Changes

Standard modeling techniques are not well suited to capturing clinoforms, particularly if they are numerous, below seismic resolution, and/or difficult to correlate between wells. Few studies have attempted to identify and correlate clinoforms in the subsurface<ref>Livera, S. E., and B. Caline, 1990, The sedimentology of the Brent Group in the Cormorant Block IV oil field: Journal of Petroleum Geology, v. 13, no. 4, p. 367–396, doi: 10.1111/j.1747-5457.1990.tb00855.x.</ref><ref>Jennette, D. C., and C. O. Riley, 1996, Influence of relative sea level on facies and reservoir geometry of the Middle Jurassic Lower Brent Group, UK North Viking Graben, inJ. A. Howell, and J. F. Aitken, eds., High-resolution sequence stratigraphy: Innovations and applications: Geological Society, London, Special Publication 104, p. 87–113.</ref><ref>Løseth, T. M., and A. Ryseth, 2003, A depositional model and sequence stratigraphic model for the Rannoch and Etive formations, Oseberg field, northern North Sea: Norwegian Journal of Geology, v. 83, p. 87–106.</ref><ref>Matthews, S., A. D. Thurlow, F. J. Aitken, S. Gowland, P. D. Jones, G. J. Colville, C. I. Robinson, and A. M. Taylor, 2005, A late life opportunity: Using a multidisciplinary approach to unlock reserves in the Rannoch Formation, Ninian field, inA. G. Doré, and B. A. Vining, eds., Petroleum geology: Northwest Europe and global perspective: Proceedings of the 6th Conference of the Geological Society (London), p. 496–510.</ref><ref name=Hmpsn2008>Hampson, G. J., A. B. Rodriguez, J. E. A. Storms, H. D. Johnson, and C. T. Meyer, 2008, Geomorphology and high-resolution stratigraphy of progradational wave-dominated shoreline deposits: Impact on reservoir-scale facies architecture, inG. J. Hampson, R. J. Steel, P. M. Burgess, and R. W. Dalrymple, eds., Recent advances in models of siliclastic shallow-marine stratigraphy: SEPM Special Publication 90, p. 117–142.</ref> or have built two-dimensional (2-D)<ref name=WB96 /><ref name=Frstr2004>Forster, C. B., S. H. Snelgrove, and J. V. Koebbe, 2004, [http://archives.datapages.com/data/specpubs/study50/sg50ch14/sg50ch14.htm Modelling permeability structure and simulating fluid flow in a reservoir analog: Ferron Sandstone, Ivie Creek area, east-central Utah], in T. C. Chidsey, Jr., R. D. Adams, and T. H. Morris, eds., Regional to wellbore analog for fluvial-deltaic reservoir modeling: The Ferron Sandstone of Utah: [http://store.aapg.org/detail.aspx?id=655 AAPG Studies in Geology 50], p. 359–382.