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Abstract:
In seismic wave propagation, the high-frequency component and low-frequency component have different attenuating properties with propagating distance, especially in strong attenuating areas. Many time-frequency analyzing tools are used to extract high-frequency component and low-frequency component of stacked seismic data to characterize attenuation quantitatively or qualitatively. However, the stacking operation on pre-stacked seismic data would affect characterizing precision seriously. In order to improve precision and robustness, we propose a qualitative attenuation estimating method for pre-stack seismic data with the help of continuous wavelet transform. This method uses continuous wavelet transform to extract the high-frequency component and low-frequency component from the common reflection point gather data, and adopts the modified best matching seismic wavelet as mother wavelet. The difference between low-frequency component and high-frequency component is used to reflect seismic attenuation qualitatively. The summation of attenuation along offset is adopted to enhance the robustness of estimation, while the amplitude normalization is adopted to reduce the affection of amplitude. The proposed method is applied to a field data which contains 901 CRP gathers. Two wells are located in this area. The results show that the proposed method obtains a seismic attenuation parameter section which accords with drilling results very well. The qualitative seismic attenuation estimating method based on stacked data is also applied to a field data. Compared with the method based on stacked data, the proposed method has better anti-noise ability and is less likely to be affected by amplitude.
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Source :
CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION
ISSN: 0001-5733
Year: 2016
Issue: 7
Volume: 59
Page: 2674-2683
0 . 7 9 5
JCR@2016
0 . 8 4 7
JCR@2020
ESI Discipline: GEOSCIENCES;
ESI HC Threshold:138
JCR Journal Grade:4
CAS Journal Grade:4
Cited Count:
WoS CC Cited Count: 1
SCOPUS Cited Count: 3
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 14
Affiliated Colleges: