A machine learning framework for seismic facies mapping of sediment input in subduction zones using reflection amplitudes from 2D profiles: a case study in the Nankai Trough, Japan

Paul Caesar Mason Flores

Presentation information

[E] Oral

S (Solid Earth Sciences ) » S-CG Complex & General

[S-CG55] Oceanic plate as inputs to subduction zone and the subduction initiation

Thu. May 28, 2026 9:00 AM - 10:30 AM Convention Hall (CH-B) (International Conference Hall, Makuhari Messe)

Chairperson:Ishizuka Osamu(Geological Survey of Japan, AIST), Akamatsu Yuya(Japan Agency for Marine-Earth Science and Technology), Zhang Jin(Texas A&M University College Station)

9:45 AM - 10:00 AM

[SCG55-04] A machine learning framework for seismic facies mapping of sediment input in subduction zones using reflection amplitudes from 2D profiles: a case study in the Nankai Trough, Japan

*Paul Caesar Mason Flores¹, Gou Fujie¹, Kazuya Shiraishi¹, Yasuyuki Nakamura¹, Gaku Kimura¹, Jun Su¹, Ryoichiro Agata¹, Shuichi Kodaira¹ (1. Japan Agency for Marine-Earth Science and Technology)

Keywords:seismic facies, machine learning, sediment input, seismic reflection