How an AI forecasting audit provided new insights for a PE fund evaluating a portfolio company proposal.
Situation
- A private equity firm evaluated a drilling proposal submitted by a portfolio company.
- Standard practice required parallel analyses by the operator, a portfolio-selected third party, and the PE firm—an expensive, time-consuming process with inherent selection and methodology bias.
- The dataset combined Enverus data with proprietary portfolio-company inputs and covered ~400 wells.
Challenge
- Prior analyses reduced the dataset and relied on traditional DCA workflows, including aggregate-then-forecast methods applied to normalized historical production.
- Different tools (DCA software and Excel models) produced inconsistent results, and individual well decline behavior was not preserved.
How AlphaX Sky Helped
- AlphaX Sky retained the full 400-well dataset, eliminating discretionary well selection.
- Independent AI models forecasted oil, gas, and water for every well individually.
- Type wells were constructed where each underlying well was forecasted before being aggregated, consistent with best practices.
- A minimum decline was applied at the type well level.
Outcome
- The AI type wells generated EURs were within 5% of the original evaluation.
- The shape of the type wells generated by AlphaX Sky were significantly different enough to impact value.
- The PE fund was able to use this information to better assess effect on early time performance of the type well.
Call to Action
When capital approval is at stake, AlphaX Sky delivers a repeatable and reproducible, AI-driven verification layer.