Transport in Porous Media

, Volume 86, Issue 2, pp 495–515 | Cite as

Microtomography and Pore-Scale Modeling of Two-Phase Fluid Distribution

  • Dmitriy Silin
  • Liviu Tomutsa
  • Sally M. Benson
  • Tad W. Patzek
Open Access
Article

Abstract

Synchrotron-based X-ray microtomography (micro CT) at the Advanced Light Source (ALS) line 8.3.2 at the Lawrence Berkeley National Laboratory produces three-dimensional micron-scale-resolution digital images of the pore space of the reservoir rock along with the spacial distribution of the fluids. Pore-scale visualization of carbon dioxide flooding experiments performed at a reservoir pressure demonstrates that the injected gas fills some pores and pore clusters, and entirely bypasses the others. Using 3D digital images of the pore space as input data, the method of maximal inscribed spheres (MIS) predicts two-phase fluid distribution in capillary equilibrium. Verification against the tomography images shows a good agreement between the computed fluid distribution in the pores and the experimental data. The model-predicted capillary pressure curves and tomography-based porosimetry distributions compared favorably with the mercury injection data. Thus, micro CT in combination with modeling based on the MIS is a viable approach to study the pore-scale mechanisms of CO2 injection into an aquifer, as well as more general multi-phase flows.

