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Local Reverse Time Migration with VSP Green’s Functions Xiang Xiao UTAM, Univ. of Utah May 1, 2008 PhD Defense 99 pages.

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Presentation on theme: "Local Reverse Time Migration with VSP Green’s Functions Xiang Xiao UTAM, Univ. of Utah May 1, 2008 PhD Defense 99 pages."— Presentation transcript:

1 Local Reverse Time Migration with VSP Green’s Functions Xiang Xiao UTAM, Univ. of Utah May 1, 2008 PhD Defense 99 pages

2 2 Outline Introduction and overview SSP  VSP  SWP interferometric transform Local reverse time migration: horizontal reflector imaging Local reverse time migration: salt flank imaging with transmitted P-to-S waves Summary Overview SSP  VSP Local RTMLocal RTM PSSummary

3 3 Outline Overview SSP  VSP Local RTMLocal RTM PSSummary Introduction and overview SSP  VSP  SWP interferometric transform Local reverse time migration: horizontal reflector imaging Local reverse time migration: salt flank imaging with transmitted P-to-S waves Summary

4 4 Data Time Offset Model Depth Offset r(x) D(g|s) Forward modelling Inverse Migration m(x) Migration Image Low subsalt resolution, Defocusing! Overview SSP  VSP Local RTMLocal RTM PSSummary

5 5 Subsalt Imaging s x G(x|g) g G(x|s) m(x) ~ ~ G(x|s) Model- based G(x|g)* Model- based g s ds * D(g|s) D(g|s)dg Overview SSP  VSP Local RTMLocal RTM PSSummary

6 6 Subsalt Imaging s x G(x|g) g G(x|s) m(x) ~ ~ G(x|s) Forward direct s ds * D(g|s) G(x|g)* Backward reflection g D(g|s)dg Errors in the overburden and salt body velocity model Defocusing Overview SSP  VSP Local RTMLocal RTM PSSummary

7 7 Interferometric Imaging s x G(x|g) G(x|s) g m(x) ~ s ~ ds G(x|s) Data- based G(x|g)* D(g|s)dg Model- based g * Overview SSP  VSP Local RTMLocal RTM PSSummary

8 8 Local Reverse Time Migration s x G(x|g) g G(x|s) g’ G(x|s)= G(x|g’)* D(g’|s)dg’ Backward Direct wave g’ Local VSP Green’s function Overview SSP  VSP Local RTMLocal RTM PSSummary

9 9 Local Reverse Time Migration s x G(x|g) g G(x|s) g’ Overview SSP  VSP Local RTMLocal RTM PSSummary s m(x) ~ ~ G(x|s) Backward approx s ds * G(x|g)* Backward reflection g D(g|s)dg

10 10 Outline Overview SSP  VSP Local RTMLocal RTM PSSummary Introduction and overview SSP  VSP  SWP interferometric transform Local reverse time migration: horizontal reflector imaging Local reverse time migration: salt flank imaging by transmitted P-to-S waves Summary

11 11 Outline Overview SSP  VSP Local RTMLocal RTM PSSummary SSP  VSP  SWP interferometric transform –Motivation –Theory –Numerical Tests SEG/EAGE salt model Double datuming –Conclusions

12 12 I. Why we need more VSP?  Surface related statics SSP VSP Twice Once Seabed Salt Target  Overburden velocity error Twice Once  Raypath Longer Shorter  Attenuation MoreLess  Frequency  Resolution LowerHigher SSP  VSP Motivation TheoryNumerical Tests Conclusions

13 13 How to get more VSP? dx G(B|A) ~ RVSP VSP G(A|x)* G(B|x) SSP S2S2 ~ S2 A Bx S1 RVSP S2 A Bx S1 VSP S2 A Bx S1 SSP SSP  VSP Motivation TheoryNumerical Tests Conclusions

14 14 3D Application 3D VSP3D SSP Naturally datuming ! 3D RVSP SSP + VSP  RVSP ! Low fold High fold ! SSP  VSP Motivation TheoryNumerical Tests Conclusions

15 15 X S Seabed Target Salt SSP/RVSP aperture g VSP aperture Shot coverage Receiver coverage SSP  VSP Motivation TheoryNumerical Tests Conclusions

