Abstract
A probabilistic multiscale model for poroelastic properties of organic-rich shale is extended to include the effect of microcracks. The approach is based on physics-based modeling of poroelastic properties and uncertainty propagation from nano- to macro-scale using homogenization schemes. The multiscale thought model used in this work improves on an existing thought model by adding another level to model embedded microcracks. From the scale of single clay particle to the scale of embedded microcracks, the model parameters are calibrated using experimental characterization at different length scales. To quantify the crack density and microcrack orientations, an inverse optimization approach is utilized which uses the UPV measurements at the macro-scale. Major model parameters representing compositional and mechanical properties at each length scale are modeled as a random variable. Probabilistic description of both scalar random variables and matrix-valued random variables is constructed using the maximum entropy principle (MaxEnt). Using such statistical description of model input parameters with Monte Carlo simulation, probabilistic descriptions of model outputs are obtained at each length scale. The results of stochastic upscaling are validated against available experimental values. Finally, a global sensitivity analysis is performed to identify the model input parameters which are most influential to the statistical fluctuation of upscaled poroelastic properties. The presented multiscale framework provides an enhanced understating regarding the effect of uncertainties associated with microcrack density and orientation, and other subscale features on homogenized poroelastic properties, thus further improves predictive capability for shale multiscale behavior.
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Abbreviations
- \(\left[ \varSigma \right]\) :
-
Stress matrix
- \(\left[ E \right]\) :
-
Strain matrix
- \(\left[\kern-0.15em\left[ C \right]\kern-0.15em\right]\) :
-
Fourth-order stiffness tensor
- \(\left[ \alpha \right]\) :
-
Second-order tensor of Biot pore pressure coefficients
- \(p\) :
-
Pore pressure
- ϕ :
-
Porosity
- \(N\) :
-
Solid Biot modulus
- \(\left[\kern-0.15em\left[ A \right]\kern-0.15em\right]\) :
-
Strain localization tensor
- \(\varOmega\) :
-
Representative volume element
- \(\left[\kern-0.15em\left[ I \right]\kern-0.15em\right]\) :
-
Fourth-order identity tensor
- \(\left[\kern-0.15em\left[ P \right]\kern-0.15em\right]\) :
-
Fourth-order Hill polarization tensor
- \(M\) :
-
Overall Biot modulus
- \(\eta^{i} , f^{i}\) :
-
Volume fraction of the ith phase at Level I and Level II, respectively
- \({\mathcal{N}}\) :
-
Number of cracks per unit volume
- \(a\) :
-
Crack radius
- \(c\) :
-
Crack width
- \(\varepsilon\) :
-
Crack aspect ratio
- \(d\) :
-
Crack density parameter
- \(M_{1} ,M_{3}\) :
-
Indentation moduli parallel to the bedding plane and normal to the bedding plane, respectively
- \(C_{ij}\) :
-
Component of stiffness matrix in Voigt’s notation
- \(\left\| \cdot \right\|_{\text{F}}\) :
-
Frobenius norm
- \(K\) :
-
Bulk modulus
- \(\nu\) :
-
Poisson’s ratio
- \(G\) :
-
Shear modulus
- \(\Delta_{\text{itz}}\) :
-
Thickness of interfacial transition zone (ITZ)
- \(C^{\text{itz}}\) :
-
Coefficient for elastic properties of ITZ
- \({\text{NRMSD}}\) :
-
Normalized root mean square deviation
- \(\varepsilon , \gamma , \delta^{*}\) :
-
Thomsen’s anisotropy parameters
- \(E_{x} , E_{z}\) :
-
Young’s modulus parallel to the bedding plane and normal to the bedding plane, respectively
- \(\lambda_{0} , \lambda_{1} , \lambda_{2} ,\lambda^{\text{sol}} ,\lambda_{1}^{\text{sol}} , \ldots ,\lambda_{5}^{\text{sol}}\) :
-
Lagrange multipliers
