Paper
5 July 2024 Detection and estimation of gas hydrates using FWI and inversion with seismic data processing
Yong Deng, Qibin Wu, Guochang Liu
Author Affiliations +
Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 1318430 (2024) https://doi.org/10.1117/12.3032809
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia
Abstract
The detection and estimation of gas hydrates have always posed challenges for geophysicists due to the multiplicity of seismic inversion solutions. In this abstract, we propose a combination of rock-physics modelling, structure-guided multiparameter full waveform inversion (FWI), and seismic inversion techniques to detect and estimate gas hydrates. We develop a rock physical model specifically for gas hydrates in three different occurrence states, tailored to the target area in the Qiongdongnan Basin. And we employ a structure-guided velocity-Q multi-parameter FWI approach, which takes into account the geological structure of the area, to obtain high-precision and high-resolution velocity and Q. Furthermore, we use poststack and amplitude versus offset (AVO) inversion techniques to estimate additional elastic parameters, providing further insights into the subsurface properties. By applying these methods to the detection and estimation of gas hydrates in the Qiongdongnan Basin, we are able to obtain relatively reliable results. These results can be used to determine potential targets for gas hydrate production. Our integrated approach combining rock physics modelling, structure-guided multi-parameter FWI, and seismic inversion techniques proves to be effective in detecting and estimating gas hydrates. This has significant implications for the exploration and exploitation of gas hydrate resources.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yong Deng, Qibin Wu, and Guochang Liu "Detection and estimation of gas hydrates using FWI and inversion with seismic data processing", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 1318430 (5 July 2024); https://doi.org/10.1117/12.3032809
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KEYWORDS
Data modeling

Data processing

Attenuation

Modeling

Signal to noise ratio

Reflectivity

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