16 16 Use it, or lost it… 3D RVSP SSP + VSP  RVSP ! High folds ! Salt Better image under the salt ! SSP, VSPWell log Better Geologic interpretation ! SSP  VSP Motivation TheoryNumerical Tests Conclusions

17 17 What is the benefit ? –Higher fold virtual RVSP data are obtained; –Sources are closer to the target; SSP + VSP  RVSP Salt –No velocity model is needed; –Multi-arrival are considered; SSP  VSP Motivation TheoryNumerical Tests Conclusions

18 18 How to skip overburden? dx G(g|g’) ~ SWP VSP G(g’|s)* G(g|s) VSP S ~ g g’ s VSP g g’ s VSP g g’ s Virtual Source Gather No velocity model is needed ! SSP  VSP Motivation TheoryNumerical Tests Conclusions

19 19 Application of VSP  SWP transform: g g’ s Virtual Source Gather  Salt flank imaging  P and S wave checkshot  Sediment imaging  Multiple/teleseismic imaging  4D Reservoir monitoring  Shear wave splitting and crack orientation  Seismic while drilling  …… Application SSP  VSP Motivation TheoryNumerical Tests Conclusions

20 20 Outline Overview SSP  VSP Local RTMLocal RTM PSSummary SSP  VSP  SWP interferometric transform –Motivation –Theory –Numerical Tests SEG/EAGE model Double datuming –Conclusions

21 21 P-wave velocity model 0 Depth (m) -78507850Offset (m) Velocity (m/s) 4500 15003600 SEG/EAGE Salt Model SSP  VSP Motivation TheoryNumerical Tests Conclusions

22 22 P-wave velocity model 0 Depth (m) -78507850Offset (m) Velocity (m/s) 4500 15003600 SSP Data Geometry… SSP SSP  VSP Motivation TheoryNumerical Tests Conclusions

23 23 Data Synthetic SSP CSG Time (s) 0 6 Offset (m) -20002000 SSP  VSP Motivation TheoryNumerical Tests Conclusions

24 24 P-wave velocity model 0 Depth (m) -78507850Offset (m) Velocity (m/s) 4500 15003600 VSP Geometry… SSP  VSP Motivation TheoryNumerical Tests Conclusions

25 25 Data Time (s) Synthetic VSP CRG 0 6 Offset (m) -78507850 Synthetic SSP CSG Time (s) 0 6 Offset (m) -78507850 SSP  VSP Motivation TheoryNumerical Tests Conclusions

26 26 Traces comparisons Amplitude Time (s)26 Synthetic RVSP CSG Time (s) 0 6 Redatumed RVSP Time (s) 0 6 Offset (m) -78507850 1.4 km Comparison Zoom area

27 27 Zoom View of Traces Normalized Amplitude Time (s)5.53 Redatumed RVSP trace Direct waves are cut poor data folds SSP  VSP Motivation TheoryNumerical Tests Conclusions

28 28 P-wave velocity model 0 Depth (m) -78507850Offset (m) Velocity (m/s) 4500 15003600 Another Datuming Results SSP  VSP Motivation TheoryNumerical Tests Conclusions

29 29 Synthetic RVSP CSG Time (s) 0 6 Redatumed RVSP Time (s) 0 6 Offset (m) -20002000 Traces comparisons Amplitude Time (s)26 2.4 km Comparison

30 30 Normalized Amplitude Time (s) 2.56 Zoom view Direct waves are cut poor data folds Redatumed RVSP trace SSP  VSP Motivation TheoryNumerical Tests Conclusions

31 31 P-wave velocity model 0 Depth (m) -78507850Offset (m) Velocity (m/s) 4500 15003600 SEG/EAGE Salt Model SSP  VSP Motivation TheoryNumerical Tests Conclusions

32 32 Shot 320 SSP primary WEM 20 Hz 1.5 3.5 Depth (km) -44 Offset (km) Shot 320 RVSP WEM 20 Hz Depth (km) 1.5 3.5

