SEAM workshop presentation GMRC Intrepid Presentation

Imaging the SEAM I Base of Salt
with Gravity Gradiometer Data
December, 2013
David Hatch, Maria Annecchione: Gedex Inc.
Richard Krahenbuhl: Colorado School of Mines
1
Copyright Gedex Inc. 2013
SEAM 1 Density Model
Incorporates major challenges
of Subsalt Imaging in Tertiary
Basins, with emphasis on
Deepwater Gulf of Mexico
Lots of targets to tackle in the
SEAM data:
• Top of salt structures, rugosity,
overhangs, grotto, mini-basin
• Variable base of salt, deep salt
feeder, mother salt etc
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2
Imaging Base of Salt is a Challenge for Seismic Method
Can gravity/gradiometry data successfully image Base of Salt?
• Quantify resolution and potential error in BoS determination
Simulate airborne survey conditions
• Calculated forward response and incorporate noise
Use reasonable constraints
• Top of salt and background density distribution
Inverted data using Gzz (or Gz)
– Interface inversion (Geosoft GM-SYS 3D™)
– Binary voxel inversion (Colorado School of Mines)
– Geologically Driven Voxel Inversion (Intrepid Geomodeller)
Conduct sensitivity studies on assumptions
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3
SEAM 1 Density Model
Challenges for Gravity/Gradiometry:
• Over-printed sources from various
depths
• Non-uniqueness
• Poor signal-to-noise ratio common
• Depth of burial
• Salt body crosses nil-zone
12960
Manage challenges and extract maximum
information through constraints
Constraints:
• Geologic knowledge
• Borehole logs
• Seismic, MT, CSEM
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4
Salt Contrast Model
Original model
Background model
Response of background
geology is totally removed
Salt density contrast model
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5
Vertical Gravity Gradient Response of the
Salt Contrast Model
Noise-free
Post-filter noise:
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1 Eo/√Hz noise
Low-pass filtered
10/√Hz Eo noise
Low-pass filtered
0.24 Eo RMS
1.15 Eo RMS
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GM-SYS 3D Inversion: Model Setup
Constraints:
• Top of salt
• Vertical density contrast
function
• Active area within salt
boundaries
Starting model: Miocene-Pliocene unconformity surface
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7
Interface Inversion: Line 12960
Base of salt error (m RMS)
Noise free
1 Eo noise
10 Eo noise
424
510
662
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Interface Inversion: Base of Salt
True base of salt
Inverted base of salt
(0 Eo noise)
Inverted base of salt
(1 Eo noise)
Inverted base of salt
(10 Eo noise)
Gzz Misfit
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GMRC Binary Inversion
• Genetic algorithm for gravity data developed by Colorado School of
Mines GMRC
• Solution at each voxel can take only two forms: salt or background
geology
Advantages:
• Sharp contacts, compact, near perfect recovery
• Nil-zone not a problem
• Multiple runs provides statistical confidence in solution
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10
Binary Inversion: Model Setup
• Populate model from top
of salt to bottom of model
with random 1/0’s
• 1=salt, 0=background
• Does flip reduce misfit?
• Repeat 10x with new
regularization parameters
Inverted with same noise
character as gradiometry
tests
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Binary Gz Inversion: Mean of Salt Solutions
Low Noise Inversion
View from Southwest
Light Blue: All 10 iterations indicate salt for that cell
Black : Only 1 iteration indicates salt
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Binary Gz Inversion: Base of Salt
True base of salt
Inverted base of salt
(1 Eo noise equivalent)
Inverted base of salt
(10 Eo noise equivalent)
Base of salt isosurface generated from lowermost cells
with 3 or more iterations indicating salt
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Binary Inversion: Line 12960
Base of salt isosurface generated from lowermost cells
with 3 or more iterations indicating salt
Base of salt error (m RMS)
1 Eo noise
10 Eo noise
666
662
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Geomodeller: Starting Density Model
660
12000
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Geomodeller Inversion
2 million iterations in total showing 1 in every 10,000
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BoS Inversion: Geomodeller vs GM-SYS
Inverted base of salt
(0 Eo noise)
Inverted base of salt
(1 Eo noise)
Inverted base of salt
(20
(10 Eo noise)
Geomodeller
True base of salt
GM-SYS
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Geomodeller: Probability of Salt
660
Final Inversion
12000
660
Probability of
salt
12000
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Geologic Tests: Commonality
What is the similarity of the proposed geologic model relative to starting model?
No geologic tests applied
Using shape ratio to
encourage less smooth
shape relative to original
model
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Geologic Tests: Commonality
No geologic constraints
Using shape ratio to
encourage less smooth
shape relative to original
model
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Sensitivity Testing: Variation in Top of
Salt Assumption
Gzz noise contributed by 25m
RMS variation added to top of
salt surface
No Noise added to ToS
25 m RMS noise
added to ToS
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Base of Salt Workflow
Next Iteration
• Constrain base of salt where known
from seismic interpretation
Update
velocity
model
Seismic
processing
and
interpretation
Gravity
Inversion
Define
Constraints
Inverted base of salt
No constraints
True base of salt
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Geomodeller inverted base of salt
BoS constraints
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Using Seismic Constraints: Iterative
workflow
1 E Noise inversion
1 E Noise inversion
with constraints
Geomodeller inverted base of salt
BoS constraints
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Conclusions and Way Forward
• Base of salt can be successfully imaged using gravity gradiometer data
– All algorithms image long-wavelength component of base of salt to
similar accuracy (RMS errors similar)
• Geomodeller pulled out more detail on deep salt feeder (peak error lower)
– Gzz version of Binary Inversion may produce similar result
– Statistical analysis with Binary/Geomodeller output provides a powerful
tool to communicate ambiguities in model
• Iterative workflow integrating various datasets will produce a progressively
improved image of BoS, confidence and will reduce risk
• A significant error in ToS is required to generate error in BoS
Can conduct sensitivity analysis on other assumptions
Lots of other challenges in the SEAM 1 model!
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24
Imaging the Base of Salt with Gravity
Gradiometer Data
Thank you
December, 2013
David Hatch, Maria Annecchione: Gedex Inc.
Richard Krahenbuhl: Colorado School of Mines
25
Copyright Gedex Inc. 2013