Transcript Interactive Web Based Teaching Tools for Extending the

Sedimentological
Processes Modeling
Christopher G. St.C. Kendall
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 longterm basin wide
Holocene data particularly carbonates
Sedimentary simulation movies & modeling.
Interconnected modules of numerical process simulations
of sedimentary basins evolution - the future
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
Types of Simulations
Sedimentary modeling:
Carbonates vs. clastics
Stochastic vs. deterministic
Fuzzy vs. empirical
Small vs large oceanic basins
Traditional Use of Sedimentary
Simulations
Sedimentary process models from outcrops, well
log & seismic cross sections used to:
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.
Sedimentological Processes
Modeling
2D & 3D sedimentary simulations, relative
sea level, physical processes, &
sedimentation & erosion:
Inverse conceptual simulation models
Numerical forward modeling
advanced.
Short-term, high-resolution local
events vs a long-term regional events
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
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.
Geometric
Model
Ross et al., 1995
Jervey, 1988
Perlmutter et al.,
1998
Chris Paola
Chris Paola
Geometric Models
“Jurassic Tank”
Chris Paola, 2002.
Geometric Model
Eberli, et al, 1994
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
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
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
Further carbonate modelers!
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
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
Data Sources
Historically sedimentary modeling
derived from real data
Seismic
Wells.
Outcrop
But less from:
Holocene
Seismic
Wells
Outcrops
Outcrops
King 1954
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”
Regional
Drainage
Into Basin
Restricted
Entrance
To Sea
Isolated linear
Belt of interior
drainage
Arid Tropics Air System
Wide Envelope of surrounding continents
Arid Climate
United Arab Emirate Coast
Barrier
Island
Coast
Coastal
Evaporite
System
Reef
Platform
Aeolian System
United Arab
Tidal
EmirateDeltas
Coast
Arid Climate
Coastal
Evaporite
System
Reef &
Lagoon
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.
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
Clastic Simulation
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
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
Chronostratigraphic Chart
P-10
HST/LST
TST
Venezuelan
Example
LST : Avg. Width 6.6 km
Avg SS H 35.0 m
Avg. W:T 220:1
# of Valleys 9
Valley Type (4) V-shaped
(3) Elongate-Straight
(2) Elongate-Sl.-Sinuous
HST:
Eroded-or not present
TST: Barrier Island sands
Avg. Width 1.75
Avg. SS H
8.84 m
Avg. W:T 143:1
Distance between sands 2.48 km
Number of Sands 10
LST Chart
Example 1: Well Log Correlation
Example 1: Well Log Correlation
Example 1: Well Log Correlation
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
Venezuelan - Example
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
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
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)
b)
c)
3D perspective
Fluid flow
Role of diagenesis
These models will probably involve
combinations of fuzzy logic, empirical,
stochastic & deterministic algorithms
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
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
Future Directions
Recently emphasis within the USA by US
Government agencies & associated
academic institutes:
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.html).
Community Model
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