33 33 33 shots SSP WEM 20 Hz 33shots VSP WEM 20 Hz Depth (km) 0 3.6 Offset (km) -4433 RVSP+VSP WEM 20 Hz Offset (km) -44 SEG/EAGE salt model 0 3.6 Depth (km)

34 34sgs’ss’gs’ g s’g’ g g’s’g’ SSP  VSP  SWP Transform SSP  VSP Motivation TheoryNumerical Tests Conclusions

35 35 1% error in migration model 2% error in migration model Depth (km) 0 3.6 Offset (km) -88 3% error in migration model Offset (km) -88 645 shots SSP WEM 0 3.6 Depth (km)

36 36 1% error in migration model 2% error in migration model Depth (km) 0 3.6 Offset (km) -88 3% error in migration model Offset (km) -88 33 shots VSP WEM 0 3.6 Depth (km)

37 37 645 shots SSP primary WEM 20 Hz 0 3.5 Depth (km) -88 Offset (km) Shot 320 BSSP WEM 20 Hz Depth (km) 1.5 3.5

38 38 645 shots SSP primary WEM 20 Hz 0 3.5 Depth (km) -88 Offset (km) Shot 320 BSSP WEM 20 Hz Depth (km) 1.5 3.5

39 39

40 40 Conclusions Natural datuming, no velocity model is needed ! Higher fold virtual VSP data are obtained ! Source are closer to the target, less approximation. Better resolution. SSP  VSP Motivation TheoryNumerical Tests Conclusions

41 41 Outline Overview SSP  VSP Local RTMLocal RTM PSSummary Introduction and overview SSP  VSP  SWP interferometric transform Local reverse time migration: horizontal reflector imaging Local reverse time migration: salt flank imaging with transmitted P-to-S waves Summary

42 42 Outline Motivation TheoryNumerical Tests Conclusions Local RTM Local reverse time migration: horizontal reflector imaging –Motivation –Theory –Numerical Tests Sigsbee VSP Data Set GOM VSP Data Set –Conclusions

43 43 VSP Forward Modeling s x g D(g|s) VSP data Motivation TheoryNumerical Tests Conclusions Local RTM

44 44 Reverse Time Migration s x g D(g|s) VSP data Motivation TheoryNumerical Tests Conclusions Local RTM

45 45 Reverse Time Migration s x G(x|g) g G(x|s) Backward D(g|s) Forward direct m(x) ~ s ~ ds G(x|s) Forward direct G(x|g)* D(g|s)dg Backward data g * Motivation TheoryNumerical Tests Conclusions Local RTM

46 46 Reverse Time Migration (RTM) s x G(x|g) g G(x|s) Backward D(g,s) Forward direct Forward direct: 1)Salt velocity model is required, but hard to build. 2) Errors due to imperfect velocity models. 3) Need to estimate statics, anisotropy, etc. Motivation TheoryNumerical Tests Conclusions Local RTM

47 47 s g g’ x VSP  SWP Interferometry Migrate virtual source gather D(g|g’) Limitations 1) s and x are at different sides of the well 2) Image near vertical structures Motivation TheoryNumerical Tests Conclusions Local RTM

48 48 Outline Motivation TheoryNumerical Tests Conclusions Local RTM Local reverse time migration: horizontal reflector imaging –Motivation –Theory –Numerical Tests Sigsbee VSP Data Set GOM VSP Data Set –Conclusions

49 49 Key Idea of Local RTM (a) VSP data: P(g|s)=T(g|s)+R(g|s) Transmission T(g|s) s g Reflection R(g|s) x Motivation TheoryNumerical Tests Conclusions Local RTM

50 50 (a) VSP data: P(g|s)=T(g|s)+R(g|s) T(g|s) s g R(g|s) x s (b) Backward reflection R(g|s) g x R(x|s)= G(x|g)*R(g|s) g (c) Backward transmission T(g|s) s g x T(x|s)= G(x|g)*T(g|s) g (d) Crosscorrelation m(x)= R(x|s)*T(x|s) s Local VSP Green’s function R(g|s) g x Key Idea of Local RTM Motivation TheoryNumerical Tests Conclusions Local RTM

