session 2 - (1) velocity model building (jacques bonnafe)
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HAGI
Bandung - 23 to 24 June 2014
Presenter : Jacques BONNAFE
1
Velocity Model Building
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2
Outline
Introduction Principles
Types of velocity models
Velocity model building methodology and tools
Anisotropy
Example
Conclusions
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3
Depth Imaging
Prestack surface
gathers
Velocity Model
Depth Migration
Algorithm PSDM image
Preprocessing required (decon, demult, )
Acquisition geometry is determinant (mon/multi/wide
azimuth, maximum offset)
Velocity Model
Major concern of a PSDM project
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4
High Performance
Computing
Integrated Depth Imaging Toolkit
Velocity Model
Building
Interpretation
Residual Moveout
Computation
Depth
Migration
Algorithm
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5
Outline
Introduction Principles
Types of velocity models
Different types of models
How to make the initial model
Velocity model building methodology and tools
Anisotropy
Example
Conclusions
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LAYERED MODEL
6
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7
GRID MODEL
Smooth Models
With constraints
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8
Hybrid parameterization
No velocity contrasts between layers
V0(x,y) and k(x,y) within each layer
Horizon not necessary geological
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Outline
Introduction Principles
Types of velocity models
Velocity model building methodology and tools
reflection tomography, principle, gamma, updates
Other techniques: refraction tomography, scan, ....
Well ties
Anisotropy
Example
Conclusions
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10
Velocity
Model
PreStk
Depth Mig.
Are
CIPS
Flat?
NO
YES
Auto Pick
Residual
Moveout
& Dip in z
3D Ray-trace
Linear
Tomography
Equations
Iterate
PreStk.
Depth Mig.
Image
Tomo Solver
for Smooth
Update To
Interval Vels
Principle of tomographic updating
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11
offset
dep
th
RMO section
x,y
dep
th OK
Too fast
Too slow
CRP Gather
RMO definition
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12
Gamma definition The ratio of the migration velocity to the true (geological) velocity
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13
Comparison of RMO before and after iteration on maps
0-1
km
1
-2 k
m
Iteration #2 isotropic Iteration #3 VTI anisotropic
-4 0 +4
-4 0 +4
-4 0 +4
-4 0 +4
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RMO Statistic Initial VTI
Interval 0 1
Km
Interval 1 2
Km
Interval 2 3
Km
Interval 3 4
Km
Interval 4 5
Km
Interval 5 6
Km
Interval 6 7
Km
Interval 7 8
Km
Comparison of RMO before and after iteration on histograms
Iteration 3 Iteration 4
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PSDM Stack Overlaid with Gamma: inline
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PSDM Stack overlaid with Gamma : depth = 500m
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GAMMA ON HORIZON
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18
Example of cdp gathers evolution
Iteration 1 Iteration 2 Iteration 3 Iteration 4
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EXAMPLE OF STACK AND VELOCITY MODEL
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Iteration 1 Iteration 5
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2 km 2 km
EXAMPLE OF STACK AND VELOCITY MODEL
Iteration 2 Iteration 3
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One iteration illustrated: Initial RMO residuals
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One iteration illustrated: Inversion + New PSDM + RMO residuals
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One iteration illustrated: Initial PSDM
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One iteration illustrated: New PSDM
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25
Other tools
Refraction tomography
Velocity scan
Information from wells of geologists
FWI
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Refraction tomography
First Break Time Low High
Shallow Gas
FB in Offset Domain
FB in Shot Domain
Manual picking done
FB in various Offset Planes
200 262.5 m 1600 1762.5 m
2000 2162.5 m 2400 2562.5 m
First Break picking:
Automated picks in good seismic area
Manual picks in degraded seismic area
Full offset used
Application:
For shallow anomalies
Down to depth approx 25% of maximum offset
First Break picks
First Break Time Low High
