Unscaled generalized S-transform and its applications on seismic attenuation delineation: A case study in the Ordos Basin, Northwest China

Abstract

Seismic attenuation estimation is an important tool for hydrocarbon identification and reservoir characterization. Conventional time-frequency (TF) methods, particularly the S-transform (ST), are widely applied but suffer from a systematic dominant-frequency shift and fixed TF resolution, which may reduce the accuracy of attenuation analysis. To address these limitations, we introduce the unscaled generalized ST (UGST) and apply it to field seismic data from the Ordos Basin in Northwest China to qualitatively estimate attenuation. The UGST corrects the frequency shift inherent in the standard ST and introduces two tunable parameters that enable flexible adjustment of TF resolution to better match local seismic responses. Application to a three-dimensional seismic dataset demonstrates that the UGST produces TF spectra with improved readability and accurate frequency localization, resulting in a reduction of approximately 10 Hz in dominant frequency error compared to ST. The attenuation attributes derived from UGST show strong correspondence with known gas-bearing intervals, as verified by well-log data. The derived attenuation attributes show strong correspondence with gas-bearing intervals, with anomaly overlap rates exceeding 85% relative to well-log fluid indicators. These results indicate that the UGST provides a robust and effective approach for delineating seismic attenuation, offering practical value for reservoir characterization in exploration geophysics.

Keywords

Seismic attenuation estimation / Time-frequency analysis / Unscaled generalized S-transform / Reservoir characterization

Acknowledgments

None.

Funding

This research was supported by the Science and Technology Projects of Yumen Oilfield Company for 2024–2025 (Grant No. YM2024-001).

Conflict of interest

The authors declare that they have no competing interests.

Author contributions

Conceptualization: Wenlong Jiao, Yongxiang Jiang

Formal analysis: Yongxiang Jiang

Investigation: Jun Yang, Wei Zhao

Methodology: Wenlong Jiao, Naihao Liu

Validation: Jun Yang, Wei Zhao

Writing-original draft: Wenlong Jiao, Wei Zhao

Writing-review & editing: Naihao Liu

Availability of data

Data are available on request through naihao_liu@mail. xjtu.edu.cn.

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