{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T14:15:30Z","timestamp":1776867330403,"version":"3.51.2"},"reference-count":60,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,3,16]],"date-time":"2021-03-16T00:00:00Z","timestamp":1615852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"TUOHAI special project 2020 from Bohai Rim Energy Research Institute of Northeast Petroleum University","award":["HBHZX202002"],"award-info":[{"award-number":["HBHZX202002"]}]},{"name":"project of Excellent and Middle-aged Scientific Research Innovation Team of Northeast Petroleum University","award":["KYCXTD201903"],"award-info":[{"award-number":["KYCXTD201903"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Estimation of the number and geo-location of oil wells is important for policy holders considering their impact on energy resource planning. With the recent development in optical remote sensing, it is possible to identify oil wells from satellite images. Moreover, the recent advancement in deep learning frameworks for object detection in remote sensing makes it possible to automatically detect oil wells from remote sensing images. In this paper, we collected a dataset named Northeast Petroleum University\u2013Oil Well Object Detection Version 1.0 (NEPU\u2013OWOD V1.0) based on high-resolution remote sensing images from Google Earth Imagery. Our database includes 1192 oil wells in 432 images from Daqing City, which has the largest oilfield in China. In this study, we compared nine different state-of-the-art deep learning models based on algorithms for object detection from optical remote sensing images. Experimental results show that the state-of-the-art deep learning models achieve high precision on our collected dataset, which demonstrate the great potential for oil well detection in remote sensing.<\/jats:p>","DOI":"10.3390\/rs13061132","type":"journal-article","created":{"date-parts":[[2021,3,16]],"date-time":"2021-03-16T21:42:41Z","timestamp":1615930961000},"page":"1132","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["An Oil Well Dataset Derived from Satellite-Based Remote Sensing"],"prefix":"10.3390","volume":"13","author":[{"given":"Zhibao","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer and Information Technology, Northeast Petroleum University, Daqing 163318, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1242-5412","authenticated-orcid":false,"given":"Lu","family":"Bai","sequence":"additional","affiliation":[{"name":"School of Computing, Ulster University, Belfast BT37 0QB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangfu","family":"Song","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology, Northeast Petroleum University, Daqing 163318, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology, Northeast Petroleum University, Daqing 163318, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinhua","family":"Tao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute of Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1554-0785","authenticated-orcid":false,"given":"Maurice D.","family":"Mulvenna","sequence":"additional","affiliation":[{"name":"School of Computing, Ulster University, Belfast BT37 0QB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raymond R.","family":"Bond","sequence":"additional","affiliation":[{"name":"School of Computing, Ulster University, Belfast BT37 0QB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liangfu","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute of Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,16]]},"reference":[{"key":"ref_1","unstructured":"(2020, December 15). 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