High-precision full-waveform inversion velocity modeling and broadband processing for a deepwater exploration of the South China Sea

Abstract

In deepwater fields, drilling costs are extremely high, and the “one sand, one well” situation is common, in which a single well must control an overly large area of the gas field. Structural accuracy decreases in areas distant from the well locations, making gas reservoir prediction and sand body delineation challenging due to the limited resolution of seismic data. To address these challenges, this study applied high-precision full-waveform inversion (FWI) velocity modeling and broadband imaging technology in a deepwater exploration of the South China Sea. In the preprocessing stage, based on the geological challenges and features of the acquired seismic data, we selected appropriate signal-processing methods and optimized the algorithms and parameter sets, successfully developing a customized broadband processing workflow specifically tailored for deepwater applications. The entire broadband processing sequence effectively supported subsequent FWI modeling. During the imaging stage, FWI was successfully applied for the 1st time in the deepwater of the South China Sea. Together with Q pre-stack depth migration, this integrated approach effectively addressed challenges in structural depth prediction and significantly improved imaging resolution. This study provided real-time support for gas field development and optimized the well placement for deepwater development.

Keywords

Deepwater / Low-frequency noise attenuation / Broadband processing / Full-waveform inversion

Acknowledgments

None.

Funding

None.

Conflict of interest

The authors declare that they have no competing interests.

Author contributions

Conceptualization: Wei Liu, Jie Cui, Yi Liao

Formal analysis: Ning Zhang

Investigation: Guo Dong Zhang

Methodology: Rong Li, Lian Lian Liu

Visualization: Zi Jing Gong, Jie Cui, Miaoyang Yuan

Writing-original draft: Wei Liu, Jie Cui, Zi Jing Gong

Writing-review & editing: Yi Liao, Ning Zhang, Guo Dong Zhang, Rong Li, Lian Lian Liu, Miaoyang Yuan

Availability of data

Data will be made available on request to the All data analyzed have been presented in the paper.

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