4c mahogony data processing and imaging by lsmf method
DESCRIPTION
4C Mahogony Data Processing and Imaging by LSMF Method. Jianhua Yu and Yue Wang. Outline. Motivation and Objective LSMF Method Examples Graben Model Mahogany Field Data Summary. Outline. Motivation and Objective LSMF Method Examples Graben Model Mahogany Field Data - PowerPoint PPT PresentationTRANSCRIPT
4C Mahogony Data Processing 4C Mahogony Data Processing and Imaging by LSMF Methodand Imaging by LSMF Method
Jianhua Yu and Yue WangJianhua Yu and Yue Wang
OutlineOutline• Motivation and ObjectiveMotivation and Objective
• LSMF MethodLSMF Method
• ExamplesExamples Graben ModelGraben Model Mahogany Field Data Mahogany Field Data
• SummarySummary
OutlineOutline Motivation and ObjectiveMotivation and Objective
• LSMF MethodLSMF Method
• ExamplesExamples Graben ModelGraben Model Mahogany Field Data Mahogany Field Data
• SummarySummary
Geological ObjectivesGeological Objectives
• Image Complex Structure Image Complex Structure • Detect Gas Reservoir OverDetect Gas Reservoir Over
SaltSalt
ProblemsProblems • P-SV Conversion at ReflectorP-SV Conversion at Reflector ??
• How to GetHow to Get ““PurePure”” P-P and P-SVP-P and P-SV
• Strong Guided WavesStrong Guided Waves
Problems for F-KProblems for F-K
Use only wave Use only wave moveoutmoveout
Strong guided Strong guided waveswaves
Near offset Near offset distortion distortion
P-PP-PSourceSource
Point Scatterer Point Scatterer
P-SV P-SV
P-P and P-SV WavesP-P and P-SV Waves
Particle Motion Particle Motion DirectionDirection++
SeparationSeparation
Tim
eT
ime
offsetoffset
MoveoutMoveout
Least Squares Migration Filtering Least Squares Migration Filtering
ObjectiveObjective• Separate P-P & P-SSeparate P-P & P-S
• Suppress Guide WavesSuppress Guide Waves• Improve Migration ImageImprove Migration Image
OutlineOutline• Motivation and ObjectiveMotivation and Objective
• LSMF MethodLSMF Method
• ExamplesExamples Graben ModelGraben Model Mahogany Field Data Mahogany Field Data
• SummarySummary
Observed dataObserved data = > D= > Dpp pp ++
OffsetOffset
Tim
eT
ime
P-P waveP-P wave
P-S waveP-S wave
LSMF MethodLSMF Method
LLp-s p-s mmp-sp-s
LLpp pp mmpppp
ReflectivtyReflectivtyModelingModelingOperatorOperator
DDp-sp-s
ddpppp = L = Lppppmmpppp ddp-sp-s = L = Lp-p-ssmmp-sp-s
P-P waveP-P wave
OffsetOffset
Tim
eT
ime
P-S waveP-S wave
OffsetOffset
Tim
eT
ime
LSMF MethodLSMF Method
Conjugate Gradient Method:Conjugate Gradient Method:
dLLLm
mTT
sp
pp 1)(
SP
L,PP
LL wherewhere
LSMF MethodLSMF Method
LSMF MethodLSMF Method
Operators are constructed based on Operators are constructed based on moveout and particle-motion directionmoveout and particle-motion direction
The migration operators are the The migration operators are the transposes of the modeling operatorstransposes of the modeling operators
OutlineOutline• Motivation and ObjectiveMotivation and Objective
• LSMF MethodLSMF Method
• ExamplesExamples Graben ModelGraben Model Mahogany Field Data Mahogany Field Data
• SummarySummary
ExamplesExamples
• Graben Model Graben Model • Mahogony Field DataMahogony Field Data
Graben Velocity ModelGraben Velocity Model
0
Dep
th (
m)
3000
50000 X (m)
V1=2000 m/sV2=2700 m/s
V3=3800 m/s
V4=4000 m/s
V5=4500 m/s
FDFD Synthetic DataSynthetic Data
1.4
0
Tim
e (s
)
0 Offset (m)5000
0 Offset (m)5000
Horizontal ComponentHorizontal Component Vertical ComponentVertical Component
P-PP-P P-SP-S
P-SP-S P-PP-P
LSMF SeparationLSMF Separation
1.4
0
Tim
e (s
)
0
Offset (m)
5000
0
Offset (m)
5000
Horizontal ComponentHorizontal Component Vertical ComponentVertical Component
P-SP-S P-PP-P
F-K Filtering Separation F-K Filtering Separation
1.4
0
Tim
e (s
)T
ime
(s)
0
Offset (m)
5000
0
Offset (m)
5000
Horizontal ComponentHorizontal Component Vertical ComponentVertical Component
P-PP-P P-SP-S
P-SP-S P-PP-P
Test Results Indicate:Test Results Indicate:
LSMF works well for separating LSMF works well for separating
P-P and P-SVP-P and P-SV
LSMF is superior to F-K filteringLSMF is superior to F-K filtering
ExamplesExamples
