Determination of Water Injection Zonal Allocation From Distributed Temperature Sensing Data

<ns0:p>This paper presents an innovative modeling of continuous fiber-optic measurements to improve the dynamic characterization of injection wells during the early stages of carbon capture and storage (CCS) projects. The approach uses distributed temperature sensing (DTS) data collected along the well profile to map the thermal behavior in real time during three key phases: before injection begins, during the initial regime when carbon dioxide (CO2) displaces the brine in the tubing and fills the borehole, and during full stable operation. This physics-based methodology provides fluid mapping based on DTS, as well as a comprehensive description of the well thermal performance, essential for understanding and optimizing CO2 injection. The results obtained during CO2 injection into a depleted natural gas reservoir demonstrate the present method. The injection well completion is equipped with permanent fiber-optic cables for continuous DTS monitoring down to the production packer. While standard DTS can be used to monitor the well thermal performance during steady-state operations, other factors are essential for accurately monitoring the distributed temperature profile during transient operations. This study begins with an analysis of brine displacement from the tubing into the borehole during well commissioning. The dynamic behavior of CO2 during these operations led to thermal effects along the well tubing, which were addressed through an innovative analysis of DTS data. A reprocessing of the space-time temperature measurements was implemented to distinguish between the downward movement of gas and liquid within the tubing. This made it possible to locate the real-time position of the contact between CO2 and brine in the tubing, thanks to their different physical properties. DTS measurements and reprocessing outputs were successfully used to calibrate a physics-based well simulation model that describes fluid dynamics and thermodynamics, involving complex well geometries and multiphase flow conditions. Thus, the DTS-calibrated physics-based simulation model provided insight into the well’s thermal evolution and allowed for the real-time computation of important physical properties, such as the density, phase, and pressure profiles of CO2. The presented methodology provides strong dynamic characterization of CO2 injection wells from the beginning of a CO2 transportation and storage (T&amp;S) project. The resulting calibrated wellbore models are essential for CO2 injection optimization, flow assurance, and risk management. While there are several approaches to maximize information from permanent DTS data, quantitatively using temperature evolution for dynamic modeling is a novel technology that can shed light on the early and uncertain stages of CO2 T&amp;S projects.</ns0:p>

Fiber optic measurements including Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) have been established as common tools to monitor the downhole condition during hydraulic fracturing treatment as well as during production. Several authors presented a methodology of quantitative interpretation for DAS and DTS data to estimate injected/produced fluid volume distribution among perforation clusters. The quantitative interpretation allows us to not only diagnose the stimulation efficiency but also optimize the completion design for subsequent fracturing jobs. This study investigates how completion parameters are correlated with fracturing stimulation performance based on the field application of DAS and DTS interpretation methodology. The field data from MIP-3H provided by the Marcellus Shale Energy and Environmental Laboratory is analyzed in this work. As previously presented, a DAS/DTS integrated interpretation method estimates fracture half-length distribution for each stage. In this approach, fractures are assumed to be created in a swarm pattern from each perforation cluster. We do not assign fractures only at the perforation cluster locations but assume that multiple fractures are initiated along a stage interval with much smaller spacing than cluster spacing. This fracture swarm model is supported by several field observations. Once the DAS interpretation estimates the injected fluid volume for each perforation cluster, by considering the fluid volume distribution as an input parameter for the DTS interpretation, the temperature inversion provides the half-length of each fracture. This interpretation approach allows us to estimate uniformity of the fracture half-length distribution. To statistically describe the fracture uniformity, a uniformity index is defined. The estimated uniformity index is compared with inflow rate for each stage to investigate how the uniformity of fracture distribution contributes to well performance. The inflow profile is estimated by interpreting the DTS data during production. The comparison shows that the stages with uniform fracture half-length distribution are more productive. This result implies that the stages more uniformly stimulated become more productive. By observing the relationship between the uniformity index and several completion parameters such as injection rate, total volume of injected fluid, proppant concentration and so on, we can investigate what parameter is more influential to the fracture stimulation efficiency. The statistical analysis illustrates that the uniformity of the fracture half-length distribution and high productivity are correlated with high injection rate. Based on this study, the injection rate would be one of the primary design parameters to maximize the fracturing stimulation performance in this field case. As demonstrated in this study, the evaluation of fracturing stimulation design based on the interpretation of DAS and DTS data would be an essential approach to optimize it.

