Supporting data for a waterflood-front-aware partitioned graph neural network surrogate for reservoir saturation and remaining-oil prediction
Published: 6 September 2026| Version 1 | DOI: 10.17632/6mbghc2rjm.1
Contributor:
zhen zhaoDescription
adds complete 18-date temporal-holdout metrics, temporal and capacity-matched baselines, front-identification sensitivity results, and derived remaining-oil volume metrics. Field-scale spatial prediction arrays and proprietary reservoir data are not included because of confidentiality and data-ownership restrictions.
Files
Institutions
- Northeast Petroleum UniversityHeilongjiang, Daqing
Categories
Petroleum Engineering