Impact of a multilayer structure on initiation and evolution of strain localization in porous rocks: Field observations and numerical modeling

• Evolution of compactive-shear deformation band networks is modeled in 3-layer models.
• Contrast of the layer properties and the interface friction are essential.
• Bands of different orientation families can be clustered or distributed homogeneously.
• In the first case the band spacing is small and in the second, it is large.
• The network organization and the porosity reduction within the bands are related.

Networks of localized conjugate compactive shear bands with large dihedral angles (corresponding to so-called shear-enhanced compaction bands) were generated in 3-layer plane strain finite-difference models. The central layer has elastic–plastic properties with a small positive internal friction coefficient, negative dilatancy factor, and the hardening modulus reducing during the deformation. The two other layers are elastic. The spatial organization of the networks in the central layer, resulting from the elastic–plastic instability of the 3-layer system, was shown to be dependent on the contrast of the elastic stiffness of the layers and on the friction between them. When the stiffness E of the elastic layers and/or the friction are small, the networks are rather symmetric (the bands of both orientation families are distributed homogeneously within the layer). An increase in E at high friction, results in the clustering of the bands of one orientation along a layer segment which is followed by another segment filled with the bands of the other orientation. Different network types are characterized by different band spacing which is smaller in the clustered networks. The intensity of inelastic deformation and hence of porosity reduction within the bands are also smaller in this case. The obtained band networks are very similar to those in nature where the same variability of the network organization is observed. Available geological and mechanical data confirm the conclusions from the modeling about the origin of this variability.