Abstract
This study explored the potential of commonly used machine learning (ML) tools to enhance first-break picking, predict reservoir properties, and achieve accurate reservoir characterization. The findings highlight the versatility and promise of ML-driven methods, which can improve both the speed and accuracy of data processing and interpretation in geophysical contexts.
| Original language | English |
|---|---|
| Title of host publication | EAGE Workshop on Advanced Seismic Solutions for Complex Reservoir Challenges |
| Publisher | European Association of Geoscientists and Engineers, EAGE |
| ISBN (Electronic) | 9789462825369 |
| DOIs | |
| State | Published - 2025 |
| Event | 2025 EAGE Workshop on Advanced Seismic Solutions for Complex Reservoir Challenges - Kuala Lumpur, Malaysia Duration: 29 Apr 2025 → 30 Apr 2025 |
Publication series
| Name | EAGE Workshop on Advanced Seismic Solutions for Complex Reservoir Challenges |
|---|
Conference
| Conference | 2025 EAGE Workshop on Advanced Seismic Solutions for Complex Reservoir Challenges |
|---|---|
| Country/Territory | Malaysia |
| City | Kuala Lumpur |
| Period | 29/04/25 → 30/04/25 |
Bibliographical note
Publisher Copyright:© 2025 EAGE Workshop on Advanced Seismic Solutions for Complex Reservoir Challenges. All rights reserved.
ASJC Scopus subject areas
- Geophysics
- Geochemistry and Petrology