EAGE Student E-Lecture: Frequency Decomposition of Seismic Data by Gaynor Paton

EAGE Student E-Lecture: Frequency Decomposition of Seismic Data by Gaynor Paton
Frequency Decomposition and RGB blending are commonly used to aid seismic interpretation. This lecture looks at the three main methods of frequency decomposition and discusses the relative advantages of each technique. It also covers some short case studies showing how the correct technique should be used depending on the interpretation objective. The lecture also covers RGB blending and how this can be used to understand and interpret the frequency response volumes.

[heshamrefayee]

I was interviewed once by Dr. Paton, she is one of the most intelligent women I have ever met. Very well informative lecture, well done!

[GeophysicsInsight]

Very well explained the frequency Decomposition & RGB Blending for seismic interpretation. Thank you.

[sumitverma]

Thanks a lot EAGE and Dr. Paton for uploading this lecture.

[amaliadw]

Finally I know now ... what is a spectral decomposition. Very nice and clear lecture.

[africaplus]

Short, interesting and irreproachable Robust e-lecture! 👊

[bitnahan]

Thanks for your presentation.
It is very helpful to understand the differences of the methods, so I can use those properly.

[rohitarora]

Thanks for the fantastic lecture...very informative....just that at 19.03 you compare two different methods using two different color scales....

[aswinidas]

Can we have more details on usage of frequency decomposition with specific reference working out pay thickness?

[marioxxx]

whats is the basis for defining 3 best frequencies in this lecture 30, 40 and 50 ??? why not 25 35, 45?

[aleksandardzunic]

~ 09:00 - Disagree: "Higher amplitudes at lower frequencies (brown-ish/red-ish)" is the consequence of the interaction of the broad band wavelet with a succession of thin layers of increasing acoustic impedance. In case of succession of layers with interchanging acoustic impedance, amplitudes will be canceled at lower frequencies (below the critical frequency or when lambda is greater than thickness of the layer). Interpretation, based on dominant frequency of the wavelet is erroneous and misleading (such in this case: "thick layer=red / thin layer=blue").