Machine Learning Powered Multi-Tier of Fracture Imaging: A Case Study
This is the poster presentation prepared for 2024 Geothermal Rising Conference, October 27-30, 2024, Waikoloa, HI. The poster is part of the LDRD project CS-GE^2 to demonstrate the multiple-tier fracture imaging analysis for geothermal reservoir applications.
Authors
- MacKenzie Mark‐Moser (ORCID: https://orcid.org/0000-0001-5138-5527)
- J. Alexandra Hakala (ORCID: https://orcid.org/0000-0003-3325-6160)
- Mark McKoy
- Abhash Kumar (ORCID: https://orcid.org/0000-0002-8254-6378)
- Dustin M. Crandall (ORCID: https://orcid.org/0000-0001-7328-9464)
- Jeffrey Nguyen
- David Vaughn (ORCID: https://orcid.org/0000-0002-5942-7477)
- Huihui Yang (ORCID: https://orcid.org/0000-0003-1976-0731)
- Luciane Cunha (ORCID: https://orcid.org/0000-0002-1268-2403)
- Diego González (ORCID: https://orcid.org/0000-0001-9154-270X)
- Gang Liu (ORCID: https://orcid.org/0000-0002-3444-3649)
- Jay Chen
- Scott Beautz
- Saif Qawasmeh
Institutions
- Oak Ridge Associated Universities (US)
- National Energy Technology Laboratory (US)
- Oak Ridge Institute for Science and Education
Publication Details
- Published
- 2024-10-27
- DOI
- https://doi.org/10.2172/2477230
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00