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解锁解决方案:美国无证废弃油井环境影响识别和缓解的创新方法。

Unlocking Solutions: Innovative Approaches to Identifying and Mitigating the Environmental Impacts of Undocumented Orphan Wells in the United States.

机构信息

Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States.

Sandia National Laboratory, Albuquerque, New Mexico 87123, United States.

出版信息

Environ Sci Technol. 2024 Nov 5;58(44):19584-19594. doi: 10.1021/acs.est.4c02069. Epub 2024 Sep 29.

DOI:10.1021/acs.est.4c02069
PMID:39344066
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11542881/
Abstract

In the United States, hundreds of thousands of undocumented orphan wells have been abandoned, leaving the burden of managing environmental hazards to governmental agencies or the public. These wells, a result of over a century of fossil fuel extraction without adequate regulation, lack basic information like location and depth, emit greenhouse gases, and leak toxic substances into groundwater. For most of these wells, basic information such as well location and depth is unknown or unverified. Addressing this issue necessitates innovative and interdisciplinary approaches for locating, characterizing, and mitigating their environmental impacts. Our survey of the United States revealed the need for tools to identify well locations and assess conditions, prompting the development of technologies including machine learning to automatically extract information from old records (95%+ accuracy), remote sensing technologies like aero-magnetometers to find buried wells, and cost-effective methods for estimating methane emissions. Notably, fixed-wing drones equipped with magnetometers have emerged as cost-effective and efficient for discovering unknown wells, offering advantages over helicopters and quadcopters. Efforts also involved leveraging local knowledge through outreach to state and tribal governments as well as citizen science initiatives. These initiatives aim to significantly contribute to environmental sustainability by reducing greenhouse gases and improving air and water quality.

摘要

在美国,数以十万计的无证件废弃油井被遗弃,导致管理环境危害的负担落在政府机构或公众身上。这些油井是由于一个多世纪以来没有充分监管的化石燃料开采造成的,缺乏位置和深度等基本信息,排放温室气体,并将有毒物质泄漏到地下水中。对于这些油井中的大多数来说,位置和深度等基本信息未知或未经核实。解决这个问题需要创新和跨学科的方法来定位、描述和减轻其对环境的影响。我们对美国的调查显示,需要工具来识别油井位置和评估状况,这促使我们开发了包括机器学习在内的技术,以从旧记录中自动提取信息(准确率达 95%以上)、航空磁力仪等遥感技术来寻找埋藏的油井,以及用于估算甲烷排放的具有成本效益的方法。值得注意的是,固定翼无人机配备磁力计已成为发现未知油井的具有成本效益和高效的方法,与直升机和四旋翼飞机相比具有优势。这些努力还涉及通过与州和部落政府以及公民科学倡议的外联来利用当地知识。这些倡议旨在通过减少温室气体排放和改善空气和水质,为环境可持续性做出重大贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/79828336b2e0/es4c02069_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/00c8906b570a/es4c02069_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/b1a46c00c4fc/es4c02069_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/f7c50f298e50/es4c02069_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/2d7cbcf51c80/es4c02069_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/79828336b2e0/es4c02069_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/00c8906b570a/es4c02069_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/b1a46c00c4fc/es4c02069_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/f7c50f298e50/es4c02069_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/2d7cbcf51c80/es4c02069_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2200/11542881/79828336b2e0/es4c02069_0005.jpg

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本文引用的文献

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2
Documented Orphaned Oil and Gas Wells Across the United States.美国有记录的废弃油气井。
Environ Sci Technol. 2022 Oct 18;56(20):14228-14236. doi: 10.1021/acs.est.2c03268. Epub 2022 Sep 26.
3
Identification and characterization of high methane-emitting abandoned oil and gas wells.
使用大语言模型从历史油井记录中提取信息。
Sci Rep. 2024 Dec 30;14(1):31702. doi: 10.1038/s41598-024-81846-5.
高甲烷排放废弃油气井的识别与特征分析
Proc Natl Acad Sci U S A. 2016 Nov 29;113(48):13636-13641. doi: 10.1073/pnas.1605913113. Epub 2016 Nov 14.
4
Direct measurements of methane emissions from abandoned oil and gas wells in Pennsylvania.对宾夕法尼亚州废弃油气井甲烷排放的直接测量。
Proc Natl Acad Sci U S A. 2014 Dec 23;111(51):18173-7. doi: 10.1073/pnas.1408315111. Epub 2014 Dec 8.