</ref> or three-dimensional (3-D)<ref name=Hwll2008a /><ref name=Hwll2008b /><ref name=Jckson2009 /><ref name=Sch09 /><ref name=EH2010 /> flow simulation models that incorporate clinoforms. Previous studies of the Ferron Sandstone Member have incorporated simple clinoform geometries into reservoir models by using either object-based<ref name=Hwll2008b /> or deterministic<ref name=Hwll2008a /> approaches. Enge and Howell<ref name=EH2010 /> used data collected by light detection and ranging (LIDAR) equipment to precisely recreate 3-D clinoform geometries from part of the Ferron Sandstone Member outcrops; the resulting flow-simulation model contained deterministically modeled clinoforms but in a volume smaller than most reservoirs (500 × 500 × 25 m [1640 × 1640 × 82 ft]). Sech et al.<ref name=Sch09 /> used a surface-based modeling approach to produce a deterministic, 3-D model of a wave-dominated shoreface–shelf parasequence from a rich, high-resolution outcrop data set (Cretaceous Kenilworth Member, Utah), and Jackson et al.<ref name=Jckson2009 /> used this model to investigate the impact of clinoforms on fluid flow. Jackson et al.<ref name=Jckson2009 /> and Enge and Howell<ref name=EH2010 /> both showed that capturing numerous clinoforms in fluid-flow simulations is feasible. Process-based forward numerical models are capable of generating geologically realistic, 3-D stratigraphic architectures containing clinoforms in shallow-marine strata (e.g., Edmonds and Slingerland;<ref name=ES2010>Edmonds, D. A., and R. L. Slingerland, 2010, Significant effect of sediment cohesion on delta morphology: Nature Geoscience, v. 3, no. 2, p. 105–109, doi: 10.1038/ngeo730.</ref> Geleynse et al.<ref name=Glnyse>Geleynse, N. L., J. E. A. Storms, D. J. R. Walstra, H. R. A. Jagers, Z. B. Wang, and M. J. F. Sive, 2011, Controls on river delta formation; insights from numerical modeling: Earth and Planetary Science Letters, v. 302, no. 1–2, p. 217–226, doi: 10.1016/j.epsl.2010.12.013.</ref>), but it can be difficult to replicate geometries observed in outcrop data, or condition models to subsurface data (e.g., Charvin et al.<ref>Charvin, K., G. J. Hampson, K. L. Gallagher, and R. Labourdette, 2009, A Bayesian approach to inverse modelling of stratigraphy, Part 2: Validation tests: Basin Research, v. 21, no. 1, p. 27–45, doi: 10.1111/j.1365-2117.2008.00370.x.</ref>); consequently, process-based approaches have yet to be developed for routine use in reservoir modeling.

