- Email: [email protected]
Evaluation of Sensitivity of Downhole Temperature Estimates From Distributed Temperature Sensing Measurements
Available online at www.sciencedirect.com
ScienceDirect Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available Energy Procedia 00 (2018) 000–000
ScienceDirect ScienceDirect
www.elsevier.com/locate/procedia
Energy (2018) 000–000 106–111 EnergyProcedia Procedia154 00 (2017) www.elsevier.com/locate/procedia
Applied Energy Symposium and Forum, Carbon Capture, Utilization and Storage, CCUS 2018, 27–29 June 2018, Perth, Australia
Evaluation of of Symposium Downhole Temperature From TheSensitivity 15th International on District Heating andEstimates Cooling Distributed Temperature Sensing Measurements Assessing the feasibility of using the heat demand-outdoor a,c b,c Ludovic *, Roman Pevzner temperature function forP.aRicard long-term district heat demand forecast a
CSIRO, 26 Dick Perry Avenue, Kensington, WA 6151, Australia c Curtin University of Technology, 20 Dick Perry Avenue, Kensington WA 6151, Australia c CO2CRC Ltd, 11-15 Argyle Place South, Carlton, VIC 3053, Australia a IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France
a,b,c a a b c b Curtin University of Technology, 20 Dick Perry Avenue, Kensington WA 6151, Australia
I. Andrić
*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Corre
Abstract
A range of Australian CCS research activities (CO2CRC Otway Stage 3, CO2CRC Otway shallow controlled release and CSIRO Abstract involving subsurface characterisation and/or CO2 injection are at the planning stage. Fibre-optic sensing is considered Insitu-lab) as part of the downhole reservoir characterisation and surveillance monitoring system for all of these projects. In this work, we District heating networksofareDTS commonly in thermal the literature as onein of the of most for decreasing the investigate the sensitivity for the addressed detection of anomalies view the effective design ofsolutions future geological storage greenhouse gas emissions from the building TheseOtway systems require high investments which are returned through thewas heat activities in Australia. Ahead of Phase 2 of thesector. CO2CRC shallow CO2 controlled release experiment, a DTS system sales. Due to the changed conditions andand building renovation policies, atheat in the future could decrease, installed in the CRC-3 well climate for equipment testing baseline characterisation, the demand same time as the acquisition of the prolonging the investment return period. CO2CRC Stage 2C M5 seismic survey. Temperature measurements were acquired from well-head to bottom-hole for 13 days at scope of thismeasurement paper is to assess of using the heat demand outdoor temperature functionover for heat demand a The ratemain of one-minute everythe4 feasibility minutes. The temperature profile –did not change significantly time. The forecast. The district of Alvalade, located Lisbon (Portugal), was used as a case study. The profile district with is consisted of 665 integration and processing of more than 3400 in temperature traces enabled estimation of a temperature a resolution of buildings that in both construction period typology. Threethe weather scenarios high) 11W and three district 0.01 °C. The usevary of DTS during the CO2CRC M5and survey highlights detectability of a(low, VSP medium, tool producing and 4W at renovation scenarios (shallow, intermediate, Tovery estimate the A error, obtained heat(0.1 demand values were two distinct depths. Thewere setupdeveloped was capable of detecting a 0.7 °C deep). anomaly quickly. smaller anomaly °C) was detected compared with results a dynamic demand previously and validated by the authors. with the benefit of datafrom processing of heat the long termmodel, dataset. The highdeveloped spatial resolution of DTS enables location of thermal The results when only weather change is considered, the margin of error could be acceptable for some applications anomalies to showed within 2that metres. (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation © 2018 The Authors. Published by Ltd. (depending on the weather and renovation scenarios combination considered). scenarios, error value increased up toreserved. 59.5% Copyright ©the 2018 Elsevier Ltd. AllElsevier rights This an open accesscoefficient article under the CCon BY-NC-ND licensethe (http://creativecommons.org/licenses/by-nc-nd/4.0/) The isvalue slope increased average within range of up to Energy 8% perSymposium decade, thatand corresponds to the Selection andofpeer-review under responsibility of the scientific committee of 3.8% the Applied Forum, Carbon Selection and peer-review under responsibility of the scientific committee the Applied Energy and Forum, Carbon decrease in the number of heating hours of 22-139h during the heating of season (depending on Symposium the combination of weather and Capture, Utilization and Storage, CCUS 2018. Capture, Utilization and Storage, CCUS 2018. renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested couldCCS be used to modify the function parameters for the scenarios considered, and Keywords: Fiber optic sensing; temperature; resolution; improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. * Corresponding author. Tel.: +61 864368523. E-mail address: [email protected] Keywords: Heat demand; Forecast; Climate change
1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, Carbon Capture, Utilization and Storage, CCUS 2018. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. 1876-6102 © 2018 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, Carbon Capture, Utilization and Storage, CCUS 2018. 10.1016/j.egypro.2018.11.018
