Establishing Well to Establishing Well to Seismic TieSeismic Tie3

Objectives

Establish Well-Seismic Tie

- Determine key marker that need to be interpreted

- Understand seismic response in respect to the wells

- Determine the seismic phase

- Check the log quality

Convolution Model & Polarity Convention

European Normal European Reverse (SEG Normal)

Seismic Bandwidth and Phase

• 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

Phase Spectrum Amplitude Spectrum

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

Zero Phase – Minimum Phase Wavelet

European Normal European Reverse (SEG Normal)

Zero Phase Wavelet Two Minimum Phase Wavelets

• 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

Zero Phase – Minimum Phase Wavelet

Illustration of phase rotation in respect to zero phase wavelet

Wavelet Shape Changes Due To Earth Filter

-120o phase rotated zero phase wavelet

Zero phase wavelet

Idealized Wavelet

Question:

Which idealized wavelet is suitable for these two different amplitude spectrums….?

Effect of Various Processing Step to Wavelet Shape

Processing Steps Affecting Wavelet Shape (Courtesy R.E. White)

Zero Phasing and Wavelet Shaping

Whitening (broadening of frequency spectrum)

Zero Phasing

Well-Seismic Tie

Log Calibration

Vp (Sonic

)

d (Densit

y)

RC AI (Vp.d)

*

-------------------V2d2 – V1d1V2d2 +V1d1

Wavelet Estimation

20 ms

Wavelet Validation

Consistent Wavelet

1

Wavelet MUST have center of energy

2 3

Synthetic match beyond interval of

interest

Log Calibration

Objective:

To calibrate sonic transit time with travel time from checkshot in order to match with the seismic

Log CalibrationCalibration Methods:

- Linear trends with knee points

- Spline or polynomial

Resolving differences in seismic and sonic travel times

Quantifying Well Tie

Reasons For Poor Well Tie

1. Different propagation paths for sonic and seismic

2. Relative scales of measurement

3. Frequency of measurement

4. Spatial sampling

5. Error in seismic migration

6. Problem in log measurement (eg: invasion, cycle skipping)

7. Bad checkshot value

Seismic Resolution and DetectionTemporal vertical resolution (tuning tickness):

- Separation by the seismic method of two features which are close together (1/4 wavelength of the signal)

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

Which sand is resolved?

Seismic Response on different geologic boundary

What is the resolution of this seismic data?

Seismic

Temporal Resolution

1. At ‘A’ the two reflections are solved

2. 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’

3. Progressive thinning of the unit results in destructive interference and the composite decreases the amplitude

4. 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

Example Of Tuning

Phenomenon

Thickness Prediction from seismic

Thickness above tuning:

(time thickness (ms)/2000 * (Vp)

Thickness below tuning:

(Utilizing plot between amplitude and temporal thickness) /2000 * Vp

Lateral Resolution

Key factors: migration aperture, geometry, fold and sampling

Resolution

The Danger Of Un-corrected Sonic Log

Resolution