The diatomite reservoir in the Belridge field, California, has been undergoing water injection for pressure maintenance to mitigate reservoir compaction and improve oil recovery. The reservoir is over one thousand feet thick with multiple layers, high compressibility, and very low permeability. Accurate placement of injection water across this massive reservoir is essential for balancing layer by layer voidage and reducing compaction. Therefore, monitoring sub-surface injection profile has become an important part of diatomite waterflood surveillance. However, monitoring profile with conventional wireline radioactive tracer tools has proven to be challenging due to the inability to access wellbores for logging because of scale build-ups or casing deformations. Over the past several years, a number of field trials have been performed to see if injection profile could be monitored using distributed temperature sensing (DTS) fiber-optic technology. If the technology works, then the strategy would be to install the DTS fiber early in the life of a well while the whole wellbore was still accessible. Once the fiber was in place, dynamic monitoring of injection profile could continue even if the well later developed scale build-ups, dog-legs, or other obstructions. Initial tests at Belridge were done with the DTS cable temporarily deployed on slickline. Once it was established that DTS could be used to measure injection profile in diatomite, several permanent installations were made in different areas of the field and in injectors with different mechanical configurations. Also, three different analysis methods were tried: stabilized injection; thermal restoration; and thermal tracer. In all cases, DTS-derived injection profiles were compared against wireline radioactive tracer profiles run at about the same time and under similar injection rates and pressures. Based on the technical success of the pilot, it was decided to scale-up to a 25-well program prior to full-field implementation in all 1000+ injectors in Belridge. This scaled-up program was focused on retrofitting DTS in existing injectors that still have an unobstructed well bore. These installations required the DTS cable to be run inside the injection tubing to the current effective depth of the well. However, the presence of the fiber-optic cable inside the tubing made the well unserviceable for future interventions such as coil-tubing clean-out, stimulation, or cased-hole logging operations. For this reason, design work is currently under way to run the DTS cable outside the injector casing at the time of initial drilling and completion of the well. This paper is a case study of the application of a new technology in solving surveillance issues in an old field. It covers the slow but methodical implementation of the DTS project, the challenges, and our solutions. It presents many examples of injection profiles derived from DTS measurements and a comparative evaluation of different interpretation techniques. The learnings from this project have potential for application in other secondary or tertiary recovery operations that require measurement of injection profile or continuous monitoring of the injection front.

