Changes

The top and base flooding surfaces of parasequence 1.6 were extracted from the model of Deveugle et al. (2011) and served as the bounding surfaces used in the clinoform algorithm ([[:File:BLTN13190fig2.jpg|Figure 2]]). The surfaces were cropped to cover a model area of 750 × 3000 m (2461 × 9843 ft) in the Ivie Creek amphitheater ([[:File:BLTN13190fig5.jpg|Figure 5D]]). Additional surfaces representing the boundaries between facies associations from the model of Deveugle et al. (2011) were also extracted and similarly cropped; these define the distribution of facies associations present in each rock volume bounded by two clinoforms (i.e., clinothem) (cf. table 1 in Deveugle et al., 2011). From distal to proximal, the modeled facies associations are prodelta mudstone (PD), distal delta-front heteroliths (dDF), proximal delta-front sandstones (pDF), and stream-mouth-bar sandstones (SMB) ([[:File:BLTN13190fig5.jpg|Figure 5D]]). Where facies associations pinch out, the facies association boundary surfaces were adjusted to coincide throughout the remainder of the model volume with either the top or base parasequence bounding surface. This ensures that the surface is defined across the entire model volume and is suitable for gridding (Jackson et al., 2009). There are no faults within the model volume of 750 × 3000 × 6 m (2461 × 9843 × 20 ft). In a final step, isochore maps were generated between the top and base flooding surfaces and between facies association boundary surfaces and the base flooding surface. The base bounding surface was flattened, to mimic clinoform progradation over a flat, horizontal sea floor, and isochore maps were used to modify the geometries of the top bounding surface and facies association boundary surfaces above this horizontal base surface. As a result of flattening on the base bounding surface, the bounding surfaces from the existing model of Deveugle et al. (2011) have been modified.

The top and base flooding surfaces of parasequence 1.6 were extracted from the model of Deveugle et al. (2011) and served as the bounding surfaces used in the clinoform algorithm ([[:File:BLTN13190fig2.jpg|Figure 2]]). The surfaces were cropped to cover a model area of 750 × 3000 m (2461 × 9843 ft) in the Ivie Creek amphitheater ([[:File:BLTN13190fig5.jpg|Figure 5D]]). Additional surfaces representing the boundaries between facies associations from the model of Deveugle et al. (2011) were also extracted and similarly cropped; these define the distribution of facies associations present in each rock volume bounded by two clinoforms (i.e., clinothem) (cf. table 1 in Deveugle et al., 2011). From distal to proximal, the modeled facies associations are prodelta mudstone (PD), distal delta-front heteroliths (dDF), proximal delta-front sandstones (pDF), and stream-mouth-bar sandstones (SMB) ([[:File:BLTN13190fig5.jpg|Figure 5D]]). Where facies associations pinch out, the facies association boundary surfaces were adjusted to coincide throughout the remainder of the model volume with either the top or base parasequence bounding surface. This ensures that the surface is defined across the entire model volume and is suitable for gridding (Jackson et al., 2009). There are no faults within the model volume of 750 × 3000 × 6 m (2461 × 9843 × 20 ft). In a final step, isochore maps were generated between the top and base flooding surfaces and between facies association boundary surfaces and the base flooding surface. The base bounding surface was flattened, to mimic clinoform progradation over a flat, horizontal sea floor, and isochore maps were used to modify the geometries of the top bounding surface and facies association boundary surfaces above this horizontal base surface. As a result of flattening on the base bounding surface, the bounding surfaces from the existing model of Deveugle et al. (2011) have been modified.