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1. Introduction Over the past two decades, the use of fiber optic sensing as a key surveillance tool has grown from a research tool to been part of completion and surface facilities systems. Fiber optic sensing is been used commonly for environment, groundwater and oil and gas resource sector. In the context of CCUS, fiber optic sensing has been used for the past decade as a key reservoir surveillance tool along other downhole measurements ([1]). The theory behind distributed temperature sensing is well described in [2] and more recently in [3]. In a distributed optical fiber sensors (DOFS), the sensing element is an optical fiber. An opto-electronic system (also called interrogator) sent light in the optical fiber. The light is reflected and return to the interrogator. The losses and the scattering of the light is then analysed with regard to the physical quantity of interest. The more common physical measurements recorded using optical fibers is temperature, known as distributed temperature sensing (DTS). More recently distributed acoustic sensing (DAS) has been deployed and delivered outstanding results [4]. Temperature is a key parameter of the CO2 storage reservoir. The properties of supercritical CO2 vary significantly depending on temperature. The reservoir and injected CO2 temperatures are unlikely to be identical, hence the surveillance of the temperature can inform on the in-situ conditions and possibly on local events. Operating downhole tools generate heat. The measurements of downhole temperature has been identified as a key reservoir surveillance tool [5]. A least three CCS demonstration projects have fiber optics sensing system installed as part of their monitoring system: The injection well at Ketzin, Germany ([6]; [7]), monitoring wells at Cranfield, Mississippi, USA ([8];[9]) and Ketzin ([10]), and two wells and more than 5 km shallow buried at Otway, Australia ([11]). A range of CCS research activities (CO2CRC Otway Stage 3, CO2CRC Otway shallow controlled release and CSIRO Insitu-lab) involving subsurface characterization and for some CO2 injection are at planning stage. Fiber optic sensing is considered as part of the downhole reservoir characterization and surveillance monitoring system for all these projects. Ahead of phase 2 of the CO2CRC Otway shallow CO2 controlled release experiment, a DTS system was installed at the CRC 3 well for equipment testing and baseline characterization. In this work, we investigate the sensitivity of DTS for the detection of wireline tools in a well in view of the design of future geological storage activities in Australia. 2. Experimental design The experiment was performed at the CRC 3 well part of the CO2CRC Otway research site. The well is suspended awaiting final decisions on perforations and internal completions design (Figure 1). No fluid communications is allowed between inside and outside the casing. The well has two fiber-optics sensing cables installed outside casing. The two cables are secured to the casing and the casing is cemented. Cable #1 has two multi-mode cores spliced together at the bottom most end of the cable so that light travels down the cable on one optical fiber core and travel back up the second optical fiber core. Cable #2 has two multi-mode cores both terminated at the bottom. In the context of the work presented here, a 4 channel 10 km Raman-based DTS (XT DTS from Silixa) is used (Raman DTS is the most developed and widely commercialised DOFS technology). The DTS acquisition setup used in this experiment is such that the two optical core from cable #1 are connected on a double-ended configuration [12], the last two channels are used by the two optical core from cable #2 on a single-ended configuration. A temperature calibration bath setup consisting of twice 80m length of optical core is connected to the DTS unit prior to be connected to the well-head optical fiber connection. The first bath is left to ambient temperature (20 °C) while the second bath is kept at a temperature of 30 °C. The temperature acquisition is setup at a spatial sampling rate of 25 cm and a temporal rate of 1 min for each channel sequentially. Hence one measurements every 4 mins per channel. The acquisition started on 27th February 2018 early morning and stopped on 12th March 2018 early morning. The DTS interrogator is connected to a field computer (Figure 1) and a local area network enabling the data acquisition to be monitored remotely. A simultaneous operation was the acquisition of the seismic M5 survey part of the CO2CRC Stage 2C experiment. As part of this survey, a vertical seismic profiling (VSP) tool was lowered down in the CRC 3 well to 775mMD on 28th February 2017 about 6.30pm and active until 12th March 2018 2pm when it was retrieved. This VSP tool has two key components, a telemetry unit and a measuring tool. The
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measuring tool is located at the bottom of the cable at 775mMD while the telemetry unit is located 10m above. Both of these items have electronics components and consume power as 11W for the telemetry unit and 4 W for the measuring tool. It is important to note that the temperature measurements starts before the VSP tool is lowered down in the well and that the measurements are taken from the DTS acquisition unit and along the entire length of the cables outside casing.
