Investigating the Midland Basin Well Performance Trends with Machine Learning
Permian Basin well performance has been a hot topic in the industry since 2022 saw the first year-over-year decline in the basin's history. In this analysis, we use our machine learning models to investigate the relative contributions of inventory exhaustion, completions design changes, increased lateral lengths, parent-child degradation, and downspacing on well performance in the Midland Basin. We find that much of the apparent decline is due to artificially high production in 2020 & 2021 due to operator high grading. We also analyze remaining inventory across the major benches and compare to other plays as part of our supply outlook, finding that, while top-tier rock is more drilled than lower-quality rock, the Midland still has years of high-quality inventory remaining.
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.