Transferring Intelligent-Well-System Triple-Gauge Data Into Real-Time Flow Allocation
- Kai Sun (Chevron) | Oluwole Omole (Hess Corporation) | Luigi Saputelli (Hess Corporation) | Fabio Gonzalez (Hess Corporation)
- Document ID
- Society of Petroleum Engineers
- SPE Drilling & Completion
- Publication Date
- June 2012
- Document Type
- Journal Paper
- 264 - 281
- 2012. Society of Petroleum Engineers
- 5.3.2 Multiphase Flow, 3.3.4 Downhole Monitoring and Control, 2.3 Completion Monitoring Systems/Intelligent Wells, 2.3.4 Real-time Optimization, 5.6.8 Well Performance Monitoring, Inflow Performance
- 2 in the last 30 days
- 633 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
Knowing the exact flow allocation for each controlled zone is important for well optimization and the management of an intelligent well system (IWS). For two-zone IWS producers, a broadly accepted downhole gauge configuration uses the triple-gauge system, where two gauges give the upstream-side pressure/temperature (P/T) of the two downhole control valves and one gauge gives the P/T inside tubing of the commingled fluid [Baker Hughes IWS installation (2012) and Halliburton-WellDynamics IWS installation (2012) databases]. Theoretically, this configuration gives the P/T boundary conditions between the two valves and the gauge carrier, where flow allocations can be solved numerically, on the basis of the gauge readings and control-valve settings. However, from what we have seen in the past 10 years of IWS applications, only a few have published successful application cases regarding this topic. Is this an indication that a large number of two-zone triple-gauge IWS wells are operating in the low-confidence region of the two zone's production flow allocations?
In this work, a comprehensive hydraulic model has been developed to address this topic. This paper will discuss a recent application of such a model to estimate the flow allocations of an existing two-zone deepwater IWS oil producer. The well began production in 2007. A total of 1,362 daily triple-gauge data points are available for this study, where the monitored P/T data indicate that the well was flowed in multiphase conditions at downhole for a large percentage of its production life. Verification was completed by comparing the predicted flow-allocation results with this well's measured total rates and daily-allocation rates. Further comparisons of the zonal allocations, between the model calculated results vs. the zonal-reservoir deliverability-study predicted results, were also provided. These comparisons showed a good match between the predicted results, measured data, and the available reservoir-study results. Descriptions of key factors to address the accuracy of the method have been provided, including compensated differential pressure, multiphase choke model, choke-discharge coefficient, and fluid pressure/volume/temperature (PVT) behavior impact. Sun's modified multiphase choke model was proposed in this study. The authors believe it will be more suitable for downhole valve operating and multiphase-flow conditions.
This case study has proven a very promising independent solution for continuous well-rate estimation, with the solution based purely on choke-pressure drops and intelligent well-valve positions. The downhole monitoring P/T is normally based on seconds, which means that intelligent well-flow allocations can be calculated in real time without installing downhole venturi flowmeters that may add completion cost. In addition, a venturi flowmeter provides a smaller ID profile for the completion strings above/below it, which is inconvenient for future potential wellbore interventions. This solution brings measurable benefits for those IWS wells with no downhole flowmeters when taking into account the time and effort spent on periodic production tests, reservoir/well deliverability studies for production allocations, and potential production loss during the production tests.
|File Size||8 MB||Number of Pages||18|
Al-Otaibi, N.M., Al-Gamber, A.A., Konopczynski, M., and Jacob, S.2006. Smart-Well Completion Utilizes Natural Reservoir Energy To ProduceHigh-Water-Cut and Low-Productivity-Index Well in Abqaiq Field. Paper SPE104227 presented at the International Oil & Gas Conference and Exhibitionin China, Beijing, 5-7 December. http://dx.doi.org/10.2118/104227-MS.
Baker Hughes. 2012. Intelligent Well System installation historydatabase. Houston, Texas: Baker Hughes.
Brill, J.P. and Mukherjee, H. 1999. Multiphase Flow in Wells, No. 17,Chap. 4, 28-67. Richardson, Texas: Monograph Series, SPE.
Dolle, N., Singh, P., Turner, R., Woodward, M., and Paino, W.-F. 2005. GasManagement, Reservoir Surveillance, and Smart Wells-An Integrated Solution forthe Bugan Field. Paper SPE 96429 presented at the SPE Annual TechnicalConference and Exhibition, Dallas, 9-12 October. http://dx.doi.org/10.2118/96429-MS.
Glandt, C.A. 2005. Reservoir Management Employing Smart Wells: A Review.SPE Drill & Compl 20 (4): 281-288. SPE-81107-PA. http://dx.doi.org/10.2118/81107-PA.
Guo, B., Lyons, W.C., and Ghalambor, A. 2007. Petroleum ProductionEngineering: A Computer-Assisted Approach, Part 1, Sec. 4.4, 4/53-4/55.Oxford, UK: Gulf Professional Publishing.
Guo, B., Sun, K., and Ghalambor, A. 2008. Well Productivity Handbook,Chap. 8, 247-311. Houston, Texas: Gulf Publishing Company.
Hagedorn, A.R. and Brown, K.E. 1965. Experimental Study of PressureGradients Occurring During Continuous Two-Phase Flow in Small Diameter VerticalConduits. J Pet Technol 17 (4): 475-484. SPE-940-PA. http://dx.doi.org/10.2118/940-PA.
Halliburton. 2012. WellDynamics Intelligent Well System installation historydatabase. Houston, Texas: Halliburton.
