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Characterization of Natural Gas Hydrate Constrained by Well and Seismic Data in Qiongdongnan Basin

Author

Listed:
  • Han Yu

    (Guangzhou Marine Geological Survey, China Geological Survey, Guangzhou 510700, China)

  • Ju Wang

    (School of Computer Science, Yangtze University, Jingzhou 434000, China)

  • Zhangshu Lei

    (School of Geosciences, China University of Petroleum (Huadong), Qingdao 266580, China)

  • Zenggui Kuang

    (Guangzhou Marine Geological Survey, China Geological Survey, Guangzhou 510700, China)

  • Wei Deng

    (Guangzhou Marine Geological Survey, China Geological Survey, Guangzhou 510700, China)

  • Lei Lu

    (Guangzhou Marine Geological Survey, China Geological Survey, Guangzhou 510700, China)

Abstract

This study investigates the natural gas hydrates within the Qiongdongnan Basin by integrating well-log and seismic data. Through pre-stack inversion and rock physics analysis, key parameters such as P-wave and S-wave impedances were utilized to distinguish hydrate-bearing formations from other geological bodies. A low-frequency model was constructed using the Inverse Distance Weighting (IDW) algorithm to improve the precision of parameter inversion. This study employs a multi-constraint inversion strategy, incorporating hard constraints from multiple wells and soft constraints from geological frameworks, ensuring reliable inversion results. Findings indicate that hydrate reservoirs are characterized by increased wave velocity and density due to hydrate accumulation, providing insights into the spatial distribution and characteristics of hydrates. This research enhances the understanding of hydrate reservoirs and offers valuable data for exploration in the Qiongdongnan Basin.

Suggested Citation

  • Han Yu & Ju Wang & Zhangshu Lei & Zenggui Kuang & Wei Deng & Lei Lu, 2024. "Characterization of Natural Gas Hydrate Constrained by Well and Seismic Data in Qiongdongnan Basin," Energies, MDPI, vol. 17(21), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:21:p:5411-:d:1510176
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