2024/10/11 by Pratinav Seth, Michelle Lin, Seth, Pratinav +9 · 1 voice
Computer Science · Engineering · #Aerospace engineering #Drilling and Well Engineering #Engineering #Environmental science #Geology #Oil and Gas Production Techniques #Petroleum engineering #Remote sensing #Reservoir Engineering and Simulation Methods #Satellite #Satellite imagery #cs.CV #cs.LG
paper · pdf · doi:10.48550/arxiv.2410.09032
openalex publication_date 2024/10/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Millions of abandoned oil and gas wells are scattered across the world, leaching methane into the atmosphere and toxic compounds into the groundwater. Many of these locations are unknown, preventing the wells from being plugged and their polluting effects averted. Remote sensing is a relatively unexplored tool for pinpointing abandoned wells at scale. We introduce the first large-scale benchmark dataset for this problem, leveraging medium-resolution multi-spectral satellite imagery from Planet Labs. Our curated dataset comprises over 213,000 wells (abandoned, suspended, and active) from Alberta, a region with especially high well density, sourced from the Alberta Energy Regulator and verified by domain experts. We evaluate baseline algorithms for well detection and segmentation, showing the promise of computer vision approaches but also significant room for improvement.