Fibre optic temperature sensing: application for subsurface and ground temperature measurements

doi:10.1016/0040-1951(95)00124-7

Tectonophysics

Volume 257, Issue 1, 30 May 1996, Pages 101-109

https://doi.org/10.1016/0040-1951(95)00124-7 Get rights and content

Abstract

The Distributed Fibre Optic Temperature Sensing Technique represents a new physical approach for temperature measurements. It is based on optical time domain reflectometry (OTDR). A laser pulse is coupled into an optical fibre and a small part of the light is backscattered as the pulse propagates through the fibre. Intensity and spectral composition of the backscattered light are determined by the molecules in the optical fibre. The Raman backscattering component is caused by thermally influenced molecular vibrations. Thus, its intensity depends on temperature. The velocity of light propagation in an optical fibre is well known, therefore, the backscattering intensity can be allocated to distance using the travel time of the backscattered light. Thus, an optical fibre works as a distributed temperature sensor which gives temperature and distance simultaneously for the entire length of the optical fibre.

To test the method studies have been made on the temperature resolution, the consistency with high-resolution borehole measurements using standard temperature probes, the capability of the method for measuring short-term temperature variations during fluid logging experiments, for long-term technically induced temperature variations in boreholes as well as for studying the two-dimensional distribution of the ground surface temperature for a given area.

From the measurements it follows that the optical fibre temperature sensing technique can be used under field conditions. The optical sensing cable can be installed in any horizontal, vertical, inclined or areal configuration. The method should be used especially for surveying the temperature field and its variations with time rather than for standard borehole logging.

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There are more references available in the full text version of this article.

Cited by (26)

