1. 3D Tomography using Efficient Wavefront Picking of Traveltimes Abdullah AlTheyab and G. T. Schuster King Abdullah University of Science and Technology (KAUST) 1

2. Outline Introduction Areal Picking 3D Tomography using Areal Picks Conclusion 2

3. Introduction For conventional acquisition geometry, receiver lines are sparse. Picking is done on time- offset sections. first-arrivals x y t 3

4. Field Data Example 4 3D OBS data parameters: – 234 OBS stations – 129 source-lines – 50m inline spacing – 400m OBS spacing – 40-50m water depth Source boat sail lines Receiver stations

5. Human picking time 30,186 sections to pick, each with 360 receivers. Estimated picking time: – 2 section/minute → 251hrs – 8 hr/day: 31 days 5 12 km 0 3 Time [sec] CRG Shingling Low SNR

6. Quality Control and Cycle-skipping 12 km 0 3 Time [sec] Shingling Traveltime [sec] Traveltime Map 14 2 Distance [km] 1 3 Shot 73Shot 74Shot 75 6

7. Memory Footprint The size of the data is 80 GB (at 4ms sampling, after windowing). Interactive picking software require: – Large memory, – Swapping to hard drives. Memory access pattern for QC is complex. 7

8. Conventional Picking Approach Disadvantages: 1.Large human piking time (31 days) 2.Laborious to QC and correct picks 3.Large memory footprint (80 GB) 8

9. Outline Introduction Areal Picking 3D Tomography using Areal Picks Conclusion 9

10. Areal picking For conventional acquisition geometry, receiver lines are sparse. Picking is done on time- offset sections. first-arrivals x y t 10

11. x y t Areal picking For dense-receiver acquisition geometry We propose picking on time- slices (Areal Picking). 11

12. Areal picking For dense-receiver acquisition geometry We propose picking on time- slices (Areal Picking). y t x 12

13. Areal picking For dense-receiver acquisition geometry We propose picking on time- slices (Areal Picking). y t x 13

14. Areal picking For dense-receiver acquisition geometry We propose picking on time- slices (Areal Picking). y t x 14

15. Areal picking: Interpolation We implemented a program that does real-time interpolation. 15 Cartesian picks Polar interpolation Continuous Polygon Picks are interpolated in polar-coordinates.

16. Field Data Example 2 4 y[km] 14 x [km] 19 4 Time slice @ 0.8 sec 16

17. Field Data Example 2 4 y[km] 14 x [km] 19 4 Time slice @ 0.8 sec 17

18. Field Data Example y[km] 14 x [km] 19 4 Time slice @ 2.4 sec 18

19. Field Data Example y[km] 14 x [km] 19 4 Time slice @ 2.4 sec 19

20. Field Data Example: Human picking time 20 200 ms time-slice spacing for 5 Hz FWI. 234 shots x 15 slices/shot= 3,510 slices (vs. 30,186 sections) to pick. Estimated picking-time: – @2 slices/minute: 30 hrs – @8 hr/day: 4 days (vs. 31 days)

21. Field Data Example: Quality Control Polygon must not cross. y[km] 14 x [km] 19 4 Time slice @ 2.4 sec 21

22. Field Data Example: Quality Control Min Apparent velocity Max 22 Detect mispicks. Apparent Velocity Map Explore regional trend

23. Field Data Example: Memory footprint 80 GB → Slicing for 5Hz FWI → 2 GB Slices are spaced at ½ of the shortest period. 23

24. Outline Introduction Areal Picking 3D Tomography using Areal Picks Conclusion 24

25. Polygon resampling y[km] 14 x [km] 19 4 Picked Traveltime Map Regularized Traveltime Tomography 0 3 Traveltime [sec] 25

26. Tomography using Areal Picks y[km] 14 x [km] 19 4 Picked Traveltime Residual Regularized Traveltime Tomography -0.1 0.1 Residuals [sec] 26

27. Tomography using Areal Picks Cycle skipping Count Traveltime Error [sec] -0.50.10.5-0.10 Traveltime Error Histogram 27

28. Final Traveltime Tomogram 28 0 3.5 10 depth slice x [km] y [km] 10 inline xline 0 z [km] y [km] 0 15004500 Velocity [m/s] 018 Structural cross-section

29. Field Data Example: Waveform Comparison 29 12 km 0 3 Time [sec] Observed

30. Field Data Example: Waveform Comparison 30 12 km 0 3 Time [sec] Calculated

31. Field Data Example: Waveform Comparison 31 12 km 0 3 Time [sec] Observed

32. Field Data Example: Waveform Comparison 32 12 km 0 3 Time [sec] Calculated

33. Field Data Example: Waveform Comparison 33 12 km 0 3 Time [sec] Observed

34. Field Data Example: Waveform comparison 34 12 km 0 3 Time [sec] Calculated

35. Field Data Example: Waveform Comparison 35 12 km 0 3 Time [sec] Observed

36. Field Data Example: Waveform Comparison 36 12 km 0 3 Time [sec] Calculated

37. Outline Introduction Areal Picking 3D Tomography using Areal Picks Conclusion 37

38. Conclusions Areal picking allows for building 3D tomograms in reasonable time. Advantages of areal picking: – About 70-90% reduction in human picking time (31 vs. 4 days) – Easier QC and correct mispicks – Much lower memory footprint (80 GB vs. 2 GB) 38

39. Thank you Acknowledgments: Pemex for providing the data. Sponsors of CSIM Saudi Aramco for supporting the FWI project. Research Computing at KAUST. 39