Keywords

Capillary pressure Microtomography Pore-scale modeling Two-phase flow 

References

  1. Al-Futaisi A., Patzek T.W.: Impact of wettability on two-phase flow characteristics of sedimentary rock: Quasi-static model. Water Resour. Res. 39(2), 1042–1055 (2003)CrossRefGoogle Scholar
  2. Anderson W.G.: Wettability literature survey. Part 4: effects of wettability on capillary pressure. J. Pet. Technol. 39(10), 1283–1300 (1987)Google Scholar
  3. Apps, J.A.: A review of hazardous chemical species associated with CO2 capture from coal-fired power plants and their potential fate in CO2 geologic storage. Technical report, Lawrence Berkeley National Laboratory, Earth Sciences Division (2006)Google Scholar
  4. Auzerais F.M., Dunsmuir J., Ferreol B.B., Martys N., Olson J., Ramakrishnan T.S., Rothman D.H., Schwartz L.M.: Transport in sandstone: a study based on three dimensional microtomography. Geophys. Res. Lett. 23, 705–708 (1996)CrossRefGoogle Scholar
  5. Bakke S., Øren P.E.: 3-D pore-scale modelling of sandstones and flow simulations in the pore networks. SPE J. 2, 136–149 (1997)Google Scholar
  6. Bernard D.: 3D quantification of pore scale geometrical changes using synchrotron computed microtomography. Oil Gas Sci. Technol. 60(5), 747–762 (2005)CrossRefGoogle Scholar
  7. Bico J., Tordeux C., Qur D.: Rough wetting. Europhys. Lett. 55, 214–220 (2001)CrossRefGoogle Scholar
  8. Blunt M.J.: Flow in porous media—pore-network models and multiphase flow. Curr. Opin. Colloid & Interface Sci. 6(3), 197–207 (2001)CrossRefGoogle Scholar
  9. Blunt M.J., King P.: Relative permeabilities from two- and three-dimensional pore-scale metwork modeling. Transp. Porous Med. 6, 407–433 (1991)CrossRefGoogle Scholar
  10. Bryant S., Blunt M.: Prediction of relative permeability in simple porous-media. Phys. Rev. A 46, 2004–2011 (1992)CrossRefGoogle Scholar
  11. Bryant S.L., King P.R., Mellor D.W.: Network model evaluation of permeability and spatial correlation in a real random sphere packing. Transp. Porous Med. 11, 53–70 (1993)CrossRefGoogle Scholar
  12. Chatzis I., Dullien F.A.L.: Mercury porosimetry curves of sandstones. Mechanisms of mercury penetration and withdrawal. Powder Technol. 29, 117–125 (1981)CrossRefGoogle Scholar
  13. Coles M.E., Hazlett R.D., Spanne P., Muegge E.L., Furr M.J.: Characterization of reservoir core using computed microtomography. SPE J. 1(3), 295–302 (1996)Google Scholar
  14. Coles M.E., Hazlett R.D., Muegge E.L., Jones K.W., Andrews B., Dowd, Siddons P., Peskin A.: Developments in synchrotron X-ray microtomography with applications to flow in porous media. SPE Reserv. Eval. Eng. 1(4), 288–296 (1998a)Google Scholar
  15. Coles M.E., Hazlett R.D., Spanne P., Soll W.E., Muegge E.L., Jones K.W.: Pore level imaging of fluid transport using synchrotron X-ray microtomography. J. Pet. Sci. Eng. 19, 55–63 (1998b)CrossRefGoogle Scholar
  16. Daley T.M., Solbau R.D., Ajo-Franklin J.B., Benson S.M.: Continuous active-source seismic monitoring of CO2 injection in a brine aquifer. Geophysics 72(5), A57–A61 (2007)CrossRefGoogle Scholar
  17. Derjagin B.V., Churaev N.V., Muller V.M.: Surface forces. Plenum Press, New York (1987)Google Scholar
  18. Dierick M., Masschaele B., Van Hoorebeke L.: Octopus, a fast and user-friendly tomographic reconstruction package developed in LabView®. Meas. Sci. Technol. 15, 1366–1370 (2004)CrossRefGoogle Scholar
  19. Doughty C., Freifeld B.M., Trautz R.C.: Site characterization for CO2 geologic storage and vice versa: the Frio Brine Pilot, Texas, USA as a case study. Env. Geol. 54(8), 1635–1656 (2008)CrossRefGoogle Scholar
  20. Fatt I.: The network model of porous media. 1. Capillary pressure characteristics. Trans. AIME 207(7), 144–159 (1956a)Google Scholar
  21. Fatt I.: The network model of porous media. 2. Dynamic properties of a single size tube network. Trans. AIME 207(7), 160–163 (1956b)Google Scholar
  22. Fatt I.: The network model of porous media. 3. Dynamic propertries of networks with tube radius distribution. Trans. AIME 207(7), 164–181 (1956c)Google Scholar
  23. Flukiger F., Bernard D.: A new numerical model for pore scale dissolution of calcite due to CO2 saturated water flow in 3D realistic geometry: principles and first results. Chem. Geol. 265(1–2), 171–180 (2009)CrossRefGoogle Scholar
  24. Huttenlocher D.P., Klanderman G.A., Rucklidge W.J.: Comparing images using the Hausdorff distance. IEEE Trans. Pattern Anal. Mach. Intel. 15, 850–863 (1993)CrossRefGoogle Scholar
  25. Intergovernmental Panel on Climate Change (IPCC): Panel on climate change special report on carbon dioxide capture and storage. Cambridge University Press, Cambridge (2005)Google Scholar
  26. Israelachvili J.N.: Intermolecular and surface forces. 2nd edn. Academic Press, New York (1992)Google Scholar
  27. Knackstedt M.A., Sheppard A.P., Sahimi M.: Pore network modelling of two-phase flow in porous rock: the effect of correlated heterogeneity. Adv. Water Resour. 24, 257–277 (2001)CrossRefGoogle Scholar
  28. Kumar, M., Senden, T.J., Knackstedt, M.A., Latham, S., Pinczewski, W.V., Sok, R.M., Sheppard, A., Turner, M.L.: Imaging of core scale distribution of fluids and wettability. In: International Symposium of the Society of Core Analysts, Abu Dhabi, UAE (2008)Google Scholar
  29. Latham, S.J., Varslot, T.K., Sheppard, A.P.: Automated registration for augmenting micro-CT 3D images. In: Mercer G.N., Roberts A.J., (eds.) Proceedings of the 14th Biennial Computational Techniques and Applications Conference, CTAC-2008. ANZIAM J. 50, C534–C548 (2008)Google Scholar
