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Evolution of the Northern Gulf of Mexico Through the Cenozoic
A 3D Visualization Tour*

By

Dennis A. Sylvia1, William E. Galloway1, and Ricardo Combellas1

Search and Discovery Article #40093, (2003)

 

*Adaptation of ePoster presentation at AAPG Annual Convention, Salt Lake City, Utah, May, 2003. 

1John A. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin ([email protected]; [email protected])  

Editorial Note: All data proprietary. For permission to use material, contact: Patricia E. Ganey-Curry, UT Institute for Geophysics ([email protected]).  

 

Abstract 

The Gulf Basin Depositional Synthesis project’s (Galloway, et al., 2000) interpretive GIS database has been combined with the published MMS paleodata (planktonic marine markers) and reconstructed paleoshorelines to produce a suite of 2-D and 3-D images that relate major depocenter evolution to the paleostructure and paleobathymetry of the northern Gulf of Mexico (GOM). Paleobathymetric Previous HitsurfacesNext Hit were constructed for thirteen time steps during the Cenozoic. The reconstructions illustrate how 3-D visualization can be used to assess the effects that eustatic and continental climate change, and tectonics  have on the sedimentation history of the GOM basin. Bathymetric Previous HitsurfacesNext Hit were modeled for each of the major Oligocene and younger depositional episodes. Doppler maps that illustrate depositional pattern  change also were constructed. Three-dimensional visualization takes advantage of the natural human ability to see patterns in pictures and help uncover hidden trends in the data. The constructs can be navigated in 3-D space and time to better understand the depositional history and focus the petroleum explorationist’s attention on those geographic areas and stratigraphic intervals with the greatest reservoir potential.

 

 

uAbstract

uConstruction

u2D paleobathymetric Previous HitsurfacesNext Hit

u3D paleobathymetric Previous HitsurfacesNext Hit

uDerivative imagery

  tDoppler maps

  tInterpretation

uFlyby

uReferences

uAcknowledgments

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uConstruction

u2D paleobathymetric Previous HitsurfacesNext Hit

u3D paleobathymetric Previous HitsurfacesNext Hit

uDerivative imagery

  tDoppler maps

  tInterpretation

uFlyby

uReferences

uAcknowledgments

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uConstruction

u2D paleobathymetric Previous HitsurfacesNext Hit

u3D paleobathymetric Previous HitsurfacesNext Hit

uDerivative imagery

  tDoppler maps

  tInterpretation

uFlyby

uReferences

uAcknowledgments

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uConstruction

u2D paleobathymetric Previous HitsurfacesNext Hit

u3D paleobathymetric Previous HitsurfacesNext Hit

uDerivative imagery

  tDoppler maps

  tInterpretation

uFlyby

uReferences

uAcknowledgments

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uConstruction

u2D paleobathymetric Previous HitsurfacesNext Hit

u3D paleobathymetric Previous HitsurfacesNext Hit

uDerivative imagery

  tDoppler maps

  tInterpretation

uFlyby

uReferences

uAcknowledgments

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uConstruction

u2D paleobathymetric Previous HitsurfacesNext Hit

u3D paleobathymetric Previous HitsurfacesNext Hit

uDerivative imagery

  tDoppler maps

  tInterpretation

uFlyby

uReferences

uAcknowledgments

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uConstruction

u2D paleobathymetric Previous HitsurfacesNext Hit

u3D paleobathymetric Previous HitsurfacesNext Hit

uDerivative imagery

  tDoppler maps

  tInterpretation

uFlyby

uReferences

uAcknowledgments

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uConstruction

u2D paleobathymetric Previous HitsurfacesNext Hit

u3D paleobathymetric Previous HitsurfacesNext Hit

uDerivative imagery

  tDoppler maps

  tInterpretation

uFlyby

uReferences

uAcknowledgments

Construction  (Figures 1, 2, 3, and 4)

Figure 1. Simplified process flow chart for paleobathymetric grid construction.

 

Figure 2. MMS marine environment classification (after Tipsword et al., 1966).

 

 

Figure 3. 3-D diagram of surface, illustrating the utilization of Surfer8 mapping program, along with the Kriging method of interpolation and a low-pass Gaussian filter.

 

Figure 4. Sample map, utilizing Surfer mapping program, with comparison of version 3x, and version 1x, to show the Previous HitsmoothingNext Hit effect of low-pass filter.

 

 

Click to view sequence of versions 1x and 3x for comparison of Previous HitsmoothingNext Hit effect. 

 

A summary of the paleobathymetric construction is shown in Figure 1.

 

Primary Input=MMS Paleodata Set

Selection of GBDS depisode paleo markers

High-grade

DEFAT--the listed paleo-bathymetry is qualified as definite.

Ecozone interpretation (Figure 2)

 

Grid Construction

High-graded MMS well data

~700 data points per surface (average)

            Pliocene best constrained (~1200 per surface average)

Paleoshoreline location

                        Shoreline at maximum transgression (SMT)

“Dummy” data points (e.g., abyssal plain, Florida scarp, paleoshelf margin)

Force a logical grid into areas lacking well control.

 

Gridding (Figure 3)

Surfer8

Kriging (best expresses trends)

                        Point (honors data @ node)

Ordinary (no drift)

Grid (22-30N, 84-97W; 3.5 mi2cell)

Grid filter

Low-pass Gaussian

                                    Previous HitSmoothingNext Hit

Remove high-frequency artifacts

 

Figure 4 is a paleobathymetric map generated by use of Surfer Grids from processing of high-graded MMS data. Grids files are converted to text files for export to ArcView.

 

2D Paleobathymetry  (Figures 5 and 6)

Figure 5. Map, illustrating 2D paleobathymetry of one of 13 Cenozoic Previous HitsurfacesNext Hit constructed in the GBDS Project.

 

 

Figure 6. Miocene depositional episode, illustrating 2D paleobathymetry. (SMT=shoreline at maximum transgression.) 

 

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Thirteen paleobathymetry Previous HitsurfacesNext Hit were constructed for Oligocene through Pleistocene depositional episodes. Figure 5 portrays the surface for one of those Previous HitsurfacesNext Hit; Figure 6 is representation of a Miocene depositional episode.   

 

Cautions in paleobathymetry interpretation

1. Data

Highly erratic distribution

2. Methodology

Gridding algorithm, spacing, filtration

3.Interpretation

Displaced environments

Displaced fauna

 

3D Paleobathymetry (Figures 7, 8, and 9

Figure 7. 3D Paleobathymetry for a Cenozoic episode in the Northern Gulf of Mexico.

 

 

Figure 8. Paleobathymetry folio example: Miocene episode (3D—left; 2D—right).

 

 

Figure 9. Paleobathymetry folio example: Pliocene episode (3D—left; 2D—right). 

 

Click to view sequence of Miocene and Pliocene 3D paleobathymetry.

 

Click to view sequence of Miocene and Pliocene 2D paleobathymetry.

 

GBDS paleobathymetry project

            13 image files

            Sand distribution overlay

3D Analyst extension

            View grid data in 3D

             Manipulate Previous HitsurfacesTop

            Add GBDS thematic overlays

 

Derivative Imagery 

Doppler Maps (Figures 10 and 11

 

Figure 10. An Intra Miocene Doppler map derived as follows: Intra Miocene B - Intra-Miocene A = apparent paleowater depth change.

 

Click here to view the above maps in sequence.

 

Figure 11. The Intra Miocene Doppler map of Figure 10 with the addition of GBDS geological overlays. Fluvial axes (C=Colorado; B=Brazos, western M=Mississippi; T=Tangipahoa; eastern M=Mobile). 

 

 

Gridded data allow application of Map Algebra, the quantitative manipulation of spatially defined variables in order to create derivative maps showing change in apparent water depth. In the generation of Paleobathymetric Difference (“Doppler”) Maps, GBDS grid data (*.txt files) are used to perform grid algebra:

ArcView Spatial Analyst Extension

Surfer8

Younger minus older paleobathymetric surface depth (e.g., Middle Miocene –

Basal Upper Miocene)

 

The resultant Doppler map outlines areas of apparent shoaling and apparent deepening. 

GBDS geological overlays include:

S.M.T. (shoreline during maximum transgression)

Shelf margin

Salt domains

Faults

Sand depocenters

Fluvial axes

 

Interpretation of Apparent Paleobathymetry Change (Figure 12) 

Figure 12. Intra-Pliocene Doppler Map derived in the same manner as that in Figure 11. 1=Starved abyssal plain; 2=shelf/slope retrogradation, down slope transport of sediments and faunas; 3=Minibasin filling in depo-axis. Fluvial axes: B=Brazos; R=Red; M=Mississippi; T= Tangipahoa.

 

1. Actual shoaling or deepening

    Depositional

    Tectonic

2. Environmental displacement

    Shifting fluvial/deltaic depocenters

3. Resedimentation

   Gravity mass transport

   Slope failure

 

Finale!

The Middle Miocene Gulf of Mexico Flyby 

Animated Middle Miocene 3D paleobathmetry, Gulf of Mexico.

 

References

Galloway. William C., Richard T. Buffler, Patricia Ganey-Curry, 2000, Gulf of Mexico Basin Depositional Synthesis: Mapping Neogene Sediment Dispersal Patterns of the Northern Gulf Continental Margin, in Integration of Geologic Models for Understanding Risk in the Gulf of Mexico: AAPG Discovery Series No. 1 (on CD-ROM). 

Tipsword, H.L., F.M. Setzer, Fred L. Smith, Jr. 1966, Interpretation of Depositional Environment in Gulf Coast Petroleum Exploration from Paleoecology and Related Stratigraphy: GCAGS Transactions, v. 16, p. 119-130.

 

Acknowledgments 

Data courtesy of sponsors of The University of Texas at Austin Gulf Basin Depositional Synthesis. They are: EnCana, ENI Petroleum, Amerada Hess, Anadarko, ConocoPhillips,

Exxon Mobil, JNOC, Kerr-McGee, Marathon, Nexen, Norsk Hydro, ChevronTexaco, Total, Unocal, and Woodside Energy.

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