References
Abedi S, Slim M, Hofmann R, Bryndzia T, Ulm F-J (2016a) Nanochemo-mechanical signature of organic-rich shales: a coupled indentation–EDX analysis. Acta Geotech 11:559–572
Abedi S, Slim M, Ulm F-J (2016b) Nanomechanics of organic-rich shales: the role of thermal maturity and organic matter content on texture. Acta Geotech 11:775–787
Ahmadov R, Vanorio T, Mavko G (2009) Confocal laser scanning and atomic-force microscopy in estimation of elastic properties of the organic-rich Bazhenov Formation. Lead Edge 28:18–23
Aleksandrov K (1961) The elastic properties of rock forming minerals II: layered silicates. Bull Acad Sci USSR Geophys Ser 9:1165–1168
Bažant ZP, Oh BH (1985) Microplane model for progressive fracture of concrete and rock. J Eng Mech 111:559–582
Bobko CP, Gathier B, Ortega JA, Ulm FJ, Borges L, Abousleiman YN (2011) The nanogranular origin of friction and cohesion in shale—a strength homogenization approach to interpretation of nanoindentation results. Int J Numer Anal Methods Geomech 35:1854–1876
Bousige C et al (2016) Realistic molecular model of kerogen’s nanostructure. Nat Mater 15:576
Carol I, Prat PC, Bažant ZP (1992) New explicit microplane model for concrete: theoretical aspects and numerical implementation. Int J Solids Struct 29:1173–1191
Chen Q, Nezhad MM, Fisher Q, Zhu H (2016) Multi-scale approach for modeling the transversely isotropic elastic properties of shale considering multi-inclusions and interfacial transition zone. Int J Rock Mech Min Sci 84:95–104
Christensen RM, Lo KH (1979) Solutions for effective shear properties in three phase sphere and cylinder models. J Mech Phys Solids 27:315–330. https://doi.org/10.1016/0022-5096(79)90032-2
Constantinides G, Ulm FJ, Abousleiman YN (2005) Material invariant poromechanics properties of shales. Taylor & Francis Group, Abingdon
Cosenza P, Prêt D, Giraud A, Hedan S (2015) Effect of the local clay distribution on the effective elastic properties of shales. Mech Mater 84:55–74
Curtis ME, Ambrose RJ, Sondergeld CH (2010) Structural characterization of gas shales on the micro-and nano-scales. In: Canadian unconventional resources and international petroleum conference, Society of Petroleum Engineers
Delafargue A, Ulm F-J (2004) Explicit approximations of the indentation modulus of elastically orthotropic solids for conical indenters. Int J Solids Struct 41:7351–7360
Devroye L (1986) Sample-based non-uniform random variate generation. In: Proceedings of the 18th conference on Winter simulation, ACM, pp 260–265
Dormieux L, Kondo D, Ulm F-J (2006) Microporomechanics. John Wiley & Sons, Chichester
Gibbons JD, Chakraborti S (2011) Nonparametric statistical inference. Springer, New York
Giraud A, Huynh QV, Hoxha D, Kondo D (2007a) Application of results on Eshelby tensor to the determination of effective poroelastic properties of anisotropic rocks-like composites. Int J Solids Struct 44:3756–3772
Giraud A, Huynh QV, Hoxha D, Kondo D (2007b) Effective poroelastic properties of transversely isotropic rock-like composites with arbitrarily oriented ellipsoidal inclusions. Mech Mater 39:1006–1024
Guilleminot J, Soize C (2013a) On the statistical dependence for the components of random elasticity tensors exhibiting material symmetry properties. J Elast 111:109–130
Guilleminot J, Soize C (2013b) Stochastic model and generator for random fields with symmetry properties: application to the mesoscopic modeling of elastic random media. Multiscale Model Simul 11:840–870
Hornby BE, Schwartz LM, Hudson JA (1994) Anisotropic effective-medium modeling of the elastic properties of shales. Geophysics 59:1570–1583
Jaynes ET (1957) Information theory and statistical mechanics. Phys Rev 106:620
