Transport in Porous Media

, Volume 116, Issue 2, pp 453–471 | Cite as

Decomposing J-function to Account for the Pore Structure Effect in Tight Gas Sandstones

  • A. Sakhaee-PourEmail author


The J-function predicts the capillary pressure of a formation by accounting for its transport properties such as permeability and porosity. The dependency of this dimensionless function on the pore structure is usually neglected because it is difficult to implement such dependency, and also because most clastic formations contain mainly one type of pore structure. In this paper, we decompose the J-function to account for the presence of two pore structures in tight gas sandstones that are interpreted from capillary pressure measurements. We determine the effective porosity, permeability, and wetting phase saturation of each pore structure for this purpose. The throats, and not the pores, are the most important parameter for this determination. We have tested our approach for three tight gas sandstones formations. Our study reveals that decomposing the J-function allows us to capture drainage data more accurately, so that there is a minimum scatter in the scaled results, unlike the traditional approach. This study can have major implications for understanding the transport properties of a formation in which different pore structures are interconnected.


Pore structure J-function Tight gas sandstone Intergranular porosity Intragranular porosity 



We are grateful for the constructive comments of the anonymous reviewers that helped improve this work.


  1. Al-Raoush, R., Thompson, K.E., Willson, C.S.: Comparison of network generation techniques for unconsolidated porous media. Soil Sci. Soc. Am. J. 67, 1687–1700 (2003)CrossRefGoogle Scholar
  2. Al-Shalabi, E.W., Sepehrnoori, K., Delshad, M.: Mechanisms behind low salinity water injection in carbonate reservoirs. Fuel 121, 11–19 (2014)CrossRefGoogle Scholar
  3. Alpak, F.O., Lake, L.W., Embid, S.M.: Validation of a Modified Carman–Kozeny Equation to Model Two-Phase Relative Permeabilities: Society of Petroleum Engineers Annual Technical Conference and Exhibition, Houston, Texas, 3–6 October 1999. Paper SPE 56479-MS (1999)Google Scholar
  4. Apourvari, S.N., Arns, C.H.: Image-based relative permeability upscaling from the pore scale. Adv. Water Res. 95, 161–175 (2016)CrossRefGoogle Scholar
  5. Arns, C.H., Knackstedt, M.A., Pinczewski, W.V., Garboczi, E.J.: Computation of linear elastic properties from microtomographic images: methodology and agreement between theory and experiment. Geophysics 67, 1396–1405 (2002)CrossRefGoogle Scholar
  6. Balhoff, M.T., Thompson, K.E.: Modeling the steady flow of yield-stress fluids in packed beds. AIChE J. 50(12), 3034–3048 (2004)CrossRefGoogle Scholar
  7. Balhoff, M.T., Thompson, K.E.: A macroscopic model for shear-thinning flow in packed beds based on network modeling. Chem. Eng. Sci. 61(2), 698–719 (2006)CrossRefGoogle Scholar
  8. Bentsen, R.G., Anli, J.: Using parameter estimation techniques to convert centrifuge data into a capillary-pressure curve. SPE J. 17(1), 57–64 (1997)CrossRefGoogle Scholar
  9. Bijeljic, B., Mostaghimi, P., Blunt, M.J.: Insights into non-Fickian solute transport in carbonates. Water Resour. Res. 49, 2714–2728 (2013)CrossRefGoogle Scholar
  10. Blunt, M.J., Bijeljic, B., Dong, H., Gharbi, O., Iglauer, S., Mostaghimi, P., Paluszny, A., Pentland, C.: Pore-scale imaging and modelling. Adv. Water Res. 51, 197–216 (2013)CrossRefGoogle Scholar
  11. Brooks, R.H., Corey, A.T.: Properties of porous media affecting fluid flow. J. Irrig. Drain. Div. 92(2), 61–90 (1966)Google Scholar
  12. Brown, H.W.: Capillary pressure investigations. J. Pet. Technol. 192, 67–74 (1951)CrossRefGoogle Scholar
  13. Bryant, S.L., Blunt, M.J.: Prediction of relative permeability in simple porous media. Phys. Rev. A. 46, 2004–2011 (1992)CrossRefGoogle Scholar
  14. Bryant, S.L., Mason, G., Mellor, D.: Quantification of spatial correlation in porous media and its effect on mercury porosimetry. J. Colloid Interface Sci. 177, 88–100 (1996)CrossRefGoogle Scholar