• Graben Model Graben Model • Mahogony Field DataMahogony Field Data
Acquisition SurveyAcquisition Survey
9 km
OBC
Shot Line
29 km
Main Processing FlowMain Processing Flow
Geometry assignment, datuming and so onGeometry assignment, datuming and so on
Trace edit, noise elimination, dual-sensor summationTrace edit, noise elimination, dual-sensor summation
Amplitude RecoveryAmplitude Recovery
Static correction, (F-K filtering), multiple suppressionStatic correction, (F-K filtering), multiple suppression
LSMF, velocity analysis LSMF, velocity analysis
Migration Migration
Output Output
0
Tim
e (s
)
725
4
Offset(m)
Raw CSGRaw CSG-750
Hydrophone componentHydrophone component
725Offset(m)-750
Vertical componentVertical component
Continuous events
Continuous events
0
Tim
eT
ime
(s)
725
4
Offset(m)Offset(m)
Raw CSGRaw CSG-750
Radial componentRadial component
725Offset(m)Offset(m)
-750
Transverse componentTransverse component
Wormy events
Wormy events
0
Tim
e (s
)T
ime
(s)
3750
4
X (m)X (m)
RawRaw CRGCRG0
Hydrophone componentHydrophone component
3750X (m)X (m)0
Vertical componentVertical component
Continuous events Continuous
events
0
Tim
e (s
)
3750
4
X (m)
Raw CRGRaw CRG0
Radial component
3750X (m)
0
Transverse component
Continuous events Continuous
events
Rough Estimate of Static ShiftRough Estimate of Static Shift
Station NumberStation Number
Sta
tic
shif
t (m
s)S
tati
c sh
ift
(ms)
-40 100
12
Receiver static
Shot static
Source Receiver
p s
Source Receiver
p s
TheThe Shear static shifts existShear static shifts exist
These shifts mainly come from These shifts mainly come from receivers and one-way Shear path receivers and one-way Shear path from deeper reflector from deeper reflector
P-S waves originate from P-S waves originate from reflectorsreflectors
Data Analysis Indicates:Data Analysis Indicates:
CRG1 Data before Using LSMFCRG1 Data before Using LSMF
CRG1 (Vertical component) CRG1 (Vertical component)
0
4
Guided wave and P-S
Tim
e (
s)T
ime
(s)
CRG1 Data after Using F-K FilteringCRG1 Data after Using F-K Filtering
CRG1 (Vertical component) CRG1 (Vertical component)
0
4
Unwanted waves remain
Tim
e (
s)T
ime
(s)
CRG1 Data after Using LSMFCRG1 Data after Using LSMF
CRG1 (Vertical component) CRG1 (Vertical component)
0
4
Less Noise remains
Tim
e (
s)T
ime
(s)
Prestack Migration Image Prestack Migration Image With F-K SeparationWith F-K Separation
Tim
e (
s)T
ime
(s)
0
3.5
Midpoint (Km)Midpoint (Km) 4.60
c
Prestack Migration Image Prestack Migration Image With LSMF SeparationWith LSMF SeparationT
ime
(s)
Tim
e (
s)0
3.5
Midpoint (Km)Midpoint (Km) 4.60
c
A Zoom View of Box AA Zoom View of Box A T
ime
(s)
Tim
e (
s)
2.02.0
3.23.2
Midpoint (Km)Midpoint (Km)0.60.6 1.41.4
Midpoint (Km)Midpoint (Km)0.60.6 1.41.4
FK+Mig.FK+Mig. LSMF+Mig.LSMF+Mig.
A Zoom View of Box CA Zoom View of Box CT
ime
(s)
Tim
e (
s)
0.20.2
0.80.8
Midpoint (Km)Midpoint (Km)3.43.4 4.64.6
Midpoint (Km)Midpoint (Km)3.43.4 4.64.6
FK+Mig.FK+Mig. LSMF+Mig.LSMF+Mig.
OutlineOutline• Motivation and ObjectiveMotivation and Objective
• LSMF MethodLSMF Method
• ExamplesExamples Graben ModelGraben Model Mahogany Field Data Mahogany Field Data
• SummarySummary
SummarySummary
• P-SV waves in Mahogony data P-SV waves in Mahogony data
originate from the deep reflectors originate from the deep reflectors
• LSMF gives better separation resultsLSMF gives better separation results
and and improves the migration image improves the migration image
SummarySummary
• LSMF can eliminate unwanted noise, LSMF can eliminate unwanted noise,
such as guided wavessuch as guided waves
• LSMF has negative impact on the LSMF has negative impact on the
fidelity of data to some extentfidelity of data to some extent
SummarySummary
• Multiple EliminationMultiple Elimination
• Prestack Depth Migration Prestack Depth Migration
• Converted Wave ImagingConverted Wave Imaging
Future ResearchFuture Research::
AcknowledgementAcknowledgement
We are grateful to the 1999 sponsors We are grateful to the 1999 sponsors of the UTAM consortium for financial of the UTAM consortium for financial supportsupport