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 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.

The AWD Dataset is released under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License ( https://creativecommons.org/licenses/by-nc/4.0/ ). The satellite imagery for this project was acquired through Planet Labs' Education & Research license, which allows the use of the data in publications and the creation of derivative products related to those publications. However, the raw imagery cannot be shared publicly. This data is for academic use only and should not be used commercially. Proper credit to the current authors, Planet Labs, and the Alberta Energy Regulator is required when using this data.