Skip to main content
SpringerLink
Log in

Estimation of Shale Intrinsic Permeability with Process-Based Pore Network Modeling Approach

  • Published:
Transport in Porous Media Aims and scope Submit manuscript

Abstract

A multi-scale pore network model is developed for shale with the process-based method (PBM). The pore network comprises three types of sub-networks: the \(\upmu \)m-scale sub-network, the nm-scale pore sub-network in organic matter (OM) particles and the nm-scale pore sub-network in clay aggregates. Process-based simulations mimic shale-forming geological processes and generate a \(\upmu \)m-scale sub-network which connects interparticle pores, OM particles and clay aggregates. The nm-scale pore sub-networks in OM and clay are extracted from monodisperse sphere packing. Nm-scale throats in OM and clay are simplified to be cylindrical and cuboid-shaped, respectively. The nm-scale pore sub-networks are inserted into selected OM particles and clay aggregates in the \(\upmu \)m-scale sub-network to form an integrated multi-scale pore network. No-slip permeability is evaluated on multi-scale pore networks. Permeability calculations verify that shales permeability keeps decreasing when nm-scale pores and throats replace \(\upmu \)m-scale pores. Soft shales may have higher porosity but similar range of permeability with hard shales. Small compaction leads to higher permeability when nm-scale pores dominate a pore network. Nm-scale pore networks with higher interconnectivity contribute to higher permeability. Under constant shale porosity, the shale matrix with cuboid-shaped nm-scale throats has lower no-slip permeability than that with cylindrical throats. Different from previous reconstruction processes, the new reconstruction process first considers the porous OM and clay distribution with PBM. The influence of geological processes on the multi-scale pore networks is also first analyzed for shale. Moreover, this study considers the effect of OM porosities and different pore morphologies in OM and clay on shale permeability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  • Afsharpoor, A., Javadpour, F.: Liquid slip flow in a network of shale noncircular nanopores. Fuel 180, 580–590 (2016)

    Article  Google Scholar 

  • Afsharpoor, A., Javadpour, F., Wu, J., Ko, L.T., Liang, Q.: Network modeling of liquid flow in Yanchang Shale. Interpretation 5(2), SF99-SF107 (2017)

    Article  Google Scholar 

  • Bakke, S., Øren, P.: 3D pore-scale modeling of sandstones and flow simulations in the pore networks. SPE J. 2(2), 136–149 (1997)

    Article  Google Scholar 

  • Bauer, D., Youssef, S., Fleury, M., Bekri, S., Rosenberg, E., Vizika, O.: Improving the estimations of petrophysical transport behavior of carbonate rocks using a dual pore network approach combined with computed microtomography. Transp. Porous Med. 94(2), 505–524 (2012)

    Article  Google Scholar 

  • Bjorlykke, K., Jahren, J., Mondol, N.H., Marcussen, O., Croize, D., Peltonen, C., Thyberg, B.: Sediment compaction and rock properties. Search and Discovery Article #50192 (2009)

  • Bryant, S., Blunt, M.: Prediction of relative permeability in simple porous media. Phys. Rev. A 46(4), 2004–2011 (1992)

    Article  Google Scholar 

  • Bryant, S.L., Cade, C., Mellor, D.W.: Permeability prediction from geological models. Am. Assoc. Pet. Geol. Bull. 77(8), 1338–1350 (1993)

    Google Scholar 

  • Bustin, T.M., Bustin, A.M., Cui, A., Ross, D., Pathi, V.M.: Impacts of shale properties on pore structure and storage characteristics. SPE (2008). https://doi.org/10.2118/119892-MS

    Google Scholar 

  • Camp, W.: Diagenesis of organic-rich shale: views from Foraminifera Penetralia, Eagle Ford Formation, Maverick Basin, Teas. Search and Discovery Article #51054 (2014)

  • Cao, T., Song, Z., Wang, S., Xia, J.: A comparative study of the specific area and pore structure of different shales and their kerogens. Sci China Earth Sci 58(4), 510–522 (2015)

