Shale gas is primarily concentrated in nanopores extensively distributed in shale. The elastic properties of nanopores are significantly different from those of pores of larger sizes due to surface effects. How nanopores and adsorbed fluids affect the overall elastic properties of rock is rarely studied. Based on a recently developed nano-elasticity theory, a new method for calculating elastic modulus of nanoporous media considering adsorption is proposed by performing a detailed analysis on the relationship of surface adsorption with surface effects. The surface parameters of nanopores (pore radius, surface elastic moduli) are converted to adsorbed gas ratio and adsorbed gas elastic moduli. The proposed method is then used in rock physics modeling to estimate the elastic properties of nanoporous shale. The quantitative relationships of the effective velocities with adsorbed gas ratio, adsorbed gas elastic modulus and porosity of the shale are established, respectively. An important finding is that the elastic properties of nanoporous shale can be enhanced by increasing adsorbed gas ratio and adsorbed gas elastic moduli. A comparison between the theoretical model with laboratory data and the well data is performed and the results indicate that they are in good agreement. The results in this paper may provide certain insights on rock physics for the quantitative characterization of elastic properties of shale.

Nanopores are widely developed in organic kerogen in shale. Due to the large surface-bulk ratio, nanopores cause significant surface effects that affect the overall elastic properties of shale. It is essential to consider the effects of nanopores when applying pre-stack seismic inversion technique for shale reservoir prediction. Based on classical elastic theory, the technique of amplitude variation with offset (AVO) can usually extract velocity of longitudinal wave and shear wave, elastic modulus and density in shale reservoir from pre-stack seismic amplitudes, but often ignore the surface effects of nanopores. For the above reason, we derive a new AVO parameterization combining the nano-poroelasticity theory and AVO technique. The new derived parameterization contains four parameters (shear modulus of matrix, nanopores related parameter, shear modulus of saturated rock and density) which can be used to estimate the nanopore properties of shale. The model test and real seismic data examples verify the feasibility and suitability of the proposed method by applying Bayesian inversion technique with smooth background constraint.

No abstract