Predicting Effective Permeability to Oil in Sandstone and Carbonate Reservoirs From Well-Logging Data
- Vivek Anand (Schlumberger) | Robert Freedman (Schlumberger) | Steven Crary (Schlumberger) | Chanh C. Minh (Schlumberger) | Robert L. Terry (Maersk Oil Company)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- December 2011
- Document Type
- Journal Paper
- 750 - 762
- 2011. Society of Petroleum Engineers
- 1.6 Drilling Operations, 1.6.9 Coring, Fishing, 4.3.3 Aspaltenes, 4.1.5 Processing Equipment, 7.5.3 Professional Registration/Cetification, 5.6.1 Open hole/cased hole log analysis, 5.8.5 Oil Sand, Oil Shale, Bitumen, 1.2.3 Rock properties, 1.12.2 Logging While Drilling, 5.6.2 Core Analysis, 5.8.7 Carbonate Reservoir, 5.5.2 Core Analysis, 1.11 Drilling Fluids and Materials, 5.1 Reservoir Characterisation, 4.1.2 Separation and Treating
- petrophysical interpretation, radial basis function, NMR, effective permeability, well logs
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- 838 since 2007
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This paper discusses a new method for predicting continuous logs of effective permeability to oil in sandstone and carbonate formations from well-logging data. This important problem in formation evaluation has remained previously unsolved because the conventional approach used to predict reservoir properties from well-log data relies on simple empirical equations and idealized models of reservoir rocks. The use of such equations and models to predict a complex reservoir property (e.g., effective permeability) can result in an inaccurate representation of the formation.
This paper shows that accurate values of effective permeability to oil can be predicted using model-independent mapping functions constructed from Gaussian radial basis functions (RBFs), which can be derived from a laboratory database of measurements on partially saturated core samples. The mapping functions replace the empirical equations used in the conventional approach and are model-independent representations of the database measurements. Once the mapping functions are constructed from the database, there are no adjustable parameters.
In this study, mapping functions for sandstones and carbonates were derived from a worldwide database of laboratory measurements made on 79 sandstone and 25 carbonate core samples. The laboratory measurements available on each sample included irreducible water saturation, effective permeability to oil, porosity, and nuclear-magnetic-resonance (NMR) T2 distributions. The mapping functions can be used to predict effective permeability to oil of reservoirs at irreducible water saturation from input measurements of porosity, T2 distribution, irreducible water saturation, and knowledge of rock lithology (e.g., sandstone or carbonate).
The methodology for deriving the mapping functions is explained in detail. The mapping functions are applied to the database itself to show the accuracy of the effective-permeability predictions on core samples. The method is also applied to log data from both sandstone and carbonate formations in three wells from different parts of the world. The predicted effective permeabilities to oil are shown to be consistent with oil mobilities measured in the formations by fluid-sampling tools.
|File Size||2 MB||Number of Pages||13|
Allen, D., Coates, G., Ayoub, J., et al. 1988. Probing forPermeability: An Introduction to Measurements. The Technical Review 36 (1): 6-20.
Anand, V. and Freedman, R. 2009. New Methods for PredictingProperties of Live Oils from NMR. Proc., The 50th annual SPWLASymposium. Transactions, The Woodlands, Texas, USA, 21-24 June, Paper AAAA,1-14.
Carman, P.C. 1956. Flow of Gases through Porous Media.New York: Academic Press.
Coates, G. and Denoo, S. 1981. The Producibility AnswerProduct. The Technical Review 29 (2): 55-63.
Freedman, R. 2006. New Approach for Solving Inverse ProblemsEncountered in Well-Logging and Geophysical Applications. Petrophysics 47 (2): 93-111.
Freedman, R. 2009. Letter to the Editor: Moving beyond Archie'sLegacy in the 21st Century. Petrophysics 50 (6): 468.
Jurgawcynski, M., Lock, P.A., Jing, X.D., and Zimmerman, R.W. 2007.Permeability Predictions Based on Two-Dimensional Pore Space Images. Paper SPE110472 presented at the SPE Annual Technical Conference and Exhibition,Anaheim, California, USA, 11-14 November. http://dx.doi.org/10.2118/110472-MS.
Kenyon, W.E., Day, P.I., Straley, C., and Willemsen, J.F.1988. A Three-Part Study of NMR Longitudinal Relaxation Properties ofWater-Saturated Sandstones. SPE Form Eval 3 (3): 622-636.SPE-15643-PA. http://dx.doi.org/10.2118/15643-PA.
Micchelli, C.A. 1986. Interpolation of scattered data: Distancematrices and conditionally positive definite functions. ConstructiveApproximation 2 (1): 11-22. http://dx.doi.org/10.1007/bf01893414.
Seevers, D.O. 1966. A Nuclear Magnetic Method for Determiningthe Permeability of Sandstones. Paper L presented at the SPWLA 7th AnnualLogging Symposium, Tulsa, May.
Timur, A., Hempkins, M.B., and Massey, G.R. 1971.Analysis of Sidewall Samples by Nuclear Magnetic Resonance Methods. Paper Tpresented at the SPWLA 12th Annual Logging Symposium, Dallas, 2-5 May.