The parameters used to insert clinoforms into the model volume are summarized in Table 2. The delta lobe in parasequence 1.6 is approximately 8.1 km (5.03 mi) wide and 12.2 km (7.58 mi) long, giving a plan-view aspect ratio of 0.7 (Deveugle et al., 2011), comparable to values for lobes of the Pleistocene Lagniappe delta (after data in Kolla et al., 2000; Roberts et al., 2004) and the modern Wax Lake Delta lobe (after data in Wellner et al., 2005) ([[:File:BLTN13190fig3.jpg|Figure 3C]]). These dimensions were likely smaller during the growth of the delta lobe, and it is assumed here that the lobe initiated with dimensions (BLTN13190eq73, BLTN13190eq74) that were a third of those of the final preserved delta lobe, consistent in areal proportions to a single mouth-bar assemblage or jet-plume complex in the modern Wax Lake Delta lobe (after data in Wellner et al., 2005). The length, BLTN13190eq75, and spacing, BLTN13190eq76, of clinoforms in depositional dip cross section were extracted from the bedding-diagram interpretations of Forster et al. (2004) ([[:File:BLTN13190fig6.jpg|Figure 6A]]), clinoform length and dip statistics of Enge et al. (2010), and the LIDAR data used to create the model of Enge and Howell (2010). A database of clinoform lengths, dips, and spacings was compiled from these data sources, yielding frequency distributions from which the geometry or spatial arrangement of clinoforms that bound mouth-bar clinothems (sensu Bhattacharya, 2006), or a trend in these parameters, can be extracted ([[:File:BLTN13190fig6.jpg|Figure 6B, C]]). The clinoform-modeling algorithm was used to build 31 clinoforms in the modeled volume of parasequence 1.6 ([[:File:BLTN13190fig7.jpg|Figure 7]]). For simplicity, clinoform spacing is fixed at 25 m (82 ft), which is the average value observed at outcrop ([[:File:BLTN13190fig6.jpg|Figure 6C]]). Heterogeneity at bed scale is recognized to be present but is not explicitly captured by surfaces in the model; rather, the effective petrophysical properties assigned to the facies associations (particularly the ratio of vertical-to-horizontal permeability) are modified to account for these (e.g., Jackson et al., 2009; Deveugle et al., 2011; Graham et al., 2015, this volume). A constant value of 2 was assigned to the clinoform shape-function exponent, P ([[:File:BLTN13190fig2.jpg|Figure 2E]]), to ensure that the clinoform dip angle is always in the range extracted from the data of Enge et al. (2010). The initial clinoform insertion point, BLTN13190eq77 ([[:File:BLTN13190fig4.jpg|Figure 4C]]), was qualitatively matched with a plan-view map of facies association belts at the top of parasequence 1.6 ([[:File:BLTN13190fig5.jpg|Figure 5D]]). The overall progradation direction for the clinoforms BLTN13190eq78 was assigned an azimuth of 274° relative to north, which corresponds to the interpreted progradation direction of the delta lobe in parasequence 1.6 (Deveugle et al., 2011). In a subsequent step, the facies association boundary surfaces extracted from the model of Deveugle et al. (2011) were used to create facies association zones within each clinothem. Application of the clinoform-modeling algorithm yields a surface-based model measuring 750 × 3000 × 6 m (2461 × 9843 × 20 ft), which contains 95 surfaces: the top- and base-parasequence bounding surfaces, 31 clinoforms, and 62 facies-association boundary surfaces ([[:File:BLTN13190fig8.jpg|Figure 8]]).

The parameters used to insert clinoforms into the model volume are summarized in Table 2. The delta lobe in parasequence 1.6 is approximately 8.1 km (5.03 mi) wide and 12.2 km (7.58 mi) long, giving a plan-view aspect ratio of 0.7 (Deveugle et al., 2011), comparable to values for lobes of the Pleistocene Lagniappe delta (after data in Kolla et al., 2000; Roberts et al., 2004) and the modern Wax Lake Delta lobe (after data in Wellner et al., 2005) ([[:File:BLTN13190fig3.jpg|Figure 3C]]). These dimensions were likely smaller during the growth of the delta lobe, and it is assumed here that the lobe initiated with dimensions (''t_D'', ''t_s'') that were a third of those of the final preserved delta lobe, consistent in areal proportions to a single mouth-bar assemblage or jet-plume complex in the modern Wax Lake Delta lobe (after data in Wellner et al., 2005). The length, ''L'', and spacing, ''S'', of clinoforms in depositional dip cross section were extracted from the bedding-diagram interpretations of Forster et al. (2004) ([[:File:BLTN13190fig6.jpg|Figure 6A]]), clinoform length and dip statistics of Enge et al. (2010), and the LIDAR data used to create the model of Enge and Howell (2010). A database of clinoform lengths, dips, and spacings was compiled from these data sources, yielding frequency distributions from which the geometry or spatial arrangement of clinoforms that bound mouth-bar clinothems (sensu Bhattacharya, 2006), or a trend in these parameters, can be extracted ([[:File:BLTN13190fig6.jpg|Figure 6B, C]]). The clinoform-modeling algorithm was used to build 31 clinoforms in the modeled volume of parasequence 1.6 ([[:File:BLTN13190fig7.jpg|Figure 7]]). For simplicity, clinoform spacing is fixed at 25 m (82 ft), which is the average value observed at outcrop ([[:File:BLTN13190fig6.jpg|Figure 6C]]). Heterogeneity at bed scale is recognized to be present but is not explicitly captured by surfaces in the model; rather, the effective petrophysical properties assigned to the facies associations (particularly the ratio of vertical-to-horizontal permeability) are modified to account for these (e.g., Jackson et al., 2009; Deveugle et al., 2011; Graham et al., 2015, this volume). A constant value of 2 was assigned to the clinoform shape-function exponent, ''P'' ([[:File:BLTN13190fig2.jpg|Figure 2E]]), to ensure that the clinoform dip angle is always in the range extracted from the data of Enge et al. (2010). The initial clinoform insertion point, ''P_o'' ([[:File:BLTN13190fig4.jpg|Figure 4C]]), was qualitatively matched with a plan-view map of facies association belts at the top of parasequence 1.6 ([[:File:BLTN13190fig5.jpg|Figure 5D]]). The overall progradation direction for the clinoforms (''θ'') was assigned an azimuth of 274° relative to north, which corresponds to the interpreted progradation direction of the delta lobe in parasequence 1.6 (Deveugle et al., 2011). In a subsequent step, the facies association boundary surfaces extracted from the model of Deveugle et al. (2011) were used to create facies association zones within each clinothem. Application of the clinoform-modeling algorithm yields a surface-based model measuring 750 × 3000 × 6 m (2461 × 9843 × 20 ft), which contains 95 surfaces: the top- and base-parasequence bounding surfaces, 31 clinoforms, and 62 facies-association boundary surfaces ([[:File:BLTN13190fig8.jpg|Figure 8]]).

