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2001 Sponsors. Aramco Amerada Hess BP-AMOCO Chevron Conoco Japan Nat. Oil Co. Inst. Mex. Pet. INCO Marathon Phillips Sisimage Texaco Veritas. Salient 2001 Research Achievements. 1. Wave-Beam Migration. Wave- Beam. Phase-Shift. Ray-Beam Kirchhoff. Migration Accuracy vs $$$.

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2001 sponsors
2001 Sponsors
  • Aramco
  • Amerada Hess
  • BP-AMOCO
  • Chevron
  • Conoco
  • Japan Nat. Oil Co.
  • Inst. Mex. Pet.
  • INCO
  • Marathon
  • Phillips
  • Sisimage
  • Texaco
  • Veritas
slide3

Wave-Beam

Phase-Shift

Ray-Beam

Kirchhoff

Migration Accuracy vs $$$

Full-Wave

No Approx.

Multiples

Anti-aliasing

Accuracy

Expense

slide4

Slant Stack

Fresnel Zone

Smear Reflection along Wavepath

Smear Reflection along Wavepath

S

R

Image

Point

slide5

Wavefront FD

Standard FD

0

1.5 km

0 4.5 km

slide6

Cost Ratio of Standard /Wavefront

45

5

Cost Ratio

500 3000

# Gridpts along side

slide7

Model

0

1.5 km

1.5 km/s

2.2 km/s

1.8 km/s

Prestack Migration Image

0

1.5 km

0 4.5 km

slide8

Eikonal Traveltime Field

0

Depth (kft)

3

0

Distance (kft)

5

Wave-Equation Traveltime Field

0

Depth (kft)

3

Distance (kft)

5

0

slide9

Model

0

Depth (km)

3

5

0

Distance (km)

Wave Equation Traveltimes

Kirchhoff

5

Depth (kft)

11

0

5

Distance (km)

0

Distance (km)

5

slide10

Wavefront Reverse Time Migration

1. Order Mag. Cheaper than 3-D RT

2. Fewer Artifacts

3. Optimal Accuracy

Open Questions

1. More Storage

2. Resorting Overhead

3. Large scale tests?

salient 2001 research achievements1
Salient 2001 Research Achievements

1. Wave-Beam Migration

2. Multiple Removal POIC

slide12

Multiple Removal by

Primary-Only Imaging Condition

Hongchuan Sun

slide13

S

R

R

S

Forward Modeling

Primary

Multiple

S

S

R

R

Depth

Depth

Distance

Distance

slide14

S

R

Migration with POIC

S

R

The rays

intersect

at point P, and the traveltime SP +RP =obs

P

Depth

Distance

slide15

The rays

never intersect;

or the traveltime SP +RP =obs

R

S

Multiple Removal

S

R

Depth

P

Distance

slide16

SEG/EAGE 2-D Salt Data

0

Depth (kft)

Model

KM Image

POIC Image

11

0

Depth (kft)

11

0

Depth (kft)

11

Distance (kft)

51

0

slide17

15

15

15

Distance (kft)

Distance (kft)

Distance (kft)

51

51

51

Offsets Used: 0 ~ 14000 ft

Model

5

Depth (kft)

11

KM Image

POIC Image

5

Depth (kft)

11

slide18

KM Image

Model

POIC Image

0

Depth (kft)

11

Distance (kft)

Distance (kft)

Distance (kft)

17

17

17

0

0

0

Offsets Used: 0 ~ 14000 ft

slide19

Offsets Used: 1600 ~ 14000 ft

KM Image

Model

POIC Image

0

Depth (kft)

11

Distance (kft)

Distance (kft)

Distance (kft)

17

17

17

0

0

0

slide20

Conclusions

  • POIC effectively remove surface
  • related multiples
  • POIC performs much better when
  • near-offset data are not used
  • POIC should be applicable to
  • interbed multiple removal
salient 2001 research achievements2
Salient 2001 Research Achievements

1. Wave-Beam Migration

2. Multiple Removal POIC

3. Sparse Fequency Migration

fourier finite difference migration with sparse frequencies

Fourier Finite Difference Migration with Sparse Frequencies

Jianhua Yu

Department of Geology & Geophysics

University of Utah

objective
Objective

 Improve computational efficiency

of wave-equation extrapolation

 Hi-quality Image

frequency domain migration
Frequency Domain Migration

o

70 Fourier Finite Difference Method

1/4 Sparser Frequency Domain Sampling

slide25

Comparison of 3D Impulse Response

X (km)

0

4

0

FD algorithm

Depth (km)

2.4

0

Main energy wider angle FFD

Depth (km)

2.4

slide26

2D Impulse Response

(Velocity contrast, i.e., V/Vmin = 3.0)

X (km)

X (km)

0

4

0

4

0

Depth (km)

2.4

Standard wider angle FFD

Main energy wider angle FFD

slide27

Comparison of FFD and Main Energy FFD Migration

X (km)

0

4

0

FFD algorithm

Depth (km)

2.4

0

Main energy FFD (computational time saving about 38 %)

Depth (km)

2.4

slide28

3D SEG/EAGE Zero Offset Imaging Result

X (km)

X (km)

4

0

4

0

0

0

Depth (km)

2.0

0

Y (km)

8

Y (km)

0

Depth (km)

8

2.0

slide29

Efficient forward extrapolation

Wider angle FFD operator

Less numerical anisotropy in 3D by applying high order implicit FD algorithm

Coding Complexity

Fewer Frequencies Reduced Quality

Strengths:

