Interdistributary bays form a major sedimentary subenvironment within many delta systems. These interdistributary bays occur as open bodies of water that are typically open to the sea. They may cover large areas of the lower delta plain and are normally surrounded by marsh and distributary-channel features. The interdistributary bay deposits in the Åre Formation of Heidrun field, offshore Norway, and in the Neslen Formation, Utah, occur as shallow, 2- to 7-km-wide features that were deposited in brackish to marine waters. Within these bays, low-energy wave action reworked a large proportion of the sedimentary features, such as crevasse splays, bayhead deltas, and distributary-mouth bars. The resulting wave-influenced bayfill lithofacies association (WLA) shows a relatively similar vertical development of lithofacies in both the Åre and the Neslen Formations. Normally the WLA is 2 to 8 m thick and contains a basal mudstone overlain by a wave-influenced lenticular and/or wavy-bed-ded heterolithic unit. The upper few meters consists of wave-rippled and small-scale hummocky cross-laminated sandstone with good reservoir qualities. Roots or coal or both are present at the top. Within the sandstone, mud drapes or heterolithic layers are common. In the Neslen Formation these drapes seem to be concentrated along gently dipping clinoform surfaces. Laterally, along the depositional strike and landward, the reservoir quality changes abruptly as the WLA passes into the bayhead delta, marsh, sub-bay/lake, and distributary-channel-fill lithofacies associations. Although individual bayfill successions are relatively thin, continuing subsidence and repetition of similar processes resulted in a stacking of one bayfill succession on top of another, building an 80-m-thick package of lower delta plain deposits.

The Lower Jurassic Åre and Tilje Formations of the Heidrun Field contain some 350 × 106Sm3(2160 × 106BBL) of oil in place. The reservoirs are highly heterogeneous and represent deposition in a wide range of fluvial, tidal and marginal marine environments. This, together with a high level of faulting and a relatively viscous oil type, has led to low recovery estimates. To help improve recovery, an integrated reservoir description project including a thorough sedimentological analysis, stochastic modelling of genetic and diagenetic facies, and an associated uncertainty analysis also using stochastic modelling was initiated.Facies architectures were modelled in 17 individual reservoir zones, each zone consisting of up to 10 × 106grid blocks. The Åre Formation is characterized by alluvial plain and low energy deltaic systems, including incised valley fills, fluvial channels, crevasse splays, upward coarsening bayfills and large splay lobe deposits. The overlying Tilje Formation is characterized by mixed tidal and marginal marine depositional systems with tidal channels, tidal sand and mud flats, tidal shoals and shoreface and offshore sands. Several facies were modelled within each zone and the desired facies architecture was often achieved by merging several individual stochastic realizations. Input to the facies modelling was based on well data as well as information from outcrop analogues and modern depositional systems. Petrophysical attributes were distributed stochastically within each facies body type, using frequency distributions from the wells and interpreted variogram functions. The realizations were finally fitted to the structural maps and upscaled for flow simulation. This enabled the building of a ‘best guess’, or most likely, full-field geological and dynamic simulation model.A subsequent uncertainty study integrated and evaluated the full spectrum of geological and petrophysical uncertainties related to the dynamic behaviour of the reservoir including facies geometries and facies volume fractions. Best, worst and intermediate case facies realizations with respect to fluid flow were first generated using stochastic modelling. These were combined with other major reservoir uncertainties (gross rock volume, petrophysical values) and 150 complete geological models were established. The hydrocarbon pore volume in each of these models was calculated, and the models were taken through a simplified flow simulation. The results from this process allowed a ranking of the models and a selection of representative models for further dynamic flow simulations. The uncertainty study shows that the uncertainty related to the gross rock volume is the most significant on a field-wide scale. Uncertainties in the facies input parameters (geometry, facies volume fraction) have relatively little impact at a field wide scale. However, their impact upon individual zones or segments (local scale) can be large.

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The Lower Jurassic Are and Tilje formations of the Heidrun Field contain some 2160 million barrels of oil in place. However, the reservoirs are highly heterogeneous and represent deposition in a wide range of fluvial, tidal and marginal marine environments. This, together with a high level of faulting and a relatively viscous oil type, has led to low simulated recoveries. To help improve recovery, an integrated reservoir description project including a thorough sedimentological analysis, stochastic modelling of genetic and diagenetic facies, and an associated uncertainty analysis also using stochastic modelling was initiated. Facies architectures were modeled in 17 individual reservoir zones, each zone consisting of up to 10 million grid blocks. The Are Formation is characterized by alluvial plain and low energy deltaic systems, including incised valley fills, fluvial channels, crevasse splays, upward coarsening bayfills and large splay lobe deposits. The overlying Tilje Formation is characterized by mixed tidal and marginal marine depositional systems with tidal channels, tidal sand and mud flats, tidal shoals and shoreface and offshore sands. Several facies were modeled within each zone and the desired facies architectures were often achieved by merging several individual stochastic realizations. Input to the facies modelling was based on well data as well as information from outcrop analogues and Recent depositional systems. Petrophysical attributes were distributed stochastically within each facies body type, using frequency distributions from the wells and interpreted variogram functions. The realizations were finally fitted to the structural maps and upscaled for flow simulation. This enabled the building of a “best guess” or most likely full-field geological and dynamic simulation model. The aim of a subsequent uncertainty study was to integrate and evaluate the entire spectrum of uncertainties related to the dynamic behavior of the reservoir including facies geometries and facies volume fractions. Best, worst and intermediate case facies realizations with respect to fluid flow were first generated using stochastic modelling. These were combined with other major reservoir uncertainties (gross rock volume, petrophysical values) and 150 complete geological models were established reflecting the total uncertainty as a function of the geological input parameters. The hydrocarbons pore volume in each of these models was calculated, and the models were also taken through a simplified flow simulation. The results from this process allowed a ranking of the models. The selection of representative models for further full-field dynamic flow simulations was based on this ranking. The uncertainty study shows that the uncertainty related to the gross rock volume is the most significant on a field-wide scale. Uncertainties in the facies input parameters (geometry, facies volume fraction) have relatively little impact at a field wide scale. However, their impact upon individual zones or segments (local scale) can be large.