Title: Unraveling the Drivers of Parent-Child Depletion with Machine Learning
Abstract: Parent-child depletion remains one of the toughest challenges in unconventionals, impacting development planning, capital expenditures, and asset-level returns. In this talk, we will delve into the intricacies of parent-child, leveraging over six years of data science research to dissect the factors influencing infill performance. Our analysis evaluates the relative contributions of variables such as time, distance, produced volumes, and completions designs to parent-child interactions. In addition to covering parent-child calculations and feature engineering, we will describe how a causal inference framework can disentangle the impact of parent depletion from geological or completions changes over time. Attendees will gain an understanding of recent parent-child trends, key data observations, and real-world case studies that illuminate successful mitigation strategies.
Bio: Ted Cross is Vice President of Product Management at Novi Labs, an Austin-based oil and gas data analytics business. At Novi, Ted drives company strategy, sets the software development roadmap, and works with engineering and data science teams to build compelling analytics tools. Prior to joining Novi, Ted worked as a geologist for ConocoPhillips in a range of roles including Williston Basin development, Lower 48 exploration, global new ventures, and deepwater Gulf of Mexico exploration. He received a Master’s in Geology from the University of Arizona, specializing in thrust belts and foreland basins, and a Bachelor’s in Geology from the University of Texas at Austin.
