Changes

[[File:BLTN13190fig2.jpg|thumb|300px|{{figure number|2}}Examples of clinoforms produced by the clinoform-modeling algorithm conditioned to different bounding surfaces and clinoform geometries. (A) Bounding surfaces represent postdepositional compaction and folding of the original (depositional) geometries of the clinoform and the top and base bounding surfaces. (B) Bounding surfaces represent a clinoform within a volume truncated at its top, for example, by a channel ([[:File:BLTN13190fig1.jpg|Figure 1]]). (C) Bounding surfaces represent a clinoform downlapping onto irregular sea-floor topography. (D) Height function, ''h(r_c)'' (equation 1; see Table 1 for nomenclature). (E) Shape function, ''s(r_c)'' (equation 7; Table 1), demonstrating that increasing the exponent, ''P'', increases the dip angle of clinoforms.]]

[[File:BLTN13190fig2.jpg|thumb|300px|{{figure number|2}}Examples of clinoforms produced by the clinoform-modeling algorithm conditioned to different bounding surfaces and clinoform geometries. (A) Bounding surfaces represent postdepositional compaction and folding of the original (depositional) geometries of the clinoform and the top and base bounding surfaces. (B) Bounding surfaces represent a clinoform within a volume truncated at its top, for example, by a channel ([[:File:BLTN13190fig1.jpg|Figure 1]]). (C) Bounding surfaces represent a clinoform downlapping onto irregular sea-floor topography. (D) Height function, ''h(r_c)'' (equation 1; see Table 1 for nomenclature). (E) Shape function, ''s(r_c)'' (equation 7; Table 1), demonstrating that increasing the exponent, ''P'', increases the dip angle of clinoforms.]]

Clinoforms occur at a wide range of spatial scales, from large, basinward-dipping surfaces at the shelf-slope margin, to smaller surfaces associated with progradation of deltaic and shoreface systems across the shelf (e.g., Helland-Hansen and Hampson, 2009). This study focuses on developing a surface-based approach to represent clinoforms at any lengthscale in reservoir models, with emphasis on clinoforms produced by the progradation of deltaic, barrier-island, and strandplain shorelines, which are typically up to a few tens of meters in height. The 3-D geometry and spatial arrangement of shoreline-scale clinoforms reflect in large part the process regime under which they were deposited (e.g., Galloway, 1975). Fluvial-dominated deltas exhibit a hierarchy of point-sourced, teardrop-shaped sediment bodies that are fed via a downstream branching network of distributary channels. From small to large lengthscales, this hierarchy consists of mouth bars, mouth-bar assemblages, and delta lobes (Bhattacharya, 2006; equivalent to the jet-plume deposits, jet-plume-complex deposits, and delta lobes of Wellner et al., 2005). Sediment-body geometry is modified by the action of waves and tides, which respectively tend to result in shoreline-parallel and shoreline-perpendicular sediment transport that suppresses branching and switching of distributary channels (e.g., Galloway, 1975; Willis, 2005; Bhattacharya, 2006; Plink-Björklund, 2012). Clinoforms exist as a preserved record of sediment-body morphologies at each of these hierarchical lengthscales (e.g., Gani and Bhattacharya<ref name=GB07>Gani, M. R., and J. P. Bhattacharya, 2007, Basic building blocks and process variability of a Cretaceous delta: Internal facies architecture reveals a more dynamic interaction of river, wave, and tidal processes than is indicated by external shape: Journal of Sedimentary Research, v. 77, no. 4, p. 284–302, doi: 10.2110/jsr.2007.023.</ref>) but are most commonly described at the scale of delta lobes in outcrop and high-resolution, shallow seismic data. For example, in Pleistocene fluvial-dominated delta deposits imaged in shallow-seismic data, Roberts et al. (2004, p. 185) comment that “each clinoform set represents rather continuous deposition from a distributary or related set of distributaries, resulting in the formation of a delta lobe.” Shale drapes and cemented concretionary layers occur along depositional surfaces at each hierarchical level but generally have greater continuity and extent at larger lengthscales of the hierarchy (e.g., Gani and Bhattacharya;<ref name=GB07 /> Lee et al., 2007; Ahmed et al., 2014). Thus, delta lobes tend to be overlain across flooding surfaces by prodelta shales and distal-delta-front heteroliths, which may cause them to behave as distinct reservoir zones that can be correlated between wells, whereas clinoforms are associated with heterogeneity between wells and within reservoir zones (e.g., Ainsworth et al.,;<ref name=Answrth1999 /> Hampson et al.<ref name=Hmpsn2008 />).

