1. Establishing Well to Seismic Tie3
Establishing Well to Seismic Tie

2. Establish Well-Seismic Tie
Objectives
Determine key marker that need to be interpreted
Understand seismic response in respect to the wells
Determine the seismic phase
Check the log quality

3. Convolution Model & Polarity Convention
European Normal
European Reverse (SEG Normal)

4. Seismic Bandwidth and Phase
Phase Spectrum
Amplitude Spectrum
The seismic trace is composed of energy that has a range of frequencies.
The seismic wavelet is the result of addition of the sin wave functions at each frequency
Amplitude and phase spectrum are another wavelet representation

5. Seismic Bandwidth and Earth Filter
It is a characteristic of the seismic data that the bandwidth of the input signal is modified by earth filter
Thus shallow targets will generally be characterized by good bandwidth whilst deeper targets will have poorer bandwidth

6. Zero Phase – Minimum Phase Wavelet
Zero Phase Wavelet
Two Minimum Phase Wavelets
European Normal
European Reverse (SEG Normal)
Sound source (explosive, airgun) has minimum phase wavelet
Most wavelet extracted from seismic data have mixed phase
Minimum phase is a condition of a wavelet rather than a description of its shape. Thus this wavelet is NOT desirable for interpretation
Minimum phase is used to describe a ‘causal’ wavelet (ie: no energy before zero) in which the phase is closest to zero but which displays the most rapid build up of energy.
Thus there is a unique minimum phase wavelet for a given amplitude spectrum

7. Zero Phase – Minimum Phase Wavelet
Illustration of phase rotation in respect to zero phase wavelet

8. Wavelet Shape Changes Due To Earth Filter
-120o phase rotated zero phase wavelet
Zero phase wavelet

9. Idealized Wavelet Question:
Which idealized wavelet is suitable for these two different amplitude spectrums….?

10. Effect of Various Processing Step to Wavelet Shape
Processing Steps Affecting Wavelet Shape (Courtesy R.E. White)

11. Zero Phasing and Wavelet Shaping
Whitening (broadening of frequency spectrum)

12. Well-Seismic Tie * Log Calibration Vp (Sonic) d (Density) AI (Vp.d) RC
V2d2 – V1d1
V2d2 +V1d1

13. Wavelet Estimation
20 ms

14. 1 2 3 Wavelet Validation Consistent Wavelet
Wavelet MUST have center of energy
Consistent Wavelet
Synthetic match beyond interval of interest

15. Log Calibration Objective:
To calibrate sonic transit time with travel time from checkshot in order to match with the seismic

16. Log Calibration Calibration Methods: Linear trends with knee points
Spline or polynomial
Resolving differences in seismic and sonic travel times

17. Quantifying Well Tie

18. Reasons For Poor Well Tie
Different propagation paths for sonic and seismic
Relative scales of measurement
Frequency of measurement
Spatial sampling
Error in seismic migration
Problem in log measurement (eg: invasion, cycle skipping)
Bad checkshot value

19. Seismic Resolution and Detection
Temporal vertical resolution (tuning tickness):
Separation by the seismic method of two features which are close together (1/4 wavelength of the signal)

20. Vertical resolution in respect to depth
T = Seismic period (peak to peak or trough to trough
Fd (Dominant frequency) = 1/T * 1000
Tr (Temporal Thickness) = 1/2.31 Fd * 1000
Vertical Resolution = Tr*Vp/2000

21. Which sand is resolved?

22. Seismic Response on different geologic boundary

23. What is the resolution of this seismic data?

24. Temporal Resolution At ‘A’ the two reflections are solved
As the units is thinned the two reflection begin to interfere resulting in a composite response that progressively increases in amplitude to the tuning thickness at ‘B’
Progressive thinning of the unit results in destructive interference and the composite decreases the amplitude
The reflections never get much closer together in time than the tuning thickness
5. For thickness below ‘tuning’ the time separation measured from the trace would greatly over-estimated the thickness
6. Interestingly, the amplitude in the zone below tuning are approximately linearly related to the actual time thickness of the bed
7. Between A and B the time separation is more or less a reasonable guide to thickness

25. Example Of Tuning Phenomenon

26. Thickness Prediction from seismic
Thickness above tuning:
(time thickness (ms)/2000 * (Vp)
Thickness below tuning:
(Utilizing plot between amplitude and temporal thickness) /2000 * Vp

28. Lateral Resolution
Key factors: migration aperture, geometry, fold and sampling

29. Resolution

30. The Danger Of Un-corrected Sonic Log

31. Resolution