Designs and preliminary results from a multi-year project for simultaneous Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) executed across multiple wells on a Steam-Assisted Gravity Drainage (SAGD) field in Canada is presented. Primary objectives of the project were to demonstrate prototypical execution of DAS and DTS data collection on a standard SAGD pad setup and to characterize inflow across the production zone. Challenges and learnings from this technically demanding project are explored alongside a discussion on the improving viability of continuous acoustic monitoring to augment temperature sensing commonly utilized in SAGD instrumentation design. The DTS technique employs a combination of an optoelectronics topside instrument and a downhole sensing fiber to produce a distributed temperature profile of the fiber string. The topside instrument comprises a laser light source, a fast optical detector and a combination of electrical and optical circuits to control light pulsing, and the detection and measurements of Raman backscattered light containing encoded temperature information about the temperature profile. The sensing fiber type is selected based on suitability with the topside instrument and the expected maximum operating temperature of its intended sensing environment. While DTS is compatible with both single-mode (SM) and multi-mode (MM) fiber type, MM graded-index fibers are often selected for SAGD environment due to its larger optical core size. Using a MM fiber allows for increased capture of the backscatter Raman light, a much weaker light signal than the laser light launched into the optical fiber. Temperature dependent Raman signals are extracted from the returned light and by applying the Optical Time Domain Reflectometry (OTDR) technique, which produces a temperature trace consisting of temperature magnitude matched to each unit distance along the sensing fiber. The temperature trace can vary in its spatial resolution subject to the topside instrument configuration with typical resolving resolution between 0.5 – 1.5 meters. Other general DTS sensing techniques are described in the literature (for example, Hartog (2017)) but are not described here. Some of the earliest uses of DTS in thermal enhanced oil recovery (EOR) was to monitor steam breakthrough and pump vapor locking in California's steam flood as reported by Carnahan (1999). Since then, advancement in specialty fiber optics suitable for thermal environment upwards to 300°C has enabled mainstream adoption within SAGD. Uses of DTS data has expanded to include, but not limited to, monitoring of well and steam chamber conformance, tubing and casing integrity, gas ingression and water coning. DAS is an optical interferometry technique employing an optoelectronics topside instrument and a downhole sensing fiber to detect minute changes in fiber length at each location along the fiber string. The instrument is sensitive at the pico-strain (ρε) level with a spatial resolution equal to a configurable distance referred to as the gauge length. The term "acoustic" in Distributed Acoustic Sensing broadly designates any mechanical perturbation able to alter the local state of strain anywhere along the optical fiber, be it from dynamic pressure changes, or dynamic strain (e.g. vibration). While DAS is compatible with both SM and MM fiber type, deployment alongside SM fiber types have been traditionally preferred as the laser light coherence is better preserved throughout its round-trip propagation compared to MM fiber. However, DAS with MM fiber can still be used for typical fiber lengths in SAGD wells without significant penalty in signal quality as shown in literatures (MacPhail (2016), Burke (2022). This cross-compatibility with MM fiber allows collection of DAS on existing DTS fibers deployments without further intervention. Prior to DAS adoption in oil and gas, it was predominantly deployed in defense and security application to perform parameter monitoring and ground disturbance detection. As DAS technology evolved, it was first trialed in Shell's unconventional tight gas wells in February 2009 to monitor plug setting, perforation shots and active clusters during fracking operation (Molenaar et al. 2012). In EOR application like SAGD, DAS provides an augmenting dataset correlating to production inflow phases (MacPhail et al. 2016) which would not be readily detectable in the temperature domain alone. Efforts like the one presented in this paper are underway to progress horizontal inflow profiling and inferred relative volumes which aids in understanding well productivity and efficacy of added inflow control devices (ICD). Unlike DTS, acoustic data is largely unaffected by temperature masking due to well completions. For events where insufficient temperature deviation are produced, DAS may be used to surveille for common industry challenges such as steam coning, gas ingression, loss of tubing/casing integrity and more. The emerging market segment for Carbon Capture and Underground Storage (CCUS) is poised to utilize DAS as one of the many leak detection toolkit for the injection monitoring wells.