  30. Leverett M.C.: Flow of oil-water mixtures through unconsolidated sands. Trans. AIME 132, 381–401 (1939)Google Scholar
  31. Leverett M.C.: Capillary behavior in porous solids. Trans. AIME 142, 152–169 (1941)Google Scholar
  32. Leverett M.C., Lewis W.B., True M.E.: Dimensional-model studies of oil-field behavior. Trans. AIME 146, 175–193 (1942)Google Scholar
  33. Lindquist W.B., Venkatarangan A.: Investigating 3D geometry of porous media from high resolution images. Phys. Chem. Earth A 25(7), 593–599 (1999)CrossRefGoogle Scholar
  34. Luquot L., Gouze P.: X-ray microtomography characterization of hydrochemical properties changes induced by CO2 injection. Geochim. Cosmochim. Acta Suppl. 73, 804 (2009)Google Scholar
  35. Muskat, M., Meres, M.W.: The flow of hetereogeneous fluids through porous media 7, 346–363 (1936)Google Scholar
  36. Noiriel C., Gouze P., Bernard D.: Investigation of porosity and permeability effects from microstructure changes during limestone dissolution. Geophy. Res. Lett. 31, L24603 (2004)CrossRefGoogle Scholar
  37. Noiriel C., Luquot L., Mad B., Raimbault L., Gouze P., van der Lee J.: Changes in reactive surface area during limestone dissolution: an experimental and modelling study. Chem. Geol. 265(1–2), 160–170 (2009)CrossRefGoogle Scholar
  38. Øren P.E., Bakke S.: Reconstruction of Berea sandstone and pore-scale modelling of wettability effects. J. Pet. Sci. Eng. 39(3–4), 177–199 (2003)CrossRefGoogle Scholar
  39. Patzek T.W.: Verification of a complete pore network simulator of drainage and imbibition. SPE J. 6(2), 144–156 (2001)Google Scholar
  40. Patzek T.W.: Subsurface sequestration of CO2 in the U.S: is it money best spent?.  Nat. Resour. Res. 19(1), 1–9 (2010)CrossRefGoogle Scholar
  41. Perrin J.C., Benson S.: An experimental study on the influence of sub-core scale heterogeneities on CO2 distribution in reservoir rocks. Transp. Porous Med. 82(1), 93–109 (2010)CrossRefGoogle Scholar
  42. Pomeau Y., Villermaux E.: Two hundred years of capillary research. Phys. Today 59(3), 39–44 (2006)CrossRefGoogle Scholar
  43. Prodanovic M., Lindquist W.B., Seright R.S.: Porous structure and fluid partitioning in polyethylene cores from 3D X-ray microtomographic imaging. J. Colloid Interface Sci. 298, 282–297 (2006)CrossRefGoogle Scholar
  44. Prodanovic M., Lindquist W.B., Seright R.S.: 3D image-based characterization of fluid displacement in a Berea core. Adv. Water Resour. 30, 214–226 (2007)CrossRefGoogle Scholar
  45. Purcell W.R.: Capillary pressure—their measurements using mercury and the calculation of permeability therefrom. AIME Petroleum Transactions 185, 39–48 (1949)Google Scholar
  46. Seright R.S., Liang J., Lindquist W.B., Dunsmuir J.H.: Characterizing disproportionate permeability reduction using synchrotron X-ray computed microtomography. SPE Form. Eval. Reserv. Eval. Eng. 5, 355–364 (2002)Google Scholar
  47. Sezgin M., Sankur B.: Survey over image thresholding techniques and quantitative performance evaluation. J. Electron Imag. 13, 146–165 (2004)CrossRefGoogle Scholar
  48. Silin D.B.: On set-valued differentiation and integration. Set Valued Anal. 5(2), 107–146 (1997)CrossRefGoogle Scholar
  49. Silin D.B., Patzek T.W.: Pore space morphology analysis using maximal inscribed spheres. Phys. A Stat. Mech. Appl. 371, 336–360 (2006)CrossRefGoogle Scholar
  50. Spanne P., Thovert J.F., Jacquin C.J., Lindquist W.B., Jones K.W., Adler P.M.: Synchrotron computed microtomography of porous media: topology and transports. Phys. Rev. Lett. 73(14), 2001–2004 (1994)CrossRefGoogle Scholar
  51. Tomutsa L., Silin D., Radmilovic V.: Analysis of chalk petrophysical properties by means of submicron-scale pore imaging and modeling. SPE Reserv. Eval. Eng. 10(3), 285–293 (2007)Google Scholar
  52. Turner M.L., Knufing L., Arns C.H., Sakellariou A., Senden T.J., Sheppard A.P., Sok R.M., Limaye A., Pinczewski W.V., Knackstedt M.A.: Three-dimensional imaging of multiphase flow in porous media. Phys. A. Stat. Mech. Appl. 339, 166–172 (2004)CrossRefGoogle Scholar
  53. van Dijke M.I.J., Piri M., Helland J.O., Sorbie K.S., Blunt M.J., Skjveland S.M.: Criteria for three-fluid configurations including layers in a pore with nonuniform wettability. Water Resour. Res. 43, W12S05 (2007)CrossRefGoogle Scholar
  54. Vogel H.J.: Digital unbiased estimation of the Euler-Poincaré characteristic in different dimensions. Acta Stereol. 16(2), 97–104 (1997)Google Scholar
  55. Wyckoff, R.T., Botset, H.G.: The flow of gas-liquid mixtures through unconsolidated sands 7, 325–345 (1936)Google Scholar
  56. Xu B., Kamath J., Yortsos Y.C., Lee S.H.: Use of pore-network models to simulate laboratory corefloods in a heterogeneous carbonate sample. SPE J. 4(4), 179–185 (1999)Google Scholar
  57. Youssef, S., Bauer, D., Bekri, S., Rosenberg, E., Vizika, O.: Towards a better understanding of multiphase flow in porous media: 3D In-Situ fluid distribution imaging at the pore scale. In: International Symposium of the Society of Core Analysts, Noordwijk aan Zee, The Netherlands (2009)Google Scholar

Copyright information

© The Author(s) 2010

Authors and Affiliations

  • Dmitriy Silin
    • 1
  • Liviu Tomutsa
    • 1
  • Sally M. Benson
    • 2
  • Tad W. Patzek
    • 3
  1. 1.Lawrence Berkeley National LaboratoryBerkeleyUSA
  2. 2.Energy Resources Engineering DepartmentStanford UniversityStanfordUSA
  3. 3.Department of Petroleum and Geosystems EngineeringThe University of Texas at AustinAustinUSA

Personalised recommendations