Hiestand, J.W. 2009. Numerical Methods with VBA Programming, Chap. 7,113-117. Sudbury, Massachusetts: Jones and Bartlett Publisher.
Hill, L.E., Izetti, R., Ratterman, G., et al. 2002. The Integration ofIntelligent Well Systems into Sandface Completions for Reservoir Inflow Controlin Deepwater. Paper SPE 77945 presented at the SPE Asia Pacific Oil and GasConference and Exhibition, Melbourne, Australia, 8-10 October. http://dx.doi.org/10.2118/77945-MS.
Konopczynski, M. and Ajayi, A. 2004. Design of Intelligent Well DownholeValves for Adjustable Flow Control. Paper SPE 90664 presented at the SPE AnnualTechnical Conference and Exhibition, Houston, 26-29 September. http://dx.doi.org/10.2118/90664-MS.
Lorenz, M.D., Ratterman, E.E., Martins, J.A.S., and Triplett, W.N. 2006.Advancement in Completion Technologies Prove Successful in Deepwater Frac-Packand Horizontal Gravel-Pack Completions. Paper SPE 103103 presented at the SPEAnnual Technical Conference and Exhibition, San Antonio, Texas, USA, 24-27September. http://dx.doi.org/10.2118/103103-MS.
Moore, W.R., Konopczynski, M.R., and Nielsen, V.J. 2002. Implementation ofIntelligent Well Completions Within a Sand Control Environment. Paper SPE 77202presented at the IADC/SPE Asia Pacific Drilling Technology, Jakarta, 8-11September. http://dx.doi.org/10.2118/77202-MS.
Omole, O.A., Saputelli, L.A., Lissanon, J.S., et al. 2011. Real-timeProduction Optimization in the Okume Complex Field, Offshore Equatorial Guinea.Paper SPE 144195 presented at the SPE Digital Energy Conference and Exhibition,The Woodlands, Texas, USA, 19-21 April. http://dx.doi.org/10.2118/144195-MS.
Perkins, T.K. 1993. Critical and Sub-Critical Flow of Multiphase MixturesThrough Chokes. SPE Drill & Compl 8 (4): 271-276.SPE-20633-PA. http://dx.doi.org/10.2118/20633-PA.
Rawding, J., Al-Matar, B.S., and Konopczynski, M.R. 2008.Application of Intelligent Well Completion for Controlled Dumpflood in WestKuwait. Paper SPE 112243 presented at the Intelligent Energy Conference andExhibition, Amsterdam, 25-27 February. http://dx.doi.org/10.2118/112243-MS.
Sachdeva, R., Schmidt, Z., Brill, J.P., and Blais, R.M. 1986. Two-Phase FlowThrough Chokes. Paper SPE 15657 presented at the SPE Annual TechnicalConference and Exhibition, New Orleans, 5-8 October. http://dx.doi.org/10.2118/15657-MS.
Snaith, N., Chia, R., Narayasamy, D., and Schrader, K. 2003.Experience With Operation Of Smart Wells To Maximise Oil Recovery From ComplexReservoirs. Paper SPE 84855 presented at the SPE International Improved OilRecovery Conference in Asia Pacific, Kuala Lumpur, 20-21 October. http://dx.doi.org/10.2118/84855-MS.
Sun, K. and Konopczynski, M.R. 2006a. Applying Wellbore Characterization andWell Injectivity Profile To Predict Flow Distribution of MultipleZones—Intelligent Injection Well. Paper SPE 104172 presented at the SPEInternational Oil & Gas Conference and Exhibition, Beijing, China, 5-7December.
Sun, K. and Konopczynski, M.R. 2006b. Prediction of Injection-FluidDistributions for Multiple Zones-Intelligent Injection System. Paper SPE 103078presented at the SPE Annual Technical Conference and Exhibition, San Antonio,Texas, USA, 24-27 September. http://dx.doi.org/10.2118/103078-MS.
Sun, K., Constantine, J.J., and Coull, C. 2008a. Interaction BetweenIntelligent Well Applications and Reservoir Management - A ComprehensiveThermal Modeling Technology for IWS Well. Paper SPE 115102 presented at the SPEAnnual Technical Conference and Exhibition, Denver, 21-24 September. http://dx.doi.org/10.2118/115102-MS.
Sun, K., Coull, C., and Constantine, J.J. 2008b. A Practice ofApplying Downhole Real Time Gauge Data and Control-Valve Settings to EstimateSplit Flow Rate for an Intelligent Injection Well System. Paper SPE 115135presented at the SPE Annual Technical Conference and Exhibition, Denver, 21-24September. http://dx.doi.org/10.2118/115135-MS.
Sun, K., Coull, C., Constantine, J.J., Albrecht, K.D., and Tirado, R.A.2008c. Modeling the Downhole Choking's Impacts on Well Flow Performance andProduction Fluid Allocations of a Multiple-Zone Intelligent Well System. PaperSPE 113416 presented at the Europec/EAGE Conference and Exhibition, Rome, 9-12June. http://dx.doi.org/10.2118/113416-MS.
Sun, K., Konopczynski, M.R., and Ajayi, A.A. 2006c. Using Downhole Real-TimeData To Estimate Zonal Production in a Commingled-Multiple-Zones IntelligentSystem. Paper SPE 102743 presented at the SPE Annual Technical Conference andExhibition, San Antonio, Texas, USA, 24-27 September. http://dx.doi.org/10.2118/102743-MS.