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Three-dimensional modeling of clinoforms in shallow-marine reservoirs (view source)

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Key factors influencing fluid flow and reservoir behavior include facies architecture and heterogeneity distribution conditioned to stratal surfaces. Within shallow-marine reservoirs, clinoforms are one such type of stratal surface. Clinoforms are dipping surfaces having geometry that preserves the depositional morphology of the delta-front or shoreface slope; and their distribution reflects the progradation history of the shoreline<ref>Barrell, J., 1912, Criteria for the recognition of ancient delta deposits: Geological Society of America Bulletin, v. 23, no. 1, p. 377–446, doi: 10.1130/GSAB-23-377.</ref><ref>Rich, J. L., 1951, Three critical environments of deposition, and criteria for recognition of rocks deposited in each of them: Geological Society of America Bulletin, v. 62, no. 1, p. 1–20, doi: 10.1130/0016-7606(1951)62[1:TCEODA]2.0.CO;2.</ref><ref name=GB05>Gani, M. R., and J. P. Bhattacharya, 2005, Lithostratigraphy versus chronostratigraphy in facies correlations of Quaternary deltas: Application of bedding correlation, inL. Giosan, and J. P. Bhattacharya, eds., River deltas—Concepts, models and examples: SEPM Special Publication 83, p. 31–47.</ref><ref name=Sch09>Sech, R. P., M. D. Jackson, and G. J. Hampson, 2009, [http://archives.datapages.com/data/bulletns/2009/09sep/BLTN08144/BLTN08144.HTM Three-dimensional modeling of a shoreface-shelf parasequence reservoir analog: Part 1. Surface-based modeling to capture high resolution facies architecture]: AAPG Bulletin, v. 93, no. 9, p. 1155–1181, doi: 10.1306/05110908144.</ref> ([[:File:BLTN13190fig1.jpg|Figure 1]]). Clinoforms control aspects of detailed facies architecture within parasequences and can also act as low-permeability barriers or baffles to flow.<ref name=WB96>Wehr, F. L., and L. D. Brasher, 1996, Impact of sequence-based correlation style on reservoir model behaviour, lower Brent Group, North Cormorant field, UK North Sea, inJ. A. Howell, and J. A. Aitken, eds., High resolution sequence stratigraphy: Innovations and applications: Geological Society, London, Special Publication 104, p. 115–128.</ref><ref name=Answrth1999>Ainsworth, B. R., M. Sanlung, and S. T. C. Duivenvoorden, 1999, [http://archives.datapages.com/data/bulletns/1999/10oct/1535/1535.htm Correlation techniques, perforation strategies, and recovery factors: An integrated 3-D reservoir modeling study, Sirikit field, Thailand]: AAPG Bulletin, v. 83, p. 1535–1551.</ref><ref>Dutton, S. P., B. J. Willis, C. D. White, and J. P. Bhattacharya, 2000, Outcrop characterization of reservoir quality and interwell-scale cement distribution in a tide-influenced delta, Frontier Formation, Wyoming USA: Clay Minerals, v. 35, no. 1, p. 95–105, doi: 10.1180/000985500546756.</ref><ref name=Hwll2008a>Howell, J. A., A. Skorstad, A. MacDonald, A. Fordham, S. Flint, B. Fjellvoll, and T. Manzocchi, 2008a, Sedimentological parameterization of shallow-marine reservoirs: Petroleum Geoscience, v. 14, no. 1, p. 17–34, doi: 10.1144/1354-079307-787.</ref><ref name=Hwll2008b>Howell, J. A., Å. Vassel, and T. Aune, 2008b, Modelling of dipping clinoform barriers within deltaic outcrop analogues from the Cretaceous Western Interior Basin, U.S.A., inA. Robinson, P. Griffiths, S. Price, J. Hegre, and A. H. Muggeridge, eds., The future of geologic modelling in hydrocarbon development: Geological Society, London, Special Publication 309, p. 99–121.</ref><ref name=Jckson2009>Jackson, M. D., G. J. Hampson, and R. P. Sech, 2009, [http://archives.datapages.com/data/bulletns/2009/09sep/BLTN08145/BLTN08145.HTM Three-dimensional modeling of a shoreface-shelf parasequence reservoir analog: Part 2. Geological controls on fluid flow and hydrocarbon production]: AAPG Bulletin, v. 93, no. 9, p. 1183–1208, doi: 10.1306/05110908145.</ref><ref name=EH2010>Enge, H. D., and J. A. Howell, 2010, [http://archives.datapages.com/data/bulletns/2010/02feb/BLTN08112/BLTN08112.HTM Impact of deltaic clinothems on reservoir performance: Dynamic studies of reservoir analogs from the Ferron Sandstone Member and Panther Tongue, Utah]: AAPG Bulletin, v. 94, no. 2, p. 139–161, doi: 10.1306/07060908112.</ref> Therefore, it is important to include clinoforms in models of shallow-marine reservoirs to properly characterize facies architecture and volumes of hydrocarbons in place.<ref name=Sch09 /> Under certain displacement conditions and if the clinoforms are associated with significant barriers to flow, clinoforms must be included in dynamic simulations to accurately predict likely drainage patterns and ultimate recovery of hydrocarbons.<ref name=Jckson2009 />

