Reservoir Characterization During Underbalanced Drilling (UBD): Methodology and Active Tests
- Erlend H. Vefring (Rogaland Research Centre) | Gerhard H. Nygaard (RF-Rogaland Research) | Rolf J. Lorentzen (RF-Rogaland Research) | Geir Naevdal (International Research Institute of Stavanger AS) | Kjell K. Fjelde (International Research Institute)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- June 2006
- Document Type
- Journal Paper
- 181 - 192
- 2006. Society of Petroleum Engineers
- 3.3 Well & Reservoir Surveillance and Monitoring, 5.3.2 Multiphase Flow, 5.6.1 Open hole/cased hole log analysis, 1.6.1 Drilling Operation Management, 5.1 Reservoir Characterisation, 1.8 Formation Damage, 5.5 Reservoir Simulation, 2 Well Completion, 5.1.5 Geologic Modeling, 5.6.4 Drillstem/Well Testing, 5.2 Reservoir Fluid Dynamics, 5.2.2 Fluid Modeling, Equations of State, 1.10.1 Drill string components and drilling tools (tubulars, jars, subs, stabilisers, reamers, etc), 1.6 Drilling Operations, 1.7.1 Underbalanced Drilling, 5.4.2 Gas Injection Methods
- 7 in the last 30 days
- 623 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
Two methods for characterizing reservoir pore pressure and reservoir permeability during UBD while applying active tests are presented and evaluated. Both methods utilize a fast, dynamic well fluid-flow model that is extended with a transient reservoir model. Active testing of the well is applied by varying the bottomhole pressure in the well during the drilling operations.
The first method uses the Levenberg-Marquardt optimization algorithm to estimate the reservoir parameters by minimizing the difference between measurements from the drilling process and the corresponding model states. The method is applied after the drilling process is finished, using all the recorded measurements. The second method is the
ensemble Kalman filter, which simulates the drilling process using the dynamic model while drilling is performed, and updates the model states and parameters each time new measurements are available. Measurements are used that usually are available while drilling are used, such as pump rates, pump pressure, bottomhole pressure, and outlet rates.
The methods are applied to different cases, and the results indicate that active tests might improve the estimation results. The results also show that both estimation methods give useful results, and that the ensemble Kalman filter calculates these results during the UB operation.
During UBD, the well pressure is kept below the reservoir pore pressure, and reservoir fluids flow into the well. The flow rate from the reservoir depends on the pressure difference between the reservoir pore pressure and the well pressure, in addition to other reservoir parameters, such as permeability and porosity. The viscosity and compressibility of the reservoir fluids also influence the influx rate.
The influx of reservoir fluids causes variations in the annulus section of the well, because of changes in well fluid composition and well fluid-flow rate. By measuring some of the fluid-flow parameters of the well, such as pressures changes and rate changes, the reservoir parameters causing the influx might be identified. This is the principal idea that also is the basis for well testing and transient reservoir analysis. Identification of the reservoir properties close to the well gives important information for planning the well-completion design. If highly productive zones can be located, then the use of smart completion can be better utilized.
Reservoir characterization during UBD has received attention from several research groups in recent years. Kardolus and van Kruijsdijk (1997) developed a transient reservoir model based on the boundary-element method. This model was compared with a transient analytical reservoir model. One of their findings was that the transient analytical reservoir model could be used for evaluation of the parameters in the reservoir. In a following study, van Kruijsdijk and Cox (1999) presented a method for identifying the permeability in a horizontal reservoir based on measurements of the reservoir inflow. The flow effects caused by the reservoir boundaries were included in the flow calculations.
|File Size||1 MB||Number of Pages||12|
Balchen, J.G. and Mumme, K.I. 1988. Process Control. Structures andApplications. New York: Van Nostrand Reinhold.
Benzoni-Gavage, S. 1991. Analyse Numérique des Modèles HydrodynamiquesD`écoulements Diphasiques Instationnaires dans le Réseaux de ProductionPétrolière. Thèse ENS, Lyon, France.
Biswas, D., Suryanarayana, P.V., Frink, P.J., and Rahman, S. 2003. An Improved Model To PredictReservoir Characteristics During Underbalanced Drilling. Paper SPE 84176presented at the SPE Annual Technical Conference and Exhibition, Denver, 5-8October.
Burgers, G., van Leeuvwen, P.J., and Evensen, G. 1998. Analysis Scheme inthe Ensemble Kalman Filter. Monthly Weather Review. 126: 1719-1724.
Cohn, S.E. 1997. An Introduction to Estimation Theory. Journal of theMeteorological Society of Japan. 75: 257-288.
Dake, L.P. 1978. Fundamentals of reservoir engineering. In Developments inPetroleum Engineering, Vol. 8. Amsterdam: Elsevier.
Evensen, G. 1994. Sequential Data Assimilation with NonlinearQuasi-geostrophic Model Using Monte Carlo Methods to Forecast Error Statistics.J. Geophys. Res. 99 (C5): 10 143-10 162.
Evensen, G. 1997. Application of Ensemble Integrations for PredictabilityStudies and Data Assimilation. Monte Carlo Simulations in Oceanography. Proc.,'Aha Huliko'a Hawaiian Winter Workshop. U. of Hawaii at Manoa, 14-17January.
