Distributed Temperature Sensing System Research Articles

Novel transient-state analysis approach for distributed temperature sensing based on spontaneous Raman scattering

The light scattering phenomenon in optical fibres has been implemented in several applications for years. Nowadays, commercial distributed sensing systems for temperature measurements – distributed temperature sensing (DTS) – are gaining more attention and are being applied in many fields. The DTS systems are commonly based on optical time domain reflectometry or optical frequency domain reflectometry analysis approaches. This paper presents the simulation model and primary experimental results of a novel approach for data analysis for DTS systems based on the measurement of the backscattered Raman anti-Stokes radiation: the optical transient-state domain reflectometry. The novelty of this approach is the fast and accurate proposed analysis algorithm, as well as the cost-effective, secure and reliable set-up, whose main aspect is the implementation of long, low-power input laser pulses.

A Novel Approach to Raman Distributed Temperature-Sensing System for Short-Range Applications.

A novel approach to the development of Distributed Temperature-Sensing (DTS) systems based on Raman Scattering in Multimode optical fibers operating at around 800 nm is presented, focusing on applications requiring temperature profile measurement in the range of a few hundreds of meters. In contrast to the standard Raman DTS systems, which aim to shorten the pulse space width as much as possible to improve the precision of measurement, the novel approach studied in this work is based on the use of pulses with a space width that is approximately equal to the distance covered by the fiber under test. The proposed technique relies on numerical post-processing to obtain the temperature profile measurement with a precision of about ±3 °C and a spatial resolution of 8 m, due to the transaction phases of the optical pulses. This solution simplifies the electronic circuit development, also minimizing the required laser peak power needed compared to the typical narrow pulse techniques.

Experimental study on a Dual-Source Heat Pump in ground mode to assess the soil thermal response by means of a Distributed Temperature Sensing system

In this paper, a Dual-Source Heat Pump (DSHP), able to exploit both aerothermal and geothermal energy sources, has been tested in ground mode to evaluate experimentally the soil thermal response in presence of an undersized Borehole Heat Exchanger (BHE) field. The field is instrumented with a Distributed Temperature Sensing (DTS) system, by which the geothermal fluid temperature can be measured over the entire length of the boreholes during the heat pump operation. The DSHP has been tested to reproduce the working profile of a heat generator coupled to a reference building, which has been numerically simulated by means of ALMABuild, a Matlab-Simulink tool. Three operating profiles have been identified within the simulation results to define three typical days of the heating season, characterized by different required loads. The results show that a DSHP operated in ground-mode and coupled to a borefield 50% undersized can meet completely the heating needs of a typical winter day, whilst higher building loads must be satisfied exploiting both air and ground sources. In this case, 80% of the undisturbed temperature of the soil can be recovered in an hour when aerothermal energy is extracted, thus the unit efficiency remains high and the investment cost is strongly reduced.

Using Distributed Temperature Sensing for Long-Term Monitoring of Pockmark Activity in the Gulf of Patras (Greece): Data Processing Hints and Preliminary Findings.

Patras Gulf pockmark field (Western Greece) is a tectonically controlled field that has been activated at least twice by strong earthquakes (M5.4, 14 July 1993 and M6.4, 8 June 2008), and episodic gas seepages have been recorded in the past using geophysical means. A distributed temperature sensor (DTS) system was deployed inside a shallow pockmark and along an active fault at the northern end of the field. This ongoing experiment represents the first long-term monitoring ever conducted on gas-bearing pockmarks and active faults by the DTS system. For now, we have acquired and analyzed data regarding about 1.56 years. One of the primary objectives of this study is to establish methodological queues for data processing and analysis, including spectral analysis and incomplete data treatment techniques, to be standardized for use in further stages of the experiment. Spectral analysis was proven capable of separating the temperature footprint of background environmental components, such as sea-atmosphere heat flux, tides, and winds/waves, from high-frequency temperature residuals. Those residuals represent unusual events that might be correlated to seismicity. Monitoring the causal relationship between seismic activity and seabed water temperature changes in the field was thus attempted. No significant local earthquakes occurred during the monitoring period. Although the relation between seismicity and irregular seabed water temperature events was not systematic, we postulate that four thermal events have a causative link with the local seismicity. The DTS system constitutes a low-cost monitoring system, and the promising preliminary results of this experiment suggest that it is worth testing for a longer period.

