Diagnosing Multiphase Flow Regime in Multilayered Reservoir by Distributed Temperature Sensor Data

Operators including Aera Energy LLC are evaluating distributed temperature sensing (DTS) systems as an alternative to production logging tools (PLT) and radioactive tracer surveys (RTS) for the determination of zonal allocation factors. If DTS data can be interpreted to provide wellbore velocities, zonal allocation can be determined without well entry and practically in real-time. In comparison to PLT and RTS, DTS could provide zonal allocation at a higher measurement frequency, lower cost, and lower risk to personnel, environment, and the well asset. In wells where casing deformation precludes wireline operations, DTS may be the only viable alternative. The purpose of this work is to investigate whether water injection zonal allocation can be derived from DTS data acquired in thermal tracer injection tests within an uncertainty comparable to RTS. Three waterflood injection wells with RTS and DTS data in Aera Energy"s Belridge field in California are analyzed. The zonal allocation factors derived from the DTS are shown to agree within uncertainty with the RTS-based results. The DTS for two of the wells is interpreted through history matching with an OLGA thermal-fluid model. The DTS for a third well is interpreted using the Temperature Inflection Point (TIP) thermal tracer method proposed in this work. The TIP method is a simpler alternative to history matching and was shown to be theoretically valid for wells with negligible heat transfer at the walls over the duration of the injection test. In this regard the TIP method is less restrictive than the Slopes method, which is currently used in industry but theoretically requires negligible heat transfer at the walls and within the fluid. The TIP method is also shown to be more consistent with the field data of this study. The paper concludes with guidelines on the design and implementation of thermal injection tests and TIP analysis. The most significant practical limitation of the TIP method is its sensitivity to noise in the data, motivating DTS acquisition at the maximum practical resolution, data smoothing, and averaging over multiple test realizations.

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.

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.

<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>

[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.

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.

As part of the strategic initiative to develop main reserves in Jambaran field in East Java, Indonesia, to supply gas and drive the national economy, six gas producers were completed targeting 300 MMscf/D of total production. The main challenge consisted in efficiently perforating underbalanced a minimum of 800 ft in each well. To this end, coiled tubing (CT) equipped with fiber optic (FO) and deployment under pressure were implemented, rigless; this was a first in the country. Understanding of zonal contribution in those long intervals early in the life of the wells was key to addressing any potential concerns over reservoir productivity and critical to the field management. Due to the high CO2and H2S contents of formation fluids (up to 34% and 10,000 ppm, respectively), traditional production logging was impossible. Instead, distributed temperature sensing (DTS) and downhole pressure point measurements through FO CT telemetry were jointly used to compute the flow distribution along each perforated interval. The acquired data were inverted and analyzed using a pressure-temperature-rate transient analysis (PTRA) software. In this field, reservoir K is a carbonate formation with a net thickness of ~1,450 ft and an average permeability of 46 md. Gas rates up to 60 MMscf/D were expected in each well. In such extreme downhole environment, DTS on FO CT was selected due to the possibility to circulate inhibitor throughout the operation to protect the CT pipe and downhole equipment. In addition, it enabled logging at gas rates as high as 60 MMScf/D without CT movement, which would not have been possible using wireline or slickline conveyance. In each well, a series of carefully planned shut-in and constant flowing phases were performed, during which temperature profiles and point pressure data were interpreted both qualitatively and quantitatively. A representative thermal model was built in the PTRA software utilizing reservoir properties, downhole point measurements, and surface well test data. Quantitative DTS interpretation indicated the same behavior in all six wells, with an uneven gas production along the perforated intervals. The minimal contributions observed from the upper section of the formation were attributed to low permeability whereas the high pressure drop observed across the bottom section was found indicative of a higher skin. Those findings will be key to future field developments in reservoir K. The use of CT equipped with FO for DTS proved a reliable alternative to production logging in high-rate gas producers. This study provided critical insights on the completion strategy performance and new considerations to minimize formation damage during future drilling campaigns. It also enabled establishing new best practices for DTS production logging in high-rate producers, in particular with respect to recommended drawdown conditions to obtain reliable readings.

