How can production forecasting scale across thousands of wells? In this episode of The Novi AI Roundup, we explore how autoregressive and machine learning models are transforming PDP forecasting in the Midland Basin. Drawing from the URTeC 2021 paper “Autoregressive and Machine Learning Driven Production Forecasting – Midland Basin Case Study”, we examine how automated ML workflows learn directly from production history, improve forecast consistency, and enable faster decision-making across large asset portfolios.

This podcast episode is based on the technical paper “Autoregressive and Machine Learning Driven Production Forecasting – Midland Basin Case Study”, authors: I. Gupta, O. Samandarli, A. Burks, D. McMaster, V. Jayaram, D. Niederhut, T. Cross. Download the full paper here.