Mathematical Modeling of Seepage–Temperature Field for Earth Dam Using Experimental Test

Monitoring the seepage field is essential to characterize the operation of the earth dam. However, conventional seepage monitoring typically involves the use of a piezometer tube or pressure sensor for point distribution. A mathematical model incorporating the feedback of the temperature field on the seepage field was proposed based on experimental test observations. First, a theoretical analysis of the mathematical model is conducted, which includes examining the relationship between the variation of temperature field and factors, such as hydraulic gradient, water and soil temperature difference, hydraulic conductivity, thermal conductivity, specific heat, and time. Second, a homogeneous earth dam model is constructed in the laboratory with a distributed temperature sensor system to obtain synchronous information of the seepage–temperature field. Finally, the parameters of the mathematical model are quantified using observations from experimental tests, demonstrating good agreement between calculated and measured values. The experimental results indicate the feasibility of inferring seepage field monitoring information from the temperature field and elucidation of the interaction mechanism of the coupled fields. The quantitative mathematical model of the temperature field feedback on the seepage field is validated for its applicability in earth dams.

Permanent Fiber-Optic DTS Evaluates Production Enhancement

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 31654, “Production Enhancement Evaluation Through Permanent Fiber-Optic Distributed-Temperature-Sensing Interpretation for a Gas-Lifted Producer in Field B, Offshore Malaysia,” by Chang Siong Ting, Nur’ain Minggu, and Dahlila Kamat, Petronas, et al. The paper has not been peer reviewed. Copyright 2022 Offshore Technology Conference. Reproduced by permission. _ In the complete paper, the authors evaluate the effectiveness of production-enhancement activities for Well B Long-String (i.e., Well BL) using distributed-temperature-sensing (DTS) technology. Installation of permanent fiber-optic cable across the reservoir sections has enabled gas-lift monitoring, identification of well-integrity issues, and zonal inflow profiling from perforation contribution. The effectiveness of executed remedial jobs is described along with findings and interpretations of DTS results. Field and Well BL Background Field B is a mature brownfield 45 km offshore east Malaysia in a water depth of approximately 230 ft. The field’s structure has a gentle rollover anticline with a collapsed crest caused by growth faulting. The reservoirs were deposited in a coastal shallow marine environment with channels. The production wells completed in these reservoirs were completed with internal gravel packs. The typical completion types for wells in Field B are dual strings with sliding sleeve doors (SSD), intended for commingled production from the multilayered reservoirs. Most of the wells in Field B were installed with permanent downhole gauges (PDGs), and five wells were equipped with permanent DTS across the reservoir section. The well was completed in 2015 as a gas-lifted dual-string producer with a 3½-in. completion string for short string (BS) and 3½×2⅞-in. tubing crossover for long string (BL). The long string of Well B also produces from two zones, Zones 2 and 3, while the short string of Well B produces from only one zone, Zone 1. Each zone consists of sublayers. In addition, DTS fiber-optic cable was installed along the long string across the reservoir sections in Well BL, and the system enabled the operator to monitor continuously the wellbore temperature across all producing intervals. Each zone also was equipped with a zonal PDG (temperature and pressure) and SSDs. DTS System The double-ended DTS system was installed permanently across the multilayered reservoir in Well BL to measure the dynamic change of temperature in the near-wellbore region over time. Double-ended temperature measurement was used to correct for differential light losses (light-loss correction) that appear gradually over the lifetime of the fiber as its quality is degraded because of hydrogen darkening or exposure to high temperatures. This measure improves the quality and accuracy of the measurement signal backscattered to the surface receiver for processing. With double-ended DTS, small thermal changes over time in the well can be tracked. Temperature measurements are detected in 1.6-ft intervals along the length of the cable. This generates a profile of temperature effects along the production string by analyzing backscattered Raman wavelength light from a pulsed laser source. This DTS measurement allows continuous monitoring of production events as they happen.

Fabrication technology and performance tests for optical fiber-encapsulated, high-temperature superconducting tapes