Figure 1. (Left) CRC-3 completion schematics. (Middle) CRC-3 wellhead. (Right) Distributed temperature sensing setup at CRC-3 showing the DTS interrogator, the controlling computer and the two temperature controlling baths.
3. Observations Temperature measurements are recorded every 4 mins during the entire sequence (over 3,400 time traces) at a spatial increment of 25 cm. Before the VSP tool is present, the temperature is constant in time and follow the local geothermal gradient down the well (Figure 2). A close examination of the temperature profile down the well lead to the identification of two anomalies as presented in Figure 3. The strongest anomaly of ~0.7 °C can be observed between 764 and 770mMD. The second anomaly of ~0.1°C can be observed between 776 and 780mMD. All measurements show that long term data processing provide estimates of temperature with variations less than 0.01 °C. A temporal profile of the temperature measurements at the depth of 767.43mMD highlights clearly a temperature increase starting on 28th February at 7.15pm, 45 min after the tool has been placed in the well (Figure 4). It corresponds to the operation of the telemetry unit at that location. From the amplitude of the temperature anomaly the power of the telemetry unit was estimated to be 15W (in comparison of 11W measured). This error is likely due to uncertainty on well design. A temporal profile of the temperature measurement at the depth of 778mMD does not provide a clear identification of the thermal anomaly produced by the bottom-most measurement tool. However, further data processing highlights the change of temperature highlights the long term trend (Figure 5). Based on the thermal anomaly amplitude, the heat produced by the downhole tool is estimated to be about 5 W (in comparison of 4W measured).
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Figure 2. (Left) Temperature versus depth from well head (m) before the VSP tool is placed in the well. (Right) Temperature versus depth over time with baseline and anomaly time periods highlighted.
Figure 3. (left) Temperature profile versus depth (m) before and after VSP tool in place. (Middle) Zoom of the temperature profile at the VSP tool depth interval (m). (Right) Reduced temperature profile (Monitor - baseline) highlight two thermal anomalies.
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Figure 4. (Left) Reduced temperature profile (Monitor-baseline). (Right) Temporal profile of temperature at 767mMD.
Figure 5. (Left) Reduced temperature profile (Monitor-baseline). (Right) Temporal temperature profile at 778mMD. Several data processing averaging are presented in different colors.
4. Conclusions The use of DTS at the CRC 3 well was presented. While the temperature profile does not change significantly over time, the integration and processing of more than 3400 temperature traces enabled to estimate a temperature profile with a resolution of 0.01 °C. The use of DTS during the CO2CRC M5 survey highlights the detectability of a VSP tool producing 11 and 4 W at two distinct depth. The setup was capable of detecting a 0.7 C anomaly very quickly. A much smaller anomaly (0.1 °C) was detected with the benefit of data processing. The high spatial resolution of the DTS enable to locate the thermal anomaly (tool) within 2m. DTS installations involve inexpensive hardware with downhole components which are relatively inert by nature with all the electronics, optics located at surface in a controlled environment. Hence DTS installations have a long life-span and are inexpensive to operate. They have the ability to provide distributed temperature measurements with a low measurement error over a long distance. Appropriate experimental design, data processing and calibration processes enable to achieve very accurate