Standard modeling techniques are not well suited to capturing clinoforms, particularly if they are numerous, below seismic resolution, and/or difficult to correlate between wells. Few studies have attempted to identify and correlate clinoforms in the subsurface<ref>Livera, S. E., and B. Caline, 1990, The sedimentology of the Brent Group in the Cormorant Block IV oil field: Journal of Petroleum Geology, v. 13, no. 4, p. 367–396, doi: 10.1111/j.1747-5457.1990.tb00855.x.</ref><ref>Jennette, D. C., and C. O. Riley, 1996, Influence of relative sea level on facies and reservoir geometry of the Middle Jurassic Lower Brent Group, UK North Viking Graben, inJ. A. Howell, and J. F. Aitken, eds., High-resolution sequence stratigraphy: Innovations and applications: Geological Society, London, Special Publication 104, p. 87–113.</ref><ref>Løseth, T. M., and A. Ryseth, 2003, A depositional model and sequence stratigraphic model for the Rannoch and Etive formations, Oseberg field, northern North Sea: Norwegian Journal of Geology, v. 83, p. 87–106.</ref><ref>Matthews, S., A. D. Thurlow, F. J. Aitken, S. Gowland, P. D. Jones, G. J. Colville, C. I. Robinson, and A. M. Taylor, 2005, A late life opportunity: Using a multidisciplinary approach to unlock reserves in the Rannoch Formation, Ninian field, inA. G. Doré, and B. A. Vining, eds., Petroleum geology: Northwest Europe and global perspective: Proceedings of the 6th Conference of the Geological Society (London), p. 496–510.</ref><ref name=Hmpsn2008>Hampson, G. J., A. B. Rodriguez, J. E. A. Storms, H. D. Johnson, and C. T. Meyer, 2008, Geomorphology and high-resolution stratigraphy of progradational wave-dominated shoreline deposits: Impact on reservoir-scale facies architecture, inG. J. Hampson, R. J. Steel, P. M. Burgess, and R. W. Dalrymple, eds., Recent advances in models of siliclastic shallow-marine stratigraphy: SEPM Special Publication 90, p. 117–142.</ref> or have built two-dimensional (2-D)<ref name=WB96 /><ref name=Frstr2004>Forster, C. B., S. H. Snelgrove, and J. V. Koebbe, 2004, [http://archives.datapages.com/data/specpubs/study50/sg50ch14/sg50ch14.htm Modelling permeability structure and simulating fluid flow in a reservoir analog: Ferron Sandstone, Ivie Creek area, east-central Utah], in T. C. Chidsey, Jr., R. D. Adams, and T. H. Morris, eds., Regional to wellbore analog for fluvial-deltaic reservoir modeling: The Ferron Sandstone of Utah: [http://store.aapg.org/detail.aspx?id=655 AAPG Studies in Geology 50], p. 359–382.</ref> or three-dimensional (3-D)<ref name=Hwll2008a /><ref name=Hwll2008b /><ref name=Jckson2009 /><ref name=Sch09 /><ref name=EH2010 /> flow simulation models that incorporate clinoforms. Previous studies of the Ferron Sandstone Member have incorporated simple clinoform geometries into reservoir models by using either object-based<ref name=Hwll2008b /> or deterministic<ref name=Hwll2008a /> approaches. Enge and Howell<ref name=EH2010 /> used data collected by light detection and ranging (LIDAR) equipment to precisely recreate 3-D clinoform geometries from part of the Ferron Sandstone Member outcrops; the resulting flow-simulation model contained deterministically modeled clinoforms but in a volume smaller than most reservoirs (500 × 500 × 25 m [1640 × 1640 × 82 ft]). Sech et al.<ref name=Sch09 /> used a surface-based modeling approach to produce a deterministic, 3-D model of a wave-dominated shoreface–shelf parasequence from a rich, high-resolution outcrop data set (Cretaceous Kenilworth Member, Utah), and Jackson et al.<ref name=Jckson2009 /> used this model to investigate the impact of clinoforms on fluid flow. Jackson et al.<ref name=Jckson2009 /> and Enge and Howell<ref name=EH2010 /> both showed that capturing numerous clinoforms in fluid-flow simulations is feasible. Process-based forward numerical models are capable of generating geologically realistic, 3-D stratigraphic architectures containing clinoforms in shallow-marine strata (e.g., Edmonds and Slingerland;<ref name=ES2010>Edmonds, D. A., and R. L. Slingerland, 2010, Significant effect of sediment cohesion on delta morphology: Nature Geoscience, v. 3, no. 2, p. 105–109, doi: 10.1038/ngeo730.</ref> Geleynse et al.<ref name=Glnyse>Geleynse, N. L., J. E. A. Storms, D. J. R. Walstra, H. R. A. Jagers, Z. B. Wang, and M. J. F. Sive, 2011, Controls on river delta formation; insights from numerical modeling: Earth and Planetary Science Letters, v. 302, no. 1–2, p. 217–226, doi: 10.1016/j.epsl.2010.12.013.</ref>), but it can be difficult to replicate geometries observed in outcrop data, or condition models to subsurface data (e.g., Charvin et al.<ref>Charvin, K., G. J. Hampson, K. L. Gallagher, and R. Labourdette, 2009, A Bayesian approach to inverse modelling of stratigraphy, Part 2: Validation tests: Basin Research, v. 21, no. 1, p. 27–45, doi: 10.1111/j.1365-2117.2008.00370.x.</ref>); consequently, process-based approaches have yet to be developed for routine use in reservoir modeling.