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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, 2010; Geleynse et al., 2011), but it can be difficult to replicate geometries observed in outcrop data, or condition models to subsurface data (e.g., Charvin et al., 2009); consequently, process-based approaches have yet to be developed for routine use in reservoir modeling.

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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.

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:<math>c(r_c) = h_{\text{min}}(r_c) + \left ( \frac{(r_{\text{max}}(x, y) - r_c(x, y))^P}{r_{\text{max}}(x, y) - r_{\text{min}}(x, y))^P} h(r_c) \right )</math>

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By varying the exponent in the clinoform shape function, ''P'', the user can increase or decrease the dip angle and change the shape of the clinoform ([[:File:BLTN13190fig2.jpg|Figure 2E]], Table 1). If a similar geometry is interpreted for each clinoform within a parasequence, because they are inferred to have formed under the influence of similar hydrodynamic and sedimentologic processes, then the same value of ''P'' (equation 7) can be applied to each clinoform modeled in the parasequence. Different values of ''P'' can be applied to distinct geographic regions of a parasequence in which clinoforms are interpreted to have different geometries (e.g., on different flanks of an asymmetric wave-dominated delta; Bhattacharya and Giosan, 2003; Charvin ~~et al~~., 2010), provided that the bounding surfaces of these geographic regions have been defined (in the initial step of the method).

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By varying the exponent in the clinoform shape function, ''P'', the user can increase or decrease the dip angle and change the shape of the clinoform ([[:File:BLTN13190fig2.jpg|Figure 2E]], Table 1). If a similar geometry is interpreted for each clinoform within a parasequence, because they are inferred to have formed under the influence of similar hydrodynamic and sedimentologic processes, then the same value of ''P'' (equation 7) can be applied to each clinoform modeled in the parasequence. Different values of ''P'' can be applied to distinct geographic regions of a parasequence in which clinoforms are interpreted to have different geometries (e.g., on different flanks of an asymmetric wave-dominated delta; Bhattacharya and Giosan, 2003;<ref>Charvin, K., G. J. Hampson, K. L. Gallagher, and R. Labourdette, 2010, High-resolution stratigraphic architecture within an interpreted asymmetrical wave-dominated deltaic parasequence: Sedimentology, v. 57, no. 3, p. 760–785, doi: 10.1111/j.1365-3091.2009.01118.x.</ref>), provided that the bounding surfaces of these geographic regions have been defined (in the initial step of the method).

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

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Our results support previous work in demonstrating that it is important to include clinoforms in models of shallow-marine reservoirs to accurately predict fluid-flow patterns and hydrocarbon recovery. However, the work presented here differs from previous modeling investigations in providing a generic method of incorporating clinoforms with geologically realistic geometries and spacing into models of shallow-marine reservoirs. The algorithm can be also be applied at a variety of lengthscales, as demonstrated in Graham et al. (2015, this volume), in which a reservoir scale model that comprises multiple stacked parasequences is used to investigate the impact of clinoforms under geologic uncertainty and reservoir engineering decisions.

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We recognize that the algorithm does not explicitly incorporate every clinoform that may be present, but instead provides a mechanism to include clinoforms at a level of stratigraphic detail defined by the user, based on a combination of stratigraphic understanding, available data, and computing resources. Nor does the algorithm represent the detailed geometry of clinoforms, as may be possible using process-based forward numerical models (e.g., Edmonds and Slingerland~~, 2010~~; Geleynse et al.~~, 2011~~). However, there are uncertainties in the values of input parameters to use in process-based models, and these parameters cannot be easily extracted from outcrop analog or subsurface data sets. There are also no explicit relationships between the input parameters for process-based models and the parameters that describe the geometries of clinoforms produced, such as clinoform length, spacing, or width. Process-based models are also difficult to condition to available data and require large computational times, which make them less feasible for modeling a range of realizations. The clinoform-modeling algorithm presented here provides a flexible and efficient method for incorporating multiple clinoforms with realistic geometries into models of shallow-marine reservoirs.

