The Global Distributed Fiber Optic Sensor Market, By Technology (Rayleigh Scattering Based Distributed Sensor, Brillouin Scattering Based Sensor, Raman Scattering Based Sensor, Interferometric Distributed Optical-fiber Sensor, and Distributed Fiber Bragg Grating Sensor), By Application( Strain Sensing, Temperature Sensing, Acoustic/Vibration Sensing, Pressure Sensing, and Others), By Vertical (Oil & Gas, Security, Energy & Utility, Transportation Infrastructure, Industrial Application, and Others) and By Region (North America, Europe, Asia Pacific, Latin America, Middle East and Africa) - Global Forecast to 2027, is expected to be valued at US$ 3,015.6 million by 2027, exhibiting a CAGR of 10.2% during the forecast period (2021-2027), as highlighted in a report published by Coherent Market Insights.
Distributed fiber optic sensing systems uses fiber optic cables and interrogator unit. The interrogator units transmit a pulse of light into the fiber optic. This pulse of light travels into the fiber optic, and the strain events within the fiber optic are determined by backscattered light.
Fiber optic sensing technology has capability to transform the way mines are being controlled and monitored. Presently, the mining sector is facing various challenges such as conventional inaccurate measurement systems, unpredictable accidents, lack of data for decision making regarding safety of mines and staff working underground, late diagnostics of hazards and faults, and others. Optical fiber technology offers safe, reliable, accurate, and cost-effective sensing and monitoring solutions. Hence, introduction of advanced and cost-effective fiber optic monitoring and sensing solutions for the mining sector presents major opportunity for manufacturers of distributed fiber optic sensors.
The global distributed fiber optic sensor market is estimated to account for US$ 1,529.8 Mn by the end of 2020
Increasing Adoption in Oil & Gas Industry
The use of effective monitoring and sensing applications such as acoustic sensing and temperature sensing in association with fiber optic sensor has vastly improved the efficiency of oil and gas production and transportation across the globe, which is encouraging deployment of distributed fiber optic sensors in oil and gas plants. One of the types of distributed fiber optic sensors, is sensitive to change in acoustic fields, regardless of the source. Hence, it becomes a primary choice to be deployed in the oil and gas industry for monitoring/surveillance of pipelines from third-party intrusions.
Furthermore, enhanced oil recovery (EOR) entails deployment of various techniques for increasing production of oil and gas from existing reservoirs. EOR comprises three main categories: thermal recovery, gas injection, and chemical injection. All these categories require effective monitoring (pipeline monitoring, well monitoring, seismic acquisition and permanent reservoir monitoring, and many more) solutions. Distributed fiber optic sensor (DFOS) enables monitoring on a truly distributed basis. Hence, DFOS is being implemented in reservoirs across the MEA region in order to achieve maximum extraction of oil from oilfields.
Additionally, the increasing number of serious incidents related to oil and gas pipelines across the U.S. is a major factor driving the government’s shift in adoption of DFOS for monitoring and controlling purposes
Increasing Demand from Utility Sector
Distributed fiber optic sensor has wide range of applications in utility sector such as monitoring power generators, switchgear temperature monitoring, and others. Utility companies across the globe are deploying distributed fiber optic sensing technology for smart grid temperature monitoring of high voltage switchgear. Distributed fiber optic sensors provide real-time temperature data, which enables operators to balance thermal stress and maximize load-efficiency that may cause system failure.
Power theft and tempering is a major concern worldwide costing energy and utility industry major losses. For instance, according to Coherent Market Insights’ report, globally, power companies lose US$ 10,200 million annually due to meter tampering, billing issues, power theft, etc. Tampering and theft of power supply can create electricity disruption and operational losses for electricity companies. The current methods of tracking metal and electricity theft can be time-consuming and expensive, as these methods are based on simulation and finding the adjacent issue becomes difficult. For such problems, distributed fiber optic sensors can provide an effective solution, as technology such as Distributed Fiber Optic Sensor does not get affected by electromagnetic field and provides continuous monitoring over single network, which helps to quickly detect the location and root cause.
Features of fiber optic such as passive nature and inherent reliability are expected to make distributed sensing a success in the utility sector. Moreover, to prevent electricity theft, many electricity providing companies are partnering with DAS solution provider companies. For instance, in November 2018, Bandweaver, a U.K.-based DAS solutions providing company, entered an agreement with Edesur SA, an Argentina-based distributor of electricity and India-based infrastructure firm SSS Group. Through this agreement, Bandweaver SA deployed Edesur SA Horizon DAS system at a sub-station in Santo Domingo, Dominican Republic to prevent power and metal theft.
Lack of Awareness, High Initial Cost, and Low Signal-to-noise Ratio of DAS Sensors
Lack of awareness about the advantages offered by fiber optic sensors and high cost are primary factors hampering growth of the global distributed fiber optic sensors market. Although demand for Distributed Fiber Optic Sensor solutions is increasing, owing to its cost-effective way of securing large areas, factors such as high initial cost (one time) and low signal-to-noise ratio may hamper growth of the market over the forecast period (2020-2027)
The major challenge during implementation of DAS sensors is that the data acquired from DAS has more noise as compared to conventional sensing technologies such as geophones. This noise is generated by interrogator unit, while the time-variant optical noise occurs equally on all receivers. This noise makes calibration of devices difficult and detection of weak signals, especially in cases of microseismic applications, is a challenge.
Furthermore, in order to ease the limitations associated with removing the time-variant noise generated from temperature fluctuations in the pipeline and optical noise, technologies such as median filter, band-pass filter, and stacking of multiple fiber measurements have been developed
Growing Adoption of Artificial Intelligence and Machine Learning for New Generation of Distributed Optical Fiber
As the first generation of optical fiber sensors have reached maturity, recent development in this sector has resulted in the possibility of a new generation of distributed optical fiber sensors. To improve the quality and technology of sensors, BigData and artificial intelligence are playing an important role. DAS solutions generate a large volume of data in a short period of time, which in turn, creates challenges for companies to store this data. For instance, during a typical hydraulic fracturing monitoring operation, a distributed fiber optic sensing system can generate data up to 5 TB per day or 1 TB an hour with ultrasensitive systems. This has created demand for new algorithms to convert data into meaningful insights. Machine learning and artificial intelligence methods are used with imaging technologies to analyze the data collected from sensor and develop new distributed fiber optic technologies. For instance, in January 2017, Future Fibre Technologies launched Aura Ai, a product that uses latest advanced optical signal processing algorithms, combined with artificial intelligence, to discriminate between intrusions, nuisance alarms, and other causes of fence disturbance. Major market players are focused on launching new products and services to manage large volume of data. For instance, in March 2017, Schlumberger launched Lift IQ production life cycle management service, which offers monitoring, diagnostics, and optimization of artificial lift systems in real-time. This new service securely collects, transmits, evaluates, and interprets data to improve production efficiency, extend equipment run life, and reduce operating costs. With this development, the company aims to use real-time data to improve equipment life and uptime.
Key players operating in the global Distributed Fiber Optic Sensor market are OSENSA Innovations Corp., AFL, SOLIFOS AG, Schlumberger Limited, FISO Technologies Inc., Yokogawa Electric Corporation, OFS Fitel, LLC., AP Sensing, Luna Innovations Incorporated, OptaSense, NEC Corporation, Halliburton Company and Omnisens S.A.
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