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quantitative interpretation. The interpretation of distributed temperature sensing measurements shows that it is possible to detect very small event and provide some quantitative estimates on the event itself when additional information on the operation in question are provided. It shows promising prospects in the context of monitoring cost reduction and early identification of events to inform near-realtime the decision-making process. 5. Acknowledgements The Otway project received CO2CRC funding through its industry members and research partners, the Australian Government under the CCS Flagships Programme, the Victorian State Government, and the Global CCS Institute. The authors wish to acknowledge financial assistance provided through Australian National Low Emissions Coal Research and Development supported by the Australian Coal Association Low Emissions Technology Limited and the Australian Government through the Clean Energy Initiative. We are grateful to Andrew Feitz (Geoscience Australia) for supporting this work as part of his SRD 3.3 project. We strongly appreciated Oleg Vashin and Jean Lepine from SERCEL providing the details of the VSP downhole tool. We thanks Michael Mondanos from Silixa for discussion on DTS parametrization. We also thank our colleagues from CO2CRC, CSIRO, and Curtin University, in particular Rajindar Singh and Konstantin Tertyshnokov, for their valuable support and contribution to this work. 6. References [1] Freifeld, B., Daley, T., Cook, P., Trautz, R., Dodds, K., 2014. The Modular Borehole Monitoring Program: a research program to optimize well-based monitoring for geologic carbon sequestration. Energy Procedia 63, 3500-3515. [2] Smolen, J. J. and van der Spek, (2003). A. Distributed temperature sensing—A DTS primer for oil & gas production - 2003. in Tech. Report, Shell. [3] Hartog, A. (2017). An Introduction to Distributed Optical Fibre Sensors. Boca Raton: CRC Press. [4] Correa, J., Egorov, A., Tertyshnikov, K., Bona, A., Pevzner, R., Dean, T., Freifeld, B., Marshall, S., (2017) Analysis of signal to noise and directivity characteristics of DAS VSP at near and far offsets — A CO2CRC Otway Project data example. The Leading Edge ; 36 (12): 994a1–994a7. doi: https://doi.org/10.1190/tle36120994a1.1 [5] Paterson, L., Boreham, C., Bunch, M., Ennis-King, J., Freifeld, B., Haese, R., Jenkins, C., Raab, M., Singh, R., Stalker, L., (2011). The CO2CRC Otway Stage 2 B Residual Saturation and Dissolution Test: Test Concept, Implementation and Data Collected, Milestone Report to ANLEC. http://hub.globalccsinstitute.com/sites/default/files/sites/default/files/co2crc-otway-stage2b-residual-saturation-dissolutiontest.pdf [6] Liebscher, A., Möller, F., Bannach, A., Köhler, S., Wiebach, J., Schmidt-Hattenberger, C., Weiner, M., Pretschner, C., Ebert, K., Zemke, J. (2013). Injection operation and operational pressure-temperature monitoring at the CO2 storage pilot site Ketzin, Germany – design, results, recommendations. Int. J. Greenhouse Gas Control, 15, pp. 163-173, 10.1016/j.ijggc.2013.02.019 [7] Wiese B., (2014). Thermodynamics and heat transfer in a CO2 injection well using distributed temperature sensing (DTS) and pressure data. Int. J. Greenhouse Gas Control, 21, pp. 232-242, 10.1016/j.ijggc.2013.12.009 [8] Núñez-López, V. (2011). Temperature monitoring at SECARB Cranfield Phase 3 site using distributed temperature sensing (DTS) technology. Poster Presented at the 10th Annual NETL Carbon Capture & Sequestration Conference, Pittsburgh, Pennsylvania, May 2–5, 2011. GCCC Digital Publication Series #11-10 (2011) [9] Doughty, C., Freifeld, B.M., (2013). Modeling CO2 injection at Cranfield, Mississippi: investigation of methane and temperature effects. Greenhouse Gas Sci. Technol., 3, pp. 475-490, 10.1002/ghg.1363 [10] Henninges, J.. (2010). Permanent distribution temperature sensing at the Ketzin CO2 storage test site. IEAGHG 6th Wellbore Network Meeting. http://www.ieaghg.org/docs/General_Docs/6wellbore/Presentations/Day2/14.25Henninges.pdf [11] Zhang, Y., Freifeld, B., Finsterle, S., Leahy, M., Ennis-King, J., Paterson, L., Dance, T., (2011). Single-well experimental design for studying residual trapping of supercritical carbon dioxide. Int. J. Greenhouse Gas Control, 5, pp. 88-98, [12] van de Giesen, N., Steele-Dunne, S.C., Jansen, J., Hoes, O., Hausner, M.B., Tyler, S., Selker, J., 2012. Double-Ended Calibration of FiberOptic Raman Spectra Distributed Temperature Sensing Data. Sensors 12, 5471.
