Kim Anastasiia, Kadeethum Teeratorn, Downs Christine, Viswanathan Hari S, O'Malley Daniel
Los Alamos National Laboratory, Los Alamos, New Mexico, 87545, USA.
Sandia National Laboratory, Albuquerque, New Mexico, 87185, USA.
Sci Data. 2024 Sep 17;11(1):1005. doi: 10.1038/s41597-024-03820-0.
Orphaned wells are wells for which the operator is unknown or insolvent. The location of hundreds of thousands of these wells remain unknown in the United States alone. Cost-effective techniques are essential to locate orphaned wells to address environmental problems. In this paper, we present a dataset consisting of 120,948 aerial images of recently documented orphan wells. Each of these 512 × 512 images is paired with segmentation masks that indicate the presence or absence of such well. These images, sourced from the National Agriculture Imagery Program, cover the continental United States with spatial resolutions ranging from 30 centimeters to 1 meter. Additionally, we included negative examples by selecting locations uniformly across the United States. Accompanying metadata includes the IDs and spatial resolution of the original images, which are available for free through the United States Geological Survey, and the pixel coordinates of documented orphaned wells identified in these images. This dataset is intended to support the development of deep-learning models that can help locating undocumented orphan wells from such imagery, thereby blunting the environmental damage they do.
废弃油井是指那些运营者身份不明或已破产的油井。仅在美国，就有数十万口此类油井的位置不明。具有成本效益的技术对于定位废弃油井以解决环境问题至关重要。在本文中，我们展示了一个数据集，该数据集由120,948张最近记录的废弃油井的航拍图像组成。这些512×512的图像每张都配有分割掩码，以表明此类油井的存在与否。这些图像源自国家农业影像计划，覆盖美国大陆，空间分辨率从30厘米到1米不等。此外，我们通过在美国各地均匀选择位置来纳入负样本。随附的元数据包括原始图像的ID和空间分辨率（可通过美国地质调查局免费获取）以及在这些图像中识别出的已记录废弃油井的像素坐标。该数据集旨在支持深度学习模型的开发，这些模型有助于从此类图像中定位未记录的废弃油井，从而减轻它们造成的环境破坏。
