Centroid-Frequency-Guided Nonstationary Reflectivity Inversion and Its Application for Top and Bottom Interface Identification of Coalbed Methane Reservoirs

Nonstationary convolution models are widely used as the forward formula of nonstationary seismic reflectivity inversion (NSRI). This forward formula is determined by the convolution of a time-varying wavelet and reflectivity. Previous NSRI algorithms just focus on the estimation of reflectivity according to different sparse regularization strategies. The forward-operator, time-varying wavelet matrix is usually generated using a user-defined constant Q-value. However, the Q-value changes with time and space; therefore, inaccurate reflectivity inversion results will be yielded by the traditional NSRI method. In order to improve the accuracy of the inverted reflectivity, we propose a new forward-operator construction method based on the monotone relationship between the equivalent Q-value (Qe) and centroid-frequency (CF). We first extract CF from the Gabor time-frequency amplitude spectrum of the seismic signal. Then, we can obtain Qe through the CF-Qe template. Hence, the blindness of selecting a Q-value is avoided and a more accurate forward operator can be constructed. Synthetic and field-data examples demonstrate that the proposed method provides a more accurate reflectivity estimation by constructing a more reliable forward operator. Furthermore, the enhanced reflectivity sections enable a clearer delineation of top and bottom interfaces of coalbed methane reservoirs, providing high-resolution seismic support for coal seam interpretation and subsequent mining planning.

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Publication Details

Journal
Applied Sciences
Published
2026-09-14
DOI
https://doi.org/10.3390/app16189117
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Centroid-Frequency-Guided Nonstationary Reflectivity Inversion and Its Application for Top and Bottom Interface Identification of Coalbed Methane Reservoirs

Youyi Shen, Yaju Hao, Lijing Wang, Peng Zhang et al.
Applied Sciences
Seismic Imaging and Inversion Techniques
article

Centroid-Frequency-Guided Nonstationary Reflectivity Inversion and Its Application for Top and Bottom Interface Identification of Coalbed Methane Reservoirs

Youyi Shen, Yaju Hao, Lijing Wang, Peng Zhang, Yinping Dong, Feng Tian
article en

Abstract

Nonstationary convolution models are widely used as the forward formula of nonstationary seismic reflectivity inversion (NSRI). This forward formula is determined by the convolution of a time-varying wavelet and reflectivity. Previous NSRI algorithms just focus on the estimation of reflectivity according to different sparse regularization strategies. The forward-operator, time-varying wavelet matrix is usually generated using a user-defined constant Q-value. However, the Q-value changes with time and space; therefore, inaccurate reflectivity inversion results will be yielded by the traditional NSRI method. In order to improve the accuracy of the inverted reflectivity, we propose a new forward-operator construction method based on the monotone relationship between the equivalent Q-value (Qe) and centroid-frequency (CF). We first extract CF from the Gabor time-frequency amplitude spectrum of the seismic signal. Then, we can obtain Qe through the CF-Qe template. Hence, the blindness of selecting a Q-value is avoided and a more accurate forward operator can be constructed. Synthetic and field-data examples demonstrate that the proposed method provides a more accurate reflectivity estimation by constructing a more reliable forward operator. Furthermore, the enhanced reflectivity sections enable a clearer delineation of top and bottom interfaces of coalbed methane reservoirs, providing high-resolution seismic support for coal seam interpretation and subsequent mining planning.

Applied SciencesVol. 16(18)
Sinopec (China) (CN), Geophysical Survey (RU), East China University of Technology (CN), Ministry of Natural Resources (RW)
National Natural Science Foundation of China, Natural Science Foundation of Jiangxi Province
Openalex Percentile: Top 14%
Seismic Imaging and Inversion Techniques
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