ScienceDirect Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available Energy Procedia 00 (2018) 000–000
ScienceDirect ScienceDirect
www.elsevier.com/locate/procedia
Energy (2018) 000–000 106–111 EnergyProcedia Procedia154 00 (2017) www.elsevier.com/locate/procedia
Applied Energy Symposium and Forum, Carbon Capture, Utilization and Storage, CCUS 2018, 27–29 June 2018, Perth, Australia
Evaluation of of Symposium Downhole Temperature From TheSensitivity 15th International on District Heating andEstimates Cooling Distributed Temperature Sensing Measurements Assessing the feasibility of using the heat demand-outdoor a,c b,c Ludovic *, Roman Pevzner temperature function forP.aRicard long-term district heat demand forecast a
CSIRO, 26 Dick Perry Avenue, Kensington, WA 6151, Australia c Curtin University of Technology, 20 Dick Perry Avenue, Kensington WA 6151, Australia c CO2CRC Ltd, 11-15 Argyle Place South, Carlton, VIC 3053, Australia a IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France
a,b,c a a b c b Curtin University of Technology, 20 Dick Perry Avenue, Kensington WA 6151, Australia
I. Andrić
*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Corre
Abstract
A range of Australian CCS research activities (CO2CRC Otway Stage 3, CO2CRC Otway shallow controlled release and CSIRO Abstract involving subsurface characterisation and/or CO2 injection are at the planning stage. Fibre-optic sensing is considered Insitu-lab) as part of the downhole reservoir characterisation and surveillance monitoring system for all of these projects. In this work, we District heating networksofareDTS commonly in thermal the literature as onein of the of most for decreasing the investigate the sensitivity for the addressed detection of anomalies view the effective design ofsolutions future geological storage greenhouse gas emissions from the building TheseOtway systems require high investments which are returned through thewas heat activities in Australia. Ahead of Phase 2 of thesector. CO2CRC shallow CO2 controlled release experiment, a DTS system sales. Due to the changed conditions andand building renovation policies, atheat in the future could decrease, installed in the CRC-3 well climate for equipment testing baseline characterisation, the demand same time as the acquisition of the prolonging the investment return period. CO2CRC Stage 2C M5 seismic survey. Temperature measurements were acquired from well-head to bottom-hole for 13 days at scope of thismeasurement paper is to assess of using the heat demand outdoor temperature functionover for heat demand a The ratemain of one-minute everythe4 feasibility minutes. The temperature profile –did not change significantly time. The forecast. The district of Alvalade, located Lisbon (Portugal), was used as a case study. The profile district with is consisted of 665 integration and processing of more than 3400 in temperature traces enabled estimation of a temperature a resolution of buildings that in both construction period typology. Threethe weather scenarios high) 11W and three district 0.01 °C. The usevary of DTS during the CO2CRC M5and survey highlights detectability of a(low, VSP medium, tool producing and 4W at renovation scenarios (shallow, intermediate, Tovery estimate the A error, obtained heat(0.1 demand values were two distinct depths. Thewere setupdeveloped was capable of detecting a 0.7 °C deep). anomaly quickly. smaller anomaly °C) was detected compared with results a dynamic demand previously and validated by the authors. with the benefit of datafrom processing of heat the long termmodel, dataset. The highdeveloped spatial resolution of DTS enables location of thermal The results when only weather change is considered, the margin of error could be acceptable for some applications anomalies to showed within 2that metres. (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation © 2018 The Authors. Published by Ltd. (depending on the weather and renovation scenarios combination considered). scenarios, error value increased up toreserved. 59.5% Copyright ©the 2018 Elsevier Ltd. AllElsevier rights This an open accesscoefficient article under the CCon BY-NC-ND licensethe (http://creativecommons.org/licenses/by-nc-nd/4.0/) The isvalue slope increased average within range of up to Energy 8% perSymposium decade, thatand corresponds to the Selection andofpeer-review under responsibility of the scientific committee of 3.8% the Applied Forum, Carbon Selection and peer-review under responsibility of the scientific committee the Applied Energy and Forum, Carbon decrease in the number of heating hours of 22-139h during the heating of season (depending on Symposium the combination of weather and Capture, Utilization and Storage, CCUS 2018. Capture, Utilization and Storage, CCUS 2018. renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested couldCCS be used to modify the function parameters for the scenarios considered, and Keywords: Fiber optic sensing; temperature; resolution; improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. * Corresponding author. Tel.: +61 864368523. E-mail address: [email protected] Keywords: Heat demand; Forecast; Climate change
1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, Carbon Capture, Utilization and Storage, CCUS 2018. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. 1876-6102 © 2018 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, Carbon Capture, Utilization and Storage, CCUS 2018. 10.1016/j.egypro.2018.11.018
