Alberta Wells Dataset: Pinpointing Oil and Gas Wells from Satellite Imagery (Papers Track)
Pratinav Seth (Arya.ai); Michelle Lin (Mila - Quebec Artificial Intelligence Institute); Brefo Dwamena Yaw (Aya data); Jade Boutot (McGill University); Mary Kang (McGill University); David Rolnick (McGill University)
Abstract
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 high-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 and room for improvement.