Abstract

Measurement of transport properties of shale in laboratories can be expensive, extremely time-intensive and inaccurate due to lack of sufficient tool resolution. On the other hand, rigorous pore-scale simulation is prohibitively compute-intensive and is limited to sub-micron scale lacking volume-representativeness. Thus, theoretical pore-network modeling is a routine method to characterize the transport properties of shales. Connectivity architecture of porous media observed in unconventional shale reservoirs is markedly different from that in conventional reservoirs. The theoretical models developed for conventional reservoirs are explicitly proven to be not appropriate in capturing the unique characteristics of unconventional reservoirs; meanwhile, most models proposed for unconventional reservoirs are too simplified to capture realistic pore distribution. This paper presents a stochastically-distributed dendroidal pore-network model based on the analysis of pore-networks extracted from scanning electron tomographic microscope (SEM) images. Semi-acyclic model is adopted to capture the non-plateau trend of mercury intrusion capillary pressure (MICP) versus non-wetting phase saturation curve. Mercury drainage experimental data have also been compensated for the effect of pore compressibility. Intrinsic permeability and relative permeability is evaluated and validated to be in an acceptable range. Apparent permeability and its relation to intrinsic permeability is predicted by different gas-slippage correlations based on the dendroidal models. Data and samples from Marcellus shales are employed to validate the new proposed pore-network model and to compare different correlations of apparent permeability. Besides the predictive power, this new dendroidal model can also be employed as an analog of real shale porous media to perform different pore-scale simulations and analyses.

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