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1. Introduction Over the past two decades, the use of fiber optic sensing as a key surveillance tool has grown from a research tool to been part of completion and surface facilities systems. Fiber optic sensing is been used commonly for environment, groundwater and oil and gas resource sector. In the context of CCUS, fiber optic sensing has been used for the past decade as a key reservoir surveillance tool along other downhole measurements ([1]). The theory behind distributed temperature sensing is well described in [2] and more recently in [3]. In a distributed optical fiber sensors (DOFS), the sensing element is an optical fiber. An opto-electronic system (also called interrogator) sent light in the optical fiber. The light is reflected and return to the interrogator. The losses and the scattering of the light is then analysed with regard to the physical quantity of interest. The more common physical measurements recorded using optical fibers is temperature, known as distributed temperature sensing (DTS). More recently distributed acoustic sensing (DAS) has been deployed and delivered outstanding results [4]. Temperature is a key parameter of the CO2 storage reservoir. The properties of supercritical CO2 vary significantly depending on temperature. The reservoir and injected CO2 temperatures are unlikely to be identical, hence the surveillance of the temperature can inform on the in-situ conditions and possibly on local events. Operating downhole tools generate heat. The measurements of downhole temperature has been identified as a key reservoir surveillance tool [5]. A least three CCS demonstration projects have fiber optics sensing system installed as part of their monitoring system: The injection well at Ketzin, Germany ([6]; [7]), monitoring wells at Cranfield, Mississippi, USA ([8];[9]) and Ketzin ([10]), and two wells and more than 5 km shallow buried at Otway, Australia ([11]). A range of CCS research activities (CO2CRC Otway Stage 3, CO2CRC Otway shallow controlled release and CSIRO Insitu-lab) involving subsurface characterization and for some CO2 injection are at planning stage. Fiber optic sensing is considered as part of the downhole reservoir characterization and surveillance monitoring system for all these projects. Ahead of phase 2 of the CO2CRC Otway shallow CO2 controlled release experiment, a DTS system was installed at the CRC 3 well for equipment testing and baseline characterization. In this work, we investigate the sensitivity of DTS for the detection of wireline tools in a well in view of the design of future geological storage activities in Australia. 2. Experimental design The experiment was performed at the CRC 3 well part of the CO2CRC Otway research site. The well is suspended awaiting final decisions on perforations and internal completions design (Figure 1). No fluid communications is allowed between inside and outside the casing. The well has two fiber-optics sensing cables installed outside casing. The two cables are secured to the casing and the casing is cemented. Cable #1 has two multi-mode cores spliced together at the bottom most end of the cable so that light travels down the cable on one optical fiber core and travel back up the second optical fiber core. Cable #2 has two multi-mode cores both terminated at the bottom. In the context of the work presented here, a 4 channel 10 km Raman-based DTS (XT DTS from Silixa) is used (Raman DTS is the most developed and widely commercialised DOFS technology). The DTS acquisition setup used in this experiment is such that the two optical core from cable #1 are connected on a double-ended configuration [12], the last two channels are used by the two optical core from cable #2 on a single-ended configuration. A temperature calibration bath setup consisting of twice 80m length of optical core is connected to the DTS unit prior to be connected to the well-head optical fiber connection. The first bath is left to ambient temperature (20 °C) while the second bath is kept at a temperature of 30 °C. The temperature acquisition is setup at a spatial sampling rate of 25 cm and a temporal rate of 1 min for each channel sequentially. Hence one measurements every 4 mins per channel. The acquisition started on 27th February 2018 early morning and stopped on 12th March 2018 early morning. The DTS interrogator is connected to a field computer (Figure 1) and a local area network enabling the data acquisition to be monitored remotely. A simultaneous operation was the acquisition of the seismic M5 survey part of the CO2CRC Stage 2C experiment. As part of this survey, a vertical seismic profiling (VSP) tool was lowered down in the CRC 3 well to 775mMD on 28th February 2017 about 6.30pm and active until 12th March 2018 2pm when it was retrieved. This VSP tool has two key components, a telemetry unit and a measuring tool. The
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Ludovic P. Ricard et al. / Energy Procedia 154 (2018) 106–111 Ricard and Pevzner / Energy Procedia 00 (2018) 000–000
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measuring tool is located at the bottom of the cable at 775mMD while the telemetry unit is located 10m above. Both of these items have electronics components and consume power as 11W for the telemetry unit and 4 W for the measuring tool. It is important to note that the temperature measurements starts before the VSP tool is lowered down in the well and that the measurements are taken from the DTS acquisition unit and along the entire length of the cables outside casing.