In order to gain insights into the hydraulic and thermal long-term behavior of deep geothermal boreholes during operation, a fiber-optic monitoring (FOM) system was implemented at the Stadtwerke Munich's (SWM) geothermal plant 'Sch&amp;#228;ftlarnstrasse' in the national project Geothermal-Alliance Bavaria (GAB). The permanently installed fiber optic cables enable continuous measuring of the temperature in boreholes with high spatial and temporal resolution via Distributed Temperature Sensing (DTS) and of acoustics/vibration via Distributed Acoustic Sensing (DAS). In 2019, one production and one injection well were equipped with FOM in different setups and have been collecting data since then. In the injector, the cable was cemented behind the anchor pipe in the upper section of the borehole, whereas the producer was equipped with a fiber-optic cable until the total depth of the reservoir. Additionally, a fiber-optic gauge provides pressure and temperature at the top of the reservoir in this well. Among other things, precise inflow profiling in the reservoir section of the producer could be carried out using the temperature data, which helps deepen the understanding of the hydraulic behavior of the reservoir. Changes over time in the temperature of the produced thermal water can be traced back to changes in the hydraulically active zones or inflow temperatures in the reservoir. Other factors that influence the wellhead temperature, such as borehole heat losses to the surrounding rock, can be quantified using the DTS data. At the beginning of 2024, a third fiber-optic cable will be installed in an injection well at the Sch&amp;#228;ftlarnstrasse geothermal site. A similar setup as in the production well will allow for continuous measuring in the entire borehole until total depth (TD) and pressure and temperature from p/T gauges at the top of the reservoir and at TD. Therefore, both production and injection conditions in the reservoir and wellbore will be continuously monitored at all depths using DTS and DAS for the first time. We present the first interpretations of the data collected from the newly installed FOM in the injection well as well as insights into the long-term monitoring of the hydraulic and thermal dynamics in the production well to underline the importance of permanent downhole monitoring to ensure efficient and sustainable use of the geothermal reservoir.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 194284, “Pushing the Limits of Damage Identification With Coiled Tubing in Extreme Conditions: A Success Story From Japan,” by Nozomu Yoshida, SPE, Satoshi Teshima, SPE, and Ryo Yamada, INPEX, and Umut Aybar, SPE, and Pierre Ramondenc, SPE, Schlumberger, prepared for the 2019 SPE/ICoTA Well Intervention Conference and Exhibition, The Woodlands, Texas, USA, 26–27 March. The paper was peer reviewed and is scheduled for publication in SPE Production &amp; Operations. The success of water-conformance operations often depends on clear identification of the water-production mechanism. Such assessment can be complicated significantly when formation damage is also occurring. Coiled tubing (CT) and distributed temperature sensing (DTS) were combined to overcome challenging conditions (high temperature, low injectivity, high deviation, long perforated intervals, and wellbore damage) to identify damaged oil zones and suspected water-bearing zones in an onshore well in Japan. Introduction Source and location affect the selection of water-shutoff techniques, which are either mechanical or chemical in nature or a combination. No matter the operational approach, identification of the water zone is a critical step for any subsequent course of actions. One method for the identification of water-producing zones is the use of production logging. Conventional production logging uses spinners and capacitance logs to detect water flow in the wellbore. Production logging tools (PLTs) can be deployed into the wellbore using slickline, wireline, or CT. To enable real-time evaluation of the acquired data, possible options include wireline, digital slickline, and CT equipped with either a conductor cable or fiber optics. In damaged wells with high water cut, flow conditions can be unstable, with drastic changes in flow regimes. Once the well can no longer sustain stable flow because of reservoir depletion or damage in the absence of an artificial-lift method, a PLT becomes impractical. Furthermore, when wellbore conditions are complicated by the presence of debris or contaminants, data acquisition itself becomes difficult. Quantification of the damage profile and of water-producing intervals is of great importance in proper planning for subsequent operations. To address these challenges, an alternative approach was used wherein DTS obtained through fiber optics deployed with CT was used to quantify damage profiles in severely damaged wells and to identify suspected water-bearing zones by integrating complementary information. The proposed operational procedures are similar to those used for the quantification of fluid placement during acidizing operations: injection of fluid to cool down the formation and shut-in to measure rate and amplitude of temperature recovery along intervals of interest. In the present case, brine was used as the injection fluid. Quantification of the damage and injection-rate profiles are achieved by temperature inversion; the measured DTS data are matched with the simulated temperature response given by combined flow and thermal numerical models accounting for key formation and near-wellbore parameters. The subject well was suspected to be severely damaged during the completion phase and yielded a relatively high water cut during flow test. This case not only highlights the validity of the proposed approach but also details the work flow and analyses performed to obtain meaningful data and to reduce uncertainty of the interpretation. The work also raises the importance of the integration of complementary data for a comprehensive understanding of well conditions.