A cornerpoint gridding scheme in which variations in facies architecture are represented by variations in grid architecture was used (White and Barton, 1999; Jackson et al., 2005; Sech et al., 2009). The grid has vertical pillars with a constant spacing of 20 m (66 ft) in x and y (horizontal) directions. Grid layering in the z (vertical) direction within each facies-association zone conforms to the underlying clinoform surface, so layers are parallel to, and build up from, the underlying clinoform. Grid layers have a constant thickness of 0.2 m (0.66 ft); however, each facies-association zone is gridded separately, and the grid layers pinch out against facies-association boundaries and parasequence-bounding flooding surfaces. This gridding approach was used by Sech et al. (2009); it ensures that the grid layering conforms to the architecture of the clinoform surfaces, preserving their dip and geometry, and captures facies association boundaries ([[:File:BLTN13190fig9.jpg|Figure 9]]). Where a grid layer pinches out, the grid cells have zero thickness and are set to be inactive in flow simulations. These zero-thickness cells are bridged using nonneighbor connections so that they do not act as barriers to flow. The chosen cell size of 20 × 20 × 0.2 m (66 × 66 × 0.66 ft) yields a total of approximately 5 million cells, of which 140,000 (2.6%) are active. Because the number of active grid cells is small, fluid-flow simulations can be performed on the grid without upscaling.

A cornerpoint gridding scheme in which variations in facies architecture are represented by variations in grid architecture was used (White and Barton, 1999; Jackson et al., 2005; Sech et al., 2009). The grid has vertical pillars with a constant spacing of 20 m (66 ft) in x and y (horizontal) directions. Grid layering in the z (vertical) direction within each facies-association zone conforms to the underlying clinoform surface, so layers are parallel to, and build up from, the underlying clinoform. Grid layers have a constant thickness of 0.2 m (0.66 ft); however, each facies-association zone is gridded separately, and the grid layers pinch out against facies-association boundaries and parasequence-bounding flooding surfaces. This gridding approach was used by Sech et al. (2009); it ensures that the grid layering conforms to the architecture of the clinoform surfaces, preserving their dip and geometry, and captures facies association boundaries ([[:File:BLTN13190fig9.jpg|Figure 9]]). Where a grid layer pinches out, the grid cells have zero thickness and are set to be inactive in flow simulations. These zero-thickness cells are bridged using nonneighbor connections so that they do not act as barriers to flow. The chosen cell size of 20 × 20 × 0.2 m (66 × 66 × 0.66 ft) yields a total of approximately 5 million cells, of which 140,000 (2.6%) are active. Because the number of active grid cells is small, fluid-flow simulations can be performed on the grid without upscaling.

We begin by investigating the ability of the clinoform-modeling algorithm to generate realistic stratal geometries from the Ferron Sandstone Member outcrops. Visual inspection of the algorithm-generated model against outcrop photo pans ([[:File:BLTN13190fig1.jpg|Figure 1]]) and bedding diagram interpretations ([[:File:BLTN13190fig6.jpg|Figure 6A]]) reveals a close correspondence between key geometric aspects of the observed data and concepts reproduced in the model, as outlined below.

We begin by investigating the ability of the clinoform-modeling algorithm to generate realistic stratal geometries from the Ferron Sandstone Member outcrops. Visual inspection of the algorithm-generated model against outcrop photo pans ([[:File:BLTN13190fig1.jpg|Figure 1]]) and bedding diagram interpretations ([[:File:BLTN13190fig6.jpg|Figure 6A]]) reveals a close correspondence between key geometric aspects of the observed data and concepts reproduced in the model, as outlined below.

