RTM Images from SEAM Data Show Interesting Features
RTM images from SEAM data
show interesting features
Christof Stork, Mark Willis, Stefan Compton
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Comparing Different 3D Models
old SEG-Salt (1996) SEAM (2010)
Size: 90 Km 2 1400 Km 2 16x
Depth: 3,700 m 16,000 4.3x
Shots: 5,000 62,000 12x
Receivers: 8×68 668×668 800x
Frequency: 15Hz 30Hz 16x
Data size: 5GB 220TB 50,000x
Model complexity: 1.0 ~1000
Compute: 1.0 50,000
Cost: 1.0 0.2
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Old SEG Salt
model (1996)
450,000 traces,
15Hz
3000 m
SEAM model
(2010)
1,000,000,000
traces, 30Hz
13,000 m
16,000 m
40,000 m
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SEAM Salt model, 35km x 40km x 15km
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Salt body, alternative view #1
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2 classic datasets:
1. Sparse shots (Full azimuth)
– 2793 shots, 600m x 600m spacing
– Receivers per shot: 661 x 661= 436,921; 30m x 30m spacing;
max offsets: 9,900m x 9,900m
– Total number of traces: 1,024,597,537
2. WAZ NS Interleaf with surface multiples
– 11,172 shots, 600m x 150m spacing, (49*228 shots)
– Receivers per shot: 70 x 268= 18,760; 120m x 30m spacing;
max offsets: 4,140m x 8,430 m
– Total number of traces: 209,586,720
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1 non-classic datasets:
• Very sparse shot
– Classic sparse shots decimated 2x in X & Y
– 1200x1200m spacing instead of 600x600m
– 690 shots instead of 2793
– Total number of traces: 301,475,490
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Position of following images:
Y=31,200
Y=21,180
Y=11,190
X=15,990
X=20,010
Z=8,500
Z=14,400
Model size: 40km x 35km x 15km
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Y= 21,180m; Impedance
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 21,180m; Sparse shots, no multiples
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 21,180m; Very sparse shots, no multiples
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 21,180m; Sparse shots, with multiples
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 21,180m; Very sparse shots, with multiples
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 21,180m; WAZ, with multiples, no stack
enhancement
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 21,180m; WAZ, with multiples, with stack
enhancement
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 21,180m; Very sparse shots, with multiples, no
stack enhancement
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 21,180m; Very sparse shots, with multiples, with
stack enhancement
X: 0 10,000 20,000 30,000
15,990 20,010
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Z= 8,500; Impedance
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
31,200
21,180
11,190
15,990 20,010
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Z= 8,500; Sparse shots, no multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
31,200
21,180
11,190
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15,990 20,010
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Z= 8,500; Very sparse shots, no multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
31,200
21,180
11,190
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15,990 20,010
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Z= 8,500; Sparse shots, with multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
31,200
21,180
11,190
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15,990 20,010
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Z= 8,500; Very sparse shots, with multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
31,200
21,180
11,190
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15,990 20,010
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Z= 8,500; FAZ Sparse shots, with multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
31,200
21,180
11,190
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15,990 20,010
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Z= 8,500; WAZ Interleaf, with multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
31,200
21,180
11,190
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15,990 20,010
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Z= 8,500; Very sparse shots, with multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
31,200
21,180
11,190
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15,990 20,010
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X= 15,990 m; Impedance
Y: 0 10,000 20,000 30,000 40,000
11,190 21,180 31,200
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X= 15,990 m; Sparse shots, no multiples
Y: 0 10,000 20,000 30,000 40,000
11,190 21,180 31,200
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X= 15,990 m; Sparse shots, with multiples
Y: 0 10,000 20,000 30,000 40,000
11,190 21,180 31,200
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X= 15,990 m; WAZ interleaf, with multiples
Y: 0 10,000 20,000 30,000 40,000
11,190 21,180 31,200
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X= 15,990 m; Very sparse shots, with multiples
Y: 0 10,000 20,000 30,000 40,000
11,190 21,180 31,200
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Z= 14,400; Sparse shots, with multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
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Z= 14,400; WAZ Interleaf, with multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
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Z= 14,400; Very sparse shots, with multiples
Y:
0 10,000 20,000 30,000 40,000
X: 0 10,000 20,000 30,000
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Y= 31,200m; Original Velocity
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 31,200m; Sediment smoothed Velocity
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 31,200m; Bad Velocity #1
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 31,200m; Bad Velocity #2
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 31,200m; RTM with Original Velocity
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 31,200m; RTM smoothed sediments
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 31,200m; RTM with Bad Velocity #1
X: 0 10,000 20,000 30,000
15,990 20,010
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Y= 31,200m; RTM with Bad Velocity #2
X: 0 10,000 20,000 30,000
15,990 20,010
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Concluding Remarks:
• Migration with the correct velocity model
produces very nice image
– Isotropic acoustic data has limited realism
• Data still very, very useful
– Algorithm, Acquisition quality analysis
– Importance of noise in analysis
• Multiples are not very organized, for this model
– Produce random noise
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Project acknowledgements:
• Biondo Biondi for initial spark
• Richard Day, Joe Stefani for a wonderful model
• SEG SEAM team (Mike Fehler, Peter Pangman
Jan Madole)
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