Detection of fluvial sand systems using seismic attributes and continuous wavelet transform spectral decomposition: case study from the Gulf of Thailand

2014 ◽  
Vol 35 (2) ◽  
pp. 105-123 ◽  
Author(s):  
Mirza Naseer Ahmad ◽  
Philip Rowell ◽  
Suchada Sriburee
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Spectral Decomposition ◽  
Seismic Attributes ◽  
Gulf Of Thailand ◽  
Continuous Wavelet ◽  
The Gulf Of Thailand

Improving reservoir geometry by integrating continuous wavelet transform seismic attributes

2012 ◽  
Author(s):  
Marcilio Castro de Matos ◽  
Oswaldo Davogustto ◽  
Carlos Cabarcas ◽  
Kurt Marfurt
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Seismic Attributes ◽  
Continuous Wavelet ◽  
Reservoir Geometry

scholarly journals On alternative wavelet reconstruction formula: a case study of approximate wavelets

2014 ◽  
Vol 1 (2) ◽  
pp. 140124 ◽  
Author(s):  
Elena A. Lebedeva ◽  
Eugene B. Postnikov
Keyword(s):  
Wavelet Transform ◽  
Wide Class ◽  
Continuous Wavelet Transform ◽  
Morlet Wavelet ◽  
Continuous Wavelet ◽  
Reconstruction Formula ◽  
Physical Processes ◽  
Admissibility Condition ◽  
Oscillatory Dynamics

The application of the continuous wavelet transform to the study of a wide class of physical processes with oscillatory dynamics is restricted by large central frequencies owing to the admissibility condition. We propose an alternative reconstruction formula for the continuous wavelet transform, which is applicable even if the admissibility condition is violated. The case of the transform with the standard reduced Morlet wavelet, which is an important example of such analysing functions, is discussed.

Multiattribute Seismic Analysis With Fractal Dimension and 2D and 3D Continuous Wavelet Transform

2014 ◽  
Vol 17 (04) ◽  
pp. 436-443 ◽  
Author(s):  
Puneet Saraswat ◽  
Vijay Raj ◽  
Mrinal K. Sen ◽  
Arun Narayanan
Keyword(s):  
Fractal Dimension ◽  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Seismic Data ◽  
Seismic Analysis ◽  
Seismic Attributes ◽  
Structural Features ◽  
Primary Concern ◽  
Continuous Wavelet ◽  
Salt Domes

Summary The 3D post-stack seismic attributes provide an intuitive and effective way of using seismic volumes for reservoir characterization and development, and further identification of exploration targets. Some of the seismic attributes can aid in the precise prediction of the geometry and heterogeneity of subsurface geological settings. These also can provide useful information on petrophysical and lithological properties when combined with well-log information. There exist numerous seismic attributes that provide a unique interpretation on some aspects of subsurface geology. Of these, the proper demarcation of structural features— such as location and edges of faults and salt domes, and their throw and extent—always has been of primary concern. In this paper, we propose new multiattribute seismic algorithms by using fractal dimension and 2D/3D continuous wavelet transform (CWT). The use of higher-dimensional wavelets incorporates information from the ensemble of traces and can correlate information between neighboring traces in seismic data. The spectral decomposition that is based on the CWT aids in resolving various features of geological interest at a particular scale or frequency, which, when rendered with fractal attribute, demarcates the boundaries between those. We apply these two algorithms separately to a seismic amplitude volume and co-render output volumes together with some weights to yield a final attribute volume incorporating information from the aforementioned algorithms. We demonstrate the efficacy of these two algorithms in terms of the resolution and proper demarcation of various geological structures on real seismic data. The application of these algorithms results in better illumination and proper demarcation of various geological features such as salt domes, channels, and faults, and it illustrates how these simple tools can help to extract detailed information from seismic data.

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