A new method to enhance the characterisation of seismically thin beds based on the generalised S transform maximum modulus
Mingfei Fan 1 Shenghe Wu 1 4 Guangyi Hu 2 Jingjing Qu 3 Jiajia Zhang 1
+ Author Affiliations
- Author Affiliations
1 China University of Petroleum – Beijing, 18 Fuxue Road, Changping, Beijing 102249, China.
2 China National Offshore Oil Corporation Research Institute, No. 25, Chaoyangmenbeidajie Road, Dongcheng, Beijing 100027, China.
3 Bureau of Geophysical Prospecting, 189 Fanyangxi Road, Zhuozhou, Hebei 072751, China.
4 Corresponding author. Email: reser@cup.edu.cn
Exploration Geophysics 49(4) 559-571 https://doi.org/10.1071/EG16123
Submitted: 9 October 2016 Accepted: 2 August 2017 Published: 4 October 2017
Abstract
Thin beds are difficult to identify by seismic traces, but the generalised S transform (GST) can be regarded as a time frequency (TF) analysis method for multi-resolution and quantitative interpretations of thin beds. However, even with a strict seismic well tie, there may still be obvious differences between the depth of a thin bed from well log interpretations and the wavelet transform maximum modulus line attribute (WTMMLA) from the seismic trace, and this has limited the application of the TF spectrum in seismic interpretations. Based on theories of the spectral decomposition and the GST, this study investigates how the phase spectrum of the thin bed seismic response and of the GST window function influence the TF spectrum, and a new method for accurate interpretation of thin beds is proposed by which thin beds can be located easily. In addition, concepts involving the ‘three-dimensional (3D) phase distribution’ and ‘TF point spectrum’ are described, which have been proven to be relevant to the TF spectrum, and these ideas may be used to guide the interpretation of the TF spectrum. Real 3D seismic data are presented as a case study to demonstrate the feasibility and validity of the new method, and the relationship between the interpretation from the well log and the GST spectrum turned out to be very good.
Key words: generalised S transform, interpretation, phase spectrum, thin bed, time frequency analysis.
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