RTM Images from SEAM Data Show Interesting Features

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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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These and many more images are

freely available. Just ask me.

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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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