measurements. To implement DAS in commercial applications, it is necessary to ensure a sufficiently high signal-noise ratio (SNR) for scattered light detection, suppress its deterioration along the sensing fiber, achieve lower noise floor for weak signals and, moreover, perform high-speed processing within milliseconds (or sometimes even less). In this paper, we present a new, real-time DAS, realized by using the time gated digital-optical frequency domain reflectometry (TGD-OFDR) method, in which the chirp pulse is divided into overlapping bands and assembled after digital decoding. The developed prototype NBX-S4000 generates a chirp signal with a pulse duration of 2 μs and uses a frequency sweep of 100 MHz at a repeating frequency of up to 5 kHz. It allows one to detect sound waves at an 80 km fiber distance range with spatial resolution better than a theoretically calculated value of 2.8 m in real time. The developed prototype was tested in the field in various applications, from earthquake detection and submarine cable sensing to oil and gas industry applications. All obtained results confirmed effectiveness of the method and performance, surpassing, in conventional SM fiber, other commercially available interrogators.

International audience; We demonstrate the performance of a novel multi-carrier MIMO fiber sensing interrogator based on OFDM approach. Over an installed telecom fiber cable, coherent fading is mitigated by means of a purely digital subcarrier combiner.

This chapter describes distributed strain sensing and distributed acoustic sensing (DAS) applications of the fiber optic sensor for power cable applications. Distributed strain monitoring (DSM) systems are arriving into the market place. The strain measurement would help identify the exact touchdown point. Including an optical fiber in the distribution cables provided opportunities not only for telecommunication and temperature measurements using a distributed temperature sensing system but also proved useful in strain measurement via a DSM system. The chapter discusses studies completed at BC Hydro's subsidiary test laboratory that aim to understand the sensitivities of such a system, and identify some of the challenges surrounding its implementation on a real submarine cable application might offer. Cable stress can be calculated from the strain values within certain limits. DAS systems are fiber optic‐based optoelectronic instruments which measure acoustic interactions along the length of a fiber optic cable.

Phase-sensitive optical time-domain reflectometry ( ${\Phi }$ -OTDR), which utilizes the phase information of Rayleigh scattered lightwave inside optical fiber, could turn a fiber cable into a massive sensor array for distributed acoustic sensing (DAS), i.e., an emerging infrastructure for Internet of Things. Given a certain fiber length, there are tradeoffs among the sensing bandwidth, the sensitivity, and the spatial resolution. In this paper, the concept of linearization and Golay pulse-coding for heterodyne ${\Phi }$ -OTDR are proposed and experimentally verified for the first time. First, we gave a full theoretical treatment on how an intensity-coded yet phase-retrieved ${\Phi }$ -OTDR can be built up as a fully linear system, therefore a significant enhancement of signal-to-noise ratio becomes viable and the sensing bandwidth equals the four-times averaging case. Second in the proof-of-concept experiment, submeter gauge length and nano-strain resolution were realized with 10 km sensing range, in other words, more than ten thousand sensitive sensing units were realized along the fiber. This paper makes a significant step toward high-performance DAS with orders-of-magnitude performance enhancement.

Summary Proper cemented casing strings are a key requirement for maintaining well integrity, guaranteeing optimal operation and safe provision of hydrocarbon and geothermal resources from the pay zone to surface facilities. Throughout the life cycle of a well, high–temperature/high–pressure changes in addition to shut–in cyclic periods can lead to strong variations in thermal and mechanical load on the well architecture. The current procedures to evaluate cement quality and to measure downhole temperature are mainly dependent on wireline–logging campaigns. In this paper, we investigate the application of the fiber–optic distributed–acoustic–sensing (DAS) technology to acquire dynamic axial–strain changes caused by propagating elastic waves along the wellbore structure. The signals are recorded by a permanently installed fiber–optic cable and are studied for the possibility of real–time well–integrity monitoring. The fiber–optic cable was installed along the 18⅝–in. anchor casing and the 21–in.–hole section of a geothermal well in Iceland. During cementing operations, temperature was continuously measured using distributed–temperature–sensing (DTS) technology to monitor the cement placement. DAS data were acquired continuously for 9 days during drilling and injection testing of the reservoir interval in the 12¼–in. openhole section. The DAS data were used to calculate average–axial–strain–rate profiles during different operations on the drillsite. Signals recorded along the optical fiber result from elastic deformation caused by mechanical energy applied from inside (e.g., pressure fluctuations, drilling activities) or outside (e.g., seismic signals) of the well. The results indicate that the average–axial–strain rate of a fiber–optic cable installed behind a casing string generates trends similar to those of a conventional cement–bond log (CBL). The obtained trends along well depth therefore indicate that DAS data acquired during different drilling and testing operations can be used to monitor the mechanical coupling between cemented casing strings and the surrounding formations, hence the cement integrity. The potential use of DTS and DAS technology in downhole evaluations would extend the portfolio to monitor and evaluate qualitatively in real time cement–integrity changes without the necessity of executing costly well–intervention programs throughout the well's life cycle.

