Injection Profiling During Limited-Entry Fracturing Using Distributed-Temperature-Sensor Data
- Hai Nam Hoang (PetroVietnam) | Jagannathan Mahadevan (Chevron) | Henry Lopez (Shell Exploration and Production Company)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- September 2012
- Document Type
- Journal Paper
- 752 - 767
- 2012. Society of Petroleum Engineers
- 2.5.2 Fracturing Materials (Fluids, Proppant), 7.4.4 Energy Policy and Regulation, 2.2.2 Perforating, 5.6.11 Reservoir monitoring with permanent sensors, 3.2.3 Hydraulic Fracturing Design, Implementation and Optimisation, 5.8.1 Tight Gas
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Tight gas plays often have multiple lenses of producing formations. Multizone fracturing or limited-entry fracturing is a cost-effective method to complete and produce tight gas wells in these layered reservoirs. The rate and volume of fracturing fluid injected into the different layers have an important role in determining the fracture characteristics. However, because of the spatial restriction of downhole conditions, it is very challenging to obtain a specific injection rate for each perforated zone. Temperature variations in the wellbore, outside of the casing, are available with new technology such as distributed-temperature-sensor (DTS) fiber-optic cables. The main objective of this study is to relate the wellbore-temperature changes as measured by DTS data to the wellbore and fractured-interval injection rates during a multizone fracturing process.
We develop a forward simulation model on the basis of mass and energy conservation for calculating the temperature profile and temperature history in the wellbore and in the rock surrounding the wellbore. The model allows for liquid flow into the fractured interval. Subsequently, the model is integrated with an inverse-estimation algorithm, which is used to estimate flow rates both in the wellbore and into the fractured interval. The estimation algorithm is based on a gradient search method. A distinguishing feature of this work is the development of a radial model used to represent the temperature evolution in the near-wellbore region. The higher order allows accurate calculation of the temperature in the wellbore while still capturing the fluid-flow and heat-transport aspects of the hydraulic-fracture propagation.
Our estimation results show a good comparison between the calculated temperature profiles and those observed in the field with DTS. Also, the model is able to estimate a flow-rate history consistent with total field-injection volume. This work enables an accurate and quick interpretation of the wellbore DTS data to determine the interval injection rates during a hydraulic-fracturing process. Knowledge of accurate interval injection rates and the corresponding fracture characteristics can be useful in designing a better limited-entry completion that can optimize the fracture length by use of rate control and/or fluid diversion.
|File Size||4 MB||Number of Pages||16|
Al-Asimi, M., Brown, G., and Cosad, C. 2003. Fiber Optic TemperatureMonitoring Optimizes Water Injection, Well Production. World Oil 224 (11): 39-42.
Brown, G. 2008. Downhole Temperatures from Optical Fiber. OilfieldReview 20 (4): 34-39.
Cramer, D.D. 1987. The Application of Limited-Entry Techniques in MassiveHydraulic Fracturing Treatments. Paper SPE 16189 presented at the SPEProduction Operations Symposium, Oklahoma City, Oklahoma, USA, 8-10 March. http://dx.doi.org/10.2118/16189-MS.
Hagoort, J. 2004. Ramey's Wellbore Heat Transmission Revisited. SPEJ. 9 (4): 465-474. SPE-87305-PA. http://dx.doi.org/10.2118/87305-PA.
Hasan, A.R. and Kabir, C.S. 1994. Aspects of Wellbore Heat Transfer DuringTwo-Phase Flow. SPE Prod & Fac 9 (3): 211-216.SPE-22948-PA. http://dx.doi.org/10.2118/22948-PA.
Hoang, H. 2011. Injection Profiling During Limited Entry Fracturing UsingDistributed Temperature Sensor Data. MS thesis, The University of Tulsa,Tulsa, Oklahoma.
Howard, G.C. and Fast, C.R. 1957. Optimum Fluid Characteristics for FractureExtension (Appendix by E.D. Carter). API Drilling & ProductionPractice (April 1957): 261-270.
Huckabee, P.T. 2009. Optic Fiber Distributed Temperature for FractureStimulation Diagnostics and Well Performance Evaluation. Paper SPE 118831presented at the SPE Hydraulic Fracturing Technology Conference, The Woodlands,Texas, USA, 19-21 January. http://dx.doi.org/10.2118/118831-MS.
Kamphuis, H., Davies, D.R., and Roodhart, L.P. 1993. A New SimulatorFor the Calculation of the In Situ Temperature Profile During Well StimulationFracturing Treatments. J Can Pet Technol 32 (5).PETSOC-93-05-03. http://dx.doi.org/10.2118/93-05-03.
Li, Z. and Zhu, D. 2010. Predicting Flow Profile of Horizontal Well byDownhole Pressure and Distributed-Temperature Data for Waterdrive Reservoir.SPE Prod & Oper 25 (3): 296-304. SPE-124873-PA. http://dx.doi.org/10.2118/124873-PA.
McAdams, W.H. 1942. Heat Transmission, 63-64. New York: McGraw-HillBook Company.
Ouyang, L.-B. and Belanger, D. 2006. Flow Profiling by DistributedTemperature Sensor (DTS) System--Expectation and Reality. SPE Prod &Oper 21 (1): 269-281. SPE-90541-PA. http://dx.doi.org/10.2118/90541-PA.
Pimenov, V., Brown, G.A., Tertychnyi, V.V. et al. 2005. InjectivityProfiling in Horizontal Wells via Distributed Temperature Monitoring. Paper SPE97023 presented at the SPE Annual Technical Conference and Exhibition, Dallas,9-12 October. http://dx.doi.org/10.2118/97023-MS.
Ramey, H.J. Jr. 1962. Wellbore Heat Transmission. J Pet Technol 14 (4): 427-435. SPE-96-PA. http://dx.doi.org/10.2118/96-PA.
Science & Technologies Facilities Council (STFC). 2010. The HSLMathetical Software Library, http://www.hsl.rl.ac.uk/ (accessed 15 June2010).
Seth, G., Reynolds, A.C., and Mahadevan, J. 2010. Numerical Model forInterpretation of Distributed Temperature Sensor Data During HydraulicFracturing. Paper SPE 135603 presented at the SPE Annual Technical Conferenceand Exhibition, Florence, Italy, 19-22 September. http://dx.doi.org/10.2118/135603-MS.
Sierra, J., Kaura, J., Gualtieri, D. et al. 2008. DTS Monitoring Data ofHydraulic Fracturing: Experiences and Lessons Learned. Paper SPE 116182presented at the SPE Annual Technical Conference and Exhibition, Denver, 21-24September. http://dx.doi.org/10.2118/116182-MS.
Whitsitt, N.F. and Dysart, G.R. 1970. The Effect of Temperature OnStimulation Design. J Pet Technol 22 (4): 493-502.SPE-2497-PA. http://dx.doi.org/10.2118/2497-PA.
Yoshioka, K., Zhu, D., Hill, A.D. et al. 2005. A Comprehensive Model ofTemperature Behavior in a Horizontal Well. Paper SPE 95656 presented at the SPEAnnual Technical Conference and Exhibition, Dallas, 9-12 October. http://dx.doi.org/10.2118/95656-MS.
Zhao, J. and Tso, C.P. 1993. Heat transfer by water flow in rock fracturesand the application to hot dry rock geothermal systems. InternationalJournal of Rock Mechanics and Mining Sciences & GeomechanicsAbstracts 30 (6): 633-641. http://dx.doi.org/10.1016/0148-9062(93)91223-6.