Clogging detection and productive layers identification along boreholes using Active Distributed Temperature Sensing
2023, Journal of Hydrology
Fiber-Optic Active Distributed Temperature Sensing (FO-ADTS) experiments were performed on an Aquifer Thermal Energy Storage system (ATES) site located on the university campus of Bordeaux, France. The experiments consisted in heating the steel core of the FO cable while monitoring the rate of temperature increase during the heating periods. The changes in temperature, that were monitored through time at every depth under various hydraulic conditions and in different boreholes, were used to evaluate both aquifer properties and wells conditions. A first ADTS experiment was conducted under cross borehole configuration using a pumping well and a monitoring well separated by a distance of 8.5 meters. Then, to check the reciprocity of the results, a second experiment was conducted by switching the monitoring and the pumping well. The results obtained through the use of analytical solutions for reproducing and interpreting the data lead to the following conclusions: (i) ADTS can be used to estimate both thermal conductivity and Darcy velocity distribution along boreholes, crucial properties for ATES performance. (ii) The proposed method is a promising tool to detect clogging locations in the boreholes when it occurs. This can be of great practical interest to maintain systems performance, since, once FO cables deployed, experiments could be easily repeated without opening boreholes and stop the system operation.
A novel Deep-Learning model for RDTS signal denoising based on graph neural networks
2022, Optical Fiber Technology
Citation Excerpt :
Optical sensors [1–3], force sensors [4] and RDTS are usually used for external environment detection. Due to its low cost, long monitoring distance, immunity to electromagnetic interference and corrosion resistance, RDTS has been widely used in many fields such as nuclear facility monitoring [5–12]. However, in practice, the optical signal propagation in wavelength division multiplexer (WDM) [13] and avalanche photodiode (APD) [14] is affected by varying degrees of random noise, which significantly reduces the signal-to-noise ratio (SNR).
Focusing on the problem of increasing the deviation of temperature measurement for Raman-based distributed temperature sensor (RDTS) caused by random noise, a new method of applying a three-layer GraphSAGE-based graph neural network (3L-GraphSAGE) to noise reduction is proposed, where the spatial relationship between each signal is first constructed, and then the effective denoised results are obtained from the developed 3L-GraphSAGE model. First, an experimental setup is built for collecting fiber signals. Then, the datasets are input into the 3L-GraphSAGE to train the model. Finally, the test datasets are input into the well-trained 3L-GraphSAGE model to obtain effective denoised signals. To evaluate the performance of 3L-GraphSAGE, three evaluation indexes are calculated, including maximum deviation (MD), root mean square error (RMSE) and smoothness. The experimental results show that it can efficiently suppress the random noise and reduce the temperature measurement deviation in RDTS compared with direct demodulation of the raw data, and significantly improve the curve smoothness compared with wavelet transform by soft threshold function (WT-soft) and fast waveform type (FWT). Therefore, 3L-GraphSAGE model can provide an available method for improving the performance of RDTS.
Raman scattering-based distributed temperature sensors: A comprehensive literature review over the past 37 years and towards new avenues
2022, Optical Fiber Technology
Over the last 37 years, particular interest has been directed towards exploring the characteristics of the optical environment for sensing, giving rise to what would now be one of the largest applications of well-known optical fibers, typically employed to transmit data at high rates. Sensing temperature, pressure, liquid level, deformation, and other physical parameters utilizing optical fibers has become a growing branch of research and a business competing with well-established electrical sensors in the industry. Optical fiber sensors have all the inherent characteristics of a fiber optic cable, such as electromagnetic immunity, small size and weight, multiplexing, and so on. These exclusive features have made fiber sensors so versatile as to become a transformative technology by enabling several industrial processes to be carried out with higher reliability. Nowadays, there are several optical sensors, including fiber Bragg grating, interferometric, polarimetric, polymer fiber, distributed, and several others. Specifically, Raman-based distributed temperature sensor (RDTS) is a class of fiber optic sensors broadly employed in temperature measurement of large structures such as oil and gas wells, tunnels, and pipelines. Since 1985, many techniques have been proposed to break through the barriers of exploring Raman scattering as a distributed temperature measurement method. Range, spatial and temperature resolutions have been the most investigated parameters. In this perspective, this paper presents a comprehensive review focused on the progress of the RDTS technology over the past 37 years (1985–2022), covering an analysis of over 500 journal papers. First, a brief introduction to fiber optic sensor technology is presented as a theoretical basis, discussing the emergence of distributed sensors. Subsequently, Raman scattering in optical fibers is introduced, as well as how this nonlinear effect can be used to build temperature sensors. Next, RDTS technology is detailed, followed by a discussion of its applications and evolution over nearly four decades of development. Lastly, future perspectives are addressed in this review for the advancements in distributed temperature sensor technologies.
RDTS noise reduction: A fast method study based on signal waveform type
2021, Optical Fiber Technology
Citation Excerpt :
Due to Raman-based Distributed Temperature Sensor (RDTS)’s low cost, long monitoring distance, immunity to electromagnetic interference, and corrosion resistance, it has been widely used in such applications as subsurface and ground temperature measurements [1], motor stator monitoring [2], oil well liquid level detection [3], pipeline leakage detection[4], power cable monitoring [5], nuclear facilities and equipment anomaly monitoring [6–8], etc.