This study aims to assess the ability of shallow distributed acoustic sensing (DAS) to serve as a cost-effective seismic sensor array for permanent monitoring applications. To this end, as part of the CO2CRC seismic monitoring program, a fibre-optic DAS array was deployed alongside a permanently buried geophone array at the Otway Project site (Victoria, Australia). The DAS array consisted of a standard commercially available tactical fibre-optic cable, which was deployed in 0.8m deep trenches. A custom-designed helically wound (HW) cable was also deployed in one of the DAS trenches for comparison of the cable designs. Simultaneous acquisition of the seismic data was carried out using 3000 vibroseis source points and geophones, DAS standard and HW cables. For initial assessment of the seismic images acquired with DAS and to compare different cable designs, preliminary 2D seismic reflection processing is conducted on both DAS cables and geophone data along a single 2D line. The geophone data processing guided processing of the DAS data. Several shallow structures (100-450ms) and some important reflectors at 450-600ms are observed on the final DAS images. Comparison of the two different DAS cable types demonstrated that seismic imaging would benefit DAS technology. However, the benefit of utilising HW cable is modest compared with the standard cable. The workflows and results of this study pave the way for processing of the 3D seismic data set acquired with the DAS array, as well as further detailed analysis of the DAS cables and the system itself.

Hydraulic fracturing operations in unconventional reservoirs are typically monitored using geophones located either at the surface or in the adjacent wellbores. A new approach to record hydraulic stimulations uses fiber-optic distributed acoustic sensing (DAS). A fiber-optic cable was installed in a treatment well in the Meramec formation to monitor the hydraulic fracture stimulation of an unconventional reservoir. A variety of physical effects, such as temperature, strain, and microseismicity are measured and correlated with the treatment program during hydraulic fracturing of the well containing the fiber and also an adjacent well. The analysis of this DAS data set demonstrates that current fiber-optic technology provides enough sensitivity to detect a considerable number of microseismic events and that these events can be integrated with temperature and strain measurements for comprehensive hydraulic fracture monitoring.

The optical fiber acoustic sensing system is suitable for long-distance monitoring of the acoustic signals generated by the external disturbances. According to the continuity of sensing units, quasi-distributed and distributed optical fiber acoustic sensing technologies are differentiated to meet different application requirements. On the one hand, the recent progress of Fabry-Perot interferometer (FPI) focusing on the diaphragm material, and the research hotspots in the field of the continuous Fiber Bragg grating (FBG) array are firstly reviewed. On the other hand, Mach-Zehnder interferometry (MZI), Michelson interferometry (MI), and Sagnac interferometry (SI) have rapidly developed in the aspect of the demodulation algorithm optimization with the purpose of the sensing performance improvement. Moreover, the current primary research works of the phase-sensitive optical time-domain reflectometer ( $\varphi $ -OTDR) are the signal-to-noise ratio improvement and the mixed optical structure design. Finally, this paper presents an overview of the recent advances of optical fiber acoustic sensing system in the application domains of military defense, structural health monitoring, petroleum exploration, and development.

Fiber-optic distributed acoustic sensing (FDAS) with phase-sensitive optical time-domain reflectometry (Φ-OTDR) is a promising technique for high-sensitivity measurement. In this paper, an improved Φ-OTDR system with a weak fiber Bragg grating (wFBG) array for partial discharge (PD) detection in cross-linked polyethylene (XLPE) power cables is demonstrated; and an event recognition method based on a convolutional neural network (CNN) model is proposed to identify and classify different types of events, including internal PD, corona PD, surface PD, and noise. A multiscale wavelet decomposition and reconstruction method is used to extract PD signals and a two-dimensional spectral frame representation of the PD signals is obtained by the mel-frequency cepstrum coefficients (MFCC). The experimental results based on 1280 training samples and 832 test samples have demonstrated high values of precision, sensitivity, and specificity for each event (up to 96.3%, 96.4%, and 98.7%, respectively), which means that the combination of multiscale wavelet decomposition and reconstruction, the MFCC and CNN may be a promising event recognition method for the FDAS systems.

