FULL-WAVEFORM INVERSION

Transcription

1 FULL-WAVEFORM INVERSION Overview & application to field data Mike Warner Imperial College London

2 Topics Overview of full-waveform inversion Application to an OBC dataset Validation 2

3 Overview of FWI 3

4 Full-Waveform Inversion Method for generating high-resolution high-fidelity models of physical properties in the subsurface Seeks a model which can predict the entire recorded wavefield, wiggle-for-wiggle Has become practical for 3D field datasets within the last few years 4

5 RTM with PSDM model 3600 m depth 5

6 RTM with FWI model 3600 m depth 6

7 Full Waveform Inversion Most of what you know about conventional imaging will not apply to FWI workflows uses low frequencies uses transmitted arrivals iterative inversion from starting model details can be critical does not fail elegantly 7

8 Generic workflow 1. Conventional acquisition, processing, model building & depth imaging 2. Use FWI to improve velocity model in top ~ 2 km of heterogeneous overburden 3. Re-migrate using RTM with the shallow FWI velocity model 8

9 Heterogeneous overburden FWI recovers shallow heterogeneity for deeper depth migration 9

10 Conventional tomography uses travel times uses simplified physics fast, cheap well-established & robust low spatial resolution ~ Fresnel zone ~ λd 10

11 Full-waveform tomography uses the raw wavefield uses the complete physics computationally intensive evolving & not yet robust high spatial resolution ~ wavelength ~ λ /2 11

12 Acquisition Long offsets 3 to 6 times target depth necessary Low frequencies 2 to 3 Hz desirable Many azimuths desirable narrow azimuth possible 12

13 Method 1. Field data, starting model & source 2. Forward model predicted wavefield 3. Form residual wavefield at receivers 4. Back propagate residuals residual wavefield 5. Cross-correlate unscaled model update 6. Step length calculation scaled model update 7. Update model and iterate 13

14 Field example Tommeliten Warner et al (2013) Anisotropic 3D full-waveform inversion. Geophysics, 78, No 2, R59-R80. 14

15 Tommeliten N 15

16 Tommeliten 4-component ocean-bottom cable invert pressure data only Vp model above reservoir shallow gas low velocities high attenuation significant anisotropy 16

17 3D OBC field data acquisition geometry 4C OBC 3 swaths of 8 cables 75 m water depth 6 km cables 25 m receiver spacing 300 m cable spacing 6000 receivers 25 m shot interval 75 m shot-line spacing 100,000 shots full azimuth to 7000 m max offset 11,000 m 180 sq km 17

18 PP PSDM PZ-summed deghosted and demultipled 18

19 PP PSDM PZ-summed deghosted and demultipled 19

20 PP PSDM PZ-summed deghosted and demultipled 20

21 Raw shot record hydrophone only include all ghosts and multiples 21

22 Picking the starting frequency Frequency (Hz) Power (db) raw data amplitude spectrum 22

23 Picking the starting frequency single-frequency phase 2.4Hz 3.0Hz 3.6Hz common receiver gather 23

24 Picking the starting frequency Frequency (Hz) Power (db) start at 3 Hz 45 db 70 raw data amplitude spectrum 24

25 Raw shot record hydrophone only include all ghosts and multiples 25

26 Pre-processing Start from raw field data Do not mute early arrivals Do not remove direct arrival No deghosting No demultiple No debubble No low-cut filter No deconvolution No PZ sum No AGC No divergence correction This raw data can be difficult to obtain 26

27 Pre-processing Mute ahead of first breaks Mute Scholte waves Truncate to 5000 ms Cut frequencies above 8 Hz Delete three quarters of receivers Delete two thirds of sources Delete offsets < 100 m Delete geophones hydrophone only Apply source-receiver reciprocity Most of this is to reduce compute time, and to avoid adding noise into the inversion 27

28 Scholte waves at lowest frequencies hydrophone 28

29 Pre-processing Mute ahead of first breaks Mute Scholte waves Truncate to 5000 ms Cut frequencies above 8 Hz Delete three quarters of receivers Delete two thirds of sources Delete offsets < 100 m Delete geophones hydrophone only Apply source-receiver reciprocity Most of this is to reduce compute time, and to avoid adding noise into the inversion 29

30 Raw shot record hydrophone 30

31 Pre-processed for acoustic FWI hydrophone 31

32 Starting model reflection tomography 32

33 Starting model reflection tomography 33

34 Anisotropy VTI, maximum Epsilon = 20%, maximum Delta = 8% 34

35 Source wavelet Full bandwidth Contractor s wavelet vs Near-source OBH 35

36 Source wavelet Full bandwidth Low-pass filtered Contractor s wavelet vs Near-source OBH 36

37 Inversion parameters Time domain, acoustic 3D, VTI anisotropy Hydrophones only include ghosts and multiples Apply reciprocity sources 80 sources per iteration Six frequency bands from Hz 18 iterations per frequency Each source used once per frequency Amplitude equalisation Conjugate gradients Approximate diagonal Hessian 37

38 Starting model reflection tomography 38

39 FWI model reflection tomography 39

40 Starting model reflection tomography 40

41 FWI model reflection tomography 41

42 FWI results from homogeneous start model 250 m depth horizontal depth slice 42

43 Starting model 1200 m depth 43

44 FWI model 1200 m depth 44

45 Validation 45

46 FWI results from homogeneous start model 250 m depth horizontal depth slice 46

47 FWI results + original PSDM from homogeneous start model 250 m depth horizontal depth slice 47

48 Starting model 1200 m depth well log 48

49 FWI model 1200 m depth well log 49

50 PSDM 1200 m depth well log 50

51 Field data 51

52 Start model Field data Start model data 52

53 FWI model Field data FWI model data 53

54 Match to Synthetics 54

55 Match to reflection geometry can mislead cycle-skipped start model 55

56 56

57 57

58 RTM with PSDM model 3600 m depth 58

59 RTM with FWI model 3600 m depth 59

60 Summary Anisotropic 3D FWI works on field data Needs low frequencies Needs refractions Needs careful QC & validation Can we do better? 60

61 Pitfalls & Practicalities 61

62 Pitfalls local minima cycle skipping inadequate low frequencies inadequate starting model Essential that starting model is not cycle skipped low frequencies high-quality start model rigorous QC 62

63 Local inversion start model misfit best estimate of new model model 63

64 Local inversion misfit local minimum global minimum model the local minimum may be a worse model, but it provides a better match to the data 64

65 Low frequency misfit start model global minimum model observed predicted 65

66 High frequency start model cycle skipped misfit local minimum model observed predicted 66

67 Workflow choose the right problem & acquire the right data determine start frequency build start model + anisotropy check adequacy of model, wavelet & field data pre-process & reduce data volume modelling & inversion strategy run FWI with QA check synthetic against field data check geometry, wells, image gathers, run RTM on broadband reflection data 67

68 FWI strategy low high frequencies smooth rough shallow deep refractions reflections phase amplitude early late arrivals primaries multiples acoustic elastic QC often Test with synthetics use variable sub-set of sources each iteration 68