Deterministic approaches are appropriate for modeling clinoforms that are tightly constrained by outcrop data, but they are time consuming to implement. Moreover, they do not allow flexibility in conditioning clinoform geometry and distribution to sparser data sets with a larger degree of uncertainty, such as those that are typically available for subsurface reservoirs. Incorporating hundreds of deterministic clinoform surfaces within a field-scale reservoir model would be a dauntingly time-consuming task, particularly if multiple scenarios and realizations that capture uncertainty in clinoform geometry and distribution are to be modeled. A stochastic, 3-D, surface-based modeling approach is required to address these issues. Similar approaches have been demonstrated for other depositional environments (e.g., Xie et al., 2001; Pyrcz et al., 2005; Zhang et al., 2009) and to create models of generic, dipping barriers to flow (e.g., Jackson and Muggeridge, 2000), but at present, there are no tools available to automate the generation of multiple 3-D clinoforms using a small number of parameters. The aims of this paper are to develop an efficient, quick, and practical method for incorporating clinoforms into models of shallow-marine reservoirs and to validate its application through building both geologic and fluid-flow simulation models.

Deterministic approaches are appropriate for modeling clinoforms that are tightly constrained by outcrop data, but they are time consuming to implement. Moreover, they do not allow flexibility in conditioning clinoform geometry and distribution to sparser data sets with a larger degree of uncertainty, such as those that are typically available for subsurface reservoirs. Incorporating hundreds of deterministic clinoform surfaces within a field-scale reservoir model would be a dauntingly time-consuming task, particularly if multiple scenarios and realizations that capture uncertainty in clinoform geometry and distribution are to be modeled. A stochastic, 3-D, surface-based modeling approach is required to address these issues. Similar approaches have been demonstrated for other depositional environments (e.g., Xie et al.;<ref>Xie, Y., A. S. Cullick, and C. V. Deutsch, 2001, Surface geometry and trend modeling for integration of stratigraphic data in reservoir models: SPE Paper 68817, 13 p.</ref> Pyrcz et al.;<ref>Pyrcz, M. J., O. Catuneanu, and C. V. Deutsch, 2005, [http://archives.datapages.com/data/bulletns/2005/02feb/0177/0177.HTM Stochastic surface-based modeling of turbidite lobes]: AAPG Bulletin, v. 89, no. 2, p. 177–191, doi: 10.1306/09220403112.</ref> Zhang et al.<ref>Zhang, X., M. J. Pyrcz, and C. V. Deutsch, 2009, Stochastic surface modeling of deepwater depositional systems for improved reservoir models: Journal of Petroleum Science and Engineering, v. 68, no. 1–2, p. 118–134, doi: 10.1016/j.petrol.2009.06.019.</ref>) and to create models of generic, dipping barriers to flow (e.g., Jackson and Muggeridge<ref>Jackson, M. D., and A. H. Muggeridge, 2000, The effect of discontinuous shales on reservoir performance during immiscible flow: SPE Journal, v. 5, no. 4, p. 446–455, doi: 10.2118/69751-PA.</ref>), but at present, there are no tools available to automate the generation of multiple 3-D clinoforms using a small number of parameters. The aims of this paper are to develop an efficient, quick, and practical method for incorporating clinoforms into models of shallow-marine reservoirs and to validate its application through building both geologic and fluid-flow simulation models.

The paper is structured in four parts. First, we present a simple conceptual framework to describe clinoform geometries and distributions, which allows them to be incorporated into reservoir volumes deposited in different shallow-marine environments. The framework is used to develop an algorithm-based method to represent clinoform surfaces, which is sufficiently flexible to match clinoform geometries and distributions observed in rich outcrop data sets and also to honor sparse subsurface data. The second part of the paper validates the clinoform-modeling algorithm via construction of a 3-D reservoir model of a single fluvial–deltaic parasequence using high-resolution outcrop data from fluvial-dominated delta-lobe deposits in the Cretaceous Ferron Sandstone Member of east-central Utah. The model is constructed using a framework of surfaces, including flooding surfaces between parasequences, surfaces that represent clinoforms, and surfaces that represent boundaries between facies associations. The third part of the paper demonstrates an application of the clinoform-modeling algorithm to generate a reservoir model using a sparse subsurface data set from the deltaic Jurassic Sognefjord Formation, in a fault-bounded sector of the Troll Field, offshore Norway. The clinoform-modeling algorithm allows flexibility in building a range of surface-based reservoir models that incorporate uncertainty in heterogeneities associated with clinoforms. The resulting 3-D surface-based reservoir models are suitable for flow simulation without upscaling. Finally, in the fourth part of the paper, we demonstrate that the algorithm produces models suitable for flow simulation using the Ferron Sandstone Member outcrop analog and subsurface Sognefjord Formation examples. This latter step is missing in many papers that report new reservoir modeling algorithms. The simulation models are used to assess the potential impact of flow barriers associated with clinoforms on drainage patterns and hydrocarbon recovery.