Late arrival
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Iterative refraction tomography updates
Smoothed PSTM velocity model as initial model
Several iterations of calculations run with
decreasing grid size
QCs performed:
Comparison with previous model with greater grid size
Visual observation by overlying the model with depth-
stretched PSTM section
Target line migration using final shallow model
Final Shallow Model
Update is effective < 400m (~1/6 cable length)
400 m
400 m 400 m
400 m
Main elements of refraction tomography:
Initial velocity model
Forward modeler module for refracted wave
First Break picks
Refraction tomography equation builder and
solver
100 x 100 m
400 x 400 m 200 x 200 m
50 x 50 m
4 km
4 km
4 km
4 km
500 m
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model for scanning
-28-
Carbonate
flooding
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Carbonate V=2750 m/s
-29-
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-30-
Carbonate V=2900 m/s
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-31-
Carbonate V=3100 m/s
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Map of reefs
-32-
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33
VELOCITIES CONTROL AT WELL
Initial velocity
Iteration 1 velocity
Iteration 2 velocity
Iteration 3 velocity
Iteration 4 final velocity
TWT TVD
1400 5000 m/s
Horizon A
Horizon B
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Basic Depth Imaging Workflow
Velocity model may be iteratively built using a layer stripping approach
Simplifies velocity update process
May rather build downwards
PSDM migration performed at each iteration
Moveout extracted from the Gathers for velocity update
Workflow and tools adapted to study
Objectives : Exploration/Reservoir imaging
Geological environment
Data : Marine/land acquisition, mono/multi/wide azimuth
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Interpretations have to be very consistent with the seismic information
Used for ray-tracing
Used for velocity contrasts positioning, e.g. salt bodies, carbonate build-ups
The accuracy of the inversion result depends on these interpretations
The RMO extracted (along interpretations) have to represent reliable
seismic information:
If multiples are picked by RMO, velocity model will be updated wrongly
Use interpretation to discriminate
In area of poor signal to noise ratio, RMO analysis can be erroneous
If maximum offset is not long enough, RMO can be inaccurate
In very complex areas or when initial model is very wrong, the moveout can be far from
hyperbolic; sometimes gathers lack coherence
Direct interpretive input into the model
Importance of seismic interpretation in the VMB
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36
Outline
Introduction Principles
Types of velocity models
Velocity model building methodology and tools
Anisotropy
Example
Conclusions
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37
Anisotropy
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39
Velocity Issue: isotropic, anisotropic STI or VTI?
Salt Salt Salt
True Model (STI) Velocity is increasing with angle
to structural dip normal
Isotropic Migration Velocity does not vary
with angle of propagation
VTI Migration Velocity is increasing
with angle of propagation
Fast
Slow Slow
Fast
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40
Thomsens VTI parameters estimation
Delta estimation (relates vertical and imaging vels.)
Comparison of depth markers on seismic and on wells
Requires accurate calibrations on wells
Epsilon estimation (relates vertical and horizontal vels.)
Measurements based on hockey sticks on gathers
Then Epsilon averaged to obtain single epsilon functionvalue per
layer
Sometimes set to a constant percentage of delta (150% or 200%)
Iter.2 isotropic Iter.2: delta applied Iter.3 VTI anisotropic
Averaged Epsilon function (z)
d,
z
Averaged Delta function d (z)
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41
Anisotropic model Building
In the Isotropic case:
Vnmo = Vvertical by layer
Vnmo = Vrms multi-layer
Isotropic model/migration, anisotropic earth:
Vertical velocity over estimated
Mismatch between horizon and well marker (typically, horizons deeper)
Mismatch between sonic and seismic velocities
In the anisotropic case : Vnmo Vvertical or Vrms
Match horizon and well marker
Match between sonic and seismic velocities Calibrated PSDM image
Very delicate and time consuming work
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3D Depth Migration
ANISOTROPIC ISOTROPIC (stretched to well)
Vertical stretch is not sufficient !!
