Reverse-Time Migration from Rugged Topography to Image Ground-Penetrating Radar Data in Complex Environments

探地雷达偏移成像中,基于高程静校正的基准面偏移方法对起伏地表下的复杂地层成像效果较差。为了优化成像效果,本文提出了一种基于麦克斯韦方程组二阶解耦形式的逆时偏移成像(reversetime migration,RTM)算法,该算法特点在于只需计算电场,且可直接从采集面而非基准面进行波场延拓,进而实现地形逆时偏移。数值模拟比较了高程静校正偏移方法和RTM方法在地表起伏及速度横向变化情况下的成像效果,结果证明RTM方法成像效果更好。为了进一步验证算法效果,利用美国犹他州珊瑚粉沙丘崎岖地形下的实测数据对两种方法进行了对比分析。研究表明,逆时偏移成像方法能够极大地提高复杂环境下探地雷达深度成像精度。

In ground-penetrating radar （GPR） imaging, it is common for the depth of investigation to be on the same order as the variability in surface topography, In such cases, migration fails when it is carried out from a datum after the application of elevation statics, We introduce a reverse-time migration （RTM） algorithm based on the second-order decoupled form of Maxwell＇s equations, which requires computation of only the electric field, The wavefield extrapolation is computed directly from the acquisition surface without the need for datuming, In a synthetic case study, the algorithm significantly improves image accuracy over a processing sequence in which migration is performed after elevation statics, In addition, we acquired a field dataset at the Coral Pink Sand Dunes （CPSD） in Utah, USA, The data were acquired over rugged topography and have the complex internal stratigraphy of multiply eroded, modern, and ancient eolian deposits, The RTM algorithm significantly improves radar depth images in this challenging environment,