How do you forecast production in basins with limited historical data? In this episode of The Novi AI Roundup, we explore how transfer learning, a cutting-edge machine learning technique, is helping operators unlock the potential of frontier basins. We dive into the challenges of data scarcity, model generalization, and how learnings from mature plays can guide decisions in emerging ones. From the Powder River to beyond, this episode is a must-listen for anyone rethinking where and how we deploy AI in E&P.This podcast episode is based on the technical paper “Can Transfer Learning Be Used to Forecast Production in Frontier Basins? A Case Study from the Powder River Basin”, co-authored by Dillon Niederhut and Gabriel Quintero. The paper was presented at URTeC 2025. Download the full paper here.

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