A single delta lobe is present in the model and extends beyond the model volume (Figures 5D, 8A). As a result, clinoforms are larger in their depositional dip and strike extent (BLTN13190eq79 and BLTN13190eq80, respectively; Table 2) than the model area, and they form arcs in plan view in the model ([[:File:BLTN13190fig8.jpg|Figure 8B]]). This plan-view geometry is consistent with the approximately lobate plan-view geometries of clinoforms in fluvial-dominated deltas ([[:File:BLTN13190fig3.jpg|Figure 3C]]). The clinoform-modeling algorithm generates the concave-upward clinoform geometry observed at the outcrop (Figures 7B, 8C), while honoring the topography of the parasequence bounding surfaces. The variation in topographic elevation of the modeled parasequence (Figures 7, 8) is attributed to postdepositional compaction. In a depositional strike cross section of the clinoform-bearing model, the algorithm produces bidirectional concave-upward dips (Figures 7C, 8D) that are consistent with delta-front bodies that are lobate in plan view (e.g., Willis et al., 1999; Kolla et al., 2000; Roberts et al., 2004). Additionally, the model contains stratal geometries observed at the outcrop, such as onlap and downlap of younger clinoforms on to older clinoforms (Figures 7B, 8C). The clinoform-modeling algorithm also produces clinoforms that are consistently distributed in the same orientation as those in the observed delta-lobe deposits and its interpreted plan-view progradation direction (Figures 5A, 8B). Facies proportions in the model are 8% SMB sandstones, 50% pDF sandstones, 31% dDF heteroliths, and 11% PD mudstone. Using porosity values that are characteristic of these facies associations in analogous reservoirs (Table 3), the volume of oil in place in the model is 7.1 million bbl. The clinoform-bearing model is now used to investigate the impact of heterogeneities associated with clinoforms on fluid flow during waterflooding within this fluvial-dominated deltaic parasequence.

A single delta lobe is present in the model and extends beyond the model volume (Figures 5D, 8A). As a result, clinoforms are larger in their depositional dip and strike extent (''t_D'' and ''t_s'', respectively; Table 2) than the model area, and they form arcs in plan view in the model ([[:File:BLTN13190fig8.jpg|Figure 8B]]). This plan-view geometry is consistent with the approximately lobate plan-view geometries of clinoforms in fluvial-dominated deltas ([[:File:BLTN13190fig3.jpg|Figure 3C]]). The clinoform-modeling algorithm generates the concave-upward clinoform geometry observed at the outcrop (Figures 7B, 8C), while honoring the topography of the parasequence bounding surfaces. The variation in topographic elevation of the modeled parasequence (Figures 7, 8) is attributed to postdepositional compaction. In a depositional strike cross section of the clinoform-bearing model, the algorithm produces bidirectional concave-upward dips (Figures 7C, 8D) that are consistent with delta-front bodies that are lobate in plan view (e.g., Willis et al., 1999; Kolla et al., 2000; Roberts et al., 2004). Additionally, the model contains stratal geometries observed at the outcrop, such as onlap and downlap of younger clinoforms on to older clinoforms (Figures 7B, 8C). The clinoform-modeling algorithm also produces clinoforms that are consistently distributed in the same orientation as those in the observed delta-lobe deposits and its interpreted plan-view progradation direction (Figures 5A, 8B). Facies proportions in the model are 8% SMB sandstones, 50% pDF sandstones, 31% dDF heteroliths, and 11% PD mudstone. Using porosity values that are characteristic of these facies associations in analogous reservoirs (Table 3), the volume of oil in place in the model is 7.1 million bbl. The clinoform-bearing model is now used to investigate the impact of heterogeneities associated with clinoforms on fluid flow during waterflooding within this fluvial-dominated deltaic parasequence.

{| class = wikitable

{| class = wikitable

===Production Strategy===

===Production Strategy===

Waterflooding was simulated using conventional black oil simulation software, using a line drive of four vertical injector wells and six vertical producer wells ([[:File:BLTN13190fig10.jpg|Figure 10A]]). The producer and injector wells were spaced 750 m (2461 ft) apart, with water being injected down the local depositional dip, from east to west. Oil production and water injection were set to maintain a group target production rate over 20 yr of BLTN13190eq118 (1100 bbl/day), a minimum bottom hole pressure constraint of 50 bars (725 psi) for each production well, and a maximum bottom hole pressure constraint of 150 bars (2175 psi) for each injection well. Further information on reservoir properties is summarized in Table 3. Heterogeneity along clinoforms is specified in terms of the percentage of each clinoform surface that acts as a barrier to flow. The volume of the barriers along clinoforms is negligible, so they have little impact on the volume of oil in place. Two simulations were completed in which (1) clinoforms are not associated with barriers to flow (0% barrier coverage along clinoforms) and (2) clinoforms are associated with significant barriers to flow (90% barrier coverage along clinoforms; [[:File:BLTN13190fig10.jpg|Figure 10B]]). All other parameters remain fixed between the simulations. In a companion article, Graham et al. (2015, this volume) apply the clinoform-modeling algorithm to build a range of models to investigate the impact of a broader range of uncertainties in clinoform parameters, such as clinoform spacing and barrier coverage, on hydrocarbon recovery in the context of uncertain geologic parameters and engineering decisions.

