JpGU-AGU Joint Meeting 2026

Presentation information

[E] Poster

S (Solid Earth Sciences ) » S-RD Resources, Mineral Deposit & Resource Exploration

[S-RD28] New Developments on Unconventional and Sustainable Resources

Sun. May 24, 2026 5:15 PM - 7:00 PM Poster Hall (Exhibition Hall 7&8, Makuhari Messe)

5:15 PM - 7:00 PM

[SRD28-P02] Machine Learning-Based Integrated Well-Seismic Prediction Method for Sandbody Characterization and Fracture Probability in Tight Sandstone Reservoirs: A Case Study from the Xu-3-3 Submember of the Xujiahe Formation in the Zitong Area, Sichuan Basin

*sheng min huang1 (1. Southwest Petroleum University)

Keywords:Tight Sandstone Reservoir, Sand Body Characterization, Fracture Probability Prediction, Integrated Well-Seismic Machine Learning, Xujiahe Formation