This paper outlines the successful application of distributed temperature sensing (DTS) and fiber-optic-equipped coiled tubing (FOE-CT) in stimulating the first Carbon Dioxide (CO2) injector well in the UAE. A Real-Time Assisted Matrix Stimulation Engineering (RTA-MSE) workflow enabled accurate injection profiling over a 600-ft perforated interval, optimizing acid placement and volume. The treatment resulted in a more than five-fold increase in injectivity, with DTS confirming uniform post-treatment acid distribution. To mitigate coiled tubing (CT) exposure to the CO2 environment and avoid integrity risks, the wellbore fluid was initially displaced back to the formation using fresh water. In a single CT run, five DTS passes were recorded: DTS-1 for geothermal baseline, DTS-2 during freshwater injection to define the pre-treatment profile, and DTS-3 warm back to confirm flow distribution. Based on this data, the 28% hydrochloric acid treatment, enhanced with a nitrified stage, was optimized and pumped. DTS-4 and DTS-5—post-treatment injection and warm back—validated stimulation effectiveness. The CT was then safely retrieved, concluding the combined intervention and evaluation operation. This CO2 injector well—the first of its kind in the Middle East—was drilled into a saline aquifer. Post-drilling, it achieved an initial injectivity of 7 bpm at 1,000 psi surface injection pressure. Distributed Temperature Sensing (DTS) profiling identified three distinct injection zones across the 600-ft perforated interval. Zones 2 and 3, located in the upper section, showed limited injectivity, which correlated with petrophysical interpretation and water injection simulation. In contrast, Zone 1, the lowermost section, exhibited uniform injection. Given the vertical well architecture, a nitrified acid stage was incorporated into the treatment to enhance coverage of the upper zones. Post-stimulation DTS data confirmed a significantly improved and uniform injection profile across all zones. As a result, the well's injectivity index increased by a factor of 5. This case validates the effectiveness of fiber-optic-enabled coiled tubing with real-time DTS in optimizing acid placement and improving zonal coverage in challenging CO2 injection environments. The methodology offers a replicable stimulation workflow for similar injector wells across the region, advancing stimulation design and monitoring practices in the petroleum industry. This paper presents the first documented case in the UAE of using DTS and downhole measurements to evaluate and optimize acid stimulation in a vertical CO2 injector. By profiling injection across a 600-ft perforated interval in real-time, the study demonstrates how DTS-enabled workflows can ensure uniform stimulation and significantly enhance injectivity, offering a new benchmark for matrix acidizing in CO2 injection wells across the industry.

The variation of temperature profile of the sandface and wellbore offers important indicators for the occurrence of various downhole phenomena, as functions of reservoir formation and fluid properties. This paper aims to investigate the assimilation of temperature and production data for robust and efficient estimation of reservoir formation properties and fluid characterization. Very few previous work in the literature used Distributed Temperature Sensing (DTS) data for the characterization of the reservoir fluid and geostatistical description. The main contribution of this work lies in the proposed methodology for integration of temperature data from DTS systems to obtain a robust estimation of the reservoir fluid description, as well as introducing the integration of temperature data as an alternative and/or complementary data for integrative reservoir characterization. Two synthetic reservoir examples are investigated. In the first example, we focus on resolving the geostatistical description of a 3D multi-phase reservoir under water flooding. An ensemble-based data assimilation algorithm is used to compare the characterization of reservoir formation porosity and permeability by integration of temperature profile and well production data as opposed to the integration of production logging tool (PLT) data. Our results show that the DTS temperature data shows good potential as an alternative to the PLT data for reservoir rock characterization, although there may be a risk of model overfitting due to the large amount of data. In the second example, we attempt to estimate the original composition of the reservoir fluid as well as reservoir rock properties using downhole temperature profile data. A relatively simple multi-layer radial reservoir model is considered in this case. However, in order to honor the physical bounds on the various model parameters, a constrained ensemble-based data assimilation algorithm based on Lagrange multipliers is adopted. The computational results show that the original reservoir fluid composition could be excellently estimated for a case with known reservoir properties. Presence of uncertainty in the reservoir formation properties resulted in an poor estimation of the original reservoir fluid composition.

Distributed Temperature Sensor (DTS) technology uses fiber-optic cable to measure a continuous temperature profile along the wellbore. Compared to conventional production logging tools (PLT), DTS can provide operators real-time well information without intervention. Applications, from flow profiling to gas lift surveillance, have grown steadily in recently years. DTS applications require reliable data modeling and analysis or measurement interpretation. The complexity of the data analysis has been a barrier to DTS usage. This paper presents software tools developed for DTS interpretation. The model behind the software is based on steady-state energy balance, and it is applicable for gas and oil wells in both onshore and offshore environments. The software allows users to run in two modes: forward simulation and flow profiling. The forward simulation mode calculates the temperature distribution along the wellbore for any given production profile, and this mode is critical for the model calibration. It is also very useful for emulating "what-if" scenarios, such as forecast and gas lift surveillance. The flow profiling estimates the production profile based on measured temperatures, which is the basis for the real-time well monitoring. The model is tested against other models and good agreement has been obtained. This paper presents two examples: result comparison against TIPP, a computer program package developed by Chevron Corp, and a field example to verify gas lift valve operation.