Waterflooding was simulated using conventional black oil simulation software, using a line drive of four vertical injector wells and six vertical producer wells ([[:File:BLTN13190fig10.jpg|Figure 10A]]). The producer and injector wells were spaced 750 m (2461 ft) apart, with water being injected down the local depositional dip, from east to west. Oil production and water injection were set to maintain a group target production rate over 20 yr of 175 S m³/day (1100 bbl/day), a minimum bottom hole pressure constraint of 50 bars (725 psi) for each production well, and a maximum bottom hole pressure constraint of 150 bars (2175 psi) for each injection well. Further information on reservoir properties is summarized in Table 3. Heterogeneity along clinoforms is specified in terms of the percentage of each clinoform surface that acts as a barrier to flow. The volume of the barriers along clinoforms is negligible, so they have little impact on the volume of oil in place. Two simulations were completed in which (1) clinoforms are not associated with barriers to flow (0% barrier coverage along clinoforms) and (2) clinoforms are associated with significant barriers to flow (90% barrier coverage along clinoforms; [[:File:BLTN13190fig10.jpg|Figure 10B]]). All other parameters remain fixed between the simulations. In a companion article, Graham et al. (2015, this volume) apply the clinoform-modeling algorithm to build a range of models to investigate the impact of a broader range of uncertainties in clinoform parameters, such as clinoform spacing and barrier coverage, on hydrocarbon recovery in the context of uncertain geologic parameters and engineering decisions.

===Simulation Results===

===Simulation Results===

===Geological Setting===

===Geological Setting===

The clinoform-modeling algorithm is now applied to construct a model of the Upper Jurassic Sognefjord Formation reservoir in a fault-bounded sector of the Troll Field, offshore Norway ([[:File:BLTN13190fig12.jpg|Figure 12A, B]]). The Troll Field is a supergiant gas field that initially hosted about 40% of the total gas reserves on the Norwegian continental shelf and still contains ca. BLTN13190eq119 (35 tcf) of gas (Norwegian Petroleum Directorate, 2013). The western and eastern parts of the Troll Field accumulation occur in different structures, Troll West and Troll East. The Sognefjord Formation is interpreted to record deposition in a mixed fluvial-, tide-, and wave-influenced delta system (Dreyer et al., 2005; Patruno et al., 2015). The formation is up to 170 m (558 ft) thick in the Troll Field and consists of five, vertically stacked regressive–transgressive successions bounded by major flooding surfaces (informally referred to as the 2-, 3-, 4-, 5- and 6-series in the reservoir; [[:File:BLTN13190fig12.jpg|Figure 12C]]) (Dreyer et al., 2005). Each regressive–transgressive succession exhibits internal stratigraphic variability across the lateral extent of the reservoir, such that it can be interpreted as a sequence with constituent systems tracts and parasequences (Dreyer et al., 2005). The reservoir volume to be modeled contains seven, vertically stacked parasequences. The lower parasequences were deposited by regression of wave-dominated delta-fronts, whereas the upper parasequences comprise more tide-influenced delta-front deposits (Dreyer et al., 2005).  

The clinoform-modeling algorithm is now applied to construct a model of the Upper Jurassic Sognefjord Formation reservoir in a fault-bounded sector of the Troll Field, offshore Norway ([[:File:BLTN13190fig12.jpg|Figure 12A, B]]). The Troll Field is a supergiant gas field that initially hosted about 40% of the total gas reserves on the Norwegian continental shelf and still contains ca. 1000 x 10⁹ S m³ (35 tcf) of gas (Norwegian Petroleum Directorate, 2013). The western and eastern parts of the Troll Field accumulation occur in different structures, Troll West and Troll East. The Sognefjord Formation is interpreted to record deposition in a mixed fluvial-, tide-, and wave-influenced delta system (Dreyer et al., 2005; Patruno et al., 2015). The formation is up to 170 m (558 ft) thick in the Troll Field and consists of five, vertically stacked regressive–transgressive successions bounded by major flooding surfaces (informally referred to as the 2-, 3-, 4-, 5- and 6-series in the reservoir; [[:File:BLTN13190fig12.jpg|Figure 12C]]) (Dreyer et al., 2005). Each regressive–transgressive succession exhibits internal stratigraphic variability across the lateral extent of the reservoir, such that it can be interpreted as a sequence with constituent systems tracts and parasequences (Dreyer et al., 2005). The reservoir volume to be modeled contains seven, vertically stacked parasequences. The lower parasequences were deposited by regression of wave-dominated delta-fronts, whereas the upper parasequences comprise more tide-influenced delta-front deposits (Dreyer et al., 2005).  

Reservoir zones in the Troll West accumulation are defined by alternating layers of fine-grained, micaceous sandstone and coarse-grained sandstone (informally referred to as m sands and c sands, respectively). The coarse-grained sandstones have higher porosity and permeability (hundreds to thousands of millidarcys) than the fine-grained, micaceous sandstones (tens to hundreds of millidarcys) (Gibbons et al., 1993; Dreyer et al., 2005). Each couplet of fine-grained, micaceous sandstone and overlying coarse-grained sandstones corresponds to the lower and upper part of a single delta-front parasequence (Dreyer et al., 2005). The 3-D seismic data image laterally extensive (up to 30 km [19 mi] along depositional strike), near-linear, north-northeast–south-southwest-trending clinoforms that dip west-northwestward at 1.5°–4° (Dreyer et al., 2005; Patruno et al., 2015). The structure of the Troll West reservoir is defined by two rotated fault blocks that formed after reservoir deposition, and the reservoir is further segmented by smaller postdepositional faults that trend west-northwest–east-southeast to north-northwest–south-southeast (Dreyer et al., 2005) ([[:File:BLTN13190fig12.jpg|Figure 12B]]).

