Summary

The permeability reported for many tight-oil reservoirs is often affected by bedding and sub-bedding scale lithological heterogeneities (microlithofacies, μLFs). These heterogeneities are usually caused by the combined effects of physical and biogenic processes occurring during and shortly after sediment deposition, resulting in local changes of reservoir properties which must be accounted for to properly assess the potential of these reservoirs. We have developed a comprehensive methodology for evaluating the geometry, volumetric distribution and reservoir properties of individual μLFs in these highly heterogeneous rocks. The workflow relies on an innovative combination of x-ray computed tomography, pressure decay profile permeability, and image analysis techniques; the combined interpretation of these datasets allows for the separate evaluation of μLFs reservoir quality and their connectivity. This approach is particularly applicable to the detailed characterization of highly bioturbated lithofacies (e.g., shoreface to offshore deposits), including those with selective diagenetic imprints (i.e., biogenic-influenced dolomitization in carbonates).

The workflow is illustrated using core samples comprising siliciclastic lower shoreface to offshore transition deposits from the Upper Cretaceous Cardium Fm. in the Western Canada Sedimentary Basin. Four dominant μLFs were identified: SS1 (sandy litharenite), SS2 (litharenitic wacke), SH1 (shale), and PB (siderite/pyrite-filled burrows). Porosity values average 13.2% and 7.7%, for the relatively high (SS1) and intermediate (SS2) reservoir quality μLFs clusters, whereas the corresponding geometric average permeability values are 4 mD, and 0.56mD, respectively. Connectivity of SS1 is rather limited compared to that of SS2, and the ratio of SS2:SS1 ranges between 3 and 5 in most instances. In these rocks the limited connectivity and volumetric abundance of μLFs SS1 prevents this rock type from dominating the fluid flow process.

The volumetric abundances of elemental rock types and their corresponding reservoir properties (i.e., ρb, ∅, and k) identified with this comprehensive methodology are valuable input for experimental and detailed flow/simulation models at the core scale. Significantly, the input data necessary for the morphological and topological characterization of individual physical and biogenic structures is established with this methodology.

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