Where is that CO2 flowing? Using Distributed Temperature Sensing (DTS) technology for monitoring injection of CO2 into a depleted oil reservoir

This article discusses key considerations in the practical application of data analysis using distributed temperature sensing (DTS) technology. Conventional temperature logging techniques provide temperature data only during specific surveys and can significantly interfere with normal well operations. Application of DTS technology has made it possible to overcome many of the limitations and problems of thermal studies and makes it possible to obtain temperature measurements along the wellbore at short intervals without changing the well operating mode. It is demonstrated that in deviated and horizontal wells, discrepancies between the DTS measured depth (MD/ML) and the actual wellbore depth (i.e., the difference between the optical fiber length and the well path) vary across different intervals due to uneven fiber tension. These discrepancies are typically more pronounced in inclined and horizontal sections compared to vertical ones and must be accounted for when interpreting temperature variations along the wellbore. To correct this technical inaccuracy, DTS data should be calibrated against conventional well logging results. The study also identifies random temperature fluctuations inherent in DTS measurements, which can influence the accuracy of the recorded values. These signal noises are also observed when the well is shut in. Based on the statistical analysis, the closeness of the distribution of DTS measurement noise when the well is shut in to the normal distribution is shown. To determine the optimal sampling interval and the minimum number of measurements required for reliable temperature profiling, a comparative analysis with data from permanent downhole temperature gauges is recommended. Keywords: well integrity; monitoring; temperature profiling; distributed temperature sensing (DTS); signal noise; thermal fluctuation; distributed sensing.

[1] Distributed temperature sensing (DTS) was used to map spatial and temporal changes in temperature on a 25 m by 6 m lakebed area in the winter (February), spring (May), and summer (August) of 2012. A constant and high discharge of groundwater with the average temperature of around 8°C to the lake will result in either lower (summer) or higher (winter) daily temperatures and reduce temperature variability at the sediment-water interface (SWI). DTS data were used as a proxy for groundwater discharge using three metrics; daily minimum temperature, diel amplitude, and daily standard deviation of temperature. During the seasons, the daily minimum temperatures at the SWI indicate a discharge zone 4–6 m offshore. From winter to summer, the extent of this zone changes and the SWI temperatures also show a shift of discharge locations toward the shore. Fluxes estimated on the basis of vertical temperature profiles from the top 50 cm of the lakebed and seepage meters in August compare well with the locations of the high-discharge zones detected by the DTS in the same period, giving confidence in the ability of the method to map both the areas and spatial variability of groundwater discharge to lakes. Compared to February, the DTS was able to detect new relatively cold temperature zones at the SWI in May and August indicating that groundwater discharge to the lake changes over time and that DTS can be used to monitor temporal variability in areas of discharge.

In steam assisted gravity drainage (SAGD), temperature instrumentation is widely used to understand steam placement across openhole liners in producer and injector wells. The accuracy of temperature readings is crucial when monitoring wellbore integrity and optimizing production. While distributed temperature sensing (DTS) on fiber-optic cables has been widely used in temperature monitoring, challenges consistently exist regarding accuracy. Several trials over a 2-year period were completed to quantify the accuracy of DTS systems. Each trial employed different operating conditions and instrumentation: Case Study 1: Dual-laser DTS and thermocouples were permanently deployed in a newly drilled SAGD producer. The well was heated from geothermal to 240°C. Newly deployed thermocouples were compared against newly deployed fiber-optic cables. Case Study 2: Dual-laser DTS temperature measurements were compared across a 1 dB point loss at a maximum optical budget of 13 dB. Case Study 3: Dual-laser DTS vs. single-laser DTS vs. new thermocouples comparisons were made. Case Study 4: Thermocouples and dual-laser DTS for a mid-life SAGD injector and producer were compared for accuracy after two years of operation. Case Study 5: An independent temperature log containing dual-laser DTS was used to quantify the thermocouple temperature discrepancy on a SAGD producer in operation for 7 years. The results of these case studies allowed Devon to determine several important learnings, as well as a troubleshooting methodology for evaluating DTS accuracy. When properly installed and calibrated, dual-laser systems are accurate up to ±2°C over the full range of SAGD operating temperatures for stable operating conditions. During the trial period, DTS was shown to maintain accuracy for 2 years. When comparing the accuracy of temperature systems, it is recommended to compare against other known metrics during falloffs. New thermocouples are still considered the most accurate measurement; however, legacy thermocouples are susceptible to drift. Independent temperature logs have proven to be a valuable tool for assessing legacy instrumentation accuracy for thermocouples and DTS.

