Integrated SOM Multi-Attribute Optimization and Seismic Waveform Inversion for Thin Sand Body Characterization: A Case Study of the Paleogene Lower E<sub>3</sub>d<sub>2</sub> Sub-Member in the HHK Depression, Bohai Bay Basin

Integrated SOM Multi-Attribute Optimization and Seismic Waveform Inversion for Thin Sand Body Characterization: A Case Study of the Paleogene Lower E<sub>3</sub>d<sub>2</sub> 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 E<sub>3</sub>...

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Bibliographic Details
Main Authors: Jing Wang, Dayong Guan, Xiaobo Huang, Youbin He, Hua Li, Wei Xu, Rui Liu, Bin Feng
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
unconventional hydrocarbon exploration
thin-layered sand bodies
beach-bar
self-organizing maps
seismic meme inversion
Online Access:https://www.mdpi.com/2076-3417/15/9/5134
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Summary: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 E<sub>3</sub>d<sub>2</sub> 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.
ISSN:2076-3417

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