1. Passive seismic imaging
Brad Artman

2. The conjecture Reminds me of imaging Proof of the matter Synthetics
Real data
Extra Modes
Business case
The road ahead

3. Ambient Noise r1 r2 r1 r1 r1 r2 t lag brad@sep.stanford.edu
1968 Jon Claerbout, Geophysics: “The reflection seismogram from a surface source and a surface receiver is one side of the autocorrelation of the seismogram from a source at depth and the same receiver.” This idea leads to the conjecture that we could create a seismic section by correlation of traces at the surface that record arrivals from a buried source. Realizing that the correlation process removes complicated source functions that may be distributed at any time through the record we hypothesize that we can record for however long our equipment allows to collect sufficient energy.
Orange on the left cartoon is energy: plane waves and rays. It is recorded by all the receivers on the surface. But receiver 2 also records a bounce from the free surface to a subsurface reflector. We don’t know when this happens, but by correlating the traces, we move the energy to zero time, and remove the complicated wave-form that was propagating through the earth. By correlating r1 w/ all others, we build hyperbolas exactly like conventional reflection seismic data. t
lag

4. Raw modeled passive data over a two reflector model
Raw modeled passive data over a two reflector model. Choosing the trace under the red line as the “shot”, we cross-correlate it with all the others to build the shot-panel on the right. Using all the traces as a “shot”, we generate n shot-gathers from n traces. While traces expand to n-squared, the time axis is drastically shortened. The shot-gathers so generated can be migrated just like conventional reflection seismic.
Faint hyperbola at 0.1 seconds is an artifact of my poor modeling. It is the correlation of the two events with themselves. There will be an internal multiple at the same time of opposite polarity in the real world that will cancel that one out. I did not model the effects of multiples. If it’s not strong enough in real life to do so, the greater the velocity or dip contrast of the two reflectors in the shot-panel, the less well the hyperbolas will correlate.

5. The conjecture Reminds me of imaging Proof of the matter Synthetics
Real data
Extra Modes
Business case
The road ahead

6. Shot-Profile Migration
I (x)=Σ U (w,x,s) D (w,x,s) ω z
Realization: If D = U , correlation requirement
of the passive seismic conjecture
is fulfilled in the migration.
Let the wave equation handle the unknown source.
Brad’s conjecture: The correlation in the imaging condition of SP migration may satisfy the correlation needed for building the shot-gathers, and thus obviating that first step. Also, the wave-equation can propagate long weird source functions just as well as short impulsive ones. So let it go, and avoid mistakes in the correlation process.
Since all geophones record the up-coming (U) and down-going (D) wave-fields, I’ll use the raw passive data for both U and D.
Down side = no reduction of time axis from the correlation process, and needs independent method to find a velocity model.
Up side= many fewer FFT’s and faster migrating 1 shot w/ n traces rather than n shots with n traces.

7. The conjecture Reminds me of imaging Proof of the matter Synthetics
Real data
Business case
The road ahead

8. Flow model R U D T T U D T T j j+1 j j j j j+1 j+1 j+1 j+1

9. Shot-profile datuming analogy
R = U D
R = R e
R = U D e
= U e (D e ) 1 *
+i Kz Dz
+i Kz(U) Dz + i Kz(D) Dz
+i Kz(U) Dz
-i Kz(D) Dz

10. Delft datuming

11. The conjecture Reminds me of imaging Proof of the matter Synthetics
Real data
Extra Modes
Business case
The road ahead

12. Finite difference modeled data w/ free surface should provide even more accurate insight.
Modeled by Deyan Dragonov of Delft: 281 random sources were modeled and summed together. This model is better than the other one.

13. 3 reference velocities w/ SSF migration of raw data (Up=Down) wave-fields in standard shot-profile migration.
Raw data looks like TV static

14. Different runs yield slightly different illuminations sometimes if the magnitude of the sources varies a lot.
Only one reference velocity was used: notice poor focus of syncline.

15. Different runs yield slightly different illuminations sometimes if the magnitude of the sources varies a lot.
Only one reference velocity was used: notice poor focus of syncline.

18. The conjecture Reminds me of imaging Proof of the matter Synthetics
Real data
Extra Modes
Business case
The road ahead

19. Artman GeoServices brad@sep.stanford.edu
Moss Landing, CA. 72 phones. 2x2meter array of 8x9 .25m spacing. NOT ENOUGH CHANNELS.
Hoping to get water table- But it was at 3.5 meters: aperture of my lens not big enough. Going back soon with more phones.
Also buried pipe 1 meter down. Hollow void target, 6” diameter, .5m long (probably less: ends not capped).

20. Spectrogram brad@sep.stanford.edu Noise spectrogram during the day –
Cultural noise and wind

21. Active data brad@sep.stanford.edu
Active data for comparison. Pipe anomaly present. Overmigration of hyperbola due to air cavity.
Water table very clear.

22. Enlarged data set brad@sep.stanford.edu
Simply cross-correlating traces w/ this few channels yields no results. If I insert 4 zero-traces between all the active phones, wave-front healing during the migration should interpolate the energy to give a finer-scale result.
Cultural noise (power grid) is predominately below120Hz. With beach 180 – 300 m/s and 2 m offset, I have to low-cut that out anyway to have waves that don’t see my whole array as one station.

23. 5min Night brad@sep.stanford.edu
First look at the pipe. Anomaly at correct location. Not too convincing, should have buried an angled pipe to avoid any doubt. Only 5 min. of data used. Surprisingly short to get results.
Bandpassed, not deconvolved.
Before the migration pushes energy across all of the empty traces, there is lots of noise at the very shallow depths.

24. 5min Night
Deconvolved data

25. 10min Day
Day time, band-passed

26. Crustal scale progress

27. The conjecture Reminds me of imaging Proof of the matter Synthetics
Real data
Extra Modes
Business case
The road ahead

28. Forward Scattering

29. Converted transmission imaging
V (x, z) and V (x, z) p s *
Forward-scattered P to S mode conversion

30. Possibilities Scattering Mode Source Prop. Dir. Source Velocity
Receiver Velocity
Receiver Comp.
FS P-P - P SV
BS P-P +
BS P-S S
BS S-P
BS S-S SH

31. Business Case It’s free and convenient
Provide information to trigger active survey
Low frequency images
including deep crustal information

32. Novel Aspects of LoFS Hydrophone w/ absolute pressure
Tide and wave-height monitoring at rig
Drill/operations noise (SWD)
3-component geophones
vector imaging condition anyone?