1. Sedimentological Processes Modeling Christopher G. St.C. Kendall

2. Outline of Presentation Data - Outcrops, well log & seismic cross sections Sequence stratigraphy & modeling Relative sea level & 2D/3D sedimentary simulations Inverse conceptual simulation models versus numerical forward modeling Short-term, high-resolution, local versus long- term basin wide Holocene data particularly carbonates Sedimentary simulation movies & modeling. Interconnected modules of numerical process simulations of sedimentary basins evolution - the future

3. Sequence Stratigraphy History 1791 - William Smith established relationship of sedimentary rocks to geologic time 1962 - Hess proposed the theory of sea-floor spreading 1963 - Vine & Matthews identified deep ocean paleomagnetic "stripes“ 1965 - Wilson began developing the theory of plate tectonics 1977 - Vail proposed the discipline of sequence stratigraphy

4. Types of Simulations Sedimentary modeling: Carbonates vs. clastics Stochastic vs. deterministic Fuzzy vs. empirical Small vs large oceanic basins

5. Traditional Use of Sedimentary Simulations Understand complexities of clastic or carbonate stratigraphy Identify & model sedimentary systems. Quantify models that explain & predict stratal geometries within sequences. Used by specialized experts who design & build the simulations. Sedimentary process models from outcrops, well log & seismic cross sections used to:

6. Sedimentological Processes Modeling Inverse conceptual simulation models Numerical forward modeling advanced. Short-term, high-resolution local events vs a long-term regional events 2D & 3D sedimentary simulations, relative sea level, physical processes, & sedimentation & erosion:

7. Approaches to modeling Geometric models Fixed depositional geometries are assumed Conservation of mass Simple computations through general nonlinear dynamic models Variations in depositional geometries Variations in surface slope vs discharge More complex computationally Chris Paola, 2002

8. Some sedimentary models Short-term local events SEDSIM (Tetzlaff and Harbaugh, 1989) SEDFLUX (Syvitski et al., 1998a; Syvitski et al., 1998b) Long-term regional events PHIL (Bowman et al 1999) SEDPAK (Eberli, et al, 1994) FUZZIM (Nordlund1999a&b) CSM (Syvitski et al., 2002) Robinson and Slingerland, 1998 Steckler et al., 1993.

9. Ross et al., 1995 Jervey, 1988 Perlmutter et al., 1998 Chris Paola Geometric Model

10. Chris Paola

11. Geometric Models “Jurassic Tank” Chris Paola, 2002.

12. Geometric Model Eberli, et al, 1994

13. Uses by Specialized Users John W. Harbaugh 3D sedimentary fill Carey et al., model high-resolution sequence stratigraphy Bowman & Vail empirical stratigraphic interpretion - stratigraphy of the Baltimore Canyon Kendall et al., empirical stratigraphic simulator for Bahamas Syvitski et al., model links fluvial discharge, suspended sediment plume, associated turbidites, the effects of slope stability, debris flow, and downslope diffusion

14. Approaches to modeling Geometric models Aigner - Deterministic 2D Bosence et al. - 3D Forward & Fieldwork Bosscher - 2D Forward Model Bowman - Forward Model Cowell - Shoreface Model Cross and Duan - 3D Forward Model Demicco - Fuzzy Modeling

15. Some of the carbonate modelers Aigner - Deterministic 2D Bosence et al. - 3D Forward & Fieldwork Bosscher - 2D Forward Model Bowman - Forward Model Cowell - Shoreface Model Cross and Duan - 3D Forward Model Demicco - Fuzzy Modeling

16. Flemmings - Meter-scale shaoling cycles Goldhammer - High-frequency platform carbonate cycles Granjeon - Diffusion-based stratigraphic model Kendall – Deterministic forward model Ulf Nordlund - Fuzzy logic Read - Two-dimensional modeling Rivanaes - Depth-dependent diffusion models of erosion, transport & sedimentation Further carbonate modelers!

