Integrated SOM Multi-Attribute Optimization and Seismic Waveform Inversion for Thin Sand Body Characterization: A Case Study of the Paleogene Lower E3d2 Sub-Member in the HHK Depression, Bohai Bay Basin
Thin-bedded beach-bar reservoirs in the continental faulted basins of eastern China hold significant potential, yet pose challenges for unconventional hydrocarbon development due to their thin-layer characteristics and heterogeneity. This study focuses on the Paleogene Lower E3d2 Sub-member in the HHK Depression, Bohai Bay Basin as a case study. We propose an innovative technical framework integrating Self-Organizing Map (SOM) multi-attribute optimization with seismic waveform inversion. Petrophysical analysis demonstrates that waveform-indicated inversion can detect 1.8–3.0 m thin sandstones, achieving a 90.2% mean match rate (95% CI: 87.5–92.7%, n = 12; bootstrap resampling) for training wells and 81.5% (95% CI: 76.8–85.3%, n = 11) for validation wells. By integrating SOM seismic attribute clustering with seismic waveform inversion, we were able to delineate microfacies boundaries with precision, enhancing the visibility of beach-bar sand body distributions. This methodology establishes a new paradigm for thin-bed sandstone prediction in low-well-control areas, providing critical support for geological interpretation and resource evaluation in complex depositional systems.
Authors
- Wei Xu (ORCID: https://orcid.org/0000-0001-7904-9728)
- Rui Liu (ORCID: https://orcid.org/0000-0002-0084-150X)
- Xiaobo Huang (ORCID: https://orcid.org/0009-0000-6211-9531)
- Bin Feng
- Hua Li (ORCID: https://orcid.org/0000-0001-6618-7216)
- Youbin He
- Jing Wang (ORCID: https://orcid.org/0009-0005-3735-734X)
- Dayong Guan
Institutions
- China National Offshore Oil Corporation (China) (CN)
- Yangtze University (CN)
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-05-05
- DOI
- https://doi.org/10.3390/app15095134
- Citations
- 3
- Primary Topic
- Seismic Imaging and Inversion Techniques
- Type
- article
- Field-Weighted Citation Impact
- 5.60
Funders
- National Natural Science Foundation of China
- China National Offshore Oil Corporation
- Yangtze University