Reservoir zones in the Troll West accumulation are defined by alternating layers of fine-grained, micaceous sandstone and coarse-grained sandstone (informally referred to as m sands and c sands, respectively). The coarse-grained sandstones have higher porosity and permeability (hundreds to thousands of millidarcys) than the fine-grained, micaceous sandstones (tens to hundreds of millidarcys) (Gibbons et al., 1993; Dreyer et al., 2005). Each couplet of fine-grained, micaceous sandstone and overlying coarse-grained sandstones corresponds to the lower and upper part of a single delta-front parasequence (Dreyer et al., 2005). The 3-D seismic data image laterally extensive (up to 30 km [19 mi] along depositional strike), near-linear, north-northeast–south-southwest-trending clinoforms that dip west-northwestward at 1.5°–4° (Dreyer et al., 2005; Patruno et al., 2015). The structure of the Troll West reservoir is defined by two rotated fault blocks that formed after reservoir deposition, and the reservoir is further segmented by smaller postdepositional faults that trend west-northwest–east-southeast to north-northwest–south-southeast (Dreyer et al., 2005) ([[:File:BLTN13190fig12.jpg|Figure 12B]]).

The stratigraphic framework of the reservoir model is defined by flooding surfaces that bound seven parasequences. The bounding surfaces are offset by two postdepositional faults that are oriented northwest–southeast across the model volume. The faulted parasequence-bounding flooding surfaces were extracted from the existing reservoir model (Dilib et al., 2015). The faulted parasequence boundaries were used to construct the final Troll West sector model but, as a quality control step for applying the clinoform-modeling algorithm, these boundaries were adjusted so that they were horizontal. Each parasequence also contains a surface that represents the facies-association boundary between m sands below and c sands above; these surfaces were extracted from the model of Dilib et al. (2015) and are laterally continuous across the clinoforms modeled here, because they were extracted from a model that omits clinoforms. Consequently, facies interfingering across clinoforms is not captured here, and this may further increase the impact of modeling clinoforms on flow (Jackson et al., 2009). The facies-association boundary surfaces were adjusted to remove the effects of faulting in the same way as the flooding surfaces. Additionally, where facies associations pinch out, the facies association boundary surfaces are adjusted to coincide throughout the remainder of the model volume with the top parasequence bounding surface. This procedure created flooding surfaces and facies-association boundaries in the model that mimic their depositional geometries, which were used as a reference framework to validate that the clinoform geometries and distributions applied later using the faulted parasequence-bounding surfaces are consistent with geologic concepts.

The stratigraphic framework of the reservoir model is defined by flooding surfaces that bound seven parasequences. The bounding surfaces are offset by two postdepositional faults that are oriented northwest–southeast across the model volume. The faulted parasequence-bounding flooding surfaces were extracted from the existing reservoir model (Dilib et al., 2015). The faulted parasequence boundaries were used to construct the final Troll West sector model but, as a quality control step for applying the clinoform-modeling algorithm, these boundaries were adjusted so that they were horizontal. Each parasequence also contains a surface that represents the facies-association boundary between m sands below and c sands above; these surfaces were extracted from the model of Dilib et al. (2015) and are laterally continuous across the clinoforms modeled here, because they were extracted from a model that omits clinoforms. Consequently, facies interfingering across clinoforms is not captured here, and this may further increase the impact of modeling clinoforms on flow (Jackson et al., 2009). The facies-association boundary surfaces were adjusted to remove the effects of faulting in the same way as the flooding surfaces. Additionally, where facies associations pinch out, the facies association boundary surfaces are adjusted to coincide throughout the remainder of the model volume with the top parasequence bounding surface. This procedure created flooding surfaces and facies-association boundaries in the model that mimic their depositional geometries, which were used as a reference framework to validate that the clinoform geometries and distributions applied later using the faulted parasequence-bounding surfaces are consistent with geologic concepts.