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Outline
Introduction Principles
Types of velocity models
Velocity model building methodology and tools
Anisotropy
Example: BEKAPAI VMB
Step 1. First Break picking
Step 2. Refraction tomography
Step 3. Initial PSDM velocity building
Step 4. Reflection tomography
Results
Conclusions
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44 - IPA11-G-121 Combined Refraction Tomography and Reflection Tomography for PSDM Velocity Model Building
Step1. First Break picking and QC
First Break Time Low High
Shallow Gas
FB in Offset Domain
FB in Shot Domain
Manual picking done
FB in various Offset Planes
200 262.5 m 1600 1762.5 m
2000 2162.5 m 2400 2562.5 m
First Break picking:
Automated picks in good seismic area
Manual picks in degraded seismic area
Full offset used
QC performed:
Visual observation of picked events in shot domain,
offset domain and various offset planes
Edit manually anomalous picks
First Break picks
First Break Time Low High
Late arrival
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45 - IPA11-G-121 Combined Refraction Tomography and Reflection Tomography for PSDM Velocity Model Building
Step 2. Iterative refraction tomography updates
Smoothed PSTM velocity model as initial model
Four iterations run with decreasing grid size
(400m, 200m, 100m, 50m)
QCs performed:
Comparison with previous model with greater grid size
Visual observation by overlying the model with depth-
stretched PSTM section
Target line migration using final shallow model
Final Shallow Model
Update is effective < 400m (~1/6 cable length)
400 m
400 m 400 m
400 m
Main elements of refraction tomography:
Initial velocity model
Forward modeler module for refracted wave
First Break picks
Refraction tomography equation builder and
solver
100 x 100 m
400 x 400 m 200 x 200 m
50 x 50 m
4 km
4 km
4 km
4 km
500 m
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46
Merge at Z = 400 m
Step 3. Initial PSDM velocity building
Final Shallow Model
Smoothed PSTM velocity*
Initial PSDM velocity model
Model is ready to be updated through
iterative reflection tomography
* PSTM velocity field was first converted to interval velocity and
then smoothed spatially
3 km
3 km
2 km
500 m
1500 m
1500 m
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Step 4. Iterative reflection tomography updates
Main elements of reflection tomography:
Initial velocity model
Pre-Stack Depth Migration
Automated RMO and Dip picking
Reflection tomography equation builder and solver
Four iterations carried-out:
Two isotropic model followed by two VTI
anisotropic updates
Kirchhoff PSDM to depth-migrate the
gathers
On 50 x 50m grid size
(Woodward, et. al., 2008, A decade of tomography)
Best model was selected based on comparison with previous model using:
Gamma map & histogram
Gamma/stack section overlay
Gathers display
Velocity model/stack overlay
Next slide
Velocity needs to be slower
Velocity is correct
Velocity needs to be faster
Gamma = ratio of the migration velocity to the true geological velocity
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48 - IPA11-G-121 Combined Refraction Tomography and Reflection Tomography for PSDM Velocity Model Building
RMO picking and QC
Too slow Too fast
Vel. error map (1-2km): iter.2 Vel. Error map (1-2km): iter.3
-4 0 +4
Automated RMO pick (50 x 50m):
Precondition gathers with de-multiple and offset
muting prior to picking
QC done through:
Visual observation of picked events on gathers
Visual observation of RMO attribute in section
and map views
Histogram plot of RMO attribute
-4 0 +4
-10%
Gamma section: initial model Gamma section: 1st update
Gamma = 0.9 (10% too slow) Gamma = 1.1 (10% too fast)
+10%
Gamma QC: iteration 1
50
0 m
4 km
10
00
m
6 km 6 km
Significant improvement of Gamma after 1st iteration
0
0.8
1.0
1.2
Significant improvement of Gamma after 3rd iteration (VTI)
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49
Thomsens VTI parameters estimation
Delta estimation (relates vertical and imaging vels.)