Jaynes ET (2003) Probability theory: the logic of science. Cambridge University Press, Cambridge
Jefferson A, Bennett T (2007) Micro-mechanical damage and rough crack closure in cementitious composite materials. Int J Numer Anal Methods Geomech 31:133–146
Jumarie G (2013) Maximum entropy, information without probability and complex fractals: classical and quantum approach, vol 112. Springer, New York
Kachanov ML (1982) A microcrack model of rock inelasticity part I: frictional sliding on microcracks. Mech Mater 1:19–27
Katahara KW (1996) Clay mineral elastic properties. In: SEG technical program expanded abstracts 1996. Society of Exploration Geophysicists, pp 1691–1694
Levin V, Markov M (2005) Elastic properties of inhomogeneous transversely isotropic rocks. Int J Solids Struct 42:393–408
Mashhadian M, Abedi S, Noshadravan A (2018a) Probabilistic multiscale characterization and modeling of organic-rich shale poroelastic properties. Acta Geotech 13:781–800
Mashhadian M, Verde A, Sharma P, Abedi S (2018b) Assessing mechanical properties of organic matter in shales: results from coupled nanoindentation/SEM-EDX and micromechanical modeling. J Pet Sci Eng 165:313–324
Mavko G, Mukerji T, Dvorkin J (2009) The rock physics handbook: tools for seismic analysis of porous media. Cambridge university press, Cambridge
McNeil L, Grimsditch M (1993) Elastic moduli of muscovite mica. J Phys Condens Matter 5:1681
Monfared S, Ulm F-J (2016) A molecular informed poroelastic model for organic-rich, naturally occurring porous geocomposites. J Mech Phys Solids 88:186–203
Ortega JA, Ulm F-J, Abousleiman Y (2007) The effect of the nanogranular nature of shale on their poroelastic behavior. Acta Geotech 2:155–182
Ortega JA, Ulm F-J, Abousleiman Y (2009) The nanogranular acoustic signature of shale. Geophysics 74:D65–D84
Pan Y, Chou T (1976) Point force solution for an infinite transversely isotropic solid ASME. Trans Ser E J Appl Mech 43:608–612
Pensée V, Kondo D, Dormieux L (2002) Micromechanical analysis of anisotropic damage in brittle materials. J Eng Mech 128:889–897
Prasad M, Mukerji T, Reinstaedler M, Arnold W (2009) Acoustic signatures, impedance microstructure, textural scales, and anisotropy of kerogen-rich shales. In: SPE annual technical conference and exhibition, Society of Petroleum Engineers
Prat PC, Bažant ZP (1997) Tangential stiffness of elastic materials with systems of growing or closing cracks. J Mech Phys Solids 45:611–636
Qi M, Giraud A, Colliat J-B, Shao J-F (2016a) A numerical damage model for initially anisotropic materials. Int J Solids Struct 100:245–256
Qi M, Shao J, Giraud A, Zhu Q, Colliat J (2016b) Damage and plastic friction in initially anisotropic quasi brittle materials. Int J Plast 82:260–282
Robinet JC, Sardini P, Coelho D, Parneix JC, Prêt D, Sammartino S, Boller E, Altmann S (2012) Effects of mineral distribution at mesoscopic scale on solute diffusion in a clay‐rich rock: Example of the Callovo‐Oxfordian mudstone (Bure, France). Water Resour Res 48(5):W05554. https://doi.org/10.1029/2011WR011352
Sayers C (1994) The elastic anisotrophy of shales. J Geophys Res Solid Earth 99:767–774
Seo Y-S, Ichikawa Y, Kawamura K (1999) Stress–strain response of rock-forming minerals by molecular dynamics simulation. J Soc Mater Sci Jpn 48:13–20
Shannon C (2001) A mathematical theory of communication. SIGMOBILE Mob Comput Commun Rev 5(1):3–55
Sobezyk K, Trȩbicki J (1990) Maximum entropy principle in stochastic dynamics. Probab Eng Mech 5:102–110
Staber B, Guilleminot J (2015) Approximate solutions of Lagrange multipliers for information-theoretic random field models SIAM/ASA. J Uncertain Quantif 3:599–621
Thomsen L (1986) Weak elastic anisotropy. Geophysics 51:1954–1966
