Performance of Continuous Wavelet Transform over Fourier Transform in Features Resolutions  

作　　者：Michael K. Appiah Sylvester K. Danuor Alfred K. Bienibuor Michael K. Appiah;Sylvester K. Danuor;Alfred K. Bienibuor(Department of Physics, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana;Department of Chemical Sciences, University of Energy and Natural Resources, Sunyani, Ghana)

机构地区：[1]Department of Physics, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana [2]Department of Chemical Sciences, University of Energy and Natural Resources, Sunyani, Ghana

出　　处：《International Journal of Geosciences》2024年第2期87-105,共19页地球科学国际期刊（英文）

摘　　要：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.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.

关 键 词：Continuous Wavelet Transform (CWT) Fast Fourier Transform (FFT) Reservoir Characterization Tano Basin Seismic Data Spectral Decomposition 

分 类 号：P31[天文地球—固体地球物理学]