Download - Digital Mapping at Corbula Gulch outcrop, Utah

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Page 1: Digital Mapping at Corbula Gulch outcrop, Utah

Digital Mapping at Corbula Gulch outcrop, Utah

• Locate 2D and 3D GPR surveys, coreholes, measured stratigraphic sections by RTK.

• Map the beds along the cliff faces by laser rangefinders.

• Interpolate the 3D geometry of the sedimentary bodies.

• Build the 3D geological model for visualization, analysis and interpretation.

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Map of San Rafael Swell

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EW

S N

Photomosaic of Cliff face

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Laser Surveyed Points

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2D Topographic Map

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3D Perspective View of Survey data Layout

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3D Perspective View of Survey data Layout

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GPR Cubes and Profiles (from Corbeanu, 2000)

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3D Perspective View of Survey data Layout

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The high-resolution topographic model at the southeast corner of the outcrop

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CD 1 Top Surface

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CD 1 Bottom Surface

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Photomosaic of Cliff face

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Thickness Contour Map of CD 1

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3D Model of Major Bounding Surfaces

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3D Model of Major Bounding Surfaces

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Conclusions

• Utilize GPS and laser sketching to locate the GPR survey lines, stratigraphic sections, coreholes, and sedimentary bounding surfaces.

• These digital data enable us to quantitatively analyze the key surfaces.

• A three-dimensional geological model was interpolated with these digital data and 4 coreholes.

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Conclusions (continuing)

• The results of this project demonstrates the usefulness of digital surface mapping and power of integration of digital subsurface information.

• The final GPR analysis and interpretation can utilize these interpolated surface fits.

• The final three-dimensional model will incorporate all of subsurface and surface geology.

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3-D GPR RESOLUTION

Seismic vertical resolution = 15 m

GPR vertical resolution = 0.5 m

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FERRON SANDSTONE LOCATION

• Sequence stratigraphic framework well established

• Reservoir analog for oil fields in Gulf of Mexico and North Sea

• Good exposure of the vertical cliff faces

• Flat mesas and an arid environment are ideal for GPR surveying

Delta shoreline

CoyoteBasin

CorbulaGulch

X

Y

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GPR METHOD

• High resolution electro-magnetic method• Similar to seismic methods• Characterizes a medium by its electrical permittivity, k and electrical conductivity, .• Decreasing velocity with depth

• Depth of penetration proportional to the loss tangent

tan() = /0k, where :0 = permittivity in a vacuum = angular frequency

v = c/ k, where c is the velocity of light in a vacuum

System console

Optic fiberAntennas

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CORBULA GULCH BASEMAP

• reservoir simulator voxel scale: 3-D GPR cubes (51m x 28m and 31m x 27)

• reservoir grid cell scale(100mx100m)

• inter-well scale(550mx350m)

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CORBULA GULCH FACIES MAP

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INTEGRATING OUTCROP AND GPR DATA

• Good correlation of lithology and permeability.

• Good correlation of lithology and velocity.

• GPR reflections are produced at the surface between layers with contrast in electrical properties.

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3-D GPR INTERPRETATION

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3-D GPR INTERPRETATION

• High amplitude, continuous, oblique GPR reflections.

• Tuning effects at thin layers interfaces resolved with GPR attributes.

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INCLINED SURFACES MAPS

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CONCLUSION

• To effectively integrate geologic and GPR data, 3-D migration of the GPR data from the time domain into the depth domain is essential.

• Correlating outcrop, boreholes and GPR data allows relationships between vertical facies successions through different architectural elements and their lateral geometry to be directly interpreted in 3-D.

• The channel deposits at Coyote Basin are interpreted as scour and fill channel deposits of distributary channels on the upper delta plain.

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CONCLUSION

• Reservoir heterogeneities are estimated by modeling 3-D experimental variograms of GPR amplitudes and are smaller (4-6 m) in scour and fill channel deposits and longer (10-15 m) in marine influenced point bar deposits.

• 3-D permeability and mudstone distributions can be predicted from empirical relationships between physical properties and GPR attributes.

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Objectives

• 3D integration of data sets, including GPR surfaces, borehole and cliff face data.

• Building 3D model for visualization, analysis and interpretation.

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Data Source

• GPR Survey

• Cliff Face Laser Mapping

• Stratigraphic Measured Sections

• Well cores

-All Integrated by GPS

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EW

S N

Photomosaics of Cliff Faces

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Laser Surveyed Points

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2D Topographic Map

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3D Perspective View of Survey Data Layout

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CD 1 Top Surface

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CD 1 Bottom Surface

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Thickness Contour Map of CD 1

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3D Model of Major Bounding Surfaces

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3D Model of Major Bounding Surfaces

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GPR Cubes and Profiles of Depth Sections

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Rendering Procedures

• Curve fitting of the data

• Generating initial surfaces

• Installing constraints to honor geologic interpretations.

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Initial surface

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Honor geologic interpretation

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Incline 0 border at Surface C

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Incline 4 with laser data

Laser data

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Major Bounding Surfaces-looking northeast

Z: X3

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Major Bounding Surfaces-looking northwest

Z: X3

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Location of the solid model

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Volume of bounding surfaces

Topography

CIncl 0

Incl 1

Unit 1 Upper unit

Incl 7Incl 6 Incl 5

Incl 4

Incl 3

Incl 2

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Volume of bounding surfaces

Surface C

Unit 1Upper unit

Incl 0

Incl 1

Incl 2

Incl 3Incl 4Incl 5Incl 6

Incl 7

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Volume of bounding surfaces

Incl

2

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Lessons Learned

• Laser Mapping provides an efficient way to map the surface geometry, but …

• Photorealistic model preferable because interpretation change and different interfaces interpreted from photos

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Mismatch

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Photorealistic Outcrop at Dallas Post Office

• Accuracy of a few centimeters• Photo registration about 0.7 – 2.7

pixels.• Bring outcrop back to office

photorealistically in three-dimensions• Directly taking measurement on photos

in three-dimensions• Virtual field trip