Ulm F-J, Delafargue A, Constantinides G (2005) Experimental microporomechanics. In: Dormieux L, Ulm F-J (eds) Applied micromechanics of porous materials. Springer, Vienna, pp 207–288
Vasin RN, Wenk HR, Kanitpanyacharoen W, Matthies S, Wirth R (2013) Elastic anisotropy modeling of Kimmeridge shale. J Geophys Res Solid Earth 118:3931–3956
Vaughan MT, Guggenheim S (1986) Elasticity of muscovite and its relationship to crystal structure. J Geophys Res Solid Earth 91:4657–4664
Vernik L (1993) Microcrack-induced versus intrinsic elastic anisotropy in mature HC-source shales. Geophysics 58:1703–1706
Vernik L, Liu X (1997) Velocity anisotropy in shales: a petrophysical study. Geophysics 62:521–532
Walpole L (1984) Fourth-rank tensors of the thirty-two crystal classes: multiplication tables. Proc R Soc Lond A Math Phys Sci 391:149–179
Wang Z, Wang H, Cates ME (2001) Effective elastic properties of solid clays. Geophysics 66:428–440
Wang W, Li J, Fan M, Abedi S (2017) Characterization of electrical properties of organic-rich shales at nano/micro scales. Mar Pet Geol 86:563–572
Xie N, Zhu Q-Z, Xu L, Shao J-F (2011) A micromechanics-based elastoplastic damage model for quasi-brittle rocks. Comput Geotech 38:970–977
Zaoui A (2002) Continuum micromechanics: survey. J Eng Mech 128:808–816
Zeszotarski JC, Chromik RR, Vinci RP, Messmer MC, Michels R, Larsen JW (2004) Imaging and mechanical property measurements of kerogen via nanoindentation. Geochim Cosmochim Acta 68:4113–4119
Zhu Q, Shao J-F (2015) A refined micromechanical damage–friction model with strength prediction for rock-like materials under compression. Int J Solids Struct 60:75–83
Zhu Q-Z, Kondo D, Shao J (2008a) Micromechanical analysis of coupling between anisotropic damage and friction in quasi brittle materials: role of the homogenization scheme. Int J Solids Struct 45:1385–1405
Zhu Q, Kondo D, Shao J, Pensee V (2008b) Micromechanical modelling of anisotropic damage in brittle rocks and application. Int J Rock Mech Min Sci 45:467–477
Acknowledgements
The authors acknowledge partial funding from the Crisman-Berg Hughes Institute at the Department of Petroleum Engineering of Texas A&M University. Computational resources provided by Texas A&M High Performance Research Computing were utilized to conduct portions of this research. Furthermore, the authors thank the reviewer and the guest editor for providing insightful comments and feedback which improved the quality of the work.
Funding
This study was partially funded by the Crisman-Berg Hughes Institute at the Department of Petroleum Engineering of Texas A&M University (Project no. 2.07.16).
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Mohammad Mashhadian was previously a graduate student at the Texas A&M University.
Appendices
Appendix A: Calibration and Validation Data Sets
Appendix B
Description of volume fractions and stiffness tensors at Level I:
Volume fraction of phases at Level I reads:
where \(\eta^{\text{c}}\) is the volume fraction of clay, \(\eta^{\text{k}}\) is the volume fraction of kerogen, and \(\phi^{\text{I}}\) is the porosity at Level I which is distributed proportionally between clay and kerogen based on their volume fraction. These volume fractions can be obtained from their counterparts at Level II [see Eq. (37)].
To obtain the stiffness tensor of porous kerogen (or porous clay), one needs to employ Eq. (2) for \(\varOmega_{\text{porous-kerogen}} = \varOmega_{\text{kerogen}} \text{U }\varOmega_{\text{pores}}\) (or \(\varOmega_{\text{porous-clay}} = \varOmega_{\text{clay}} \text{U }\varOmega_{\text{pores}}\)). For this two-phase composite, volume fraction of porosity is equal to \(\phi^{\text{I}}\), and volume fraction of kerogen (or clay) is equal to \(\left( {1 - \phi^{\text{I}} } \right)\).