Figure 1. (Left) CRC-3 completion schematics. (Middle) CRC-3 wellhead. (Right) Distributed temperature sensing setup at CRC-3 showing the DTS interrogator, the controlling computer and the two temperature controlling baths.
3. Observations Temperature measurements are recorded every 4 mins during the entire sequence (over 3,400 time traces) at a spatial increment of 25 cm. Before the VSP tool is present, the temperature is constant in time and follow the local geothermal gradient down the well (Figure 2). A close examination of the temperature profile down the well lead to the identification of two anomalies as presented in Figure 3. The strongest anomaly of ~0.7 °C can be observed between 764 and 770mMD. The second anomaly of ~0.1°C can be observed between 776 and 780mMD. All measurements show that long term data processing provide estimates of temperature with variations less than 0.01 °C. A temporal profile of the temperature measurements at the depth of 767.43mMD highlights clearly a temperature increase starting on 28th February at 7.15pm, 45 min after the tool has been placed in the well (Figure 4). It corresponds to the operation of the telemetry unit at that location. From the amplitude of the temperature anomaly the power of the telemetry unit was estimated to be 15W (in comparison of 11W measured). This error is likely due to uncertainty on well design. A temporal profile of the temperature measurement at the depth of 778mMD does not provide a clear identification of the thermal anomaly produced by the bottom-most measurement tool. However, further data processing highlights the change of temperature highlights the long term trend (Figure 5). Based on the thermal anomaly amplitude, the heat produced by the downhole tool is estimated to be about 5 W (in comparison of 4W measured).
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Temperature (°C)
Figure 2. (Left) Temperature versus depth from well head (m) before the VSP tool is placed in the well. (Right) Temperature versus depth over time with baseline and anomaly time periods highlighted.
Figure 3. (left) Temperature profile versus depth (m) before and after VSP tool in place. (Middle) Zoom of the temperature profile at the VSP tool depth interval (m). (Right) Reduced temperature profile (Monitor - baseline) highlight two thermal anomalies.
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Figure 4. (Left) Reduced temperature profile (Monitor-baseline). (Right) Temporal profile of temperature at 767mMD.
Figure 5. (Left) Reduced temperature profile (Monitor-baseline). (Right) Temporal temperature profile at 778mMD. Several data processing averaging are presented in different colors.
4. Conclusions The use of DTS at the CRC 3 well was presented. While the temperature profile does not change significantly over time, the integration and processing of more than 3400 temperature traces enabled to estimate a temperature profile with a resolution of 0.01 °C. The use of DTS during the CO2CRC M5 survey highlights the detectability of a VSP tool producing 11 and 4 W at two distinct depth. The setup was capable of detecting a 0.7 C anomaly very quickly. A much smaller anomaly (0.1 °C) was detected with the benefit of data processing. The high spatial resolution of the DTS enable to locate the thermal anomaly (tool) within 2m. DTS installations involve inexpensive hardware with downhole components which are relatively inert by nature with all the electronics, optics located at surface in a controlled environment. Hence DTS installations have a long life-span and are inexpensive to operate. They have the ability to provide distributed temperature measurements with a low measurement error over a long distance. Appropriate experimental design, data processing and calibration processes enable to achieve very accurate
