The Novi AI Roundup

What if your forecasted uplift isn’t real? In this episode of The Novi AI Roundup, we explore how standard machine learning models can mislead engineers by overestimating production drivers due to bias in the data. Drawing from our URTeC 2025 paper “When Numbers Lie: De-Biasing Horizontal Well Production Datasets with Causal Forecasting”, we discuss how causal AI helps separate correlation from ca...

What does inventory look like beyond the Permian? In this episode of The Novi AI Roundup, we explore how machine learning is helping engineers forecast longer-duration inventory across Rockies unconventional plays. Drawing from our URTeC 2025 paper “Using Machine Learning To Forecast Longer Duration Inventory Across Rockies Unconventional Plays”, we discuss how AI models built for variability and...

How much does development design affect production outcomes? In this episode of The Novi AI Roundup, we unpack how small changes in spacing, stacking, and timing can lead to big differences in recovery. Drawing from our URTeC 2025 paper “A Bottoms-Up Analysis of Development Scenarios in the Midland Basin Using Machine Learning”, we explore how engineers are using physics-informed ML to evaluate tr...

In this episode of The Novi AI Roundup, we go beyond traditional metrics like “feet between wells” or “wells per section” to explore a more physical, multi-dimensional way to teach spacing to machine learning models. Drawing from the URTeC 2025 paper “Describing Well Spacing: Dimensionality at Work”, we dive into how techniques like Voronoi tessellations, nonlinear transformations, and causal mode...

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...

How close is too close when spacing horizontal wells? In this episode of The Novi AI Roundup, we break down one of the industry’s most important questions: well spacing. Drawing from our URTeC 2025 paper “Optimizing Well Spacing to Maximize Horizontal Well Performance and Recovery”, we explore how machine learning reveals the balance between tighter spacing, production uplift, and long-term recove...

The unconventional oil and gas industry relies heavily on publicly available production data for environmental impact assessments, economic evaluations, and regulatory decision-making. However, a comprehensive analysis across over 10,000 tight oil wells in four states reveals alarming discrepancies between public and proprietary water production data that fundamentally undermine the reliability of...

While data-driven reservoir characterization has gained traction among operators, most analyses remain constrained to operator-specific acreage or single-basin datasets. This limited scope may introduce systematic bias in feature importance estimation, particularly for geological parameters. This study leverages a comprehensive dataset of 100,000 horizontal wells across seven major U.S. basins to...

The Novi AI Roundup Welcome to The Novi AI Roundup, the podcast that brings you sharp insights, bold conversations, and repurposed gems from our most impactful content at Novi Labs. Whether it's AI-powered forecasting, the latest in energy innovation, or the future of reservoir engineering, we’ve got the mic on what matters. Each episode transforms our internal know-how, blog gold, and field-teste...