Realizing fast and accurate quench detection is a great challenge for the application of long high-temperature superconducting (HTS) conductors. The combination of a distributed temperature sensing (DTS) system and optical fiber-encapsulated HTS (OFE-HTS) tape may become a promising approach to solve this problem. As a recently proposed composite HTS tape, its properties have not been studied systematically yet. Therefore, in this study, the electromagnetic and thermal behaviors of the OFE-HTS and traditional HTS tapes are compared by finite element simulation technology. The simulation results predict that the embedded optical fibers will hardly change the original electric, magnetic and thermal characteristics of the HTS tapes. In addition, a detailed fabrication method for OFE-HTS tape is introduced, and the composite tape performances including structural integrity, critical current uniformity, anti-bending/tensile force and quench response are tested seriatim. According to the microscope and x-ray detection results, the optical fibers are fully embedded in the OFE-HTS tape through the presented fabrication process. The critical current uniformity test results show the average critical current of the prepared 76 m long OFE-HTS tape is about 520 A, and the uniformity variation is about ±4%. The prepared OFE-HTS and traditional tapes have similar anti-bending/tensile properties. Finally, to check the effectiveness of the embedded optical fiber for quench detection, the fabricated OFE-HTS coil is tested. The quench detection results show that the temperatures in the same area measured by the optimized DTS system and a thermocouple are similar. Moreover, the temperature response ability of the optimized DTS system is better than that of the thermocouples, and the optimized DTS system is able to effectively avoid environmental electromagnetic field interference.

Studies on thermal profile measurement and fire detection in a power supply cable of a synchrotron radiation source by Raman optical fiber distributed temperature sensor system

The paper presents the work on development and application of Raman optical fiber distributed temperature sensor (ROFDTS). ROFDTS has been used for monitoring the temperature profile and detecting the progress of unforeseen fire events anywhere in a 160 m long power supply cable (current 760 A, DC) of dipole magnets in the Indus-2 synchrotron radiation source (SRS). Indus-2 is a national facility and is being operated in round the clock mode. The sensing fiber could survive in the harsh environment of Indus-2 SRS that consists of bremsstrahlung radiation of 6.7 Rad/h, high magnetic field of 1.5 T and radio frequency (RF) field of 1.27 MV at 505.812 MHz. The fire detecting capability of ROFDTS was first tested on the mock test setup in the laboratory by artificially creating the four hot zones. Each hot zone has the width of 1.0 m in the sensing fiber at the spatial locations of 26 m, 48 m, 70 m and 92 m respectively. An audio-visual alarm was generated when the temperature of the hot zones exceeded the set temperature limit of 50 °C within 30 s of the start of the fire. Finally, ROFDTS system was deployed to measure the temperature profile of power supply cable during ‘no operation’, ‘injection’ of the electron beam current (109 mA with the energy of electrons @ 550 MeV) and at ‘normal operation’ of the electron beam current (145 mA with the energy of electrons @ 2.5 GeV) in Indus-2 SRS. The peak temperature of power cable reached from 26 °C to 44 °C from ‘no operation’ to during the ‘normal operation’ condition of the Indus-2 SRS.

A Novel Deep-Learning Model for RDTS Signal Denoising Based on Down-Sampling and Convolutional Neural Network

Since the optical signal is attenuated when it propagates forward, the uncertainty of the measurement at the end of the optical fiber is increased, which restricts the performance of the Raman Scattering Distributed Temperature Sensing System (RDTS). Therefore, it is essential to study the signal denoising method of the system. Existing signal denoising methods, such as wavelet transform, median filtering, singular value decomposition, 1DDCNN, etc., still have room for improvement in parameter adjustment, computational complexity, and denoising effect. Thus, we have proposed a novel deep-learning model called the down-sampling double network model (DSDN) for RDTS signal denoising with high performance based on down-sampling and convolutional neural network (CNN). The DSDN model includes a down-sampling part, a one-dimensional full convolution part, and a ResNet part. It uses synthetic data as a training dataset. We have designed model performance evaluation experiments based on synthetic data and real RDTS data under different noise intensities. The root mean square error (RMSE) of the RDTS signal after DSDN noise reduction has been reduced to 0.189 °C, which is better than 2.117 °C of wavelet, 2.077 °C of median filter, 0.968 °C of 1DDCNN model. The mean absolute error (MAE) has been reduced to 0.165 °C, which is better than 1.716 °C of the wavelet transform, 1.402 °C of median filter, 0.564 °C of 1DDCNN. And smooth has been reduced to 0.074, which is better than wavelet's 1.298, median filter's 1.171, and 1DDCNN's 0.149. The results show that the DSDN model proposed in this article has excellent signal denoising performance and good robustness on different noise intensities and can be applied to RDTS systems.