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We recognize that the algorithm does not explicitly incorporate every clinoform that may be present, but instead provides a mechanism to include clinoforms at a level of stratigraphic detail defined by the user, based on a combination of stratigraphic understanding, available data, and computing resources. Nor does the algorithm represent the detailed geometry of clinoforms, as may be possible using process-based forward numerical models (e.g., Edmonds and Slingerland;<ref name=ES2010 /> Geleynse et al.<ref name=Glnyse />). However, there are uncertainties in the values of input parameters to use in process-based models, and these parameters cannot be easily extracted from outcrop analog or subsurface data sets. There are also no explicit relationships between the input parameters for process-based models and the parameters that describe the geometries of clinoforms produced, such as clinoform length, spacing, or width. Process-based models are also difficult to condition to available data and require large computational times, which make them less feasible for modeling a range of realizations. The clinoform-modeling algorithm presented here provides a flexible and efficient method for incorporating multiple clinoforms with realistic geometries into models of shallow-marine reservoirs.

The impact of clinoforms on flow also has implications for history matching reservoir models to production data. If the underlying geologic model has omitted clinoforms and is not representative of the reservoir, then history matching will fail to produce reliable models for accurate forecasting future production. The clinoform-modeling algorithm allows multiple surface-based, clinoform-bearing models to be generated rapidly to investigate uncertainty in reservoir characterization and to develop production strategies to mitigate this uncertainty. The algorithm can thus be used in conjunction with other modeling tools and techniques as a basis to inform fast decision making in reservoir management.

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# Bhattacharya, J. P., 2006, Deltas, inH. W. Posamentier, and R. Walker, eds., Facies models revisited: SEPM Special Publication 84, p. 237–292.

# Bhattacharya, J. P., and L. Giosan, 2003, Wave-influenced deltas: Geomorphological implications for facies reconstruction: Sedimentology, v. 50, no. 1, p. 187–210, doi: 10.1046/j.1365-3091.2003.00545.x.

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# 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.

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#

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# Charvin, K., G. J. Hampson, K. L. Gallagher, and R. Labourdette, 2010, High-resolution stratigraphic architecture within an interpreted asymmetrical wave-dominated deltaic parasequence: Sedimentology, v. 57, no. 3, p. 760–785, doi: 10.1111/j.1365-3091.2009.01118.x.

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#

# Ciammetti, G., P. S. Ringrose, T. R. Good, J. M. L. Lewis, and K. S. Sorbie, 1995, Waterflood recovery and fluid flow upscaling in a shallow marine and fluvial sandstone sequence: SPE Paper 30783, 14 p.

# Cotter, E., 1976, The role of deltas in the evolution of the Ferron Sandstone and its coals: Brigham Young University Studies in Geology, v. 22, p. 15–41.

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# Dreyer, T., M. Whitaker, J. Dexter, H. Flesche, and E. Larsen, 2005, From spit system to tide-dominated delta: Integrated reservoir model of the Upper Jurassic Sognefjord Formation on the Troll West field, inA. G. Doré, and B. A. Vining, eds., Petroleum geology: From mature basins to new frontiers—Proceedings of the 6th Petroleum Geology Conference: Petroleum Geology Conference Series 6: London, Geological Society, p. 423–448.

#

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# ~~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.~~

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#

# Enge, H. D., J. A. Howell, and S. Buckley, 2010, The geometry and internal architecture of stream mouth bars in the Panther Tongue and the Ferron Sandstone Members, Utah, U.S.A.: Journal of Sedimentary Research, v. 80, no. 11, p. 1018–1031, doi: 10.2110/jsr.2010.088.

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# Gardner, M. H., 1993, Sequence stratigraphy and facies architecture of the Upper Cretaceous Ferron Sandstone Member of the Mancos Shale, east-central Utah: Ph.D. dissertation, Colorado School of Mines, Golden, Colorado, 528 p.

# Garrison, J. R., and T. C. V. Van den Bergh, 2004, High resolution depositional sequence stratigraphy of the Upper Ferron Sandstone Last Chance Delta: An application of coal-zone stratigraphy, inT. C. Chidsey, Jr., R. D. Adams, and T. H. Morris, eds., Regional to wellbore analog for fluvial-deltaic reservoir modelling: The Ferron Sandstone of Utah: AAPG Studies in Geology 50, p. 125–192.

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# 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.

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#

# Gibbons, K., T. Hellem, A. Kjemperud, S. D. Nio, and K. Vebenstad, 1993, Sequence architecture, facies development and carbonate-cemented horizons in the Troll Field reservoir, offshore Norway, inM. Ashton, ed., Advances in reservoir geology: Geological Society, London, Special Publication 69, p. 1–31.

# Google Earth, 2013, accessed January 14, 2013, http://www.google.co.uk/intl/en_uk/earth/index.html.

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Three-dimensional modeling of clinoforms in shallow-marine reservoirs (view source)

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