Operator-specific monthly type wells provide a transparent, repeatable foundation for fair market value (FMV) assessment of undeveloped permits.
Situation
- Three operators held active drilling permits on acreage within the estate.
- No wells had been drilled; all locations were fully undeveloped.
- The estate required forward-value estimates for fair market valuation (FMV).
- Permian development velocity required type wells reflecting current technology and operator behavior.
Challenges
- Basin-average type curves masked material operator-level differences.
- Traditional hyperbolic fitting (Qi, b, Di) imposed unrealistic early-time behavior.
- FMV demanded a transparent, repeatable methodology.
- Oil, gas, and NGL volumes needed to be forecast consistently for future wells.
How AlphaX Sky Helped
- Curated wells by operator to eliminate geology and lateral-length bias.
- Generated AI-driven aggregated monthly type wells capturing real variability.
- Reflected technology improvements across vintages (completion design, stimulation).
- Produced operator-specific EURs and decline profiles for undeveloped locations.
- Exported type wells directly into FMV economic models.
Quantitative Outcomes
- Three operator-specific type wells generated via AI aggregation.
- Laterals standardized at ~2 miles to isolate operator performance.
- Significant EUR spread identified despite near-identical geology.
- Monthly forecasting improved early-time realism and PV accuracy.
- Full-stack forward modeling enabled across oil, gas, and NGL.
Impact
- Estate received an operator-differentiated valuation of undeveloped assets.
- Type wells reflected true operational capability, not curve-fitting artifacts.
- FMV accuracy improved by capturing elevated early-time production.
- Producing and undeveloped assets were integrated in a single unified workflow.
Call to Action
If your team needs type wells that reflect operator performance, not generic hyperbolic curves, AlphaX Sky delivers AI-generated monthly profiles built from real field behavior.