Modeling Permeability Distributions in a Sandstone Core for History Matching Coreflood Experiments
- Michael H. Krause (Stanford University) | Jean-Christophe Perrin (Stanford University) | Sally M. Benson (Stanford University)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- December 2011
- Document Type
- Journal Paper
- 768 - 777
- 2011. Society of Petroleum Engineers
- 6.5.7 Climate Change, 5.1.1 Exploration, Development, Structural Geology, 5.5.8 History Matching, 5.6.2 Core Analysis, 5.3.2 Multiphase Flow, 1.6.9 Coring, Fishing, 4.3.4 Scale
- capillary pressure, carbon capture and storage, permeability, coreflooding, history matching
- 4 in the last 30 days
- 829 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
Saline-aquifer storage of carbon dioxide (CO2) has become recognized as an important strategy for climate-change mitigation. Saline aquifers have very large estimated storage capacities, are distributed broadly across the globe, and have the potential for geologic-scale retention times. Many of these storage sites are not well characterized, and it is critical to conduct detailed experiments and analysis to understand how features such as heterogeneity can influence the theoretical storage capacity, spatial extent of plume migration, and secondary trapping processes. Coreflooding experiments are used routinely by the oil and gas industry for such analysis and provide a very useful tool for studying saline-aquifer formations also. Numerical simulations of these coreflooding experiments can provide insight beyond the experimental measurements themselves, such as numerically studying how properties such as relative permeability and capillary pressure affect CO2 distribution in these systems under various flow conditions. However, accurate subcore-scale simulations of these experiments have remained a challenge, and the issue of how to represent subcore-scale permeability has not been resolved previously.
Laboratory coreflooding experiments injecting CO2 into a saline-water-saturated Berea sandstone core have been conducted at reservoir conditions. Computed-tomography (CT) scans of the core show large spatial variations of CO2 saturation, even within a relatively homogeneous core. Numerical simulations of the experiment have been conducted to study the effect of subcore-scale heterogeneity and the role of permeability in determining the subcore-scale CO2 distribution in the core to explain these very large spatial variations in CO2 saturation.
Numerical simulations of the experiment consistently showed that use of traditional methods for estimating subcore-scale permeability, typically based solely on porosity distributions, results in subcore-scale saturation distributions that do not match experimental measurements. In this paper, we develop a new method for calculating subcore-scale permeability distributions on the basis of capillary pressure measurements and porosity distributions as an alternative to the traditional porosity-only-based models. Using experimentally measured saturation and porosity distributions and capillary pressure data to calculate permeability, simulations based on this new method show a substantial improvement both in the absolute value and in the spatial distribution of predicted CO2-saturation values. With this technique for accurately calculating permeability distributions, it is possible to study subcore-scale multiphase flow of brine and CO2 to understand how small-scale heterogeneities influence the spatial distribution of CO2 saturation and to improve our ability to predict the fate of stored CO2.
|File Size||2 MB||Number of Pages||10|
Akin, S. and Kovscek, A.R. 2003. Computed Tomography in PetroleumEngineering Research. In Applications of Computerized X-ray Tomography inGeology and Related Domains, ed. P. Jacobs, F. Mees, R. Swennen, and M. VanGeet, No. 215, 23-38. London: Special Publication, Geological Society.
Bachu, S., Bonijoly, D., Bradshaw, J., Burruss, R., Holloway, S.,Christensen, N.P., and Mathiassen, O.M. 2007. CO2 Storage CapacityEstimation: Methodology and Gaps. International Journal of GreenhouseGas Control 1 (4): 430-443. doi:10.1016/S1750-5836(07)00086-2.
Benson, S.M., Perrin J.-C., Krause, M., Kuo, C.-W., and Esposito, A. 2009.Experimental Investigations of Multiphase Flow of CO2 and Brine in SalineAquifers--Annual Report 2008. Annual Report, Global Climate and Energy Project,Stanford University, Stanford, California.
Brown, H.W. 1951. Capillary Pressure Investigations. SPE-951067-G.Trans., AIME, 192: 67-74.
Calhoun, J.C., Lewis, M., and Newman, R.C. 1949. Experiments on theCapillary Properties of Porous Solids. SPE-949189-G. Trans., AIME,186: 189-196.
Carbon Sequestration Atlas of the United States and Canada (AtlasII), second edition. 2008. Washington, DC: National Energy TechnologyLaboratory (NETL).
Carmen, P.C. 1937. Fluid Flow Through Granular Beds. Trans. Inst. Chem.Engrs. London 15: 150-166.