    Article  Google Scholar 

  • Chalmers, G.R., Bustin, R.M., Power, I.M.: Characterization of gas shale pore systems by porosimetry, pycnometry, surface area, and field emission scanning electron microscopy/transmission electron microscopy image analyses: examples from the Barnett, Woodford, Haynesville, Marcellus, and Foig units. AAPG Bull. 56(6), 1099–1119 (2012)

    Article  Google Scholar 

  • Clarkson, C.R., Bustin, R.M.: Variation in micropore capacity and size distribution with composition in bituminous coal of the Western Canadian Sedimentary Basin: implications for coalbed methane potential. Fuel 75(13), 1483–1498 (1996)

    Article  Google Scholar 

  • Curtis, M.E., Amborse, R.J., Sondergeld, C.H., Rai, C.S.: Structural characterization of gas shales on the micro- and nano-scales. SPE (2010). https://doi.org/10.2118/137693-MS

    Google Scholar 

  • Dadvar, M., Sahimi, M.: Pore network model of deactivation of immobilized glucose isomerase in packed-bed reactors. Part III: multiscale modelling. Chem. Eng. Sci. 58, 4935–4951 (2003)

    Article  Google Scholar 

  • Dewhurst, D.N., Yang, Y., Aplin, A.C.: Permeability and fluid flow in natural mudstones. Geol. Soc. Lond. Spec. Publ. 158, 23–43 (1999)

    Article  Google Scholar 

  • Dræge, A., Jakobsen, M., Johansen, T.A.: Rock physics modelling of shale diagenesis. Pet. Geosci. 12, 49–57 (2006)

    Article  Google Scholar 

  • Fatt, I.: The network model of porous media: I. Capillary pressure characteristics. Trans. AIME Pet. Trans. 207, 144–159 (1956a)

    Google Scholar 

  • Fatt, I.: The network model of porous media: III. Dynamic properties of networks with tube radius distribution. Trans. AIME 207, 164–181 (1956b)

    Google Scholar 

  • Finney, J.: Random packing and the structure of the liquid state. Ph.D. Thesis, University of London, London (1968)

  • Finsterle, S., Persoff, P.: Determining permeability of tight rock samples using inverse modelling. Water Resour. Res. 33(8), 1803–1811 (1997)

    Article  Google Scholar 

  • Gu, X., Cole, D.R., Rother, G., Mildner, D.F.R., Brantly, S.L.: Pores in Marcellus shale: a neutron scattering and FIB-SEM study. Energy Fuels 29, 1295–1308 (2015)

    Article  Google Scholar 

  • Hazlett, R.D.: Satistical characterization and stochastic modeling of pore networks in relation to fluid flow. Math. Geol. 29(6), 801–822 (1997)

    Article  Google Scholar 

  • Hidajat, I., Rastogi, A., Singh, M., Mohanty, K.K.: Transport properties of porous media reconstructed from thin-sections. SPE J. 7(1), 40–48 (2002)

    Article  Google Scholar 

  • Houben, M.E., Desbois, G., Urai, J.L.: A comparative study of representative 2D microstructures in shaly and sandy facies of Opalinus Clay (Mont Terri, Switzerland) inferred from BIB-SEM and MIP methods. Mar. Pet. Geol. 49, 143–161 (2013)

    Article  Google Scholar 

  • IUPAC (International Union of Pure and Applied Chemistry).: Physcial Chemistry Division Commission on Colloid and Surface Chemistry, Subcommittee on Characterization of Porous Solids: Recommendations for the Characterization of Porous Solids (Technical Report): Pure and Applied Chemistry 66(8),1739–1758 (1994)

  • Javadpour, F., Farshi, M.M., Amrein, M.: Atomic-force microscopy: a new tool for gas-shale characterization. J. Can. Pet. Technol. 51(04), 236–243 (2012)

    Article  Google Scholar 

  • Joshi, M.: A Class of Stochastic Models for Porous Media. University of Kansas, Chemical and Petroleum Engineering, Lawrence (1974)

    Google Scholar 

  • Katsube, T.J., Williamson, M.A.: Effects of diagenesis on shale nano-pore structure and implications for sealing. Clay Miner. 29, 451–461 (1994)

    Article  Google Scholar 

  • Keehm, Y.: Computational rock physics: transport properties in porous media and applications. Stanford University Thesis (2003)