We have proposed and demonstrated a hybrid optical-fiber sensor that enables simultaneous distributed acoustic sensing (DAS) and distributed temperature sensing (DTS). The hybrid fiber sensor is realized through space-division multiplexed (SDM) reflectometers in a multicore fiber (MCF), where Raman optical time-domain reflectometry (ROTDR) for DTS is implemented simultaneously with phase-sensitive optical time-domain reflectometry (Φ-OTDR) for DAS through space-division multiplexing. The SDM reflectometers share an identical pulse source, but use separate interrogation fiber cores, allowing simultaneous measurement of ROTDR and Φ-OTDR. The proposed hybrid sensor based on MCF does not suffer from the incompatible pump power levels issue existing in its counterpart based on single mode fiber thanks to the SDM implementation. Thus it effectively eliminates the restriction imposed by fiber nonlinear effects (e.g., modulation instability). Wavelet transform denoising method is employed to reduce the noise of temporal ROTDR traces; as a result, the worst temperature uncertainty is reduced from 4.1 to 0.5 °C over 5.76 km sensing range. The proposed SDM hybrid fiber sensor can realize simultaneous distributed intrusion detection and temperature monitoring. It offers great potential in long-term real-time pipeline monitoring for oil and gas industry.

Distributed acoustic sensing (DAS) is a recent instrumental approach allowing the conversion of fiber-optic cables into dense arrays of acoustic sensors. This technology is attractive in marine environments where instrumentation is difficult to implement. A promising application is the monitoring of environmental and anthropic noise, leveraging existing telecommunication cables on the seafloor. We assess the ability of DAS to monitor such noise using a 41.5 km-long cable offshore of Toulon, France, focusing on a known and localized source. We analyze the noise emitted by the same tanker cruising above the cable, first 5.8 km offshore in 85 m deep bathymetry, and then 20 km offshore, where the seafloor is at a depth of 2000 m. The spectral analysis, the Doppler shift, and the apparent velocity of the acoustic waves striking the fiber allow us to separate the ship radiated noise from other noise. At 85 m water depth, the signal-to-noise ratio is high, and the trajectory of the boat is recovered with beamforming analysis. At 2000 m water depth, although the acoustic signal of the ship is more attenuated, signals below 50 Hz are detected. These results confirm the potential of DAS applied to seafloor cables for remote monitoring of acoustic noise even at intermediate depth.

The sound source localization method using conventional microphone arrays has been widely used in industrial and military fields. However microphones cannot immune to electromagnetic interference. Fiber-optic acoustic sensing system has become an important acoustic sensing method because of its high sensitivity and adapt to work in hash environment. In this paper, a fiber acoustic system with three-dimensional sound source localization in air is proposed which use beamforming to complete spatial coordinate estimation. Experimental results show that the system can estimate the spatial sound source accurately. The system has the advantages of simple construction and can be applied in harsh environments, which has greater application value.

We demonstrate the capability of distributed acoustic sensing (DAS) to record volcano-related dynamic strain at Etna (Italy). In summer 2019, we gathered DAS measurements from a 1.5 km long fibre in a shallow trench and seismic records from a conventional dense array comprised of 26 broadband sensors that was deployed in Piano delle Concazze close to the summit area. Etna activity during the acquisition period gives the extraordinary opportunity to record dynamic strain changes (∼ 10−8 strain) in correspondence with volcanic events. To validate the DAS strain measurements, we explore array-derived methods to estimate strain changes from the seismic signals and to compare with strain DAS signals. A general good agreement is found between array-derived strain and DAS measurements along the fibre optic cable. Short wavelength discrepancies correspond with fault zones, showing the potential of DAS for mapping local perturbations of the strain field and thus site effect due to small-scale heterogeneities in volcanic settings.

In coherent optical time-domain reflectometry, external modulation is used to maintain the coherence of laser probe pulses launched into optical fibers. However, the residual continuous wave (CW) component produced by modulation may considerably degrade the system sensitivity. The backscattered signal from the pulse must be dominant compared to the CW signal. We discuss the effects of the finite extinction ratio (ER) on the instrument’s sensing range. A model analyzing the impact of the CW component on the backscattered signal as a function of the ER, fiber length, and pulse widths is proposed. It is also shown that acousto-optic modulation is more suitable than electro-optic modulation in optical fiber for longer distances. The results are confirmed experimentally in a 31–km-long fiber. A 1-Hz vibration was applied at 25.5 km, and the resulting signal-to-noise ratio of ∼13 dB was measured using 75-ns pulses. This result is in agreement with the performance predicted by the model.

