The Information Content and Integration of Distributed-Temperature-Sensing Data for Near-Wellbore-Reservoir Characterization
- Bohan Xu (University of Tulsa) | Fahim Forouzanfar (University of Tulsa)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- November 2017
- Document Type
- Journal Paper
- 906 - 923
- 2017.Society of Petroleum Engineers
- Distributed Temperature Sensing (DTS), Uncertainty Reduction, Information Content of Temperature Data, Ensemble Smoother with Multiple Data Assimilation, History Matching
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- 258 since 2007
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Downhole-temperature measurements provide valuable data for characterizing the flow between the reservoir and wellbore, which in turn is a function of the individual-reservoir-layer properties. In this paper, we investigate the use of downhole-temperature-profile data, provided from distributed-temperature-sensing (DTS) systems, as a cost-effective and robust alternative to other common approaches, such as use of data from production-logging tools, for estimating the formation properties and production profile along the wellbore. Previous applications of history-matching techniques by use of downhole-temperature-profile data have been mostly limited to simple reservoirs, and the quality of their results was unacceptable for more-complex cases. In this work, we present the evaluation and application of temperature-profile data from DTS systems for uncertainty reduction in the reservoir description. We focus on the characterization of multilayer multiphase reservoir cases with a high degree of vertical heterogeneity. First, by use of the principles of information theory, we investigate the information content of the temperature-profile data regarding various reservoir properties. By computing the mutual information between the reservoir parameters and the temperature-profile data, the reservoir properties with higher influence on the reservoir- and wellbore-temperature-profile data are identified. The associated uncertainty in these reservoir properties can be reduced by assimilating the downhole-temperature-profile data. Through these analyses, we also present an estimation for the expected reduction of uncertainty in the reservoir properties by assimilating the temperature data. Then, we apply the ensemblesmoother-with-multiple-data-assimilation (ES-MDA) algorithm to estimate the reservoir properties selected by use of our previous analysis. The set of observed data contains the wellbore-temperature profile, the temperature profile of the reservoir adjacent to the wellbore, and the flowing bottomhole pressure (BHP) of the well at a reference depth. We investigate the performance of the history-matching algorithm by use of various combinations of these observed data for estimating the properties of a synthetic layered reservoir. In addition, the implementation of a doubly stochastic model is also investigated to account for possible uncertainties in the prior mean of the reservoir properties. Our results show that the downhole-temperature-profile data contain a significant amount of information regarding the permeability and porosity of the reservoir layers. Moreover, the use of temperature-profile data within the ES-MDA history-matching algorithm is able to provide a good estimation of these properties and significantly reduce the uncertainty in the reservoir description.
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Bear, H. 1972. Dynamics of Fluids in Porous Media. Mineola, New York: Dover Publishing.
Beirlant, J., Dudewicz, E. J., Gyo¨rfi, L. et al. 1997. Nonparametric Entropy Estimation: An Overview. Int. J. Math. Stat. Sci. 6 (1): 17–39.
Bloomfield, J. P. and Williams, A. T. 1995. An Empirical Liquid Permeability–Gas Permeability Correlation for Use in Aquifer Properties Studies. Q. Eng. Geol. Hydroge. 28 (S2): S143–S150. https://doi.org/10.1144/GSL.QJEGH.1995.028.S2.05.
Curtis, M. R. and Witterholt, E. J. 1973. Use of the Temperature Log for Determining Flow Rates in Producing Wells. Presented at the Fall Meeting of the Society of Petroleum Engineers of AIME, Las Vegas, Nevada, 30 September–3 October. SPE-4637-MS. https://doi.org/10.2118/4637-MS.
Denney, D. 2012. DTS Technology: Improving Acid Placement. J Pet Technol 64 (6): 96–99. SPE-0612-0096-JPT. https://doi.org/10.2118/0612-0096-JPT.
Edmister, W. C. 1988. Applied Hydrocarbon Thermodynamics, Vol. 2. Houston: Gulf Publishing Company.
Emerick, A. A. and Reynolds, A. C. 2012. History Matching Time-Lapse Seismic Data Using the Ensemble Kalman Filter With Multiple Data Assimilations. Computat. Geosci. 16 (3): 639–659. https://doi.org/10.1007/s10596-012-9275-5.