51 51 (d1) Crosscorrelation imaging condition m(x)= R(x|s)*T(x|s) s R(g|s) g x Deconvolution Imaging Condition Motivation TheoryNumerical Tests Conclusions Local RTM (d2) Deconvolution imaging condition m(x)= R(x|s)*T(x|s) ss T(x|s)*T(x|s)

52 52 Benefits Target oriented! –Only a local velocity model near the well is needed. –Salt and overburden is avoided. –Fast and easy to perform. Source statics are automatically accounted for. Immune to salt-related interbed cross- talk. Motivation TheoryNumerical Tests Summary Local RTM

53 53 Outline Motivation TheoryNumerical Tests Conclusions Local RTM Local reverse time migration: horizontal reflector imaging –Motivation –Theory –Numerical Tests Sigsbee VSP Data Set GOM VSP Data Set –Conclusions

54 54 Sigsbee P-wave Velocity Model 0 Depth (km) 9.2 4500 1500 m/s -12.5 12.5Offset (km) 279 shots 150 receivers Motivation TheoryNumerical Tests Conclusions Local RTM

55 55 Local Reverse Time Migration Results 4.6 9.2 Depth (km) -33Offset (km) True modelMigration image f = fault f d d (1) (2) (3) (1)specular zone (2)diffraction zone (3)unreliable zone d = diffractor Motivation TheoryNumerical Tests Conclusions Local RTM

56 56 Outline Motivation TheoryNumerical Tests Conclusions Local RTM Local reverse time migration: horizontal reflector imaging –Motivation –Theory –Numerical Tests Sigsbee VSP Data Set GOM VSP Data Set –Conclusions

57 57 Depth (m) Offset (m) 4878 0 1829 0 GOM VSP Well and Source Location Source @150 m offset 2800 m 3200 m Salt 82 receivers Motivation TheoryNumerical Tests Conclusions Local RTM @600 m offset@1500 m offset

58 58 P-to-S ratio = 2.7 Velocity Profile S Wave P Wave Depth (m) 0 4500 050000 2800 m 3200 m Salt Incorrect velocity model P-to-S ratio = 1.6 Velocity (m/s) Motivation TheoryNumerical Tests Conclusions Local RTM

59 59 Z-Component VSP Data Depth (m) Traveltime (s) 2652 3887 1.23.0 Salt Direct P Reflected P Reverberations Motivation TheoryNumerical Tests Conclusions Local RTM

60 60 X-Component VSP Data Depth (m) Traveltime (s) 2652 3887 1.23.0 Salt Direct P Reflected P ReverberationsDirect S Motivation TheoryNumerical Tests Conclusions Local RTM

61 61 Local Reverse Time Migration Result (1) (2) (3) (1) specular zone, (2) diffraction zone, (3) unreliable zone 3.3 Depth (km) 3.9 0100Offset (m) 39 receivers reflectivity Motivation TheoryNumerical Tests Conclusions Local RTM

62 62 150 m offset 3.3 3.9 0100 Motivation TheoryNumerical Tests Conclusions Local RTM Depth (km) Offset (m) 0100 Offset (m) Without deconvolution With deconvolution

63 63 600 m offset 3.3 4.4 0600 Motivation TheoryNumerical Tests Conclusions Local RTM Depth (km) Offset (m) 0600 Offset (m) Without deconvolution With deconvolution

64 64 1500 m offset 3.3 4.4 0600 Motivation TheoryNumerical Tests Conclusions Local RTM Depth (km) Offset (m) 0600 Offset (m) Without deconvolution With deconvolution

65 65 Conclusions Subsalt reflectors are accurately imaged near the well with subsalt velocity model only. Diffractors are also imaged. GOM local RTM image agrees with the well reflectivity. Deconvolution imaging condition helps. I lluminates horizontal subsalt reflectors around a vertical well. Motivation TheoryNumerical Tests Conclusions Local RTM

66 66 Outline Overview SSP  VSP Local RTMLocal RTM PSSummary Introduction and overview SSP  VSP  SWP interferometric transform Local reverse time migration: horizontal reflector imaging Local reverse time migration: salt flank imaging with transmitted P-to-S waves Summary

