Progress Report on Separation of Multisource Data
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Transcript of Progress Report on Separation of Multisource Data
Progress Report on Separation of Progress Report on Separation of Multisource Data Multisource Data
Xin WangXin Wang
February 5, 2009February 5, 2009
OutlineOutline
• MotivationMotivation::
• Numerical Results Numerical Results
• MethodologyMethodology
• ConclusionsConclusions
Separating multisource data in order to get single shot gathersSeparating multisource data in order to get single shot gathers
Applying a combination of several local adaptive filtersApplying a combination of several local adaptive filters
Synthetic tests of 2, 5 and 10 sources on 2D SEG/EAGE modelSynthetic tests of 2, 5 and 10 sources on 2D SEG/EAGE model
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MotivationMotivationGoal:Goal:Shoot more times in a certain time to Shoot more times in a certain time to
improve the efficiency of seismic improve the efficiency of seismic
survey, especially in wide azimuth survey, especially in wide azimuth
angles surveys. angles surveys.
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Constraint:Constraint:Avoid time overlaps in seismic records Avoid time overlaps in seismic records
from different sources.from different sources.
CSG without time overlap0
81 129Trace #ChallengeChallenge::
Can we separate multisource Can we separate multisource
data with time overlaps to get data with time overlaps to get
single shot gathers?single shot gathers?
Multisource CSG with time overlap
0Single CSG 1 Single CSG 2
81 129Trace # 1 129Trace # 1 129Trace #
0
8
0
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OutlineOutline
• MotivationMotivation::
• Numerical Results Numerical Results
• MethodologyMethodology
• ConclusionsConclusions
Separation multisource data to get single shot gathersSeparation multisource data to get single shot gathers
Applying a combination of several local adaptive filtersApplying a combination of several local adaptive filters
Synthetic tests of 2, 5 and 10 sources on 2D SEG/EAGE modelSynthetic tests of 2, 5 and 10 sources on 2D SEG/EAGE model
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Random time shooting with known time delay (Chevron, 2008).
MethodologyMethodology
0481 Trace #
Multisource CSG 1
129
0
81 Trace #
Multisource CSG 2
129
0
Resort data from CSGs to CRGs.
0
1 Trace #
Multisource CSG
129
0
81 Trace #
Multisource CRG
1298
Apply a combination of slant stacking, median filtering, threshold mute filtering and adaptive subtraction matching filtering.
Trace #1 9
0
1Trace #1 9
0
1
Original dataApplying slant stacking
and median filtering
Trace #1 9
0
1Trace #1 9
0
1
Original dataApplying threshold
mute filterOriginal data
Slant stacking and median filtering
Local adaptive subtraction matching
filtering 0
1
Trace #1 10
1 Trace #
Filtered CRG
45
Filtered CSG
451 Trace #
0
8
0
8Resort filtered data from CRGs to CSGs.
