From time to time, you will see a vendor describe “AI forecasting” when the underlying capability is AI-assisted decline curve analysis—i.e., using algorithms to select a decline curve method and auto-fit parameters. That distinction matters, because it changes what the tool can and cannot claim.
What AI-assisted DCA actually does
- Searches faster across decline options (Arps, Power Law, Duong, etc).
- Reduces manual knob-turning and analyst-to-analyst variability.
- Still depends on curve choice and fit window—like any DCA workflow.
What AI forecasting is (and why it is different)
AI forecasting is not “picking the best decline.” It is a different approach altogether.
- Uses more than rate-time history by leveraging basin context (location, timing, completion style, operator behavior, interference effects, etc.).
- Does not require forcing the future into an Arps-style family.
- Produces a forecast directly (monthly volumes), without first choosing a decline-curve equation or debating b-factors.
Here is how you can tell
If the output is ultimately: hyperbolic vs harmonic vs exponential (or variants), plus b-factor management, it is automated DCA.
If the output is forward monthly forecasts learned from basin-wide outcomes and focused on volumetric exports, it is AI forecasting.