  15. Byrnes, A.P., Cluff, R.M., Webb, J.C.: Analysis of Critical Permeability, Capillary Pressure and Electrical Properties for Mesaverde Tight Gas Sandstones from Western U.S. basins. University of Kansas Center for Research, Prepared for the U.S. Department of Energy 2009; DOE Award No. DE-FC26-05NT42660, 247 pp (2009)Google Scholar
  16. Buryakovsky, L., Chilingar, G.V., Rieke, H.H., Shin, S.: Fundamentals of the Petrophysics of Oil and Gas Reservoirs. Wiley, New York (2012)CrossRefGoogle Scholar
  17. Dong, H., Blunt, M.J.: Pore-network extraction from micro-computerized-tomography images. Phys. Rev. E 80(3), 036, 307 (2009)CrossRefGoogle Scholar
  18. Fathi, E., Akkutlu, I.Y.: Matrix heterogeneity effect on gas transport and adsorption in coalbed and shale gas reservoirs. Trans. Porous Media 80(2), 281–304 (2009)CrossRefGoogle Scholar
  19. Fatt, I.: The network model of porous media. I. Capillary pressure characteristics. Trans Soc. Min. Eng. AIME 207, 144–159 (1956)Google Scholar
  20. Heller, R., Zoback, M.: Adsorption of methane and carbon dioxide on gas shale and pure mineral samples. J. Unconv. Oil Gas Res. 8, 14–24 (2014)CrossRefGoogle Scholar
  21. Javadpour, F., Fisher, D., Unsworth, M.: Nanoscale gas flow in shale gas sediments. J. Can. Pet. Technol. 46(10), 55–61 (2007)CrossRefGoogle Scholar
  22. Joekar-Niasar, V., Hassanizadeh, S.M., Leijnse, A.: Insights into the relationships among capillary pressure, saturation, interfacial area and relative permeability using pore-scale network modeling. Transp. Porous Media 74, 201–219 (2008)CrossRefGoogle Scholar
  23. Kethireddy, N., Chen, H., Heidari, Z.: Quantifying the effect of kerogen on electrical resistivity measurement in organic-rich source rocks. Petrophysics 55, 136–146 (2014)Google Scholar
  24. Leverett, M.C.: Capillary behavior in porous solids. Trans. AIME 142, 159–172 (1941)Google Scholar
  25. Lindquist, W.B., Venkatarangan, A.: Investigating 3d geometry of porous media from high resolution images. Phys. Chem. Earth 24, 639–644 (1999)CrossRefGoogle Scholar
  26. Mason, G., Mellor, D.W.: Simulation of drainage and imbibition in a random packing of equal spheres. J. Colloid Sci. 176(1), 214–225 (1995)CrossRefGoogle Scholar
  27. Mehmani, A., Prodanovic, M.: The effect of microporosity on transport properties in porous media. Adv. Water Res. 63, 104–119 (2014)CrossRefGoogle Scholar
  28. Milliken, K.L.: Diagenetic heterogeneity in sandstone at the outcrop scale, Breathitt Formation (Pennsylvanian), eastern Kentucky. AAPG Bull. 85(5), 795–816 (2001)Google Scholar
  29. Mostaghimi, P., Blunt, M.J., Bijeljic, B.: Computations of absolute permeability on micro-CT images. Math. Geosci. 45, 103–125 (2012)CrossRefGoogle Scholar
  30. Mousavi, M., Bryant, S.: Connectivity of pore space as a control on two-phase flow properties of tight-gas sandstones. Trans. Porous Media 94, 537–554 (2012)CrossRefGoogle Scholar
  31. Oren, P.E., Bakke, S., Arntzen, O.J.: Extending predictive capabilities to network models. SPE J. 3(4), 324–336 (1998)CrossRefGoogle Scholar
  32. Oren, P.E., Bakke, S.: Process based reconstruction of sandstones and prediction of transport properties. Trans. Porous Media 46(2–3), 311–343 (2002)CrossRefGoogle Scholar
  33. Oren, P.E., Bakke, S., Held, R.: Direct pore-scale computation of material and transport properties for North Sea reservoir rocks. Water Resour. Res. 43, W12S04 (2007)CrossRefGoogle Scholar
  34. Ovaysi, S., Piri, M.: Direct pore-level modeling of incompressible fluid flow in porous media. J. Comput. Phys. 229(19), 7456–7476 (2010)CrossRefGoogle Scholar
  35. Ovaysi, S., Piri, M.: Pore-scale modeling of dispersion in disordered porous media. J. Contam. Hydrol. 124(1–4), 68–81 (2011)CrossRefGoogle Scholar
  36. Peters, E.J.: Advanced Petrophysics. Greenleaf Book Group, Austin (2012)Google Scholar
  37. Piri, M., Blunt, M.J.: Three-dimensional mixed-wet random pore-scale network modeling of two- and three-phase flow in porous media. I. Model description. Phys. Rev. E 71, 026301 (2005)CrossRefGoogle Scholar
