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Targeted Reflection-Waveform Inversion of Experimental Ground-Penetrating Radar Data for Quantification of Oil Spills Under Sea Ice

机译:实验性探地雷达数据的定向反射波形反演用于海冰下溢油量化

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摘要

Rapid spill detection and mapping are needed with increasing levels of oil exploration and production in the Arctic. Previous work has found that ground-penetrating radar (GPR) is effective for qualitative identification of oil spills under, and encapsulated within, sea ice. Quantifying the spill distribution will aid effective spill response. To this end, we have developed a targeted GPR reflection-waveform inversion algorithm to quantify the geometry of oil spills under and within sea ice. With known electric properties of the ice and oil, we have inverted for oil thickness and variations in ice thickness. We have tested the algorithm with data collected during a controlled spill experiment using 500-MHz radar reflection data. The algorithm simultaneously recovered the thickness of a 5-cm-thick oil layer at the base of the ice to within 8% of the control value, estimated the thickness of a 1-cm-thick oil layer encapsulated within the ice to within 30% of the control value, and accurately mapped centimeter-scale variations in ice thickness.
机译:随着北极地区石油勘探和生产水平的提高,需要快速进行泄漏检测和测绘。先前的工作已经发现,探地雷达(GPR)可有效地定性识别海冰下和封装在海冰中的溢油。量化泄漏分布将有助于有效的泄漏响应。为此,我们开发了一种有针对性的GPR反射波形反演算法,以量化海冰下和海里溢油的几何形状。有了已知的冰和油的电特性,我们就可以改变油的厚度和冰厚度的变化。我们使用在500 MHz雷达反射数据进行的受控泄漏实验期间收集的数据对算法进行了测试。该算法可同时将冰底处5厘米厚的油层的厚度恢复到控制值的8%以内,估计包裹在冰层中1厘米厚的油层的厚度至30%以内控制值,精确绘制冰层厚度的厘米尺度变化。

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