Poster: ML & AI for Seismic Interpretation
Tracks
Geophysics
Geophysics
Geology
Reservoir Engineering & Integrated Subsurface
Energy Transition & Mining and Infrastructure
Dedicated Sessions
Data and Computer Science
| Thursday, June 13, 2024 |
| 1:30 PM - 2:30 PM |
| Posters Area (Hall E) |
Speaker
Ms Fan Yang
China University of Petroleum(Beijing)
Physics-constrained high-resolution seismic impedance inversion for thin-layer structure characterization
Mr XIONG ZHU
China University Of Petroleum (Beijing)
Formation pressure prediction based on MC dropout convolutional neural network
Hamed Fouladi
Bluware
Interactive ML-Assisted Seismic Interpretation Using Advanced Meta-Labelling
Dr Yuxing Chen
PetroChina Research Institute of Petroleum Exploration and Development
Nonlinear amplitude inversion using Deep Extreme Learning Machine Optimized by Improved Sparrow Search Algorithm
Prof. Zhonghua Ma
Tianjin University of Technology and Education
Seismic Fault Recognition Method Based on Neural Architecture Search
Mr Li Zewei
Bgp
MultiRes-Unet3D: An improved convolutional neural network faults recognition method Introduction
Ms Anjali Dixit
Student
IIT Kanpur, India
Broadband acoustic impedance inversion using seismic multi-attributes and sequential-convolution neural network
Zheng Zhang
Phd Student
China University Of Geosciences
3D Seismic Fault Detection with Barely Supervised Learning and Fault Orthogonal Annotation
Dr Jiankun Jing
China University of Geosciences
CNN-based intracratonic strike-slip fault detection by generating a realistic seismic training data set
Mr Zhi Qiang Zhang
Tianjin Ltd.
The Application of multi-directional phase attributes in analysis of salt identification-A Case study in Laizhouwan Sag
Mr Shiyou Liu
China University Of Petroleum (east China)
Impedance inversion based on TransUnet constrained by seismic facies
Mr Cao Song
100086
School of Automation, Tsinghua University
Seismic Impedance Inversion Based on Conditional Diffusion Probabilistic Model
