ITR: A Novel Framework with Fast Inverse Scattering Algorithms for Future Environmental Sensing

ITR：用于未来环境传感的快速逆散射算法的新颖框架

• 批准号: 0219528
• 负责人: Qing Huo Liu
• 金额: $ 28.5万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-15 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0219528&HistoricalAwards=false
• 关键词: ITR; Novel; Framework; Fast; Inverse

Qing Huo LiuDuke UniversityThis research aims to develop a novel framework for rapid and accurate processing ofgeophysical subsurface measurements in multilayer media. At present, only 2-D mappings(i.e., the low-resolution images on the ground surface) are available, greatly limiting the targetdepth information. Due to the excessive computational demand, previous inverse scatteringalgorithms for these sensors have been developed, but only for objects in a homogeneousbackground medium. This new computational framework is expected to dramatically improvethe way environmental site characterization is being performed.The investigator will develop rapid and accurate computational algorithms for the process-ing of some of the arguably most important measurements in environmental site characteriza-tion and oil exploration, namely electromagnetic induction (EMI), ground penetrating radar(GPR), surface seismic, and borehole sonic imaging measurements in 3-D heterogeneous,multilayer media. These algorithms, coupled with large-scale computing and visualizationplatforms, form a novel framework for current and future environmental site characterizationwhere 3-D subsurface structures can be directly investigated, and sensor arrays can be adap-tively optimized. The main contributions of this research are: (1) Rapid inversion methodsbased on accelerated extended Born/Rytov approximations in layered media; (2) High-fidelityimaging algorithms based on preconditioned contrast source inversion methods in a multi-layer background; (3) A 3-D imaging and adaptive optimization framework using these fastinverse scattering algorithms for multi-sensors. These approaches are expected to yield ahigh resolution because they account for the important multiple scattering effects that causethe resolution degradation in previous linear inversion methods. The development of the al-gorithms for objects embedded in multilayer media represents significant advances in inversescattering and its applications in environmental site characterization and oil exploration.

本研究旨在开发一种新的框架，用于快速准确地处理多层介质中的地球物理地下测量。目前，只有二维映射（即，地面上的低分辨率图像），极大地限制了目标深度信息。由于过多的计算需求，这些传感器的逆散射算法已经开发出来，但仅适用于复杂背景介质中的物体。这一新的计算框架有望极大地改善环境场地表征的执行方式。研究人员将开发快速准确的计算算法，用于处理环境场地表征和石油勘探中一些最重要的测量，即电磁感应（EMI）、探地雷达（GPR）、地表地震、以及在三维非均匀多层介质中的钻孔声波成像测量。这些算法，再加上大规模的计算和可视化平台，形成了一个新的框架，为当前和未来的环境站点characterizationwhere三维地下结构可以直接调查，传感器阵列可以自适应优化。本文的主要研究成果包括：（1）基于加速扩展Born/Rytov近似的层状介质快速反演方法;（2）基于预处理对比度源反演方法的多层背景高分辨率成像算法;（3）基于这些快速逆散射算法的多传感器三维成像和自适应优化框架。这些方法预计将产生高分辨率，因为它们占了重要的多次散射效应，导致在以前的线性反演方法的分辨率退化。多层介质中目标探测技术的发展代表了逆散射技术及其在环境场地表征和石油勘探中的应用的重大进展。