Computed based on time-picked horizons at nine wells
Workflow consists of:
1) Seismic to well calibration to obtain calibrated vertical
velocity field
2) Extraction of horizons TWT and the corresponding depth
TVDSS (Zo)
3) Convert the horizons TWT to depth (Ziso) using isotropic
velocity field
4) For each horizon, compute the delta
Single delta function (depth-variant) was used in 3rd VTI iteration
Delta set inactive (0.0001) at last iteration; considering quite
important depth errors in deep interval after 3rd VTI iteration
Epsilon estimation (relates vertical and horizontal vels.)
Automated based on far offsets at gathers located in nine wells
Individual Epsilon function at well was averaged to obtain single
epsilon function
QC done by comparing gathers before and after application of
Delta and Epsilon
Iter.2 isotropic Iter.2: delta applied Iter.3 VTI anisotropic
Averaged Epsilon function (z)
z
Step 5. Introducing anisotropy
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50
VTI anisotropy model: improvement of depthing & focusing
Initial model 1st iteration model 2nd iteration model 3rd iteration VTI model
Isotropic Isotropic Anisotropic
Improvement of gather flatness = more focused stack
60
0 m
Multiple
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51
Final PSDM velocity model
2 km
2 km
Initial model for reflection tomography
Final model
Initial velocity
Iteration 1 velocity
Iteration 2 velocity
Iteration 3 velocity
Iteration 4 final velocity
1400 m/s 5000 m/s
Measured interval velocity
Velocity reversal well captured thanks to reflection tomography
Low velocity anomaly captured by refraction tomography
Converging RMO (projected) G
am
ma r
eduction
Iteration #
1000 m
1000 m
600 m
s
Velocities in time domain (TWT)
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52
Improvement of image at shallow interval Enable the delineation of shallow gas anomaly
Shallow slice 2002 dataset
Shallow slice 2010 PSDM dataset
2002 Post-STM: IL20600 converted in depth
2010 PSDM: IL20600
Low velocity anomaly imaged properly
1.5 km
500 m
500 m
1.5 km
2.5 km
2.5 km
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Improvements of image at target interval
2002 Post-STM: IL20500
COHERENCY @ BETA
50
0 m
s
2 km
2.5 km
Note: AGC was applied on the dataset
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54
Improvements of image at target interval COHERENCY
@ BETA
2 km
60
0 m
2010 PSDM: IL20500
More focused fault image
Higher S/N ratio
More preserved amplitude
Clearer shallow gas image
Push-down and statics not fully solved
2.5 km
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Operational added-values brought by PSDM dataset More accurate post-mortem evaluation of recently drilled wells
Well G drilled before PSDM (targeting Central Panel)
Well G results (sedimentology, fluid, etc) are more coherent with the West Panel consistent with the new structural scheme on PSDM
Structural interpretation on PSDM performed independently from well G results
Two other wells drilled after PSDM showed acceptable consistency in term of structural scheme and expected HC column
SW SW NE NE
BETA old map
Well G Well G
Well G Well G
1 km 1 km
750 m 750 m
BETA new map
WEST CENTRAL EAST WEST CENTRAL EAST
Old interpretation overlaid on
PSDM
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56
Conclusions of Bekapai PSDM example
Reliable full-field velocity model was obtained by combining refraction
tomography at shallow depth and reflection tomography at deeper depth
Refraction tomography proved to be a solution to build a reliable shallow
velocity model that would not be achieved by using reflection tomography
Efficiency of refraction tomography relies on the quality of first break picks;
QC and editing are therefore fundamental, but time consuming
PSDM final product has improved drastically structural image and
understanding of the field
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Outline
Introduction Principles
Types of velocity models
Velocity model building methodology and tools
Anisotropy
Example:
Conclusions
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58
Conclusions on VMB
Great variety of tools
Strong involvements of interpreters
The survey should be big enough to allow proper tomography
Time consuming process
A good model is the key to the success of the PSDM project
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