EP 18 · Understanding the Drivers of Parent-child Depletion: A Machine Learning Approach

Why do some child wells succeed, and others fall short? In this episode of The Novi AI Roundup, we explore how machine learning is helping engineers better understand the impact of parent well depletion on infill performance. Drawing from the technical paper “Understanding the Drivers of Parent-child Depletion: A Machine Learning Approach”, we discuss how depletion varies by parent strength, geometry, and timing, and how ML is helping operators design smarter spacing plans and reduce future production losses.This podcast episode is based on the technical paper “Understanding the Drivers of Parent-child Depletion: A Machine Learning Approach”, authors: Dillon Niederhut, Alexander Cui. Download the full paper here.