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| Amplitude ratio average method in frequency domain for Q estimation of extrinsic attenuation based on Taylor series expansion with different orders |
| ZHANG Jin1,2, WANG Yanguo2,3, LAN Huitian4, ZHANG Guoshu5, PAN Yeli2 |
1. Engineering Research Center for Seismic Disaster Prevention and Engineering Geological Disaster Detection of Jiangxi Province, Nanchang, Jiangxi 330013, China;
2. School of Geophysics and Measurement-Control Technology, East China University of Technology, Nanchang, Jiangxi 330013, China;
3. State Key Laboratory of Nuclear Resources and Environment, East China University of Technology, Nanchang, Jiangxi 330013, China;
4. Exploration and Development Research Institute of Daqing Oilfield Company, Daqing, Heilongjiang 163712, China;
5. School of Nuclear Science and Engineering, East China University of Technology, Nanchang, Jiangxi 330013, China |
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Abstract In the actual quality factor Q estimation， it is prone to have a large estimation error due to factors such as frequency band selection， wavelet superposition， noise interference， and extrinsic attenuation. Thus， the amplitude ratio average method in the frequency domain （FARA） for Q estimation based on Taylor series expansion with different orders considering extrinsic attenuation is presented. Firstly， the continuous multiplication of the amplitude ratio in the reference frequency band is utilized to eliminate the effect of extrinsic attenuation. Then， based on the 1st-4th order Taylor series expansion expression of the amplitude factor at the reference frequency point， the single-frequency point Q estimation formula for the seismic records with extrinsic attenuation is derived. Secondly， the combination of high and low reference frequency bands is adopted to weaken the impact of reference frequency bands. Finally， the average processing of all frequency points average in dominant frequency bands is leveraged to improve the algorithm’s stability. The model test shows that the combination of high and low reference frequency bands can significantly improve the Q estimation accuracy of this method， and the proposed method is less sensitive to the time difference， time window， and noise interference than the logarithmic spectral area double difference （LSADD） method. The example application shows that the Q value estimated by the FARA method with different orders has good consistency， with greater overall Q value than that of the LSADD method. This is consistent with the model test results， indicating that the Q value estimated by the FARA method is more reliable.
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Received: 17 October 2022
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2023, Vol. 58 