  • Klaver, J., Desbois, G., Littke, R., Urai, J.: BIB-SEM characterization of pore space morphology and distribution in postmature to overmature samples from the Haynesville and Bossier Shales. Mar. Pet. Geol. 59, 451–456 (2015)

    Article  Google Scholar 

  • Laughrey, C.D., Ruble, T.E., Lemmens, H., Kostelnik, J., Butcher, A.R., Walker, G., Knowles, W.: Black shale diagenesis: insights from integrated high-definition analyses of post-mature marcellus formation rocks, Northeastern Pennsylvania. Search and Discovery Article #110150 (2011)

  • Liang, Y., Price, J.D., Wark, D.A., Watson, E.B.: Non-linear pressure diffusion in a porous medium: approximate solutions with applications to permeability measurements using transient pulse decay method. J. Geophys. Res. 106(B1), 529–536 (2001)

    Article  Google Scholar 

  • Liu, X., Sun, J., Wang, H.: Reconstruction of 3-D digital cores using a hybrid method. Appl. Geophys. 6(2), 105–112 (2009)

    Article  Google Scholar 

  • Loucks, R.G., Ruppel, S.C.: Mississippian Barnett Shale: lithofacies and depositional setting of a deep-water shale gas succession in the Fort Worth Basin, Texas. AAPG Bull. 91(4), 579–601 (2007). https://doi.org/10.1306/11020606059

    Article  Google Scholar 

  • Loucks, R.G., Reed, R.M., Ruppel, S.C., Hammes, U.: Spectrum of pore types and networks in mudrocks and a descriptive classification for matrix-related mudrock pores. Am. Assoc. Pet. Geol. Bull. 96(6), 071–1098 (2012)

    Google Scholar 

  • Loucks, R.G., Reed, R.M., Ruppel, S.C., Jarvie, D.M.: Morphology, genesis, and distribution of nanometer-scale pores in siliceous mudstones of the Mississippian Barnett Shale. J. Sediment. Res. 79, 848–861 (2009). https://doi.org/10.2110/jsr.2009.092

    Article  Google Scholar 

  • Manson, G.: A model of the pore space in a random packing of equal spheres. J. Colloid Interface Sci. 35(2), 279–287 (1971)

    Article  Google Scholar 

  • Mehmani, A., Prodanović, M.: The application of sorption hysteresis in nano-petrophysics using multiscale multiphysics network models. Int. J. Coal Geol. 128–129, 96–108 (2014)

    Article  Google Scholar 

  • Mehmani, A., Prodanović, M., Javadpour, F.: Multiscale, multiphysics network modeling of shale matrix gas flows. Transp. Porous Med. 99(2), 377–390 (2013)

    Article  Google Scholar 

  • Mellor, D.W.: Random close packing (RCP) of equal spheres : structure and implications for use as a Model Porous Medium. Ph.D. Dissertation, Open University, Buckinghamshire (1989)

  • Mousavi, M.A.: Pore scale characterization and modeling of two-phase flow in tights gas sandstones. Ph.D. dissertation, The University of Texas at Austin, Austin (2010)

  • Mousavi, M.A., Bryant, S.L.: Connectivity of pore space as a control on two-phase flow properties of tight-gas sandstones. Transp. Porous Med. 94(2), 537–554 (2012)

    Article  Google Scholar 

  • Mousavi, M., Prodanović, M., Jacobi, D.: New classification of carbonate rocks for process-based pore-scale modeling. SPE J. 18(2), 243–263 (2013)

    Article  Google Scholar 

  • Okabe, H., Blunt, M.J.: Prediction of permeability for porous media reconstructed using multiple-point statistics. Phys. Rev. E 70(6), 066135 (2004)

    Article  Google Scholar 

  • Okabe, H., Blunt, M.J.: Pore space reconstruction of vuggy carbonates using microtomography and multiple-point statistics. Water Resour. Res. 43, W12S02 (2007)

    Article  Google Scholar 

  • Øren, P., Bakke, S.: Reconstruction of Berea sandstone and pore-scale modeling of wettability effects. J. Pet. Sci. Eng. 39, 177–199 (2003)