67 67 Outline Local RTM PS Motivation TheoryNumerical Tests Summary Local reverse time migration: salt flank imaging by transmitted P-to-S waves –Motivation –Theory –Numerical Tests Schlumberger VSP Data Set GOM VSP Data Set –Conclusions

68 68 Standard P-to-S Migration x s m(x) ~ s ~ ds G(x|s) Forward source P P S g’ G(x|g’)*D(g’|s)dg’ Backward data S g’ * Converted wave VSP D(g|s) Local RTM PS Motivation TheoryNumerical Tests Summary Salt and overburden velocity model is needed

69 69 Interferometric P-to-S Migration x s P P S D(g|g’) ~ s ~ ds * g’ g D(g’|s) D(g|s) m(x) ~ g’ ~ dg’dg g D(g|g’)G(x|g)G(x|g’) ** Virtual source gather Local RTM PS Motivation TheoryNumerical Tests Summary

70 70 Kirchhoff P-to-S Migration x s m(x) ~ s ~ ds P S g’ e -i  t xg’ D(g’|s)dg’ g’ Converted wave VSP D(g|s) Local RTM PS Motivation TheoryNumerical Tests Summary e -i  t sx P g

71 71 Reduce Time Migration ~( t + t )- ( t + t ) sx xgxgxgxgpickpicksx xgxgxgxg error t sx xg’ =( t + t )- ( t + t ) pickpicksx xg’ x s P S g Converted wave VSP D(g|s) Local RTM PS Motivation TheoryNumerical Tests m(x) ~ s ~ ds e -i  t xg’ D(g’|s)dg’ g’ e -i  (t sx+ t error ) Summary P g

72 72 Outline Local RTM PS Motivation TheoryNumerical Tests Summary Local reverse time migration: salt flank imaging by transmitted P-to-S waves –Motivation –Theory –Numerical Tests Schlumberger VSP Data Set GOM VSP Data Set –Conclusions

73 73 x s P P S m(x) ~ s ~ ds g’ G(x|g’)* D(g’,s) dg’ Backward P G(x|g)* D(g,s)dg Backward S g g’ g * Local Reverse Time Migration Theory Local RTM PS Motivation TheoryNumerical Tests Summary

74 74 Outline Local RTM PS Motivation TheoryNumerical Tests Summary Local reverse time migration: salt flank imaging by transmitted P-to-S waves –Motivation –Theory –Numerical Tests Schlumberger VSP Data Set GOM VSP Data Set –Conclusions

75 75 Depth (km) Offset (km) 10 -1212 0 Schlumberger 2D Isotropic Elastic Model 0 291 shots 287 receivers Local RTM PS Motivation TheoryNumerical Tests Summary

76 76 Depth (km) 10 0 Offset (km) -12 12 0 (a) Ray tracing direct P (c) PPS events (d) Pp events (b) PSS events Depth (km) 10 0 Offset (km) -12 12 0 Aperture by Ray Tracing Local RTM PS Motivation TheoryNumerical Tests Summary

77 77 Direct P PPS PSS Depth (km) Time (s) 8 0 8 VSP CSG X-component VSP CSG Z-component 4 Depth (km) 8 4 Two-component VSP Synthetic Data Set Local RTM PS Motivation TheoryNumerical Tests Summary

78 78 4.5 2.0 km/s(a) P-wave submodel Depth (km) 8.7 6.02.5 1.0 km/s(b) S-wave submodel 4.5 2.0 km/s(c) P background model Depth (km) 8.7 6.0 Offset (km) 0 1.8 2.5 1.0 km/s (d) S background model Offset (km) 0 1.8

79 79 Depth (km) 8.7 6 Offset (km) 0 1.8 (a) Standard Kirchhoff (c) Interferometric migration (IM)(d) Local RTM (b) Reduced-time migration (RM) Depth (km) 8.7 6 Offset (km) 1.8 0 Comparison with Migration Methods Local RTM PS Motivation TheoryNumerical Tests Summary