17. Why limited use of simulations Software integrates seismic, well logs, outcrops & current depositional systems On site interpretations & evalutation of data revealing origin of sediment depositional systems Models explain sedimentary geometries displayed on interpreted seismic & well log sections

18. Historically sedimentary modeling derived from real data Seismic Wells. Outcrop But less from: Holocene Data Sources

19. Seismic

20. Wells

21. Outcrops

22. King 1954

23. Simulation Data Needs Models are commonly based on subsurface Input variables known but values are inferred from geologic record Need to refine observations at deposition Complexity needs to be handled by a team approach Need to gather data from a Holocene setting like the “Arabian Gulf ”

24. Restricted Entrance To Sea Isolated linear Belt of interior drainage Regional Drainage Into Basin Arid Tropics Air System Wide Envelope of surrounding continents

25. United Arab Emirate Coast Barrier Island Coast Aeolian System Arid Climate Coastal Evaporite System Reef Platform

26. United Arab Emirate Coast Tidal Deltas Arid Climate Coastal Evaporite System Reef & Lagoon

27. Power of Simulation Movies Annotated movies of sedimentary simulation show evolution of sedimentary geometries in response to variations in rates of: Sedimentation Tectonic movement Sea-level position Movies involve hypothetical & real-life examples based on outcrops, well log & seismic cross sections.

28. Clastic Simulation

58. Geometric Effects of Sea Level Change On-lap with rising sea level Off-lap with falling sea level By-pass at low stands of sea level Erosion at low stands of sea level Ravinement with sea level transgressions Landward continental clastics at high stands Seaward carbonates at high stands

59. Chronostratigraphic Chart

90. Venezuelan Example

91. Example 1: Well Log Correlation

94. Venezuelan - Example

120. Sedimentary Simulations & Sequence Stratigraphy Factors controlling sequence stratigraphic geometries Efficient interpretations of data Enhances biostratigraphy & infers ages Quantifies models Identifies & models ancient sedimentary systems Sharing data with others

121. Potential use of sedimentary simulations Stratal architecture - hydrocarbon exploration Water storage & geochemistry of hydrologic cycle Natural hazards assessment of risk Landscapes management Sedimentary basins as incubators of the deep biosphere Control carbon & other elemental cycles from sedimentary basins & eroded landscapes Tracking global & regional climate change

122. Sedimentary Simulations Conclusions Earlier sedimentary simulation modelled large scale processes Will focus on smaller scale processes, to predict distribution of heterogeneous sedimentary facies from a) 3D perspective b) Fluid flow c) Role of diagenesis These models will probably involve combinations of fuzzy logic, empirical, stochastic & deterministic algorithms

123. Simulation Design The design & use of sedimentary simulations involves: Complexity of stratigraphic geometries and sedimentation Changes in base level Data sources & quality Types of output Sensitivity of the results to errors in data input & model used

124. Simulations - which way ? Sedimentary models are a mix of deterministic and process driven Input variables are know but their value has to inferred from the geologic record Sedimentary models are going 3D Subsurface models are commonly oil field based Movies are worth a thousand words Sharpens & accelerates ability to observe & interpret complex sequence stratigraphic geometric relationships

125. Future Directions Interconnected modules of numerical process simulations Track the evolution of sedimentary basins & their associated landscapes Time scales ranging from individual events to many millions of years http://instaar.Colorado.EDU/deltaforce/workshop/csm.htmlhttp://instaar.Colorado.EDU/deltaforce/workshop/csm.html). Recently emphasis within the USA by US Government agencies & associated academic institutes:

126. Community Model

127. Conclusions – Future Emphasis has been switched to whether: One process should be coupled or uncoupled with respect to another A particular process is deterministic or stochastic Analytical solutions have yet been formulated for a particular process Processes can be scaled across time and space Developing adequate databases on key parameters from field or laboratory measurement Levels of simplification (1D, 2D, 3D) Thus initially while over simple forward conceptual & empirical models were more widely used, lately computational process driven forward models have gained greater acceptance, & collective models may be the new wave