New mathematical formulations for accurate estimate of nitrogen leakage rate using distributed temperature sensing in Mechanical Integrity Tests

Current practices for estimating calculated nitrogen leakage rate (CNLR) have been a great challenge in Mechanical Integrity tests (MIT) for underground solution-mined storage caverns due to the insufficient wellbore temperature measurements. The use of a traditional temperature logging system for detecting gas leakage relies on the existence of steady-state temperature conditions which is difficult to validate with current measurement technologies. Accurate estimation of CNLR is essential for making correct decisions on the use of underground caverns. Recently, an advanced MIT system with a new measurement technique, namely distributed temperature sensing (DTS), was developed to overcome the limitations of the conventional measurement system. DTS produces continuous measurements of real-time temperature data throughout the wellbore which are used to estimate the gas leakage rate. In this paper, new mathematical formulations for the DTS system are developed to adapt the new measurement technique and allow incorporating real-time temperature measurements in estimating both volume- and mass-based CNLR. The new mathematical formulations are applicable for unsteady-state temperature conditions and account for the compressibility effect of nitrogen gas. To evaluate the efficiency of the new mathematical formulations, a computational fluid dynamics (CFD) model for a solution-mined wellbore was developed and validated. The CFD model was then used to predict the thermodynamics response of complex leakage scenarios with minimum detectable leak rates (MDLR) for nitrogen and brine. The results demonstrate the ability of the DTS method utilizing the new formulations to improve the accuracy in estimating MDLR compared with conventional temperature logging methods. The advantage of using a mass-based formulation versus volume-based formulation is also highlighted.

Quantifying the coastal urban surface layer structure using distributed temperature sensing in Helsinki, Finland

Abstract. The structure of the urban boundary layer, and particularly the surface layer, displays significant complexity, which can be exacerbated by coastal effects for cities located in such regions. Resolving the complexity of the coastal urban boundary layer remains an important question for many applications such as air quality and numerical weather prediction. One of the most promising new techniques for measuring the structure of the surface layer is fibre-optic distributed temperature sensing (DTS), which has the potential to provide new significant insights for boundary layer meteorology by making it possible to study thermal turbulence with high spatial and temporal resolution. We present 14 weeks of profile measurements with a DTS system at an urban site in Helsinki, Finland, during the winter and spring of 2020. We assess the benefits and drawbacks of using DTS measurements to supplement sonic anemometry for longer measurement periods in varying meteorological conditions, including those found difficult for the DTS method in prior studies. Furthermore, we demonstrate the capabilities of the DTS system using two case scenarios: a study of the erosion of a near-ground cold layer during the passage of a warm front, and a comparison of the near-ground thermal structure with and without the presence of a sea-breeze cell during springtime convective boundary layer development. This study demonstrates the utility of DTS measurements in revealing the internal surface layer structure, beyond the predictions of traditional surface layer theories. This knowledge is important for improving surface layer theories and parametrisations, including those used in numerical weather prediction. The study also highlights the drawbacks of DTS measurements, caused by low signal-to-noise ratios in near-neutral atmospheric conditions, especially when such a system would be used to supplement turbulence measurements over longer periods. Overall, this study presents important considerations for planning new studies or ongoing measurements utilising this exciting and relatively new instrumentation.

A Review of Distributed Fiber–Optic Sensing in the Oil and Gas Industry

Fiber–optic sensors have been widely deployed in various applications, and their use has gradually increased since the 1980 s. Distributed fiber–optic sensors, which enable continuous and real–time measurements along the entire length of an optical fiber cable, have undergone significant improvements in underlying industries. In the oil and gas industry, distributed fiber–optic sensors can provide significantly valuable information throughout the life cycle of a well and can monitor pipelines transporting hydrocarbons over great distances. Here, we review the deployment of fiber–optic Rayleigh–based distributed acoustic sensing (DAS), Raman–based distributed temperature sensing (DTS), and Brillouin–based distributed temperature and strain sensing (DTSS) in the oil and gas industry. In particular, we describe the operation principle and basic experimental setups of the DAS, DTS, and DTSS, highlighting their applications in the upstream, midstream, and downstream sectors of the oil and gas industry. We further developed a prototype of a fiber–optic hybrid DAS–DTS system that simultaneously measures vibration and temperature along a multimode fiber (MMF). The reported hybrid sensing system was tested in an operational oil well. This work also discusses the challenges that might hinder the growth of the distributed fiber–optic sensing market in the petroleum industry, and we further point out the future directions of related research.