Table 4 shows the parameters used in the clinoform-modeling algorithm. To honor the nearly linear plan-view geometry of clinoforms observed in seismic data (figures 3, 12 in Dreyer et al., 2005), a width for the top-clinoform ellipse (BLTN13190eq120 that is far greater than the depositional-dip extent of the bounding surfaces in the model area (3200 m [10,499 ft]) was defined; the top-clinoform ellipse length BLTN13190eq121 is half of BLTN13190eq122, to give a plan-view aspect ratio of 2 (cf. wave-dominated shoreface systems in Howell et al., 2008a). Seismically resolved clinoform dip values of 1.5°–4° (Dreyer et al., 2005; Patruno et al., 2015) were used in conjunction with the estimated parasequence thickness to calculate clinoform length (BLTN13190eq123) using simple trigonometry. As there are only a small number of seismically resolved clinoforms in a few paleogeographic locations and within a few stratigraphic levels to extract clinoform length, a normal distribution based on the extracted data was generated ([[:File:BLTN13190fig13.jpg|Figure 13A]]), and values were then drawn at random from this distribution to populate the model volume ([[:File:BLTN13190fig13.jpg|Figure 13A]]). Finally, the premodeling lengths were compared with the seismically resolved clinoforms (Dreyer et al., 2005) to validate that the algorithm-generated lengths are reasonable. Similarly, the horizontal spacing of seismically resolved clinoforms (figures 3, 12 in Dreyer et al., 2005) was used to generate a normal distribution of values for clinoform spacing, S ([[:File:BLTN13190fig13.jpg|Figure 13B]]), and values were drawn at random from this distribution to populate the model volume ([[:File:BLTN13190fig13.jpg|Figure 13B]]). The resulting values of clinoform length and spacing are consistent with those observed at the outcrop for other wave-dominated shorelines (e.g., Hampson, 2000; Sech et al., 2009) ([[:File:BLTN13190fig13.jpg|Figure 13]]). A value of 2 was used for the exponent in the clinoform shape function (defined by BLTN13190eq124 in equation 8), as this gives a good match to the seismically resolved clinoforms; and, furthermore, it was assumed that a similar geometry is shared by clinoforms in all parasequences in all locations throughout the model volume, consistent with observations of seismically resolved clinoforms over similar-size volumes (Patruno et al., 2015). Although, BLTN13190eq125 has the same value as used in the Ferron Sandstone Member example, BLTN13190eq126 values in the Troll Field sector model are larger ([[:File:BLTN13190fig13.jpg|Figure 13A]], Table 4) such that clinoform dip angles are shallower, consistent with the seismically resolved clinoforms (Dreyer et al., 2005; Patruno et al., 2015). As a first step, the insertion point of the first clinoform (BLTN13190eq127) was arbitrarily selected in the center of the proximal model boundary, and consistent west-northwest progradation of clinoforms (Dreyer et al., 2005; Patruno et al., 2015) was used to define a BLTN13190eq128 of 320°. The facies-association boundary surfaces extracted from the model of Dilib et al. (2015) were then used to create zones of m sands and c sands within each clinothem. The application of the clinoform-modeling algorithm yields a model containing 100 clinoforms. A visual quality control check was then performed to ensure that the clinoforms produced by the algorithm are consistent with the geologic concepts of the model (e.g., clinoform spacing, dip, length) in the absence of postdepositional faults.

Table 4 shows the parameters used in the clinoform-modeling algorithm. To honor the nearly linear plan-view geometry of clinoforms observed in seismic data (figures 3, 12 in Dreyer et al., 2005), a width for the top-clinoform ellipse (''t_s'') that is far greater than the depositional-dip extent of the bounding surfaces in the model area (3200 m [10,499 ft]) was defined; the top-clinoform ellipse length ''t_D'' is half of ''t_s'', to give a plan-view aspect ratio of 2 (cf. wave-dominated shoreface systems in Howell et al., 2008a). Seismically resolved clinoform dip values of 1.5°–4° (Dreyer et al., 2005; Patruno et al., 2015) were used in conjunction with the estimated parasequence thickness to calculate clinoform length (''L'') using simple trigonometry. As there are only a small number of seismically resolved clinoforms in a few paleogeographic locations and within a few stratigraphic levels to extract clinoform length, a normal distribution based on the extracted data was generated ([[:File:BLTN13190fig13.jpg|Figure 13A]]), and values were then drawn at random from this distribution to populate the model volume ([[:File:BLTN13190fig13.jpg|Figure 13A]]). Finally, the premodeling lengths were compared with the seismically resolved clinoforms (Dreyer et al., 2005) to validate that the algorithm-generated lengths are reasonable. Similarly, the horizontal spacing of seismically resolved clinoforms (figures 3, 12 in Dreyer et al., 2005) was used to generate a normal distribution of values for clinoform spacing, S ([[:File:BLTN13190fig13.jpg|Figure 13B]]), and values were drawn at random from this distribution to populate the model volume ([[:File:BLTN13190fig13.jpg|Figure 13B]]). The resulting values of clinoform length and spacing are consistent with those observed at the outcrop for other wave-dominated shorelines (e.g., Hampson, 2000; Sech et al., 2009) ([[:File:BLTN13190fig13.jpg|Figure 13]]). A value of 2 was used for the exponent in the clinoform shape function (defined by ''P'' in equation 8), as this gives a good match to the seismically resolved clinoforms; and, furthermore, it was assumed that a similar geometry is shared by clinoforms in all parasequences in all locations throughout the model volume, consistent with observations of seismically resolved clinoforms over similar-size volumes (Patruno et al., 2015). Although, ''P'' has the same value as used in the Ferron Sandstone Member example, ''L'' values in the Troll Field sector model are larger ([[:File:BLTN13190fig13.jpg|Figure 13A]], Table 4) such that clinoform dip angles are shallower, consistent with the seismically resolved clinoforms (Dreyer et al., 2005; Patruno et al., 2015). As a first step, the insertion point of the first clinoform (''P_o'') was arbitrarily selected in the center of the proximal model boundary, and consistent west-northwest progradation of clinoforms (Dreyer et al., 2005; Patruno et al., 2015) was used to define a ''θ'' of 320°. The facies-association boundary surfaces extracted from the model of Dilib et al. (2015) were then used to create zones of m sands and c sands within each clinothem. The application of the clinoform-modeling algorithm yields a model containing 100 clinoforms. A visual quality control check was then performed to ensure that the clinoforms produced by the algorithm are consistent with the geologic concepts of the model (e.g., clinoform spacing, dip, length) in the absence of postdepositional faults.