    Article  Google Scholar 

  • Øren, P., Bakke, S., Arntzen, O.J.: Extending predictive capabilities to network models. SPE J. 3(04), 324–336 (1998)

    Article  Google Scholar 

  • Passey, Q.R., Bohacs, K.M., Esch, W.L., Klimentidis, R., Sinha, S.: From oil-prone source rock to gas-producing shale reservoir-geologic and petrophysical characterization of unconventional shale-gas reservoirs. SPE (2010). https://doi.org/10.2118/131350-MS

    Google Scholar 

  • Peng, S., Yang, J., Xiao, X., Loucks, B., Ruppel, S.C., Zhang, T.: An integrated method for upscaling pore-network characterization and permeability estimation: example from the Mississippian Barnet Shale. Transp. Porous Med. 109(2), 359–376 (2015)

    Article  Google Scholar 

  • Sakhaee-Pour, A., Bryant, S.L.: Pore structure of shale. Fuel 143, 467–475 (2014)

    Article  Google Scholar 

  • Saraji, S., Piri, M.: High-resolution three-dimensional characterization of pore networks in shale reservoir rocks. URTEC (2014). https://doi.org/10.15530/URTEC-2014-1870621

    Google Scholar 

  • Sondergeld, C.H., Ambrose, R.J., Rai, C.S., Moncrieff, J.: Micro-structure studies of gas shales. SPE. https://doi.org/10.2118/131771-MS (2010)

  • Tahmasebi, P., Javadpour, F., Sahimi, M.: Multiscale and multiresolution modeling of shales and their flow and morphological properties. Sci. Rep. 5, 16373 (2015)

    Article  Google Scholar 

  • Tahmasebi, P., Javadpour, F., Sahimi, M.: Stochastic shale permeability matching: three-dimensional characterization and modeling. Int. J. Coal Geol. 165, 231–242 (2016)

    Article  Google Scholar 

  • Tahmasebi, P., Javadpour, F., Sahimi, M., Piri, M.: Multiscale study for stochastic characterization of shale samples. Adv. Water Resour. 89, 91–103 (2016)

    Article  Google Scholar 

  • Wang, Y., Zhu, Y., Chen, S., Li, W.: Characteristics of the nanoscale pore structure in northwestern Hunan shale gas reservoirs using field emission scanning electron microscopy, high-pressure mercury intrusion and gas adsorption. Energy Fuels 28, 945–955 (2014)

    Article  Google Scholar 

  • Washburn, E.W.: The dynamics of capillary flow. Phys. Rev. 17(3), 273–283 (1921)

    Article  Google Scholar 

  • White, F.M.: Viscous Fluid Flow. McGraw-Hill International Editions, Mechanical Engineering Series, New York (1991)

    Google Scholar 

  • Wu, K., VanDijke, M.I.J., Couples, G.D., Jiang, Z., Ma, J., Sorbie, K.S., Crawford, J., Young, I., Zhang, X.: 3D stochastic modelling of heterogeneous porous media-applications to reservoir rocks. Transp. Porous Med. 65(3), 443–467 (2006)

    Article  Google Scholar 

  • Yao, J., Wang, C., Yang, Y., Hu, R., Wang, X.: The construction of carbonate digital rock with hybrid superposition method. J. Pet. Sci. Eng. 110(1), 263–267 (2013)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Petroleum Systems Engineering, University of Regina, Regina, SK, S4S 0A2, Canada

    Shanshan Yao & Fanhua Zeng

  2. Shaanxi Yanchang Petroleum (Group) Corp. Ltd., Xian, Shaanxi, People’s Republic of China

    Xiangzeng Wang

  3. Department of Energy Resources Engineering, Stanford University, Stanford, CA, USA

    Qingwang Yuan

Authors
  1. Shanshan Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiangzeng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qingwang Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fanhua Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fanhua Zeng.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yao, S., Wang, X., Yuan, Q. et al. Estimation of Shale Intrinsic Permeability with Process-Based Pore Network Modeling Approach. Transp Porous Med 125, 127–148 (2018). https://doi.org/10.1007/s11242-018-1091-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11242-018-1091-5

Keywords

Search

Navigation