Studies on Thermal Profile Measurement and Fire Detection in a Power Supply Cable of a Synchrotron Radiation Source by Raman Optical Fiber Distributed Temperature Sensor System

Studies on Thermal Profile Measurement and Fire Detection in a Power Supply Cable of a Synchrotron Radiation Source by Raman Optical Fiber Distributed Temperature Sensor System

Field-scale experimental and numerical analysis of a downhole coaxial heat exchanger for geothermal energy production

The experimental and computational analyses of a 500 m deep coaxial borehole heat exchanger system for geothermal power generation are studied in this paper. The experiments are carried out on a high temperature resourced well with an average thermal gradient of 0.38 °C/m. The experiment lasts 456 h, and the findings are described in terms of fluid inlet and outlet temperatures, subsurface temperature distribution profiles over time, and flowrate. The in-situ ground temperature distribution profile is measured using Distributed Temperature Sensing System for different hours of the experiment. A detailed, three-dimensional, unsteady-state, finite volume-based computational model has been developed, which solves conjugate fluid-flow and heat transfer phenomena. The simulation outcomes are compared to the results of the experiments. With validated numerical model, to determine the circle of influence, temperature profile of the ground is observed at various radial distances from the borehole. A parametric study is performed by varying inlet temperature of the fluid, mass flow rate, and the thermal conductivity of the ground. The numerical model developed also predicts the temperature recovery behavior of the ground. The results indicate that the average output thermal power for 456 h from the geothermal system ranges from 172 kW to 262 kW based on operating condition chosen and the total thermal energy generated changes between 82 MWh and 194 MWh from a single borehole. After the extraction is terminated, around 86% of the initial ground temperature is restored after 456 h.

Distributed temperature sensing system based on a densely spaced FBG array for small fire recognition

A distributed temperature sensing (DTS) system based on a densely spaced fiber Bragg grating (FBG) array is proposed in this work for small fire recognition. A large capacity identical FBG array with centimeter-scale grating spacing is employed to build a high-density sensor network, increasing the probability that the small fire will affect at least one FBG. To retrieve the sensing information, we exploit an FBG interrogation system based on optical time-domain reflectometry and swept laser techniques, together with a fiber section (FS) spectrum interrogation method. The sensing technique consists in scanning the sensing array by means of a low-coherence wavelength-tunable pulsed laser and in reconstructing and analyzing the returned spectra signals. The sensing performance of the proposed DTS system is studied by theoretical analysis and experimental demonstration, verifying the feasibility and superiority of the densely-spaced FBG array based DTS system for small fire recognition and location.

Photovoltaic Panel Temperature Monitoring and Prediction by Raman Distributed Temperature Sensor With Fuzzy Temperature Difference Threshold Method

Solar cells can operate at a lower efficiency after a certain temperature, which is caused by a negative thermal coefficient. Therefore, the temperature prediction of photovoltaic (PV) modules is critical to accurately evaluate the efficiency of photovoltaic devices. We propose and experimentally demonstrate a Fuzzy Temperature Difference Threshold Method (FTDTM) based on Raman Distributed Temperature Sensor (RDTS) system for the detection and prediction of PV module temperature. The FTDTM consists of four steps, i.e., division of the universe, establishment of fuzzy relationships, definition of relationship matrix and calculation of predicted temperature. The experimental results show that the proposed RDTS can detect and accurately predict temperature trends by using the FTDTM. When the system window base of the FTDTM is set to 2, the average absolute error of the predicted temperature is 1.08 °C, and the fluctuation range of prediction error is ±3.7 °C. In addition, the experiment studied some factors affecting temperature distribution characteristics of PV modules, including solar radiation intensity, surface dust and inclination angle. We provide a solution for large-scale PV module temperature detection and early warning through RDTS systems with FTDTM.

Experimental study on temperature distribution measurement of an optical fiber encapsulated coil in liquid nitrogen

Fast quench detection technique is extremely important for high temperature superconducting (HTS) applications, especially HTS magnets. As one of potential candidates, the method based on distributed optical fiber sensors were suggested recently. To keep HTS tape structure intact and reduce thermal propagation time from HTS tape to optical fiber, a method that optical fiber is encapsulated in HTS tape edge along the length direction could be satisfied. In this paper, an optical fiber encapsulated tape (OF-tape) was successfully fabricated. To verify the feasibility of temperature measurement for this tape, a coil wound with OF-tape and a distributed temperature sensor (DTS) system were prepared. The main results show that temperature of the coil can be measured accurately in air and in liquid nitrogen. After suffering impulse currents with peak values of 570 A and durations of 1, 2, and 3 s, temperature rises of the coil are 98.5, 137.8, and 271.0 K, respectively. Moreover, the highest temperature appears from 3.6 m to 21.7 m of the coil when it suffers the impulse current of 460 A/3 s.

