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Rapid screening approach for cavity detection using surface-based seismic measurements.

机译:使用基于表面的地震测量方法进行腔探测的快速筛选方法。

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摘要

A rapid screening method for detection of shallow cavities using surface-based seismic waves has been developed and documented. Emphasis is placed on seismic surface waves due to their ease of measurement and dispersive nature in heterogeneous media.; The study includes a numerical experiment, field experiments, and an analytical study of data collected for buried voids. Multi-channel and two-channel data acquisition technology are explored. An alternative analysis of the data based on impulse response is investigated. The field experiments were conducted at sites with known natural caves, buried barrels, and earth fissures. Two historic data sets were used. The numerical experiment was performed for a cavity buried in a homogeneous medium.; Based on results of field and numerical experiments a new constant-offset method for rapid cavity detection is proposed. Parameters introduced include detection index, normalized receiver spacing, and normalized wavelength. All steps in data reduction are combined into one single automated process. Trends observed in the experimental data match the numerical data well and most of the targets were identified; thus the algorithm was validated. Optimal testing configurations, including source configuration, minimum and maximum receiver spacings and offset are proposed.
机译:已经开发并记录了使用基于表面的地震波检测浅腔的快速筛选方法。由于地震面波易于测量并且在非均质介质中具有分散性,因此重点放在地震面波上。该研究包括数值实验,现场实验和对埋藏的空隙收集的数据的分析研究。探索了多通道和两通道数据采集技术。研究了基于冲激响应的数据的替代分析。野外实验是在有已知自然洞穴,埋藏的桶和地裂缝的地点进行的。使用了两个历史数据集。对埋在均质介质中的空腔进行了数值实验。基于现场结果和数值实验,提出了一种新的恒定偏移量快速腔检测方法。引入的参数包括检测指数,归一化接收器间距和归一化波长。数据缩减的所有步骤都组合到一个自动化过程中。实验数据中观察到的趋势与数值数据吻合得很好,并且大多数目标得以确定。从而验证了算法。提出了最佳的测试配置,包括信号源配置,最小和最大接收器间距以及偏移。

著录项

  • 作者

    Tsarev, Gennady.;

  • 作者单位

    University of Nevada, Las Vegas.;

  • 授予单位 University of Nevada, Las Vegas.;
  • 学科 Engineering Civil.
  • 学位 M.S.E.
  • 年度 2003
  • 页码 232 p.
  • 总页数 232
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;
  • 关键词

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