Noble.AI — surrogate reservoir modeling
Physics- and chemistry-informed AI on sparse data: fast what-if analysis that works alongside your existing simulators.
Noble.AI in brief
What it does
- Physics-Informed Reservoir Analytics: Integrates field, geological, petrophysical, and production data with physics-constrained AI to validate models, estimate recovery, and assess injector–producer connectivity.
- Static QC, Saturation & Reserves: Automates geological consistency checks, reconciles saturation vs. production, and generates P1/P2/P3 polygons for layer-level volume estimation.
- Waterflood & Production Engineering: Identifies layer-specific connectivity, sweep efficiency issues, and bypassed zones; automates well diagnostics.
Results
- Cut reservoir model calibration time by >1,000×, enabling rapid scenario evaluation and more confident field development decisions. Vendor-reported
- Improve asset performance and recovery through optimized materials, surfactants, polymers, and operating conditions, informed by physics- and chemistry-based modeling. Vendor-reported
- Increase R&D productivity by up to 20×, unlocking greater throughput without expanding headcount. Vendor-reported
Gala, D., Becker, G., Kaul, K., DallAqua, M., Hegde, A., Moisselin, S., Fuda, C., Doraiswamy, S., Verma, V., and Wu, X. 2023. "AI-Powered, Lightning-Fast Production Modeling of Multi-Well and Multi-Bench Unconventional Development." SPE-214818-MS, SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 16–18 October 2023. https://doi.org/10.2118/214818-MS (opens in a new tab)
(Co-published by ExxonMobil and Noble AI.)
The follow-on ADIPEC 2025 paper SPE-229440-MS reports a multi-scenario history match in ~2.5 hours versus ~160 hours with a conventional simulator. Vendor-reported
Figures marked Vendor-reported are published by Noble.AI and not verified by K'nexion.