The stiffness tensor of kerogen reads:
where \(K\) and \(G\) are the bulk and shear moduli of kerogen. \(\left[\kern-0.15em\left[ J \right]\kern-0.15em\right]\) and \(\left[\kern-0.15em\left[ K \right]\kern-0.15em\right]\) are the spherical and deviatoric tensor: \({\left[\kern-0.15em\left[ J \right]\kern-0.15em\right]}_{ijkl} = \frac{1}{3}\left( {\delta_{ij} \delta_{kl} } \right)\) and \(\left[\kern-0.15em\left[ K \right]\kern-0.15em\right]{\text{ }} = {\text{ }}\left[\kern-0.15em\left[ I \right]\kern-0.15em\right] - \left[\kern-0.15em\left[ J \right]\kern-0.15em\right]{\text{ }}\). \(\delta_{ij}\) represents Kronecker delta symbol (\(\delta_{ij} = 1\) if \(i = j\), \(\delta_{ij} = 0\) otherwise)
Description of volume fractions and stiffness tensors at Level II:
Volume fraction of phases at Level II reads:
where \(f^{\text{c}}\),\(f^{\text{k}}\),\(f^{\text{inc}}\), and \(\phi^{\text{II}}\) are volume fractions of clay, kerogen, inclusions and pore space at Level II, respectively. Self-consistent texture implies that \(\phi^{\text{I}} = \phi^{\text{II}}\). Moreover, it is assumed that solid-phase inclusions consist of either calcite, with volume fraction of \(f^{\text{calcite}}\), or quartz, with volume fraction of \(f^{\text{quartz}}\).
Volume fractions of clay and kerogen at Level I, i.e., \(\eta^{\text{c}}\) and \(\eta^{\text{k}}\), can be obtained from their counterparts at Level II, i.e., \(f^{\text{c}}\) and \(f^{\text{k}}\), as follows:
where \(\phi_{{{\text{k}} + {\text{c}}}}^{\text{II}}\) denotes the portion of \(\phi^{\text{II}}\) that belongs to clay and kerogen phases. The stiffness tensor of each solid phase in inclusion reads:
where \(K_{\text{inc}}^{m}\) and \(G_{\text{inc}}^{m}\) are the bulk and shear moduli of inclusion \(m\), respectively (\(K_{\text{inc}}^{\text{quartz}}\) = 37.9 GPa; \(G_{\text{inc}}^{\text{quartz}}\) = 44.3 GPa and \(K_{\text{inc}}^{\text{calcite}}\) = 58.2 GPa; \(G_{\text{inc}}^{\text{calcite}}\) = 28.3 GPa (Mavko et al. 2009)).
Effect of weakened interface:
Interfacial transition zone (ITZ) is utilized to model an imperfect interface between matrix and inclusions. Introduction of ITZ alters the relationship of volume fractions at Eq. (36) to:
One should note that the ratio \(\frac{{f^{\text{calcite}} }}{{f^{\text{quartz}} }}\) is constant before and after the introduction of ITZ. The effect of weakened interface can be integrated into the multiscale model through a three-step homogenization scheme known as generalized self-consistent method (Christensen and Lo 1979). In the first step of homogenization, the effective elasticity of solid matrix, i.e., a self-consistent mixture of quartz, and calcite is obtained. Next, the weakened interface is introduced to the homogenized solid matrix obtained from previous step by performing a generalized self-consistent homogenization. Finally, the porosity is introduced to the effective medium obtained from second step by implementing a self-consistent homogenization. Following relationships for relevant volume fractions involved in the three-step homogenization are considered:
where \(\Delta_{\text{itz}}\) denotes the thickness of ITZ in micrometer. In the right-hand side of Eq. (41), the number 2 represents the average sum of radius of solid inclusion grain and the thickness of ITZ in micrometer (see Fig. 1), which is reported in Monfared and Ulm (2016).
Appendix C
Level I:
Level II:
In the above equations, \(\varphi^{\text{clay}} = \phi^{\text{I}} \frac{{\eta^{\text{c}} }}{{\eta^{\text{c}} + \eta^{\text{k}} }}\), \(\varphi^{\text{kerogen}} = \phi^{\text{I}} \frac{{\eta^{\text{k}} }}{{\eta^{\text{c}} + \eta^{\text{k}} }}\), and \(f^{\text{porous-inc}} = f^{\text{inc}} + \phi^{\text{inc}}\). \(S^{\text{clay}}\) and \(\left[ I \right]\) represent compliance tensor for clay and identity matrix, respectively. Also, superscript “inc” stands for inclusion.
Appendix D
A description of Hamilton function reads:
Appendix E
Following flowchart represents a schematic of the calibration and validation process
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Dubey, V., Mashhadian, M., Abedi, S. et al. Multiscale Poromechanical Modeling of Shales Incorporating Microcracks. Rock Mech Rock Eng 52, 5099–5121 (2019). https://doi.org/10.1007/s00603-019-01833-5
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DOI: https://doi.org/10.1007/s00603-019-01833-5