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Comparing Natural Gas Leakage Detection Technologies Using an Open-Source 'Virtual Gas Field' Simulator

机译:使用开放源代码“虚拟气田”模拟器比较天然气泄漏检测技术

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摘要

We present a tool for modeling the performance of methane leak detection and repair programs that can be used to evaluate the effectiveness of detection technologies and proposed mitigation policies. The tool uses a two-state Markov model to simulate the evolution of methane leakage from an artificial natural gas field. Leaks are created stochastically, drawing from the current understanding of the frequency and size distributions at production facilities. Various leak detection and repair programs can be simulated to determine the rate at which each would identify and repair leaks. Integrating the methane leakage over time , enables a meaningful comparison between technologies, using both economic and environmental metrics. We simulate four existing or proposed detection technologies: flame ionization detection, manual infrared camera, automated infrared drone, and distributed detectors. Comparing these four technologies, we found that over 80% of simulated leakage could be mitigated with a positive net present value, although the maximum benefit is realized by selectively targeting larger leaks. Our results show that low-cost leak detection programs can rely on high-cost technology, as long as it is applied in a way that allows for rapid detection of large leaks. Any strategy to reduce leakage should require a careful consideration of the differences between low-cost technologies and low-cost programs.
机译:我们提供了一种用于对甲烷泄漏检测和修复程序的性能进行建模的工具,可用于评估检测技术和拟议的缓解策略的有效性。该工具使用两态马尔可夫模型来模拟从人工天然气田泄漏甲烷的过程。泄漏是根据当前对生产设施的频率和尺寸分布的了解而随机产生的。可以模拟各种泄漏检测和修复程序,以确定每个程序识别和修复泄漏的速率。整合随时间推移的甲烷泄漏量,可以使用经济和环境指标对各种技术进行有意义的比较。我们模拟了四种现有或提议的检测技术:火焰电离检测,手动红外摄像头,自动红外无人机和分布式检测器。通过比较这四种技术,我们发现,使用正的净现值可以缓解80%以上的模拟泄漏,尽管通过有选择地针对较大的泄漏实现最大的收益。我们的结果表明,低成本的泄漏检测程序可以依赖于昂贵的技术,只要它能够以快速检测大泄漏的方式进行应用即可。任何减少泄漏的策略都应仔细考虑低成本技术与低成本程序之间的差异。

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  • 来源
    《Environmental Science & Technology》 |2016年第8期|4546-4553|共8页
  • 作者单位

    Department of Energy Resources Engineering, Stanford University, 367 Panama Street, Stanford, California 9430S, United States;

    Department of Energy Resources Engineering, Stanford University, 367 Panama Street, Stanford, California 9430S, United States;

    Department of Energy Resources Engineering, Stanford University, 367 Panama Street, Stanford, California 9430S, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
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