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SAGE Record 019, Deng et al.

Deng, Z., R. Zhang, L. Gou, S. Zhang, Y. Yue, X. Chang, Y. Wu, Y. Wang, Y. Ni, Z. Yan, T. Gong, H. Wang, F. Feng, Z. Liu, and L. Wu, 2022, Direct shear-wave seismic survey in the Sanhu area, Qaidam Basin, west China: SAGE Record 019, 1 p., <http://sagetech.org/sage_record_019_deng_et_al/>. Southwest Louisiana Geophysical Society (SWLGS) luncheon presentation at SAGE 2022, 23–25 March, Lafayette, Louisiana, and Virtual.

SOUTHWEST LOUISIANA GEOPHYSICAL SOCIETY (SWLGS) LUNCHEON PRESENTATION: Direct Shear-Wave Seismic Survey in the Sanhu Area, Qaidam Basin, West China

Deng, Zhiwen, Rui Zhang*, Liang Gou, Shaohua Zhang, Yuanyuan Yue, Xuejun Chang, Yongguo Wu, Yan Wang, Yudong Ni, Zhihui Yan, Ting Gong, Haili Wang, Faquan Feng, Zhigang Liu, and Long Wu (Asterisk denotes speaker, University of Louisiana at Lafayette; all other authors, Bureau of Geophysical Prospecting, China National Petroleum Corporation, Zhuozhou, China)

The formation containing shallow gas clouds poses a major challenge for conventional P–wave seismic surveys in the Sanhu area, Qaidam Basin, west China, as it dramatically attenuates seismic P–waves, resulting in high uncertainty in the subsurface structure and complexity in reservoir characterization. To address this issue, we proposed a workflow of direct shear-wave seismic (S–S) surveys. This is because the shear wave is not significantly affected by the pore fluid. Our workflow includes acquisition, processing, and interpretation in calibration with conventional P–wave seismic data to obtain improved subsurface structure images and reservoir characterization. To procure a good S–wave seismic image, several key techniques were applied: (1) a newly developed S–wave vibrator, one of the most powerful such vibrators in the world, was used to send a strong S–wave into the subsurface; (2) the acquired 9C S–S datasets initially were rotated into SH–SH and SV–SV components and subsequently were rotated into fast and slow S–wave components; and (3) a surface-wave inversion technique was applied to obtain the near-surface shear-wave velocity, used for static correction. As expected, the S–wave data were not affected by the gas clouds. This allowed us to map the subsurface structures with stronger confidence than with the P–wave data. Such S–wave data materialize into similar frequency spectra as P–wave data with a better signal-to-noise ratio. Seismic attributes were also applied to the S–wave datasets. This resulted in clearly visible geologic features that were invisible in the P–wave data.

Note: Abstract reproduced with permission of the Society of Exploration Geophysicists from Deng et al., 2022, The Leading Edge, https://doi.org/10.1190/tle41010047.1.