  38. Piri, M., Karpyn, Z.T.: Prediction of fluid occupancy in fractures using network modeling and X-ray microtomography. Part 2: results. Phys. Rev. E 76, 016316 (2007)CrossRefGoogle Scholar
  39. Prodanovic, M., Bryant, S., Davis, S.J.: Numerical simulation of diagenetic alteration and its effect on residual gas in tight gas sandstones. Trans. Porous Media 96(1), 39–62 (2013)CrossRefGoogle Scholar
  40. Purcell, W.R.: Capillary pressures-their measurement using mercury and the calculation of permeability therefrom. J. Pet. Technol. 1(02), 39–48 (1949)CrossRefGoogle Scholar
  41. Sahimi, M.: Application of Percolation Theory. Taylor & Francis, Bristol (1994)Google Scholar
  42. Sakhaee-Pour, A., Bryant, S.L.: Gas permeability of shale. SPE Res. Eval. Eng. 15(4), 401–409 (2012)Google Scholar
  43. Sakhaee-Pour, A., Bryant, S.L.: Effect of pore structure on the producibility of tight gas sandstones. AAPG Bull. 98(4), 663–694 (2014)CrossRefGoogle Scholar
  44. Sakhaee-Pour, A., Bryant, S.L.: Pore structure of shale. Fuel 143, 467–475 (2015)CrossRefGoogle Scholar
  45. Saneifar, M., Aranibar, A., Heidari, Z.: Rock classification in the Haynesville Shale based on petrophysical and elastic properties estimated from well logs. Interpretation 3(1), SA65–SA75 (2014)CrossRefGoogle Scholar
  46. Shanley, K.W., Cluff, R.M., Robinson, J.W.: Factors controlling prolific gas production from low-permeability sandstone reservoirs: implications for resource assessment, prospect development, and risk analysis. AAPG Bull. 88(8), 1083–1121 (2014)CrossRefGoogle Scholar
  47. 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
  48. Takbiri Borujeni, A., Lane, N., Tyagi, M., Thompson, K.E.: Effects of image resolution and numerical resolution on computed permeability of consolidated packing using LB and FEM pore-scale simulations. Comput. Fluids 88, 753–763 (2013)CrossRefGoogle Scholar
  49. Teufel, L.W.: Determination of in-situ stress from anelastic strain recovery measurements of oriented core. In: Society of Petroleum Engineers/Department of Energy Symposium on Low Permeability. Denver, Colorado. SPE/DOE Paper 11649, pp. 421–430 (1983)Google Scholar
  50. Teufel, L.W.: Acoustic emissions during an-elastic strain recovery of cores from deep boreholes. In: Khair, A.W. (ed.) Rock Mechanics as a Guide for Efficient Utilization of Natural Resources, pp. 269–276. Balkema, Rotterdam (1989)Google Scholar
  51. Thomas, L.K., Katz, D.L., Tek, M.R.: Threshold pressure phenomena in porous media. SPE J. 8(2), 174–184 (1968)CrossRefGoogle Scholar
  52. Thomeer, J.H.M.: Introduction of a pore geometrical factor defined by the capillary pressure curve. J. Pet. Technol. 12(3), 73–77 (1960)CrossRefGoogle Scholar
  53. Thompson, K.E., Fogler, H.S.: Pore-level mechanisms for altering multiphase permeability with gels. SPE J. 2(3), 350–362 (1997)CrossRefGoogle Scholar
  54. Thompson, K.E., Fogler, H.S.: A pore-scale model for fluid injection and in-situ gelation in porous media. Phys. Rev E. 57(5B), 5825 (1998)CrossRefGoogle Scholar
  55. Thompson, K.E., Willson, C.S., White, C.D., Nyman, S., Bhattacharya, J., Reed, A.H.: Application of a new grain-based reconstruction algorithm to microtomography images for quantitative characterization and flow modeling. SPE J. 13(2), 164–176 (2008)CrossRefGoogle Scholar
  56. Valvatne, P.H., Piri, M., Blunt, M.J.: Predictive pore scale modeling of single and multiphase flow. Transp. Porous Media 58(1–2), 23–41 (2005)CrossRefGoogle Scholar
  57. Washburn, E.W.: The dynamics of capillary flow. Phys. Rev. 17, 273–283 (1921)CrossRefGoogle Scholar
  58. Wildenschild, D., Sheppard, A.: X-ray imaging and analysis techniques for quantifying pore-scale structure and processes in subsurface porous medium systems. Adv. Water Resour. 51, 217–246 (2013)CrossRefGoogle Scholar
  59. Yu, W., Sepehrnoori, K.: Simulation of gas desorption and geomechanics effects for unconventional gas reservoirs. Fuel 116, 455–464 (2014)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Petroleum and Geological EngineeringThe University of OklahomaNormanUSA

Personalised recommendations