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Fluvial reservoirs are inherently heterogeneous. They typically have a complex connectivity between sandbodies of limited predictability and have highly variable reservoir properties at a range of scales. Attention is typically focused on the connectivity of fluvial channels because this primarily determines the feasibility of hydrocarbon recovery. However, in sand-rich fluvial reservoirs, where connectivity is less of an issue, the internal heterogeneity related to deposition and preservation of the fluvial deposit still results in uneven fluid movement and presents a challenge for prediction of reservoir behavior. The Triassic Skagerrak Formation provides an example of a sand-rich, dryland fluvial reservoir that would, prior to production, be regarded as having no critical issues relating to depositional architecture. The Skagerrak was deposited as widespread, coarsening-upward sheets by terminal fluvial systems extending several hundred kilometers from the basin margins. These sheets are typically playa and splay dominated in the lower part and become increasingly channel dominated upwards. Multistory channel-belt packages at the top of coarsening-upward sheets form the main producing intervals, and were likely to have been the product of mobile, avulsive, multiple channel systems which generated kilometer-scale channel belts. Well-test and pressure data indicate that these channel belts constitute a dual-permeability system consisting of a network of higher-permeability bodies that are variably distributed within a lower-permeability matrix. This behavior is a product of the channel belts comprising discontinuous, coarse-grained thalweg and lower bar bodies embedded in a finer-grained matrix of upper bar and splay sands. Intervals where these coarse-grained facies are well connected form high-permeability pathways which dominate early production, and these tend to be located at the bases of multistory units. However, long-term production rates are ultimately determined by inflow to these depleting pathways from the finer-grained, lower-permeability upper bar and splay facies. Well tests typically encounter boundaries, which reflect the common presence of internal barriers and baffles within the channel belts. These boundaries are composed of abandonment plugs, bar-draping fines, mud-chip conglomerates, and cemented calcrete-clast lags. However, despite the apparent abundance of flow baffles, long-term production indicates that the channel belts are fully connected laterally and that such features are likely to be discontinuous. Whilst the high sand-shale ratio of the Skagerrak would suggest that there should be few problems related to the connectivity of the fluvial sandbodies, the vertical connectivity is considerably reduced as a result of compartmentalizing shales. The origin of these shales is variable. Predictable shale packages of semi-regional extent mark intervals of terminal fluvial contraction, resulting in regional interfingering of fluvial sand sheets and floodbasin fines. In addition, more localized bar-top and floodplain shale remnants which scale with the areal extent of a field introduce more random flow barriers which are less predictable. Despite developments in the conceptual understanding of the facies architecture of such fluvial reservoirs, prediction of reservoir behavior is hindered by a paucity of quantitative and qualitative data on the geometry of preserved fluvial lithosomes with which to construct 3D models of complex bar architectures at a sub-channel-belt scale. This is particularly important when such belts are larger than the field extent, and the heterogeneities which need to be modelled are therefore at a finer hierarchical scale. The prediction of effective permeability of the reservoir requires information on the grain-size architecture within these lithosomes, together with the geometry and distribution of flow-baffling fines drapes and mud-chip lags. However, there are currently insufficient data from good-quality outcrops to be able to fully capture the potential impact ofthe natural variability of this architecture and construct predictive, quantitative models with a range of realistic geometries and properties.

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