Emerick, A. A. and Reynolds, A. C. 2013. Ensemble Smoother With Multiple Data Assimilation. Comput. Geosci. 55 (June): 3–15. https://doi.org/10.1016/j.cageo.2012.03.011.
Forouzanfar, F., Pires, A. P., and Reynolds, A. C. 2015. Formulation of a Transient Multi-Phase Thermal Compositional Wellbore Model and its Coupling with a Thermal Compositional Reservoir Simulator. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 28–30 September. SPE-174749-MS. https://doi.org/10.2118/174749-MS.
Freeze, R. A. and Cherry, J. A. 1979. Groundwater. Upper Saddle River, New Jersey: Prentice Hall.
Guerin, G. 2000. Acoustic and Thermal Characterization of Oil Migration, Gas Hydrates Formation and Silica Diagenesis. PhD dissertation, Columbia University, New York City.
Guo, F., Yang, D., Eriksson, K. A. et al. 2015. Paleoenvironments, Stratigraphic Evolution and Reservoir Characteristics of the Upper Cretaceous Yingjisha Group, Southwest Tarim Basin. Mar. Petrol. Geol. 67 (November): 336–355. https://doi.org/10.1016/j.marpetgeo.2015.05.023.
Hasan, A. R. and Kabir, C. S. 1998. A Simplified Model for Oil/Water Flow in Vertical and Deviated Wellbores. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 27–30 September. SPE-49163-MS. https://doi.org/10.2118/49163-MS.
Hasan, A. R. and Kabir, C. S. 2012. Wellbore Heat-Transfer Modeling and Applications. J. Pet. Sci. Eng. 86–87 (May): 127–136. https://doi.org/10.1016/j.petrol.2012.03.021.
Huckabee, P. T. 2009. Optic Fiber Distributed Temperature for Fracture Stimulation Diagnostics and Well Performance Evaluation. Presented at the SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, 19–21 January. SPE-118831-MS. https://doi.org/10.2118/118831-MS.
Johnson, D. O., Sierra, J. R., Kaura, J. D. et al. 2006. Successful Flow Profiling of Gas Wells Using Distributed Temperature Sensing Data. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 24–27 September. SPE-103097-MS. https://doi.org/10.2118/103097-MS.
Kon?a´kova´, D., Vejmelkova´, E., and C? erny´ , R. 2013. Thermal Properties of Selected Sandstones. Proc., 4th International Conference on Fluid Mechanics and Heat & Mass Transfer, Duborvnik, Croatia, 2–527 June, 100–104.
Kraskov, A., Sto¨gbauer, H., and Grassberger, P. 2004. Estimating Mutual Information. Phys. Rev. E 69 (6): 066138. https://doi.org/10.1103/PhysRevE.69.066138.
Le, D. H. and Reynolds, A. C. 2014. Optimal Choice of a Surveillance Operation Using Information Theory. Computat. Geosci. 18 (3–4): 505–518. https://doi.org/10.1007/s10596-014-9401-7.
Li, G., Han, M., Banerjee, R. et al. 2009. Integration of Well Test Pressure Data Into Heterogeneous Geological Reservoir Models. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 4–7 October. SPE-124055-MS. https://doi.org/10.2118/124055-MS.
Livescu, S., Durlofsky, L. J., Aziz, K. et al. 2010. A Fully-Coupled Thermal Multiphase Wellbore Flow Model for Use in Reservoir Simulation. J. Pet. Sci. Eng. 71 (3–4): 138–146. https://doi.org/10.1016/j.petrol.2009.11.022.
Onur, M. and Çinar, M. 2016. Temperature Transient Analysis of Slightly Compressible, Single-Phase Reservoirs. Presented at SPE Europec featured at 78th EAGE Conference and Exhibition, Vienna, Austria, 30 May–2 June. SPE-180074-MS. https://doi.org/10.2118/180074-MS.
Onur, M., Ulker, G., Kocak, S. et al. 2016. Interpretation and Analysis of Transient Sandface and Wellbore Temperature Data. Presented at the SPE Annual Technical Conference and Exhibition, Dubai, 26–28 September. SPE-181710-MS. https://doi.org/10.2118/181710-MS.