WorkflowWorkflow
Multisource data
Resort CSG to CRG with known time shift
Apply slant stacking and median filter
Apply threshold mute filter
Apply local adaptive subtraction matching
filter
Apply slant stacking and median filter
Near offset: Far offset:
Apply local adaptive subtraction matching
filter
Resort CRG to CSG
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Resort CSG to CRG with known time shift
OutlineOutline
• MotivationMotivation::
• Numerical Results Numerical Results
• MethodologyMethodology
• ConclusionsConclusions
Separation multisource data to get single shot gathersSeparation multisource data to get single shot gathers
Applying a combination of several local adaptive filtersApplying a combination of several local adaptive filters
Synthetic tests of 2, 5 and 10 sources on 2D SEG/EAGE modelSynthetic tests of 2, 5 and 10 sources on 2D SEG/EAGE model
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Numerical ResultsNumerical Results
Model Size: 5.9 (km) * 1.4 (km)
Receiver number: 129
Range of random shooting time : 0~4s
SEG/EAGE model
5.9X (km)01.4
0
2 sources number of shots: 120, shot interval: 27.4 m, multisource interval: 2600 m
5 sources number of shots : 45, shot interval: 27.4 m, multisource interval: 1152 m
10 sources number of shots : 65, shot interval: 9.14 m, multisource interval: 585 m
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Multisource CSG Multisource CRG
1 Trace # 129
0
81 Trace # 120
0
8
1 Trace # 129
0
81 Trace # 120
0
8
Filtered CRGFiltered CSG
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Numerical ResultsNumerical Results2 simultaneous sources2 simultaneous sources
Numerical ResultsNumerical Results2 simultaneous sources2 simultaneous sources
Multisource CRG Filtered CRG
1 Trace # 120
0
81 Trace # 120
0
8
1 Trace # 120
0
81 Trace # 120
0
8
Filtered CRGMultisource CRG
Near offset traces
Far offset traces
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Numerical ResultsNumerical Results5 simultaneous sources5 simultaneous sources
Multisource CRG Filtered CRG
1 Trace # 45
0
81 Trace # 45
0
8
1 Trace # 45
0
81 Trace # 45
0
8
Filtered CRGMultisource CRG
Near offset traces
Far offset traces
10
Numerical ResultsNumerical Results5 simultaneous sources5 simultaneous sources
1 Trace # 129
0
8
Multisource CSG
1 Trace # 129
0
8
Filtered CSG
1 Trace # 129
0
8
Actual CSG
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Numerical ResultsNumerical Results5 simultaneous sources5 simultaneous sourcesKirchhoff Migration Image Kirchhoff Migration Image
KM image of simultaneous data
5,9X (km)01.4
0
KM image of filtered data
5.9X (km)0
0
KM image of actual data
5.9X (km)0
0
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1.4
Numerical ResultsNumerical Results5 simultaneous sources5 simultaneous sourcesKirchhoff migration image only with far offset dataKirchhoff migration image only with far offset data
KM of far offset multisource data
5.9X (km)01.4
0
KM of far offsetfiltered data
5.9X (km)01.4
0
KM of far offset actual data
5.9X (km)01.4
0
13
5.9X (km)01.4
0
40 Receivers , 1.82 km45 shots, 1.23 km 45 shots, 1.23 km40 Receivers , 1.82 km
Numerical ResultsNumerical Results10 simultaneous sources10 simultaneous sources
Near offset traces:Near offset traces:
1 Trace # 65
0
8
Multisource CRG
1 Trace # 658
Filtered CRG
1 Trace # 65
0
8
Actual CRG 0
14
Numerical ResultsNumerical Results10 simultaneous sources10 simultaneous sources
Far offset traces:Far offset traces:
1 Trace # 65
0
8
Multisource CRG
1 Trace # 658
Applying threshold mute filter
1 Trace # 65
0
8
Applying 10 iterations of median filter and adaptive
subtraction filter0
Applying slant stacking and median filter
Applying adaptive subtraction filter
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OutlineOutline
• MotivationMotivation::
• Numerical Results Numerical Results
• MethodologyMethodology
• ConclusionsConclusions
Separation multisource data to get single shot gathersSeparation multisource data to get single shot gathers
Applying a combination of several local adaptive filtersApplying a combination of several local adaptive filters
Synthetic tests of 2, 5 and 10 sources on 2D SEG/EAGE modelSynthetic tests of 2, 5 and 10 sources on 2D SEG/EAGE model
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ConclusionsConclusions
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• Separation of multisource data can greatly improve the efficiency of seismic surveys, especially with wide azimuth angle.
• By applying several filters, we can separate 2 and 5 multisource data with acceptable results. • With increasing number of multisource, the effectiveness of separation degrades.
• The effectiveness of separation method degrades with increasing offsets. More effort is needed for the far offset data.
• Future Work: improving filters, more multisource, and realistic field data.
Acknowledgement
We would like to thank the UTAM 2008 sponsors for their support.
Thank You