TN966 : Buried channel¬ identification in 3D seismic data using multi- resolution edge detection methods
Thesis > Central Library of Shahrood University > Mining, Petroleum & Geophysics Engineering > MSc > 2020
Authors:
Hassan Khasraji Nezhad [Author], Amin Roshandel Kahoo[Supervisor], Mehrdad Soleimani Monfared[Supervisor], Mohammad Radad[Advisor]
Abstarct: Seismic data interpretation reveals properties of the subsurface structures, further geological or exploration investigations. Buried channels are desired exploratory targets for petroleum reservoir exploration, drilling concerns or geological investigations appropriate for. Therefore, it is required to precisely identify geometry of buried channels through seismic data interpretation. The continuous wavelet transform (CWT) is a spectral discrete transform method for non-stationary signal analysis to enhance resolution of seismic data both in time and frequency domains. In the presented study, we propose a strategy for precise identification of buried channels using vast number of time-frequency seismic attributes on 3D seismic data. Hence, initially spectral decomposition by the CWT method was performed on 20, 25, 30, 35 and 40 Hz frequency sections. Subsequently, related attributes, such as energy, instantaneous amplitude, average root mean square, Prewitt and Grubbs filters, similarity, semblance, and grey-level covariance matrix attributes were extracted. The most favorable results then were selected to be integrated and provide new attribute through RGB composition. This integration was performed both for single frequency and multi-frequency sections. Result of applying the proposed strategy on the selected dataset could image boundaries of the buried channel as well as its internal texture. The final attribute model reveals that the proposed strategy could be considered as an alternative to the conventional procedure of buried channel identification. Also, for combining horizons containing more than three numbers, the frequency analysis spectral decomposition of continuous wavelet transform (along with the application of the above markers) PCA method has been used. With both combinations, we were able to observe the internal texture of the buried channel differently from its outer texture. As a result, the boundaries of the buried channel are clearly distinguishable from other points. In addition, the crevasse splay of the buried canal is more clearly visible.
Keywords:
#Seismic attribute #RGB composition #CWT #attribute combination #buried channel #PCA Keeping place: Central Library of Shahrood University
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