80 80 Offset (km) 0 1.8 Local RTM without wavefield separation Depth (km) 8.7 6

81 81 Offset (km) 0 1.8 Local RTM with wavefield separation Depth (km) 8.7 6

82 82 Offset (km) 0 1.8 Local RTM using Z component only Depth (km) 8.7 6

83 83 Outline Motivation Theory Numerical Tests Schlumberger VSP Data Set GOM VSP Data Set Conclusions Local RTM PS Motivation TheoryNumerical Tests Summary

84 84 Depth (m) Offset (m) 4878 0 1829 0 GOM VSP Well and Source Location Source @150 m offset 2800 m 3200 m Salt 82 receivers Local RTM PS Motivation TheoryNumerical Tests Summary @600 m offset@1500 m offset

85 85 P-to-S ratio = 2.7 Velocity Profile S Wave P Wave Depth (m) 0 4500 050000 2800 m 3200 m Salt Incorrect velocity model P-to-S ratio = 1.6 Velocity (m/s) Local RTM PS Motivation TheoryNumerical Tests Summary

86 86 Z-Component VSP Data Depth (m) Traveltime (s) 2652 3887 1.23.0 Salt Direct P Reflected P Reverberations Local RTM PS Motivation TheoryNumerical Tests Summary

87 87 X-Component VSP Data Depth (m) Traveltime (s) 2652 3887 1.23.0 Salt Direct P Reflected P ReverberationsDirect S Local RTM PS Motivation TheoryNumerical Tests Summary

88 88 Processing Workflow Original Data Rotate components Pick desired events Median filtering Migration (KM, RM, IM, RTM) Local RTM PS Motivation TheoryNumerical Tests Summary

89 89 Raypath Coverage 2000 4200 0200 Depth (m) Migration of PPS Salt Offset (m) 39 receivers Local RTM PS Motivation TheoryNumerical Tests Summary

90 90 Migration of PPS Salt RMIM 02000 KM 2000 4200 0200 Depth (m) Offset (m) Local RTM PS Motivation TheoryNumerical Tests Summary

91 91 Migration of PPS Salt IM, sediment floodLocal RTM 02000 RM 2000 4200 0200 Depth (m) Offset (m) Local RTM PS Motivation TheoryNumerical Tests Summary

92 92 Depth (km) 3.9 2.9 Offset (m) 0 100 (a) Without deconvolution (b) With deconvolution Offset (m) 0 100 150 m Offset LRM Image

93 93 600 m Offset LRM Image Depth (km) 4.4 2.9 Offset (m) 0 600 (a) Without deconvolution (b) With deconvolution Offset (m) 0 600

94 94 Depth (km) 4.4 2.9 Offset (m) 0 600 (a) Without deconvolution (b) With deconvolution Offset (m) 0 600 1500 m Offset LRM Image

95 95 a) Syntheticb) 150 m offset Reduce time migration c) 600 m offset Reduce time migration Reduce Time Migration Image Salt 2800 m 3200 m Depth (km) 4.5 2.4

96 96 Summary Target oriented! –Only a local velocity model near the well is needed. –Salt and overburden is avoided. –Fast and easy to perform. Source statics are automatically accounted for. Immune to salt-related interbed cross- talk. Local RTM PS Motivation TheoryNumerical Tests Summary

97 97 Summary Introduction and overview SSP  VSP  SWP interferometric transform Local reverse time migration: horizontal reflector imaging Local reverse time migration: salt flank imaging with transmitted P-to-S waves Summary Overview SSP  VSP Local RTMLocal RTM PSSummary

98 98 Acknowledgements Dr. Gerard Schuster and my committee members: Dr. Michael Zhdanov, Dr. Robert smith, Dr. Cari Johnson, Dr. Jianming Sheng for their advice and constructive criticism; Scott Leaney and Hornby Brian for their help on modeling;

99 99 Acknowledgements UTAM friends: –Jianhua Yu and Yonghe Sun on the research; –Jianming Sheng and Min Zhou for their experiences on interferometric imaging; –Zhiyong Jiang and Ruiqing He for their help on classes; –Travis Crosby and all UTAM students for their cheerful attitude; All UTAM sponsors for their support; Family –My parents, brother and sister; Friends –Liyun Ma, Min Zhou, Jun Wang, Shuqian Dong, Chaoxiong Ma, who encouraged me to continue on with my research.

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