{| class = wikitable

{| class = wikitable

</gallery>

</gallery>

The clinoforms incorporated into the Troll sector model show similar geometries and spacing to those that are seismically resolved in the Sognefjord Formation (Dreyer et al., 2005; Patruno et al., 2015). The clinoforms are linear in plan view over the small (750 m [2461 ft]) depositional-strike extent of the model ([[:File:BLTN13190fig14.jpg|Figure 14B]]), consistent with the interpreted plan-view geometries of wave-dominated shoreface systems ([[:File:BLTN13190fig3.jpg|Figure 3A]]) (Howell et al., 2008a), consistently prograde west-northwestward (BLTN13190eq140), as established through 3-D seismic data (Dreyer et al., 2005; Patruno et al., 2015), and have the concave-upward geometry observed in seismic dip sections through the Sognefjord Formation (Dreyer et al., 2005; Patruno et al., 2015) (Figures 14A, 15B). In depositional strike cross section, the algorithm produces near-horizontal clinoform geometries, consistent with seismically resolved clinoforms (Dreyer et al., 2005; Patruno et al., 2015) ([[:File:BLTN13190fig15.jpg|Figure 15C]]). The stochastic component of the clinoform-modeling algorithm distributes clinoforms with cross-sectional geometries and spacings (Figures 14A, 15B) that are consistent with outcrop studies of wave-dominated deltas (Hampson, 2000; Sech et al., 2009) ([[:File:BLTN13190fig13.jpg|Figure 13]]) and honor the sparse subsurface data. In contrast to the Ferron Sandstone Member example, the Troll West sector model does not contain subtle clinoform geometries, such as onlap and downlap of younger clinoforms on to older clinoforms ([[:File:BLTN13190fig14.jpg|Figures 14A]], [[:File:BLTN13190fig15.jpg|15B]]). Such features are below the resolution of the seismic data used to extract the parameters that were used in the algorithm. The clinoforms are also faulted in the same way as the parasequence-bounding flooding surfaces (cf. [[:File:BLTN13190fig2.jpg|Figures 2A]], [[:File:BLTN13190fig15.jpg|15C]]).

The clinoforms incorporated into the Troll sector model show similar geometries and spacing to those that are seismically resolved in the Sognefjord Formation (Dreyer et al., 2005; Patruno et al., 2015). The clinoforms are linear in plan view over the small (750 m [2461 ft]) depositional-strike extent of the model ([[:File:BLTN13190fig14.jpg|Figure 14B]]), consistent with the interpreted plan-view geometries of wave-dominated shoreface systems ([[:File:BLTN13190fig3.jpg|Figure 3A]]) (Howell et al., 2008a), consistently prograde west-northwestward (θ = 320°), as established through 3-D seismic data (Dreyer et al., 2005; Patruno et al., 2015), and have the concave-upward geometry observed in seismic dip sections through the Sognefjord Formation (Dreyer et al., 2005; Patruno et al., 2015) (Figures 14A, 15B). In depositional strike cross section, the algorithm produces near-horizontal clinoform geometries, consistent with seismically resolved clinoforms (Dreyer et al., 2005; Patruno et al., 2015) ([[:File:BLTN13190fig15.jpg|Figure 15C]]). The stochastic component of the clinoform-modeling algorithm distributes clinoforms with cross-sectional geometries and spacings (Figures 14A, 15B) that are consistent with outcrop studies of wave-dominated deltas (Hampson, 2000; Sech et al., 2009) ([[:File:BLTN13190fig13.jpg|Figure 13]]) and honor the sparse subsurface data. In contrast to the Ferron Sandstone Member example, the Troll West sector model does not contain subtle clinoform geometries, such as onlap and downlap of younger clinoforms on to older clinoforms ([[:File:BLTN13190fig14.jpg|Figures 14A]], [[:File:BLTN13190fig15.jpg|15B]]). Such features are below the resolution of the seismic data used to extract the parameters that were used in the algorithm. The clinoforms are also faulted in the same way as the parasequence-bounding flooding surfaces (cf. [[:File:BLTN13190fig2.jpg|Figures 2A]], [[:File:BLTN13190fig15.jpg|15C]]).

===Production Strategy===

===Production Strategy===