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quantitative interpretation. The interpretation of distributed temperature sensing measurements shows that it is possible to detect very small event and provide some quantitative estimates on the event itself when additional information on the operation in question are provided. It shows promising prospects in the context of monitoring cost reduction and early identification of events to inform near-realtime the decision-making process. 5. Acknowledgements The Otway project received CO2CRC funding through its industry members and research partners, the Australian Government under the CCS Flagships Programme, the Victorian State Government, and the Global CCS Institute. The authors wish to acknowledge financial assistance provided through Australian National Low Emissions Coal Research and Development supported by the Australian Coal Association Low Emissions Technology Limited and the Australian Government through the Clean Energy Initiative. We are grateful to Andrew Feitz (Geoscience Australia) for supporting this work as part of his SRD 3.3 project. We strongly appreciated Oleg Vashin and Jean Lepine from SERCEL providing the details of the VSP downhole tool. We thanks Michael Mondanos from Silixa for discussion on DTS parametrization. We also thank our colleagues from CO2CRC, CSIRO, and Curtin University, in particular Rajindar Singh and Konstantin Tertyshnokov, for their valuable support and contribution to this work. 6. References [1] Freifeld, B., Daley, T., Cook, P., Trautz, R., Dodds, K., 2014. The Modular Borehole Monitoring Program: a research program to optimize well-based monitoring for geologic carbon sequestration. Energy Procedia 63, 3500-3515. [2] Smolen, J. J. and van der Spek, (2003). A. Distributed temperature sensing—A DTS primer for oil & gas production - 2003. in Tech. Report, Shell. [3] Hartog, A. (2017). An Introduction to Distributed Optical Fibre Sensors. Boca Raton: CRC Press. [4] Correa, J., Egorov, A., Tertyshnikov, K., Bona, A., Pevzner, R., Dean, T., Freifeld, B., Marshall, S., (2017) Analysis of signal to noise and directivity characteristics of DAS VSP at near and far offsets — A CO2CRC Otway Project data example. The Leading Edge ; 36 (12): 994a1–994a7. doi: https://doi.org/10.1190/tle36120994a1.1 [5] Paterson, L., Boreham, C., Bunch, M., Ennis-King, J., Freifeld, B., Haese, R., Jenkins, C., Raab, M., Singh, R., Stalker, L., (2011). The CO2CRC Otway Stage 2 B Residual Saturation and Dissolution Test: Test Concept, Implementation and Data Collected, Milestone Report to ANLEC. http://hub.globalccsinstitute.com/sites/default/files/sites/default/files/co2crc-otway-stage2b-residual-saturation-dissolutiontest.pdf [6] Liebscher, A., Möller, F., Bannach, A., Köhler, S., Wiebach, J., Schmidt-Hattenberger, C., Weiner, M., Pretschner, C., Ebert, K., Zemke, J. (2013). Injection operation and operational pressure-temperature monitoring at the CO2 storage pilot site Ketzin, Germany – design, results, recommendations. Int. J. Greenhouse Gas Control, 15, pp. 163-173, 10.1016/j.ijggc.2013.02.019 [7] Wiese B., (2014). Thermodynamics and heat transfer in a CO2 injection well using distributed temperature sensing (DTS) and pressure data. Int. J. Greenhouse Gas Control, 21, pp. 232-242, 10.1016/j.ijggc.2013.12.009 [8] Núñez-López, V. (2011). Temperature monitoring at SECARB Cranfield Phase 3 site using distributed temperature sensing (DTS) technology. Poster Presented at the 10th Annual NETL Carbon Capture & Sequestration Conference, Pittsburgh, Pennsylvania, May 2–5, 2011. GCCC Digital Publication Series #11-10 (2011) [9] Doughty, C., Freifeld, B.M., (2013). Modeling CO2 injection at Cranfield, Mississippi: investigation of methane and temperature effects. Greenhouse Gas Sci. Technol., 3, pp. 475-490, 10.1002/ghg.1363 [10] Henninges, J.. (2010). Permanent distribution temperature sensing at the Ketzin CO2 storage test site. IEAGHG 6th Wellbore Network Meeting. http://www.ieaghg.org/docs/General_Docs/6wellbore/Presentations/Day2/14.25Henninges.pdf [11] Zhang, Y., Freifeld, B., Finsterle, S., Leahy, M., Ennis-King, J., Paterson, L., Dance, T., (2011). Single-well experimental design for studying residual trapping of supercritical carbon dioxide. Int. J. Greenhouse Gas Control, 5, pp. 88-98, [12] van de Giesen, N., Steele-Dunne, S.C., Jansen, J., Hoes, O., Hausner, M.B., Tyler, S., Selker, J., 2012. Double-Ended Calibration of FiberOptic Raman Spectra Distributed Temperature Sensing Data. Sensors 12, 5471.