The relentless pursuit of well integrity is a critical mission in the oil and gas industry, especially in mature fields where the risks of casing leaks loom large. This study from Kuwait highlights the necessity of constant vigilance to proactively tackle these leaks, which threaten both production efficiency and environmental safety. Emphasizing early leak detection, this research aims to demonstrate how advanced methodologies can significantly reduce the costs and risks associated with extensive workover operations and the potential need for well suspension or abandonment. The focus lies in accurately identifying and quantifying casing leaks, including their depth and directional flow, crucial for effective well diagnostics and integrity management. This study introduces a cutting-edge approach for pinpointing casing leaks in wells, especially those with simpler completion designs. It showcases the deployment of an optical fiber-enabled coiled tubing system to implement distributed temperature sensing (DTS). This innovative combination enables real-time downhole measurements, including pressure and casing collar locator (CCL) readings for precise depth determination. The key advancement here is the ability to capture temperature anomalies in real-time, offering a comprehensive and dynamic profile of both the borehole environment and the surrounding formation. This approach represents a significant leap forward in well diagnostics technology. In a North Kuwait oil-producing well with a deviated trajectory, conventional production logging tools (PLT) were inadequate in locating a casing leak. Utilizing well hydraulics analysis, the DTS technology, facilitated by fiber optics-equipped coiled tubing, was employed. Different operational stages were correlated through a series of DTS surveys, ultimately leading to the successful identification of the leak. Notably, this operation was performed without a rig, incorporating a novel nitrogen injection workflow to stimulate leak production. This approach, a first of its kind, marked a shift in industry practices. The precision of this Coiled Tubing and fiber optic system in detecting temperature variations at the influx point was unprecedented, showcasing the method’s effectiveness. This case study offers invaluable insights into leveraging DTS in conjunction with Coiled Tubing for diagnosing completion leaks. The innovative strategy of nitrogen injection via the annulus of the kill string, enhancing fluid column visibility and inducing wellbore production, while simultaneously monitoring temperature shifts, represents a significant breakthrough. This approach not only confirms the leak location with enhanced accuracy but also adds a new layer to the standard DTS protocol. It sets a new benchmark for industry practices in leak detection and well integrity assurance.

This work presents an experimental study conducted using a modular flow-loop apparatus to evaluate flow diagnostics with Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) across simulated well scenarios. Dedicated simulators, including horizontal and vertical injection and production wells, enable repeatable emulation of subsurface dynamics such as steady-state and transient flow regimes, leak inflow/outflow, time-varying injectivity and productivity, and intervention responses. Each simulator incorporates programmable flow conditions with synchronized acquisition of DAS and DTS data, co-registered with reference pressure and flow instrumentation. In addition to passive sensing, we investigate active modalities that strengthen flow-signal detectability, reduce interpretation ambiguity, and increase confidence in physics-based flow profiling. In active DAS, low-frequency flow stimulation generates broadband harmonics that enhance spectral content and signal-to-noise ratio. For active DTS, a novel distributed anemometry approach uses the temperature response to a controlled, steady heat input to estimate the flow velocity profile. The results provide experimental validation and example self-learning flow allocation workflows for distributed sensing as a quantitative diagnostic tool for transient well dynamics. With high-resolution sensing, operators gain immediate insight into downhole flow phenomena, supporting on-the-fly data-driven adjustments to interventions and robust assessments of zonal performance in complex subsurface environments.