Interferometric Multiple Migration of UPRC Data

1
Interferometric Multiple Migration of UPRC Data

• Jianhua Yu
• University of Utah

2
? Motivation and Objective ? Interferometric
Migration Crosscorrelogram migration
Autocorrelogram migration ? Examples
Synthetic Data UPRC data ? Summary
Outline
3
Motivation and Objective ? Interferometric
Migration Crosscorrelogram migration
Autocorrelogram migration ? Examples
Synthetic Data UPRC data ? Summary
Outline
4
IVSPWD Objective

• ? Provide Look-ahead Image Below Drill Bit
• ? Reduce Uncertainty in Drilling

?
5
Problem
? No Source Wavelet ? No Source Initiation
Time ? Not Easy to Get Pilot Signal in
Deviated Well
6
Solution
Interferometric Migration
No need to know source wavelet
No need to know source location
No limits to deviated well
No need to know initial time
7
Outline . Motivation and
Objective . Interferometric Migration .
Examples . Summary
8
. Crosscorrelogram migration .
Autocorrelogram migration
Interferometric Migration
9
Well
Receiver
Ghost
Direct Wave
Primary
Drill bit
Primary, Ghost and Direct Wave
10
Free-surface related Ghost Travel Time
g
g
s
x
11
Ghost Imaging Condition After Correlation of
Traces
Condition recording data have to be dense !!
12
Crosscorrelogram Ghost Imaging Condition
13
Crosscorrelogram Migration
14
. Crosscorrelogram migration .
Autocorrelogram migration
Interferometric Migration
15
Free-surface related Ghost Travel time
g
g
s
x
16
Autocorrelogram Ghost Imaging Condition
g
g
s
x
17
Autocorrelogram Migration
18
Outline . Motivation and
Objective . Autocorrelogram Migration
Method . Examples . Summary
19
Geological Model
X (m)
4
0
0
V1
V2
Depth (m)
V3
V4
V5
V6
3
20
Velocity Model
X(km)
X(km)
0 4
0 4
0
0
3.5
3.5
Depth(km)
2.0
2.0
3
3
Interval Velocity
RMS Velocity
21
Shot Gather and Crosscorrelogram
Traces
Traces
1 200
1 200
0
0
Time (s)
Time (s)
4
4
CSG 10 and Master trace at 80
22
Shot Gather and Autocorrelogram
Traces
Traces
1 200
1 200
0
0
Time (s)
Time (s)
4
4
CSG 10
23
Crosscorrelogram Migration Results
X (km)
X (km)
1.6 2.1
1.6 2.1
0
Time (s)
2.2
With primary
Without primary
24
Autocorrelogram Migration Results
X (km)
X (km)
1.6 2.1
1.6 2.1
0
Time (s)
2.2
With primary
Without primary
25
Acquisition Survey
East (kft)
0
4.5
0
Drill bit
North (kft)
Well Rig
3C Receivers
-5
0
Depth (kft)
10
26
Main Acquisition Parameters
Drill-bit Depth 9188 ft Offset Range
1135-4740 ft Recording Length 20
s Sample Interval 2 ms Station Number
10
27
Drill-bit Data of CSG 96
Trace Number
1 10
0
Time (s)
7
28
Main Processing Steps
Trace editing and static shift
Frequency panel analysis and noise elimination
Amplitude balance and energy normalization
Velocity analysis
Calculating cross- and autocorrelograms,
vertical stacking
Cross- and Autocorelogram migration
29
Frequency Panel Analysis
1 10
1 10
0
0
Time (s)
Time (s)
7
7
5-15 Hz
lt 5 Hz
30
Frequency Panel Analysis
1 10
1 10
0
0
Time (s)
Time (s)
7
7
25-40 Hz
15-25 Hz
31
Processed CSG 96 Part of CRG 6
1 10
1 13
0
0.5
Time (s)
Time (s)
7
4.5
32
Crosscorrelogram of CSG 96
Trace No.
1 10
1 10
1 10
0
Time (s)
4
12 s
16 s
8 s
33
Autocorrelogram of CSG 96
1 10
1 10
1 10
0
Time (s)
4
12 s
16 s
8 s
34
Autocorrlogram Migration Images
Traces
Traces
1
50
1
50
0.5
Time (s)
3.2
Window 8 s
Window12 s
35
Crosscorrlogram Migration Images
Traces
Traces
1
50
1
50
0.5
Time (s)
3.2
Window 8 s
Window12 s
36
Acquisition Survey Map
Well Rig
0
Line AC4
North (ft)
Drill bit
3C Receivers
-5000
0
1500
3000
4500
East (ft)
37
SP
1255
1215
1235
1.0
Drilling hole
Time (s)
2.0
3.0
Autocorrelation Ghost Image(Corr. Window8 s)
38
SP
1255
1215
1235
1.0
Drilling hole
Time (s)
2.0
3.0
Crosscorrelation Ghost Image ( Corr. Window 12 s)
39
Outline . Objective .
Autocorrelogram Migration . Examples .
Summary
?
40
SUMMARY
41
SUMMARY
Difficulty of separating upgoing and downgoing
wave can cause artifacts in migration image
42
Whats Next
Improve the methods efficiency for real-time
purpose
Reduced the virtual multiple and other waves
influence
Integrated migration image of both borehole data
and CDP data
43
Acknowledgements

• I greatly appreciate Union Pacific Resources for
  donating this data
• I am grateful to the 2000 sponsors of the UTAM
  consortium for financial support
• I also thank all of people who give me some
  suggestions and help for this work