Chalbaud, C., Robin, M., Lombard, J-M., Martin, F., Egermann, P., andBertin, H. 2009. Interfacial TensionMeasurements and Wettability Evaluation for Geological CO2 Storage.Advances in Water Resources 32 (1): 98-109. doi:10.1016/j.advwatres.2008.10.012.
Honarpour, M., Koederitz, L., and Harvey, A.H. 1986. RelativePermeability of Petroleum Reservoirs. Boca Raton, Florida: CRC Press.
Huet, C.C., Rushing, J.A., Newsham, K.E., and Blasingame, T.A. 2005. A Modified Purcell/Burdine Model forEstimating Absolute Permeability from Mercury Injection Capillary PressureData. Paper 951067 presented at the International Petroleum TechnologyConference, Doha, 21-23 November. doi: 10.2523/10994-MS.
Krause, M., Perrin, J.-C., Kuo, C.-W., and Benson, S.M. 2009. Characterization of CO2Storage Properties Using Core Analysis Techniques and Thin Section Data.Energy Procedia 1 (1): 2969-2974. doi:10.1016/j.egypro.2009.02.073.
Leverett, M.C. 1941. Capillary Behavior in Porous Solids. SPE-941152-G.Trans., AIME, 142: 152-169.
Leverett, M.C., Lewis, W.B., and True, M.E. 1942. Dimensional-Model Studiesof Oil-Field Behavior. SPE-942175-G. Trans., AIME, 146:175-193.
Mavko, G. and Nur, A. 1997. The Effect of a PercolationThreshold in the Kozeny-Carman Relation. Geophysics 62(5): 1480-1482. doi: 10.1190/1.1444251.
Nelson, P. 1994. Permeability-porosity relationships in sedimentary rocks.The Log Analyst 35 (3): 38-62.
Pape, H. and Clauser, C. 2000. Variation of Permeability WithPorosity in Sandstone Diagenesis Interpreted with a Fractal Pore SpaceModel. Pure and Applied Geophysics 157 (4): 603-619.doi: 10.1007/PL00001110.
Pape, H., Clauser, C., and Iffland, J. 1999. Permeability Prediction Based onFractal Pore-Space Geometry. Geophysics 64 (5):1447-1460. doi: 10.1190/1.1444649.
Perrin, J.-C. and Benson, S.M. 2010. An Experimental Study on theInfluence of Sub core-scale Heterogeneities on CO2 Distribution in ReservoirRocks. Transport in Porous Media 82 (1): 93-109. doi:10.1007/s11242-009-9426-x.
Philips, S.L., Igbene, I., Fair, J.A., Ozbek, H., and Tavana, M. 1981.Technical Databook for Geothermal Energy Utilization. Technical ReportLBL-12810, Contract No. W-7405-ENG-48, Lawrence Berkeley National Lab,Berkeley, California.
Pruess, K. 2005. ECO2N: A TOUGH2 Fluid Property Module for Mixtures ofWater, NaCl and CO2. Report No. LBNL-57952, Contract No. DE-AC03-76SF00098,Lawrence Berkeley National Laboratory, Berkeley, California (August 2005).
Pruess, K., Oldenburg, C., and Moridis, G. 1999. TOUGH2 User's Guide,Version 2.0. Report LBNL-43134, Contract No. DE-AC03-76SF00098, LawrenceBerkeley National Laboratory, Berkeley, Calforina (November 1999).
Purcell, W.R. 1949. Capillary Pressures--Their Measurement Using Mercury andthe Calculation of Permeability Therefrom. Trans., AIME, 186:39-48. (T.P. 2544 presented at the Branch Fall Meeting, Dallas, 4-6 October1948.)
Richardson, J.G., Krever, J.K., Hafford, J.A., and Osaba, J.S. 1952.Laboratory Determination of Relative Permeability. SPE-952187-G. Trans.,AIME, 195: 187-197.
Silin, D., Patzek, T., and Benson, S.M. 2009. A Model of Buoyancy-DrivenTwo-Phase Countercurrent Fluid Flow. Transport in Porous Media 76 (3): 449-469. doi: 10.1007/s11242-008-9257-1.
Zhang, K., Y-S, Wu., and Pruess, K. 2008. User's Guide for TOUGH2-MP--AMassively Parallel Version of the TOUGH2 Code. Report No. LBNL-315E, LawrenceBerkeley National Laboratory, Berkeley, California (May 2008).