A high-resolution simulation model of a highly heterogeneous tight oil rock sample is used to investigate the effects of physical and biogenic sedimentary structures on scaling and anisotropy of absolute permeability at the core scale. Results are compared to routine core analysis (RCA) available for similar samples.

The volumetric distribution, quality and connectivity of different contrasting types of elementary flow units [microlithofacies (μLFs)] are individually evaluated for a highly heterogeneous Pembina Cardium lithofacies. Reservoir properties were measured/calculated at a sub-centimeter scale for a core sample using a combination of x-ray computer tomography, pressure decay profile permeability, and image analysis techniques. The derived high-resolution porosity, permeability, and μLFs distribution represents the primary input to a single phase flow model. This model was used to simulate whole-core steady-state tests from which absolute permeability for different orientations was derived. Several simulation sub samples with random location and volume are also selected for evaluation of the effect of scale/composition on the calculated permeability.

The core sample evaluated exhibits three dominant rock types and a bimodal permeability within the microdarcy (μLFs SS2+SH1) and millidarcy ranges (μLFs SS1). The calculated (from whole core simulation) vertical and horizontal permeability values are in good agreement with actual RCA measurements from offset cores. Despite relatively good reservoir quality associated with μLFs SS1, results from the full diameter core simulation demonstrate that its limited volumetric abundance and restricted connectivity prevent this rock type from dominating the fluid flow process in these rocks. In fact, permeability seems to be dominated by the tighter encasing matrix (μLFs SS2 + SH1), which exhibits average permeability values very close to those reported from routine core analysis.

The methodology used in this work is particularly applicable to the detailed characterization of reservoir rocks with high degree of heterogeneity associated with biological reworking and/or selective diagenetic imprints. The model incorporates statistical variations for several key geological/engineering parameters and offers a direct comparison to results obtained from laboratory measurements.

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