Estimation of Temperature and Associated Uncertainty from Fiber-Optic Raman-Spectrum Distributed Temperature Sensing.

Distributed temperature sensing (DTS) systems can be used to estimate the temperature along optic fibers of several kilometers at a sub-meter interval. DTS systems function by shooting laser pulses through a fiber and measuring its backscatter intensity at two distinct wavelengths in the Raman spectrum. The scattering-loss coefficients for these wavelengths are temperature-dependent, so that the temperature along the fiber can be estimated using calibration to fiber sections with a known temperature. A new calibration approach is developed that allows for an estimate of the uncertainty of the estimated temperature, which varies along the fiber and with time. The uncertainty is a result of the noise from the detectors and the uncertainty in the calibrated parameters that relate the backscatter intensity to temperature. Estimation of the confidence interval of the temperature requires an estimate of the distribution of the noise from the detectors and an estimate of the multi-variate distribution of the parameters. Both distributions are propagated with Monte Carlo sampling to approximate the probability density function of the estimated temperature, which is different at each point along the fiber and varies over time. Various summarizing statistics are computed from the approximate probability density function, such as the confidence intervals and the standard uncertainty (the estimated standard deviation) of the estimated temperature. An example is presented to demonstrate the approach and to assess the reasonableness of the estimated confidence intervals. The approach is implemented in the open-source Python package “dtscalibration”.

Analysis of Seepage in a Laboratory Scaled Model Using Passive Optical Fiber Distributed Temperature Sensor

Seepage is the key factor in the safety of dikes and earth-fill dams. It is crucial to identify and localize the seepage excesses at the early stages before it initiates the internal erosion process in the structure. A proper seepage monitoring system should ensure a continuous and wide area seepage measurement. Here, continuous monitoring of seepage at the laboratory-scale is achieved by a passive optical fiber Distributed Temperature Sensing (DTS) system. An experimental model was designed which consists of initially unsaturated sand model, water supply, seepage outflow, optical fiber DTS system, and water and air temperature measurement. Initially, the sand temperature was higher than the temperature of the seepage water. An optical fiber DTS system was employed with a high-temperature resolution, short sampling intervals and short time intervals for temperature monitoring in the sand model. In the system, the small variation in the temperature due to groundwater flow was detected. The numerical analysis was conducted for both the seepage process and the heat transfer progression in the sand model. The results of the heat flow simulation were evaluated and compared with the measured temperature by the optical fiber DTS. Obvious temperature reduction was obtained due to seepage propagation in the sand. The rate of temperature reduction was observed to be dependent on the seepage flow velocity.

Error correction of temperature measurement data obtained from an embedded bifilar optical fiber network in concrete dams

Conventional distributed optical fiber systems employed for internal temperature sensing in concrete dams suffer from low survival rate, insufficient measurement data, and low-accuracy temperature measurements that are subject to large fluctuations. Therefore, the present study proposes a bifilar optical fiber embedding technique running within each of the concrete dam blocks forming a dam. The proposed fiber optic network design is based on multiple considerations, including the embedding requirements of optical fiber to ensure good system longevity, the requirements of internal temperature monitoring in concrete dams to ensure the capture of adequate monitoring data, and the temperature measurement principle of distributed temperature sensing (DTS) systems to develop effective error correction methods. In terms of error correction, the light intensity attenuation caused by transmission- and wavelength-related losses is calculated based on the symmetrical temperature measurement points of the primary and secondary strands of the embedded bifilar optical fiber in conjunction with error correction theory to correct for temperature measurement fluctuations and thereby ensure the capture of accurate and stable temperature measurement data. Experimental error correction test results demonstrate that the mean absolute error (MAE) and root mean squared error (RMSE) of the error corrected temperature data obtained under various temperature conditions are reduced by 0.28 °C and 0.34 °C, with fluctuations that are decreased by 53.4% and 52.4%, respectively. The results derived from an actual engineering application under construction demonstrate that the survival rate of the embedded bifilar optical fibers is 100%. In addition, the average MAE and RMSE values of the temperature data obtained by the DTS system during the first water cooling stage are reduced by 0.14 °C and 0.22 °C, and their fluctuations are decreased by 41.5% and 47.0%, respectively. These results verify the reliability and feasibility of the error correction method proposed in this paper, and the method is demonstrated to provide reliable technical support for obtaining stable and high-precision DTS temperature data in concrete dams.