Clinoforms occur at a wide range of spatial scales, from large, basinward-dipping surfaces at the shelf-slope margin, to smaller surfaces associated with progradation of deltaic and shoreface systems across the shelf (e.g., Helland-Hansen and Hampson<ref name=HHH>Helland-Hansen, W., and G. J. Hampson, 2009, Trajectory analysis: Concepts and applications: Basin Research, v. 21, no. 5, p. 454–483, doi: 10.1111/j.1365-2117.2009.00425.x.</ref>). This study focuses on developing a surface-based approach to represent clinoforms at any lengthscale in reservoir models, with emphasis on clinoforms produced by the progradation of deltaic, barrier-island, and strandplain shorelines, which are typically up to a few tens of meters in height. The 3-D geometry and spatial arrangement of shoreline-scale clinoforms reflect in large part the process regime under which they were deposited (e.g., Galloway, 1975). Fluvial-dominated deltas exhibit a hierarchy of point-sourced, teardrop-shaped sediment bodies that are fed via a downstream branching network of distributary channels. From small to large lengthscales, this hierarchy consists of mouth bars, mouth-bar assemblages, and delta lobes (Bhattacharya, 2006; equivalent to the jet-plume deposits, jet-plume-complex deposits, and delta lobes of Wellner et al., 2005). Sediment-body geometry is modified by the action of waves and tides, which respectively tend to result in shoreline-parallel and shoreline-perpendicular sediment transport that suppresses branching and switching of distributary channels (e.g., Galloway, 1975; Willis, 2005; Bhattacharya, 2006; Plink-Björklund, 2012). Clinoforms exist as a preserved record of sediment-body morphologies at each of these hierarchical lengthscales (e.g., Gani and Bhattacharya<ref name=GB07>Gani, M. R., and J. P. Bhattacharya, 2007, Basic building blocks and process variability of a Cretaceous delta: Internal facies architecture reveals a more dynamic interaction of river, wave, and tidal processes than is indicated by external shape: Journal of Sedimentary Research, v. 77, no. 4, p. 284–302, doi: 10.2110/jsr.2007.023.</ref>) but are most commonly described at the scale of delta lobes in outcrop and high-resolution, shallow seismic data. For example, in Pleistocene fluvial-dominated delta deposits imaged in shallow-seismic data, Roberts et al. (2004, p. 185) comment that “each clinoform set represents rather continuous deposition from a distributary or related set of distributaries, resulting in the formation of a delta lobe.” Shale drapes and cemented concretionary layers occur along depositional surfaces at each hierarchical level but generally have greater continuity and extent at larger lengthscales of the hierarchy (e.g., Gani and Bhattacharya;<ref name=GB07 /> Lee et al., 2007; Ahmed et al., 2014). Thus, delta lobes tend to be overlain across flooding surfaces by prodelta shales and distal-delta-front heteroliths, which may cause them to behave as distinct reservoir zones that can be correlated between wells, whereas clinoforms are associated with heterogeneity between wells and within reservoir zones (e.g., Ainsworth et al.,;<ref name=Answrth1999 /> Hampson et al.<ref name=Hmpsn2008 />).

The clinoform-modeling algorithm developed here is simple to use, requiring specification of only a few input parameters: (1) the upper and lower surfaces that define the rock volume within which the clinoforms are to be modeled; (2) the plan-view geometry of clinoforms; (3) clinoform geometry in depositional-dip-oriented cross section; and (4) spacing and progradation direction of the clinoforms. The user can also use a stochastic component of the clinoform-modeling algorithm if there are uncertainties in the parameter values to be used.

The clinoform-modeling algorithm developed here is simple to use, requiring specification of only a few input parameters: (1) the upper and lower surfaces that define the rock volume within which the clinoforms are to be modeled; (2) the plan-view geometry of clinoforms; (3) clinoform geometry in depositional-dip-oriented cross section; and (4) spacing and progradation direction of the clinoforms. The user can also use a stochastic component of the clinoform-modeling algorithm if there are uncertainties in the parameter values to be used.