Weaknesses:

salient 2001 research achievements3
Salient 2001 Research Achievements

1. Wave-Beam Migration

2. Multiple Removal POIC

3. Sparse Fequency Migration

4. AVO Migration Decon

prestack migration decon for avo analysis

Prestack Migration Decon for AVO Analysis

Jianhua Yu

Department of Geology & Geophysics

University of Utah

solution deconvolve the point scatterer response from the migrated image

Lr

d = L r

but

Migration Section = Blured Image of r

T

m = L d

-1

r = ( L L ) m

T

Reflectivity Migrated

Section

Reason:

Solution: Deconvolve the point scatterer response from the migrated image

Migrated

Section

Data

objective of pmd avo
Objective of PMD AVO

Suppress unwanted interference

 Increase estimation accuracy of AVO

parameters

 Enhance resolution of AVO sections

slide34

X(km)

1.0

2.0

0.5

Time (s)

2.0

After PMD

Zoom View of AVO parameter Section Before and After PMD

X(km)

1.0

2.0

0.5

Time (s)

2.0

Before PMD

slide35

Migration CRG Before and After PMD

Trace

Trace

1

60

1

60

0.6

0.6

Time (s)

Time (s)

1.8

1.8

Before PMD

After PMD

slide36

Comparison of Amplitude & Angle Estimation Before and After PMD

1st layer

2rd layer

3rd layer

1

Amplitude

0

0

60

0

Angle

60

0

Angle

60

Angle

+: Before PMD

*: After PMD

Solid line: Theoretical value

summary future
Summary & Future
  • MD reduces artifacts
  • MD improves resolution & AVO
  • MD field data case by Feb.
salient 2001 research achievements4
Salient 2001 Research Achievements

1. Wave-Beam Migration

2. Multiple Removal POIC

3. Sparse Fequency Migration

4. AVO Migration Decon

5. Joint Autocorrelation Imaging

joint imaging using both primary and multiple for ivsp data

Joint Imaging Using Both Primary and Multiple for IVSP Data

Jianhua Yu

Department of Geology & Geophysics

University of Utah

problems for deviated and horizontal well
Problems for Deviated and Horizontal well

No Source Wavelet & Initiation Time

 Not Easy to Get Pilot Signal in

 Hard to Separate Primary and Ghost

Static Shift at Source and Receiver

slide42

Geological Model

X (m)

0

4

0

V1

V2

Depth (m)

V3

V4

V5

V6

3

slide43

Shot Gather and Autocorrelogram

Traces

Traces

1 200

1 200

0

0

Time (s)

Time (s)

4

4

slide44

X (km)

1.6 2.1

Joint Migration

Eliminate Interferences using Joint Imaging in Time Domain

X (km)

1.6 2.1

0

Time (s)

2.2

Standard Migration

slide45

X (km)

1.6

2.1

Joint Imaging

Eliminate Interferences using Joint Imaging in Depth Domain

X (km)

1.6

2.1

0

Depth (km)

2.8

Conventional Imaging

slide46

Kirchhoff and Auto. Migration with Statics Error at Source and Receiver

X (km)

X (km)

1.6

2.0

1.6

2.0

0

Depth (km)

2.8

Kirchhoff joint migrationg

Auto. joint migrationg

summary

Works for deviated and horizontal well

Eliminating static shift errors

Don’t require pilot signal & wavelet initial time

Avoiding separating primary and ghost waves for horizontal well data

SUMMARY

Joint Migration method:

salient 2001 research achievements5
Salient 2001 Research Achievements

1. Wave-Beam Migration

2. Multiple Removal POIC

3. Sparse Fequency Migration

4. AVO Migration Decon

5. Joint Autocorrelation Imaging

6. Xwell Statics & Tomography

slide49

INCO Project Report

M. Zhou

Geology and Geophysics Department

University of Utah

slide50

Objective

Invert velocity & geometry jointly

slide51

2.5

1.0

Velocity (km/sec)

5.0

0.5

0.0

7.5

0.0

250

-250

0.0

30

-250

0.0

250

-30

Vertical Shift (m)

Horizontal shift (m)

Rotation (degree)

500 m

V=5.0km/sec

Normalized Traveltime Residuals vs.

Velocity & Geometry Changes

slide52

Problems

1) Geometry is coupled with velocity

2) Joint inversion is ill-posed

slide53

Km/s

Km/s

5.0

5.0

4.5

4.5

3.0

3.0

2.5

2.5

80

0

80

10

-10

Geometry Error: synthetic example I

b) Standard Inversion with 10 m shot shift

a) Synthetic Model

0

100

Depth (m)

200

c) Joint Inversion for the shot shift

( all shots have the same shift )

d) Joint Inversion + a priori information

for individual shot locations

0

Depth (m)

100

200

80

0

-10

0

80

-10

Offset (m)

Offset (m)

slide54

Km/s

3.2

2.8

2.4

2.0

100

0

80

10

-10

-10

Geometry Error: synthetic example II

a) Synthetic Model

b) Standard Inversion without shot shift

0

100

Depth (m)

200

300

d) Joint Inversion for the shot shift

c) Standard Inversion with +10 m shot shifts

Km/s

0

3.2

100

2.8

Depth (m)

2.4

200

2.0

300

80

0

-10

0

80

-10

Offset (m)

Offset (m)

slide55

Km/s

3.2

2.8

2.4

2.0

100

0

80

10

-10

-10

Geometry Error: synthetic example II

b) Standard Inversion without shot shift

a) Synthetic Model

0

100

Depth (m)

200

300

c) Joint Inversion + a priori information

for the shot shift

d) Joint Inversion + a priori information

for individual shot locations

Km/s

0

3.2

100

2.8

Depth (m)

2.4

200

2.0

300

80

0

-10

0

80

-10

Offset (m)

Offset (m)

slide56

Conclusions

Joint inversion

  • works for simple model
  • needs additional information