Rapid basin evaluation with convergent models provides faster, more consistent insights for screening and prioritization.
Situation
- An asset in the San Juan Basin was evaluated to support an acquisition decision; engineers had limited basin experience and time to develop a credible assessment.
Challenge
- Traditional DCA workflows make broad sensitivity testing slow and operationally heavy when engineers evaluate assets in a basin they do not know well.
How AlphaX Sky Helped
- Evaluated the asset using basin-scale datasets, not reduced well subsets.
- Applied three independent AI enabled forecasting models to the same PDP and inventory wells.
- Built type curves and basin benchmarks within a unified workflow.
- Tested variables independently and observed convergence across models.
- Generated repeatable and reproducible results as assumptions were adjusted.
Outcome
- Engineers reached confidence through model agreement rather than single-model reliance.
- The asset was contextualized against basin-wide performance without prior basin expertise.
- Decision-makers received a consistent, defensible view suitable for competitive deal evaluation and were able to quickly respond to the RBL lender with their decision.
Call to Action
When entering a new basin, AlphaX Sky delivers basin-scale evaluation with repeatable, convergent forecasts that build confidence across independent engineers.