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 study demonstrated a new method for mapping high resolution (spatial: 1 m, and temporal: 1 hour) soil moisture by assimilating distributed temperature sensing (DTS) observed soil temperatures at intermediate scales. In order to provide robust soil moisture and property estimates, we first proposed an adaptive particle batch smoother algorithm (APBS). In the APBS, a tuning factor, which can avoid severe particle weight degeneration, is automatically determined by maximizing the reliability of the soil temperature estimates of each batch window. A multiple truth synthetic test was used to demonstrate the APBS can robustly estimate soil moisture and properties using observed soil temperatures at two shallow depths. The APBS algorithm was then applied to DTS data along a 71 m transect, yielding an hourly soil moisture map with meter resolution. Results show the APBS can draw the prior guessed soil hydraulic and thermal properties significantly closer to the field measured reference values. The improved soil properties in turn remove the soil moisture biases between the prior guessed and reference soil moisture, which was particularly noticeable at depth above 20 cm. This high resolution soil moisture map demonstrates the potential of characterizing soil moisture temporal and spatial variability and reflects patterns consistent with previous studies conducted using intensive point scale soil moisture samples. The intermediate scale high spatial resolution soil moisture information derived from the DTS may facilitate remote sensing soil moisture product calibration and validation. In addition, the APBS algorithm proposed in this study would also be applicable to general hydrological data assimilation problems for robust model state and parameter estimation. This article is protected by copyright. All rights reserved.

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.

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.

Fiber Optics Distributed sensing technologies are evolving in the petroleum industry with its potential applicability in many areas of surveillance. Petroleum Development Oman (PDO) is embarking upon the implementation of this technology in various assets including both Gas and Oil fields. The vision of the company is to have the Fiber Optics distributed sensing technology as a surveillance tool in the Well and Reservoir Management (WRFM) toolbox and to become, where appropriate, a key element of its cycle. In comparison to conventional surveillance, fiber optic distributed sensing requires no well intervention and thereby reducing HSSE exposure and production deferment. In addition, the installed fibers can be used for multiple applications, e.g. hydraulic fracture performance monitoring and inflow performance monitoring. Recently, PDO trialed Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) technologies utilizing both, dip-in surveys and permanent installation of fiber optics in the wells. Fiber optic implementation in PDO included a polymer flooding trial in heavy oil, high permeability clastic reservoir with a strong bottom water aquifer drive. The objective was to monitor well conformance as the polymer injection progressed. The horizontal injectors were completed with pre-drilled liner and divided into four zones, each with an independent Inflow Control Valve (ICV). The well was completed with a multi-mode (MM) fiber pumped into control lines three injectors. Real time DTS data was acquired continuously in all three wells while DAS was acquired as per the injection program in one injector. DAS and DTS data were analyzed to quantify the changes in injection profile and rate in each ICV zone. This provided timely information needed for decisions related to manipulation of the ICV valves to ensure best utilization of the polymer. Another example of fiber optics was a dip-in survey in a deep gas well with commingled production which covered stacked reservoirs. This was run in order to prove the concept of flow response on DAS/DTS signals in terms of gas flowing and liquid lifting detection. The acoustic signature observed was mainly due to gas entering the well through perforations. This was detected by DAS and DTS and allowed a qualitative inflow profile to be generated. The dip in survey proved the concept and allowed justification for the permanent installation of fiber optics behind casing. The objective of the permanent setup is to improve the sensitivity of the measurement and allow for better quantification of inflow per zone. In this paper, the approach of implementing fiber optic technologies in PDO is discussed with emphasis on value generation in the various assets. Additionally, the examples mentioned in this abstract are discussed in more details and based on the results, the way forward is described.

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.

Effective reservoir management is critical to the success of water flood developments. Continuous monitoring of downhole parameters such as pressure, temperature and flow profile in water injector wells is vital in order to optimize the water-flood sweep efficiency and to avoid early water breakthrough in nearby oil producer wells. The target field has three stacked tight carbonate reservoirs with low reservoir energy and as such is being developed with water injection scheme from day one. As such, effective monitoring of downhole injection parameters is important from an early stage. A common industry practice to monitor these parameters is to install Permanent Downhole Gauge (PDHG) and Distributed Temperature Sensing (DTS) system. Recently, a new smart Hybrid Technology has been developed to measure the downhole data at surface. This paper describes the successful application of this hybrid technology in a green onshore oil field development. Details are presented about the well bore segmentation design of the DTS system, the hybrid cable installation and the operational challenges with the hookup to the wellhead control system. The paper also presents the data acquired during commissioning job, and interpretation of the temperature data which was used to generate the injection profile along the wellbore. Finally, a strategy for future implementation of the DTS system is discussed. Overall, this technology showcases the application of the smart hybrid completion for real-time monitoring of the water injection profile, including the pressure and rates along with injection volume per segment in the horizontal section. Real-time data from the hybrid technology has been integrated to digital oil field implementation to enhance the real time decision making to optimize the injection rates and to allow the operator to implement the decisions without any delay. This technology optimized the cables requirement and maximized the utilization of cable for multi-application environment to support acquiring Pressure, DTS and DAS data to generate real time injection profile.