In order to reduce the measurement error of Raman-based distributed temperature sensor (RDTS) caused by random noise, we have proposed an effective noise reduction method, which can reduce the time consumption of data processing due to the low time complexity of the method. We classified the signal as five models based on the waveform types, thus to filter the raw data according to the waveform types. Then, we established an experimental device to test the effects of different signal noise reduction methods, including maximum deviation (MD), root mean square error (RMSE), smoothness, and time consumption. Experimental results show that it can efficiently suppress random noise and reduce temperature measurement errors in RDTS compared with direct demodulation of the raw data, and significantly improve the curve smoothness compared with D-SVD and WT-Soft. The time consumption test based on three different devices shows that the time consumption of the proposed method is approximately 10% of the D-SVD method, and about 30% of the WT-Soft method. It proves that this method is an effective and fast noise reduction method in RDTS systems.
Hydrogeophysical characterization and monitoring of the hyporheic and riparian zones: The Vermigliana Creek case study
2019, Science of the Total Environment
Citation Excerpt :
Other examples comprise 3D ERT acquisitions from the surface to monitor surface water-groundwater interactions (Johnson et al., 2012), or in boreholes using the river water as tracer (Coscia et al., 2011), while Cardenas and Markowski (2010) present a 2D ERT time-lapse monitoring with electrodes placed on the streambed and partly also on the adjacent soil surface. With regard to the DTS, despite being a relatively recent technique in the hydrogeophysical field (e.g. Hurtig et al., 1996), many applications are available in the literature: some authors investigated the surface water-groundwater interactions placing the fiber-optic cable on the riverbed, also in contaminated contexts (e.g. Anderson et al., 2014; Briggs et al., 2012a, 2013; Mwakanyamale et al., 2012; Slater et al., 2010; Voytek et al., 2014; Westhoff et al., 2011), while others opted for vertical boreholes, with the fiber-optic cables wrapped around a PVC tube (e.g. Briggs et al., 2012b; Vogt et al., 2010). Although all these pieces of work demonstrate the wide applicability of both ERT and DTS for a better characterization of the regions surrounding a riverbed, literature lacks (to the best of our knowledge) of studies where the instrumentation is located beneath the riverbed, i.e. directly inside and/or surrounding the hyporheic zone where the exchanges between surface water and groundwater occur.
The hyporheic and riparian zones are critical domains in a river ecosystem since they mediate the interactions between surface water and groundwater. These domains are generally strongly heterogeneous and difficult to access; yet their characterization and monitoring still rely mostly on hard-to-perform invasive surveys that provide only point information. These well-known issues, however, can be overcome thanks to the application of minimally invasive methods. In this paper, we present the results of the hydrogeophysical characterization of the Vermigliana Creek's hyporheic and riparian zones, performed at an experimental site in the Adige catchment, northern Italy, by means of electrical resistivity tomography (ERT), distributed temperature sensing (DTS), and hydrological modeling. A major advancement is given by the placement of electrodes and of an optical fiber in horizontal boreholes at some depth below the river bed, put in place via directional drilling. The results of this static and dynamic (time-lapse) geophysical characterization identify the presence of two subdomains (the sub-riverbed and the left and right banks) and define the water flow and solute dynamics. The ERT information is then used, together with other hydrological data, to build a 3D subsurface hydrological model (driven mainly by the watercourse stage variations) that is calibrated against local piezometric information. A solute transport model is then developed to reproduce the variations observed in the dynamic geophysical monitoring. The results show good agreement between ERT data and the model outcome. In addition, the transport model is also consistent with the temperature data derived from DTS, even though some slight discrepancies show that the heat capacity of the solid matrix and heat conduction cannot be totally neglected.
Distributed Temperature Sensing for Soil Physical Measurements and Its Similarity to Heat Pulse Method
2018, Advances in Agronomy
Citation Excerpt :
It was then applied in the oil and gas industry throughout the 1990s (Kersey, 2000), and in the environmental sciences for temperature monitoring since the mid-1990s (Forster et al., 1997; Hurtig et al., 1994, 1996), but only starting in the mid-2000s had it achieved an acceptable spatial and temporal resolution for environmental studies, for example, for measurements of soil temperature, water content, or thermal properties (Dong et al., 2015b; Selker et al., 2006a, b; Suárez et al., 2011b; Tyler et al., 2009; Weiss, 2003). Recent improvements in DTS systems make them a very powerful tools capable of obtaining distributed measurements of temperature (Hurtig et al., 1994, 1996) at high precision, high temporal, and spatial resolutions (e.g., 0.01°C, ~ 0.1–60 Hz/1–60 s at 0.1–2 m spacing) from meters to tens of kilometers in length with just a single instrument. FO cables have been widely deployed in telecommunication industries over the last few decades due to their good performance in light transmission.
Application of the distributed temperature sensing (DTS) system in environmental and earth sciences is a rapidly evolving field. The aim of this review is to provide information to the novice and expert alike for the use of a DTS system for soil physical measurements. DTS is capable of measuring soil temperature at scales of meters to kilometers, and soil thermal properties and water contents can be derived based on DTS-measured temperatures. This literature review summarizes the interdisciplinary results obtained by theoretical, experimental, and numerical methods in laboratory and field investigations. This review is organized as follows: (1) review of theories and principles for Raman-DTS, the components of a DTS system, methods for measurements, calibration, data interpretation, and accuracy and precision assessment of the DTS method for soil science and hydrological application; (2) discussion of the applications of the DTS method for soil temperature, thermal properties, and water/moisture measurement; and (3) discussion of the limitations and perspectives for the application of DTS and its similarity to the heat pulse method. The chapter closes with a brief overview of future needs and opportunities for further development and application of the DTS method.

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Fibre optic temperature sensing: application for subsurface and ground temperature measurements

Abstract

Distributed Fiber Optic Temperature Sensing

Distributed optical fiber Raman temperature sensor using a semiconductor light source and detector

Electron. Lett.

Distributed sensing using stimulated Raman action in a monomode optical fibre

Photonic distributed sensing

Phys. World

Fluid logging with fixed probe arrays