A New Multiphysics Method for Simultaneous Assessment of Hydrocarbon Saturation, Directional Permeability, and Saturation-Dependent Capillary Pressure
- Artur Posenato Garcia (The University of Texas at Austin) | Zoya Heidari (The University of Texas at Austin)
- Document ID
- Society of Petroleum Engineers
- SPE Europec featured at 81st EAGE Conference and Exhibition, 3-6 June, London, England, UK
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- Capillary Pressure, multi-frequency electric measurements, Nuclear Magnetic Resonance, Directional Permeability, Hydrocarbon Reserves
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- 78 since 2007
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Cost-effective exploitation of heterogeneous/anisotropic reservoirs (e.g., carbonate formations) reckons on accurate description of pore structure, dynamic petrophysical properties (e.g., directional permeability, saturation-dependent capillary pressure), and fluid distribution. However, techniques for reliable quantification of permeability and hydrocarbon saturation still rely on model calibration using core measurements. Furthermore, assessment of saturation-dependent capillary pressure has been limited to experimental measurements, such as mercury injection capillary pressure (MICP). The objectives of this paper include (a) developing a new multiphysics workflow to simultaneously quantify rock fabric features (e.g., porosity, tortuosity, and effective throat size) and hydrocarbon saturation from integrated interpretation of nuclear magnetic resonance (NMR) and electric measurements, (b) introducing rock physics models that incorporate the quantified rock fabric and partial water/hydrocarbon saturation for assessment of directional permeability and saturation-dependent capillary pressure, and (c) validating the reliability of the new workflow in pore- and core-scale domains.
To achieve these objectives, we introduce a new multiphysics workflow integrating NMR and electric measurements, honoring rock fabric, and minimizing calibration efforts. We estimate water saturation from the interpretation of dielectric measurements. Next, we develop a fluid substitution algorithm to estimate the T2 distribution corresponding to fully water-saturated rocks from the interpretation of NMR measurements. We use the estimated T2-distribution for assessment of porosity, pore-size distribution, and effective pore-body size. Then, we develop a new physically meaningful resistivity model and apply it to obtain the constriction factor and, consequently, throat-size distribution from interpretation of resistivity measurements. Finally, throat-size distribution, porosity, and tortuosity are used to calculate directional permeability and saturation-dependent capillary pressure. We test the reliability of the new multiphysics workflow in core- and pore-scale domains on rock samples at different water saturation levels.
The introduced multiphysics workflow provides accurate description of the pore structure and fluid distribution in partially water-saturated formations with complex pore structure. Moreover, this new method enables real-time well-log-based assessment of saturation-dependent capillary pressure and directional permeability (in presence of directional electrical measurements) in reservoir conditions, which was not possible before. Quantification of capillary pressure has been limited to measurements in laboratory conditions, where the differences in stress field reduce the accuracy of the estimates. We verified that the estimates of permeability, saturation-dependent capillary pressure, and throat-size distribution obtained from the application of the new workflow agreed with those experimentally determined from core samples. Finally, since the new workflow relies on fundamental rock physics principles, hydrocarbon saturation, permeability, and saturation-dependent capillary pressure can be estimated from well-logs with minimum calibration efforts, which is another unique contribution of this work.
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Archie, G. E. 1942. The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics. Transactions of the AIME 146 (01): 54–62. http://dx.doi.org/10.2118/942054-G.
Arns, C. H. 2004. A Comparison of Pore Size Distributions Derived by NMR and X-Ray-CT Techniques. Physica A: Statistical Mechanics and Its Applications 339 (1–2): 159–165. http://dx.doi.org/10.1016/j.physa.2004.03.033.
Berg, C. F. 2012. Re-examining Archie's Law: Conductance Description by Tortuosity and Constriction. Physical Review E 86 (4): 046314. http://dx.doi.org/10.1103/PhysRevE.86.046314.
Berg, C. F. 2014. Permeability Description by Characteristic Length, Tortuosity, Constriction and Porosity. Transport in Porous Media 103 (3): 381–400. http://dx.doi.org/10.1007/s11242-014-0307-6.
Birchak, J. R.,Gardner, C. G.,Hipp, J. E., and Victor, J. M. 1974. High Dielectric Constant Microwave Probes for Sensing Soil Moisture. Proceedings of the IEEE 62 (1): 93–98. http://dx.doi.org/10.1109/PROC.1974.9388.
Chen, S. and Doolen, G. D. 1998. Lattice Boltzmann Method for Fluid Flows. Annual Review of Fluid Mechanics 30: 329–364. http://dx.doi.org/10.1146/annurev.fluid.30.1.329.