Perry, R. H. and Green, D. W. ed. 1984. Perry’s Chemical Engineers’ Handbook, sixth edition. New York City: McGraw-Hill Professional.
Quintero, L. F., Manrique, E. J., Linares, J. A. et al. 1993. Permeability Measurement Through Temperature Logging. Presented at the SPWLA 34th Annual Logging Symposium, Calgary, 13–16 June. SPWLA-1993-C.
Raman, C. V. 1928. A New Radiation. Indian J. Phys. 2: 387–398.
Ren, J., Zhang, L., Ezekiel, J. et al. 2014. Reservoir Characteristics and Productivity Analysis of Tight Sand Gas in Upper Paleozoic Ordos Basin China. J. Nat. Gas Sci. Eng. 19 (July): 244–250. https://doi.org/10.1016/j.jngse.2014.05.014.
Reynolds, A. C., He, N., and Oliver, D. S. 1999. Reducing Uncertainty in Geostatistical Description with Well-Testing Pressure Data. In AAPG Memoir 71: Reservoir Characterization-Recent Advances, ed. R. A. Schatzinger and J. F. Jordan, Chap. 10, 149–162. Tulsa: American Association of Petroleum Geologists.
Schlumberger. 2013. Eclipse Technical Description Manual.
Shannon, C. E. 1948. A Mathematical Theory of Communication. AT&T Tech. J. 27 (3): 379–423.
Shi, H., Holmes, J. A., Durlofsky, L. J. et al. 2003. Drift-Flux Modeling of Multiphase Flow in Wellbores. Presented at the SPE Annual Technical Conference and Exhibition, Denver, 5–8 October. SPE-84228-MS. https://doi.org/10.2118/84228-MS.
Shi, H., Holmes, J., Diaz, L. et al. 2005. Drift-Flux Parameters for Three-Phase Steady-State Flow in Wellbores. SPE J. 10 (2): 130–137. SPE-89836-PA. https://doi.org/10.2118/89836-PA.
Shoham, O. 2006. Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes. Richardson, Texas: Society of Petroleum Engineers. Smekal, A. 1923. Zur Quantentheorie der Dispersion. Die Naturwissenschaften 11 (43): 873–875. https://doi.org/10.1007/BF01576902.
Stone, T. W., Bennett, J., Law, D. S. et al. 2001. Thermal Simulation with Multisegment Wells. Presented at the SPE Reservoir Simulation Symposium, Houston, 11–14 February. SPE-66373-MS. https://doi.org/10.2118/66373-MS.
Tarrahi, M., Gildin, E., Moreno, J. et al. 2014. Dynamic Integration of DTS Data for Hydraulically Fractured Reservoir Characterization with the Ensemble Kalman Filter. Presented at the SPE Energy Resources Conference, Port of Spain, Trinidad and Tobago, 9–11 June. SPE-169990-MS. https://doi.org/10.2118/169990-MS.
Villesca, J., Glasbergen, G., and Attaway, D. J. 2011. Measuring Fluid Placement of Sand Consolidation Treatments Using DTS. Presented at the SPE European Formation Damage Conference, Noordwijk, The Netherlands, 7–10 June. SPE-144432-MS. https://doi.org/10.2118/144432-MS.
Wang, X. and Bussear, T. R. 2011. Real Time Horizontal Well Monitoring Using Distributed Temperature Sensing (DTS) Technology. Presented at OTC Brasil, Rio de Janeiro, 4–6 October. OTC-22293-MS. https://doi.org/10.4043/22293-MS.
Wang, Z. 2012. The Uses of Distributed Temperature Survey (DTS) Data. PhD dissertation, Stanford University, Stanford, California (August 2012).
Willhite, G P. 1986. Waterflooding. Richardson, Texas: Society of Petroleum Engineers.
Zhao, Y., Forouzanfar, F., and Reynolds, A. C. 2016. Assisted History Matching for Multi-Facies Channelized Reservoir Using ES-MDA with Common Basis DCT. Oral presentation given at ECMOR XIV–15th European Conference on the Mathematics of Oil Recovery, Amsterdam, 29 August–1 September.