This study presents a comparative analysis of two
image enhancement techniques, Continuous
Wavelet Transform (CWT) and Fast Fourier Transform (FFT), in the context
of improving the clarity of high-quality 3D seismic data obtained from the Tano
Basin in West Africa, Ghana. The research focuses on a comparative analysis of
image clarity in seismic attribute analysis
to facilitate the identification of reservoir features within the subsurface
structures. The findings of the study indicate that CWT has a significant
advantage over FFT in terms of image quality and identifying subsurface
structures. The results demonstrate the superior performance of CWT in
providing a better representation, making it more effective for seismic
attribute analysis. The study
highlights the importance of choosing the appropriate image enhancement technique based on the specific
application needs and the broader context of the study. While CWT provides
high-quality images and superior performance in identifying subsurface
structures, the selection between these methods should be made judiciously,
taking into account the objectives of the study and the characteristics of the
signals being analyzed. The research provides valuable insights into the
decision-making process for selecting image enhancement techniques in seismic
data analysis, helping researchers and practitioners make informed choices that
cater to the unique requirements of their studies. Ultimately, this study
contributes to the advancement of the field of subsurface imaging and
geological feature identification.
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