Gill, P.E., Murray, W., and Wright, M.H. 1981. Practical Optimization. SanDiego: Academic Press. 167.
Hasan, A.R., Kabir, C.S., and Srinivasan, S. 1994. Countercurrent Bubbleand Slug Flows in a Vertical System. Chemical Eng. Science 49:2567-2574.
Hunt, J.L. and Rester, S. 2000. Reservoir Characterization DuringUnderbalanced Drilling: A New Model. Paper SPE 59743 presented at theSPE/CERI Gas Technology Symposium, Calgary, 3-5 April.
Hunt, J.L. and Rester, S. 2003. Multilayer Reservoir Model EnablesMore Complete Reservoir Characterization During Underbalanced Drilling.Paper SPE 81638 presented at the IADC/SPE Underbalanced Technology Conferenceand Exhibition, Houston, 25--26 March.
Ioannou, P.A. and Sun, J. 1996. Robust Adaptive Control. Upper Saddle River,New Jersey: Prentice-Hall, 255.
Ishii, M. 1975. Thermo-Fluid Dynamic Theory of Two-Phase Flow. Paris:Eyrolles.
Kardolus, C.B. and van Kruijsdijk, C.P.J.W. 1997. Formation Testing While UnderbalancedDrilling. Paper SPE 38754 presented at the SPE Annual Technical Conferenceand Exhibition, San Antonio, Texas, 5-8 October.
Kneissl, W. 2001. ReservoirCharacterization Whilst Underbalanced Drilling. Paper SPE/IADC 67690 in theproceedings for the SPE/IADC Drilling Conference, Amsterdam, 27 February-1March.
Lage, A.C.V.M. 2000. Two-Phase Flow Models and Experiments for Low-Head andUnderbalanced Drilling. PhD dissertation, Stavanger U. College, Stavanger,Norway.
Lage, A.C.V.M., Fjelde, K.K., and Time, R.W. 2000a. Underbalanced Drilling Dynamics:Two-Phase Flow Modeling and Experiments. 2000. Paper IADC/SPE 62743presented at the IADC/SPE Asia Pacific Drilling Technology Conference, KualaLumpur, 11-13 September.
Lage, A.C.V.M., Frøyen, J., Sævareid, O., and Fjelde, K.K. 2000b.Underbalanced Drilling Dynamics: Two-Phase Flow Modeling, Experiments andNumerical Solution Techniques. Paper IBP 41400 presented at the Rio Oil and GasConference, Rio de Janerio, 16-19 October.
Larsen, L. and Nilsen, F. 1999. Inflow Predictions and Testing WhileUnderbalanced Drilling. Paper SPE 56684 presented at the SPE AnnualTechnical Conference and Exhibition, Houston, 3-6 October 1999.
Lorentzen, R.J., Fjelde, K.K., Frøyen, F., Lage, A.C.V.M., Nævdal, G., andVefring, E.H. 2001a. UnderbalancedDrilling: Real-Time Data Interpretation and Decision Support . PaperSPE/IADC 67693 presented at the SPE/IADC Drilling Conference, Amsterdam, 27February-1 March.
Lorentzen, R.J., Fjelde, F., Frøyen, J., Lage, A.C.V.M., Nævdal, G., andVefring, E.H. 2001b. Underbalancedand Low-Head Drilling Operations: Real-Time Interpretation of Measured Data andOperational Support. Paper SPE 71384 presented at the SPE Annual TechnicalConference and Exhibition, New Orleans, 30 September-3 October.
Lorentzen, R.J., Nævdal, G., and Lage, A.C.V.M. 2003. Tuning of parameters ina two-phase flow model using an ensemble Kalman filter . InternationalJournal of Multiphase Flow 29: 1283-1309.
Moré, J.J. 1977. The Levenberg-Marquardt algorithm: implementation andtheory. In Numerical Analysis (Lecture Notes in Mathematics), Vol. 630. ed.G.A. Watson, 105. Berlin: Springer Verlag.
Nævdal, G., Mannseth, T., and Vefring, E.H. 2002. Near-Well Reservoir MonitoringThrough Ensemble Kalman Filter. Paper SPE 75235 presented at the SPE/DOEImproved Oil Recovery Symposium, Tulsa, 13-17 April.
Nævdal, G., Johnsen, L.M., Aanonsen, S.I., and Vefring, E.H. 2005. Reservoir Monitoring and ContinuousModel Updating Using Ensemble Kalman Filter . SPEJ 10 (1): 66-74.SPE-84372-PA.
Taitel, Y. and Barnea, D. 1983. Counter CurrentGas-Liquid Vertical Flow, Model for Flow Pattern and Pressure Drop.International Journal of Multiphase Flow 9: 637-647.
van Kruijsdijk, C.P.J.W. and Cox, R.J.W. 1999. Testing While Underbalanced Drilling:Horizontal Well Permeability Profiles . Paper SPE 54717 presented at theSPE European Formation Damage Conference, The Hague, 31 May-1 June.
Vefring, E.H., Nygaard, G., Fjelde, K.K, Lorentzen, R.J., Nævdal, G., andMerlo, A. 2002. ReservoirCharacterization During Underbalanced Drilling: Methodology, Accuracy, andNecessary Data. Paper SPE 77530 presented at the SPE Annual TechnicalConference and Exhibition, San Antonio, Texas, 29 September-2 October.