The paper is structured in four parts. First, we present a simple conceptual framework to describe clinoform geometries and distributions, which allows them to be incorporated into reservoir volumes deposited in different shallow-marine environments. The framework is used to develop an algorithm-based method to represent clinoform surfaces, which is sufficiently flexible to match clinoform geometries and distributions observed in rich outcrop data sets and also to honor sparse subsurface data. The second part of the paper validates the clinoform-modeling algorithm via construction of a 3-D reservoir model of a single fluvial–deltaic parasequence using high-resolution outcrop data from fluvial-dominated delta-lobe deposits in the Cretaceous Ferron Sandstone Member of east-central Utah. The model is constructed using a framework of surfaces, including flooding surfaces between parasequences, surfaces that represent clinoforms, and surfaces that represent boundaries between facies associations. The third part of the paper demonstrates an application of the clinoform-modeling algorithm to generate a reservoir model using a sparse subsurface data set from the deltaic Jurassic Sognefjord Formation, in a fault-bounded sector of the Troll Field, offshore Norway. The clinoform-modeling algorithm allows flexibility in building a range of surface-based reservoir models that incorporate uncertainty in heterogeneities associated with clinoforms. The resulting 3-D surface-based reservoir models are suitable for flow simulation without upscaling. Finally, in the fourth part of the paper, we demonstrate that the algorithm produces models suitable for flow simulation using the Ferron Sandstone Member outcrop analog and subsurface Sognefjord Formation examples. This latter step is missing in many papers that report new reservoir modeling algorithms. The simulation models are used to assess the potential impact of flow barriers associated with clinoforms on drainage patterns and hydrocarbon recovery.

# Jackson, M. D., G. J. Hampson, J. H. Saunders, A. El Sheikh, G. H. Graham, and B. Y. G. Massart, 2014, Surface-based reservoir modelling for flow simulation, in A. W. Martinius, J. A. Howell, and T. R. Good, eds., Sediment-body geometry and heterogeneity: Analogue studies for modelling the subsurface: Geological Society, London, Special Publication 387, p. 271–292, doi: 10.1144/SP387.2.

# Jackson, M. D., G. J. Hampson, J. H. Saunders, A. El Sheikh, G. H. Graham, and B. Y. G. Massart, 2014, Surface-based reservoir modelling for flow simulation, in A. W. Martinius, J. A. Howell, and T. R. Good, eds., Sediment-body geometry and heterogeneity: Analogue studies for modelling the subsurface: Geological Society, London, Special Publication 387, p. 271–292, doi: 10.1144/SP387.2.

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# Jackson, M. D., and A. H. Muggeridge, 2000, The effect of discontinuous shales on reservoir performance during immiscible flow: SPE Journal, v. 5, no. 4, p. 446–455, doi: 10.2118/69751-PA.

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# Jackson, M. D., S. Yosida, A. H. Muggeridge, and H. D. Johnson, 2005, Three-dimensional reservoir characterisation and flow simulation of heterolithic tidal sandstones: AAPG Bulletin, v. 89, no. 4, p. 507–528, doi: 10.1306/11230404036.

# Jackson, M. D., S. Yosida, A. H. Muggeridge, and H. D. Johnson, 2005, Three-dimensional reservoir characterisation and flow simulation of heterolithic tidal sandstones: AAPG Bulletin, v. 89, no. 4, p. 507–528, doi: 10.1306/11230404036.