Distributed sensing optical fibers have been recognized for their unparalleled ability in discriminating and measuring environmental variables on strain, temperature, and vibration behaviors. For its ubiquitous industrial values in monitoring dynamic events in pipelines, railroads, perimeter surveillance, subsea, highway and so forth, distributed acoustic sensing (DAS) market is expected to grow steadily in the next few years. However, the inferior thermal stability of standard optical fiber coating, along with the native weakness Rayleigh scattering reflectivity, make the traditional telecommunication grade fibers-based DAS component suboptimal for mid-temperature environment deployment such as oilfield exploration and detection. Here, we report DAS fibers prototype with enhanced backscattering reflection and improved thermal robustness for feasible mid-temperature application. Typically, the 8/125/200 μm DAS fiber is fabricated from a G.652 compliant single-mode preform, coated with dual-layer of proprietary UV curable and high optical transparent write-through coatings, and further followed by a post-draw UV processing technology to increase the elastic scattering reflectivity in the optical fiber. Depending on the selected coating materials and fiber designs, developed DAS fibers are demonstrated with low level of OTDR attenuation, enhanced elastic backscattering signal amplitude about 15+ dB above Rayleigh level, and exceptional thermal reliability against elevated temperature conditions.

Red palm weevil (RPW) is a detrimental pest, which has wiped out many palm tree farms worldwide. Early detection of RPW is challenging, especially in large-scale farms. Here, we introduce the combination of machine learning and fiber optic distributed acoustic sensing (DAS) techniques as a solution for the early detection of RPW in vast farms. Within the laboratory environment, we reconstructed the conditions of a farm that includes an infested tree with ∼12 day old weevil larvae and another healthy tree. Meanwhile, some noise sources are introduced, including wind and bird sounds around the trees. After training with the experimental time- and frequency-domain data provided by the fiber optic DAS system, a fully-connected artificial neural network (ANN) and a convolutional neural network (CNN) can efficiently recognize the healthy and infested trees with high classification accuracy values (99.9% by ANN with temporal data and 99.7% by CNN with spectral data, in reasonable noise conditions). This work paves the way for deploying the high efficiency and cost-effective fiber optic DAS to monitor RPW in open-air and large-scale farms containing thousands of trees.

Distributed Fibre optic Sensing is an innovative technology enabling to turn a fibre optic cable into hundreds to thousands of sensors. This solution can be adapted for temperature, strain or acoustic sensing using a same optical fibre. It then appears as a powerful leverage for the monitoring of Enhanced Geothermal Systems during geothermal production. In the framework of the European funded project MEET, FEBUS OPTICS has been mandated for deployment and exploitation of a fibre optic cable in an observation well located in the geothermal plant of Soultz-sous-Forêts. Distributed Temperature Sensing, Distributed Strain and Temperature Sensing and Distributed Acoustic Sensing monitoring have been achieved at various moments after the fibre optic cable descent. We observe and discuss here the results of those acquisition campaigns.

In this work, we present the signal-to-noise ratio comparison results of six different buried fiber optic cable for identical external perturbations using a home-made direct detection φ-OTDR system.

A spatio-temporal oversampling-downsampling fiber DAS system is proposed and demonstrated. Without increasing the complexity and cost of the system, the demodulated SNR can be increased by 15dB, and the fading noise can be completely eliminated.

A tunnel steel loop reinforcement invalidation monitoring technology based on optical fiber distributed acoustic sensing (DAS) is proposed and demonstrated. Assisted with machine learning, the identification accuracy rate of invalid degree is up to 97.8%.

Summary Distributed acoustic sensing (DAS) is a a powerful technology for seismic data acquisition. Employing optical fibres, DAS senses strain induced by seismic wavefields along the tangent of the fibre. The noninvasive nature of DAS allows for its use in borehole applications not accessible by traditional geophones, including producing wells, injecting wells, and treatment wells during hydraulic fracture treatment. The complementary data supplied by DAS at transmission angles holds the potential to improve parameter estimates provided by inversion frameworks like full waveform inversion (FWI). Little work has focused on the inclusion of the data supplied by DAS in FWI, usually assuming a straight fibre in a vertical well. Here we present a method for full waveform inversion of DAS data that is flexible in its ability to consider data from arbitrarily shaped DAS fibres. The approach we propose here also offers the ability for simultaneous inversion of complementary DAS and geophone datasets, improving the quality of parameter estimates over considering either dataset alone.

Optical fiber networks can be transformed into powerful seismic sensing arrays through Distributed Acoustic Sensing (DAS). We review here the principles of DAS and the opportunities it offers in seismic monitoring, particularly in the sea-bottom.

We use distributed acoustic sensing to determine the velocity of trains from train vibration patterns using artificial neural network and conventional algorithms. The velocity uncertainty depends on track conditions, train type and velocity.