Least Squares Migration of JAPEX Data and PEMEX Data

Least Squares Migration ofLeast Squares Migration of JAPEX JAPEX Data and PEMEX DataData and PEMEX Data

Naoshi AokiNaoshi Aoki

OutlineOutline

1. Theory2. LSM resiliency to artifacts from poor acquisition

geometry3. LSM image sensitivity to wavelet estimation errors4. Multi-scale LSM applied to poststack JAPEX data5. Target-oriented LSM applied to poststack PEMEX

data6. Conclusions

TheoryTheoryPoststack 2D Syncline Model

Ricker wavelet (15 Hz)

Kirchhoff Migration

LSM

Forward modeling

Inversion

Steepest descent algorithm

OutlineOutline



data6. Conclusions

LSM Resiliency to Artifacts fromLSM Resiliency to Artifacts from Poor Acquisition Geometry Poor Acquisition Geometry

3D U Model Model Description• Model size:

– 1.8 x 1.8 x 1.8 km • U shape reflectivity anomaly

• Cross-spread geometry– Source : 16 shots, 100 m int.– Receiver : 16 receivers , 100 m int.

Depth (m) Reflectivity

250 1

500 -1

750 1

1000 -1

1250 1

● Source● Receiver

U model is designed for testing Prestack 3D LSM with arbitrary 3D survey geometry.

CSG0

5

TW

T (

s)

0 1.8X (m)

Kirchhoff Migration vs. LSMKirchhoff Migration vs. LSMApplied to the 3D Applied to the 3D UU Model Model

(c) Z = 250 m (e) Z = 750 m (g) Z=1250m(a) Actual Reflectivity

Kirchhoff Migration Images

(b) Test geometry(d) Z=250m

LSM Images after 30 Iterations(f) Z=750m (h) Z=1250m

● Source● Receiver

LSM Resiliency to ArtifactsLSM Resiliency to Artifacts

• Test Summary– LSM showed a significant resiliency to artifacts

from poor acquisition geometry.

– LSM has an ability to reduce data acquisition expense.

OutlineOutline



data6. Conclusions

LSM Image Sensitivity to LSM Image Sensitivity to Wavelet Estimation ErrorsWavelet Estimation Errors

• LSM algorithm requires a source wavelet.

• I tested LSM image sensitivity to wavelet estimation errors in the following 2 cases :1. LSM with correct wavelet,2. LSM with a Ricker wavelet (15 Hz).

LSM Image with Correct Source WaveletLSM Image with Correct Source Wavelet

0

2D

epth

(km

)0 2

X (km)

0

2

TW

T (

s)

0 2X (m)

Data LSM ImageActual Model

LSM Image with a Ricker Wavelet (15 Hz)LSM Image with a Ricker Wavelet (15 Hz)

Actual Model 0

2D

epth

(km

)0 2

X (km)

LSM ImageKirchhoff Migration

Image

LSM Image Sensitivity to Errors in the Source LSM Image Sensitivity to Errors in the Source WaveletWavelet

• Test Summary– An accurate estimate of the source wavelet is

important to obtain an accurate LSM image.

– However, LSM images are usually better than the standard migration image.

2D Poststack Data from Japan Sea2D Poststack Data from Japan SeaJAPEX 2D SSP marine data description:Acquired in 1974, Dominant frequency of 15 Hz.

0

5

TW

T (

s)

0 20X (km)

Multi-scale LSMMulti-scale LSM

• Starts by estimating a low wavenumber reflectivity model in order to avoid getting trapped in a local minimum.

• Band-pass filters, where the frequency bandwidth increases with the number of iterations, were iteratively applied to the input data.

Multi-scale LSM applied to JAPEX DataMulti-scale LSM applied to JAPEX Data

Multi-scale (MS) LSM vs. Standard LSM Convergence Curves

20 　Hz

25

3032

34 36 3840

MS LSM Image

0.7

1.9

Dep

th (

km)

2.4 4.9X (km)

Standard LSM Image

0.7

1.92.4 4.9

X (km)

X10 5

3.0

0.5R

esid

ual

0 40Iteration

Multi-scale LSM

Standard LSM

LSM vs. Kirchhoff MigrationLSM vs. Kirchhoff Migration

LSM Image0.7

1.9

Dep

th (

km)

2.4 4.9X (km)

0.7

1.9

Dep

th (

km)

2.4 4.9X (km)

Kirchhoff Migration Image

Resolution comparisonResolution comparison

LSM vs. Standard Migration Magnitude Spectrum of Migration Image

1

0

Mag

nitu

de

0 0.04Wavenumber (1/m)

0.7

1.2

Dep

th (

km)

3.7 4.3X (km)

0.7

1.2

Dep

th (

km)

3.7 4.3X (km)

LSM Image Kirchhoff Migration Image

OutlineOutline



data6. Conclusions

PEMEX 3D OBC Data from GOMPEMEX 3D OBC Data from GOM

0

4

TW

T (

s)

1 1001XL Number

IL3100 Stacked Section

Acquired in1990s.Since acquisition geometry is sparse, noise is dominant in the shallow part.

LSM Image0.7

1.9

Dep

th (

m)

2.4 4.9X (m)

LSM vs. Kirchhoff MigrationLSM vs. Kirchhoff Migration from PEMEX Data IL3100 from PEMEX Data IL3100

0.7

1.9

Dep

th (

m)

2.4 4.9X (m)


Resolution comparisonResolution comparison

LSM vs. Standard Migration Magnitude Spectrum of Migration Image

1

0

Ma

gn

itude

0 0.04Wavenumber (1/m)

LSM Image

1

2.2

Dep

th (

km)

551 650XL Number 551 650

XL Number


LSM

Kirchhoff Migration

TO LSM Applied for 3D DataTO LSM Applied for 3D Data

Preliminary Result of LSM Image after 4 iterations


ConclusionsConclusions• Numerical results show:

• LSM has a significant resilience to artifacts from poor acquisition geometries .

• an accurate wavelet estimate provides an accurate LSM image.

• Results from JAPEX and PEMEX data show:– faster convergence rate is provided by a multi-scale migration

scheme.– 2D LSM is a practical means for improving quality image.– Encouraging results for TO LSM obtained from the 3D data

subset.

Future workFuture work

• GOAL: 3D LSM in less than 10 iterations.– Further improvement in efficiency will be

investigated.

AcknowledgementsAcknowledgements

• We thank PEMEX Exploration and Production for permission to use and publish its Gulf of Mexico data.

• I would like to thank JOGMEC and JAPEX for supporting my study at the University of Utah.

• We also thank the UTAM consortium members for supporting my work.

Least Squares Migration of JAPEX Data and PEMEX Data

Documents

Transcript of Least Squares Migration of JAPEX Data and PEMEX Data