Clennell, M. B. 1997. Tortuosity: A Guide Through the Maze, in Lovell, M.A., and Harvey, P.K., Editors, Developments in Petrophysics. London: Geological Society, Special Publications, 122: 299–344. http://dx.doi.org/10.1144/GSL.SP.1997.122.01.18.
Garcia, A. P. and Heidari, Z. 2018a. Development of a Resistivity Model That Incorporates Quantitative Directional Connectivity and Tortuosity for Enhanced Assessment of Hydrocarbon Reserves. SPE Journal 23 (05): 1552–1565. Paper SPE-181571. http://dx.doi.org/10.2118/181571-PA.
Hizem, M.,Budan, H.,Deville, B.et al. 2008. Dielectric Dispersion: A New Wireline Petrophysical Measurement. Presented at the SPE Annual Technical Conference and Exhibition, Denver, Colorado, USA, 21–24 September. http://dx.doi.org/10.2118/116130-MS.
Johnson, D. L.,Koplik, J., and Schwartz, L. M. 1986. New Pore-Size Parameter Characterizing Transport in Porous Media. Physical Review Letters 57 (20): 2564. http://dx.doi.org/10.1103/PhysRevLett.57.2564.
Katz, A. J., and Thompson, A. H. 1987. Prediction of Rock Electrical Conductivity from Mercury Injection Measurements. Journal of Geophysical Research 92 (B1): 599–607. http://dx.doi.org/10.1029/JB092iB01p00599.
Medellin, D.,Ravi, V. R., and Torres-Verdín, C. 2019a. Pore-Size-Dependent Fluid Substitution Method for Magnetic Resonance Measurements. Geophysics 84 (1): D25–D38. http://dx.doi.org/10.1190/geo2017-0457.1.
Medellin, D.,Ravi, V. R., and Torres-Verdín, C. 2019b. Nonlinear Mixing Law for Magnetic Resonance Transverse-Relaxation Measurements of Dispersed Mixtures. Geophysics 84 (1): MR1–MR11. http://dx.doi.org/10.1190/geo2017-0342.1.
Müller-Huber, E.,Börner, F.,Börner, J. H., and Kulke, D. 2018. Combined Interpretation of NMR, MICP, and SIP Measurements on Mud-Dominated and Grain-Dominated Carbonate Rocks. Journal of Applied Geophysics 159: 228–240. http://dx.doi.org/10.1016/j.jappgeo.2018.08.011.
Palabos. 2013. Geophysics: Compute the Permeability of a 3D Porous Medium. The Palabos Software Project. http://www.palabos.org/documentation/tutorial/permeability.html (accessed 2 September 2018).
Rosenfeld, A. and Pfaltz, J. L. 1968. Distance Functions on Digital Pictures. Pattern Recognition 1 (1): 33–61. http://dx.doi.org/10.1016/0031-3203(68)90013-7.
Schindelin, J.,Arganda-Carreras, I.,Frise, E.et al. 2012. Fiji: An Open-Source Platform for Biological-Image Analysis. Nature Methods 9 (7): 676–682. http://dx.doi.org/10.1038/nmeth.2019.
Senturia, S. D. and Robinson, J. D. 1970. Nuclear Spin-Lattice Relaxation of Liquids Confined in Porous Solids. SPE Journal 10 (03): 237–244. http://dx.doi.org/10.2118/2870-pa.
Stogryn, A. 1971. Equations for Calculating the Dielectric Constant of Saline Water (Correspondence). IEEE Transactions on Microwave Theory and Techniques 19 (8): 733–736. http://dx.doi.org/10.1109/tmtt.1971.1127617.
Toumelin, E.,Torres-Verdín, C.,Sun, B., and Dunn, K. J. 2007. Random-Walk Technique for Simulating NMR Measurements and 2D NMR Maps of Porous Media with Relaxing and Permeable Boundaries. Journal of Magnetic Resonance 188 (1):83–96. http://dx.doi.org/10.1016/j.jmr.2007.05.024.
Washburn, E. W. 1921. The Dynamics of Capillary Flow. Physical Review 17 (3): 273. http://dx.doi.org/10.1103/PhysRev.17.273.
Wyllie, M. R. J. and Spangler, M. B. 1952. Application of Electrical Resistivity Measurements to Problem of Fluid in Porous Media. AAPG Bulletin 36 (2): 359–403. http://dx.doi.org/10.1306/3D934403-16B1-11D7-8645000102C1865D.