===Spacing and Progradation Direction of Clinoforms===

===Spacing and Progradation Direction of Clinoforms===

The clinoform-modeling algorithm allows the user to specify the main progradation direction of the clinoforms and to define the intervals along the progradation path at which clinoforms are generated (i.e., the clinoform spacing). The user specifies a progradation direction relative to north, ''θ'' ([[:File:BLTN13190fig4.jpg|Figure 4C]], Table 1), along which successive clinoforms are generated, which corresponds to the progradation path of the shoreline during clinoform deposition (plan-view shoreline trajectory of Helland-Hansen and Hampson, 2009). The user also specifies the initial insertion point for the clinoforms, ''P_o'' ([[:File:BLTN13190fig4.jpg|Figure 4C]]). This provides flexibility in determining where to place the initial clinoform relative to the proximal model boundary. The spacing between each clinoform surface, ''S'' (Table 1), is also designated by the user. Clinoform spacing is defined as the distance between the top-truncation points of two successive clinoforms, and it determines the origin position, ''(x_origin, y_origin)'', of successive clinoforms ([[:File:BLTN13190fig4.jpg|Figure 4D]]).

The clinoform-modeling algorithm allows the user to specify the main progradation direction of the clinoforms and to define the intervals along the progradation path at which clinoforms are generated (i.e., the clinoform spacing). The user specifies a progradation direction relative to north, ''θ'' ([[:File:BLTN13190fig4.jpg|Figure 4C]], Table 1), along which successive clinoforms are generated, which corresponds to the progradation path of the shoreline during clinoform deposition (plan-view shoreline trajectory of Helland-Hansen and Hampson<ref name=HHH />). The user also specifies the initial insertion point for the clinoforms, ''P_o'' ([[:File:BLTN13190fig4.jpg|Figure 4C]]). This provides flexibility in determining where to place the initial clinoform relative to the proximal model boundary. The spacing between each clinoform surface, ''S'' (Table 1), is also designated by the user. Clinoform spacing is defined as the distance between the top-truncation points of two successive clinoforms, and it determines the origin position, ''(x_origin, y_origin)'', of successive clinoforms ([[:File:BLTN13190fig4.jpg|Figure 4D]]).

===Stochastic Modeling of Clinoforms===

===Stochastic Modeling of Clinoforms===

# Hampson, G. J., and J. E. A. Storms, 2003, Geomorphological and sequence stratigraphic variability in wave-dominated shoreface-shelf parasequences: Sedimentology, v. 50, no. 4, p. 667–701, doi: 10.1046/j.1365-3091.2003.00570.x.

# Hampson, G. J., and J. E. A. Storms, 2003, Geomorphological and sequence stratigraphic variability in wave-dominated shoreface-shelf parasequences: Sedimentology, v. 50, no. 4, p. 667–701, doi: 10.1046/j.1365-3091.2003.00570.x.

# Haug, B. T., 1992, The second long-term horizontal well test in Troll: Successful production from a 13-in. oil column with the well partly completed in the water zone: SPE Paper 24943, 10 p.

# Haug, B. T., 1992, The second long-term horizontal well test in Troll: Successful production from a 13-in. oil column with the well partly completed in the water zone: SPE Paper 24943, 10 p.

# Helland-Hansen, W., and G. J. Hampson, 2009, Trajectory analysis: Concepts and applications: Basin Research, v. 21, no. 5, p. 454–483, doi: 10.1111/j.1365-2117.2009.00425.x.

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# Holgate, N. E., G. J. Hampson, C. A.-L. Jackson, and S. A. Petersen, 2014, Constraining uncertainty in interpretation of seismically imaged clinoforms in deltaic reservoirs, Troll Field, Norwegian North Sea: Insights from forward seismic models of outcrop analogs: AAPG Bulletin, v. 98, no. 12, p. 2629–2663, doi: 10.1306/05281413152.

# Holgate, N. E., G. J. Hampson, C. A.-L. Jackson, and S. A. Petersen, 2014, Constraining uncertainty in interpretation of seismically imaged clinoforms in deltaic reservoirs, Troll Field, Norwegian North Sea: Insights from forward seismic models of outcrop analogs: AAPG Bulletin, v. 98, no. 12, p. 2629–2663, doi: 10.1306/05281413152.

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