1. Interferometric Prediction and Least Squares Subtraction of Surface Waves Shuqian Dong and Ruiqing He University of Utah

2. OUTLINE  Motivation: Surface Wave Filtering  Interfer. Surface Wave Theory  Conclusions  Land Field Data Test

3. OUTLINE  Motivation: Surface Wave Filtering  Interfer. Surface Wave Theory  Conclusions  Land Field Data Test

4. Motivation  Problem: Surface waves = strong coherent noise blurs seismogram. Moveout- based filtering not always effective for dispersive waves.  Solution: Interfer. Predict. + Least Squares Subtraction. Accounts for dispersion. Offset (m) Time (s) 0 1.0 0 7200 A CSG with Strong Surface Waves Offset (m) Time (s) 0 1.0 0 7200 A CSG with Strong Surface Waves

5. OUTLINE  Motivation: Surface Wave Filtering  Interfer. Surface Wave Theory  Conclusions  Land Field Data Test

6.  Prediction of multiples by convolution (SRME)  Prediction of Primaries by Crosscorrelation (Interferometry) ABC AB* ⊕BC

7. u (s,g’)= A(s,g’) eikx sg’ u (s,g)= A(s,g) eikx sg u (s,g) u (s,g’) gg’ u(g,g’) u(g,g’) ⊕ = u (s,g) u (s,g’) * eik(x Sg’ = A(s,g) A(s,g’)-xsg )  Predict Surface Waves by Crosscorrelation ⊕g’Sg } xgg’ τ τ

8. AB CA B⊕ B C ⊕ B C + A’ B C B  Predict Surface Waves by Crosscorrelation

9.  Coherent Stacking: surface waves (all src pts = stationary) S gg’ 1 gg’ S2 S N… Incoherent Stacking: primaries Incoherent Stacking: primaries  Coherent Stacking: FS Multiples? Avoid stationary source points Avoid stationary source points ⊕

10. Surface Waves Prediction Offset (m) Time (s) 0 2.003600 Original Data 36000 Time (s) 0 2.0 Offset (m) Predcted Surface Waves 0 Time (s) 2.0 Amplitude 1 0

11. Least Square Matching Filter d (t)Refl.Surf.= d (t) d (t) + Pred.≈ d (t) * f (t) d (t) Refl. d (t) - - * f (t) =

12. Surface Waves Filtering Results Time (s) 0 2.0 Offset (m) 07200 07200 Time (s) 0 2.0 Original Data Filtered Data

13. Time (s) 0 2.0 0 2.0 Offset (m) 0 7200 07200 Results of f-k method Results of interferometric method Result Comparison

14. Conclusions  Preliminary results promising for interfer. Prediction + subtraction surface waves.  Future work: iterative prediction + subtraction.

15. Can Interferometric Prediction+Subtraction work for Irregular 3D Arrays? Answer?: Irregular S. Calif. Earthquake Array Stations (Andrew Curtis, The Leading Edge, 2006) Predicted Surface Waves Station Offset (km) Time (s) Longitude 120 W 115 W 32 N Latitude 38 N Predicted Surface Waves -200200 0 400

16. Acknowledgements We thank the UTAM sponsors for the support of the research.

17. Thanks