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# Pirmez, C., L. F. Pratson, and M. S. Steckler, 1998, Clinoform development by advection-diffusion of suspended sediment; modeling and comparison to natural systems: Journal of Geophysical Research B: Solid Earth and Planets, v. 103, p. 24,141–24,157, doi: 10.1029/98JB01516.

# Pirmez, C., L. F. Pratson, and M. S. Steckler, 1998, Clinoform development by advection-diffusion of suspended sediment; modeling and comparison to natural systems: Journal of Geophysical Research B: Solid Earth and Planets, v. 103, p. 24,141–24,157, doi: 10.1029/98JB01516.

# Plink-Björklund, P., 2012, Effects of tides on deltaic deposition: Causes and responses: Sedimentary Geology, v. 279, p. 107–133, doi: 10.1016/j.sedgeo.2011.07.006.

# Plink-Björklund, P., 2012, Effects of tides on deltaic deposition: Causes and responses: Sedimentary Geology, v. 279, p. 107–133, doi: 10.1016/j.sedgeo.2011.07.006.

# Pyrcz, M. J., O. Catuneanu, and C. V. Deutsch, 2005, Stochastic surface-based modeling of turbidite lobes: AAPG Bulletin, v. 89, no. 2, p. 177–191, doi: 10.1306/09220403112.

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# Roberts, H. H., R. H. Fillon, B. Kohl, J. M. Robalin, and J. C. Sydow, 2004, Depositional architecture of the Lagniappe delta; sediment characteristics, timing of depositional events, and temporal relationship with adjacent shelf-edge deltas, inJ. B. Anderson, and R. H. Fillon, eds., Late Quaternary stratigraphic evolution of the northern Gulf of Mexico margin: Tulsa, Oklahoma, SEPM Special Publication 79, p. 143–188.

# Roberts, H. H., R. H. Fillon, B. Kohl, J. M. Robalin, and J. C. Sydow, 2004, Depositional architecture of the Lagniappe delta; sediment characteristics, timing of depositional events, and temporal relationship with adjacent shelf-edge deltas, inJ. B. Anderson, and R. H. Fillon, eds., Late Quaternary stratigraphic evolution of the northern Gulf of Mexico margin: Tulsa, Oklahoma, SEPM Special Publication 79, p. 143–188.

# Willis, B. J., 2005, Deposits of tide-influenced river deltas, inL. Giosan, and J. P. Bhattacharya, eds., River deltas—Concepts, models, and examples: SEPM Special Publication 83, p. 87–129.

# Willis, B. J., 2005, Deposits of tide-influenced river deltas, inL. Giosan, and J. P. Bhattacharya, eds., River deltas—Concepts, models, and examples: SEPM Special Publication 83, p. 87–129.

# Willis, B. J., J. P. Bhattacharya, S. L. Gabel, and C. D. White, 1999, Architecture of a tide-influenced river delta in the Frontier Formation of central Wyoming, USA: Sedimentology, v. 46, no. 4, p. 667–688, doi: 10.1046/j.1365-3091.1999.00239.x.

# Willis, B. J., J. P. Bhattacharya, S. L. Gabel, and C. D. White, 1999, Architecture of a tide-influenced river delta in the Frontier Formation of central Wyoming, USA: Sedimentology, v. 46, no. 4, p. 667–688, doi: 10.1046/j.1365-3091.1999.00239.x.

# Xie, Y., A. S. Cullick, and C. V. Deutsch, 2001, Surface geometry and trend modeling for integration of stratigraphic data in reservoir models: SPE Paper 68817, 13 p.

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# Zhang, X., M. J. Pyrcz, and C. V. Deutsch, 2009, Stochastic surface modeling of deepwater depositional systems for improved reservoir models: Journal of Petroleum Science and Engineering, v. 68, no. 1–2, p. 118–134, doi: 10.1016/j.petrol.2009.06.019.

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