Improving the imaging capabilities of modern portable loop-loop electromagnetic induction (EMI) systems using ground-penetrating radar (GPR) data

使用探地雷达 (GPR) 数据提高现代便携式环路电磁感应 (EMI) 系统的成像能力

• 批准号: 418056756
• 负责人: Dr. Julien Guillemoteau, Ph.D.
• 金额: --
• 依托单位: Institut für Geowissenschaften
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/418056756?language=en
• 关键词: Improving; imaging; capabilities; modern; portable

In near-surface geophysical applications, portable loop-loop electromagnetic induction (EMI) sensors are increasingly used to rapidly image the electrical conductivity of the uppermost meters of the subsurface across rather large areas (several hectares). The resulting 3D models of electrical conductivity can serve to characterize a large selection of targets because many rocks, soil layers and anthropogenic materials show contrast of electrical conductivity. However, because electrical conductivity of subsurface materials is influenced by many different soil and rock properties, the interpretation of the EMI electrical conductivity models is often complex and non-unique; especially, in contexts where no reliable background information about the imaged subsurface is available. Moreover, even if the nature of the targets is known, EMI data are limited in terms of their structural resolution capabilities because each measurement is sensitive to an integrated volume of subsurface.The ground-penetrating radar (GPR) method is another popular near-surface imaging method. As a wave-based imaging technique, which is sensitive to dielectric permittivity contrasts, GPR is typically considered as the geophysical method providing the highest structural resolution. However, a more quantitative analysis in terms of physical property models is often limited with typical 2D/3D GPR reflection data. Although both EMI and GPR methods are used to explore similar depth ranges, they have never been combined in the framework of a quantitative integrated imaging/inversion procedure. Considering weaknesses and strengths of each method and that they can provide complementary information, we hypothesize that a quantitative integration results in an improved characterization of subsurface structures and properties. In this project, we propose to develop and evaluate approaches for quantitively combining EMI and GPR data in order to reduce the classical ambiguities and resolution limitations encountered when using the EMI method only. In doing so, we will first study the typical non-uniqueness of the EMI methods by comparing three different EMI data inversion strategies on several types of controlled targets. Then, we will focus on incorporating the structures as derived from GPR data into the inversion of EMI data, and study how such a strategy helps to reduce the non-uniqueness of the inverted EMI models. In this respect, we will develop and evaluate two constrained inversion strategies: one deterministic grid-based approach, which was recently reported in the literature for larger scale problems, and one stochastic parametric approach. Thus, we expect from this project general conclusion regarding the possibilities of combining EMI and GPR data as well as methodological innovations regarding EMI data inversion further improving the imaging capabilities and the applicability of the EMI method.

在近地形地球物理应用中，越来越多地使用便携式环环电磁诱导（EMI）传感器来快速对地下上最上面的电导率进行跨相当大的面积（几公顷）的电导率。所得的3D电导率模型可以用来表征大量目标，因为许多岩石，土壤层和人为材料都显示出电导率的对比。但是，由于地下材料的电导率受许多不同的土壤和岩石特性的影响，因此对EMI电导率模型的解释通常是复杂且不唯一的。特别是，在没有可靠的背景信息的上下文中。此外，即使已知目标的性质，EMI数据也受到结构分辨率功能的限制，因为每个测量都对集成体积的地下敏感。地面渗透雷达（GPR）方法是另一种流行的近乎表面成像方法。作为一种基于波浪的成像技术，对介电介电常数的对比敏感，GPR通常被视为地球物理方法提供了最高的结构分辨率。但是，在物理特性模型方面进行更定量的分析通常受到典型的2D/3D GPR反射数据的限制。尽管EMI和GPR方法都用于探索相似的深度范围，但它们从未在定量集成成像/反转过程的框架中合并。考虑到每种方法的弱点和优势，并且它们可以提供互补信息，我们假设定量整合会改善地下结构和特性的表征。在该项目中，我们建议开发和评估定量组合EMI和GPR数据的方法，以减少仅使用EMI方法时遇到的经典歧义和解决方案限制。在此过程中，我们将通过比较几种类型的受控靶标的三种不同的EMI数据反转策略来研究EMI方法的典型非唯一性。然后，我们将专注于将来自GPR数据的结构纳入EMI数据的反转，并研究这种策略如何有助于降低倒置EMI模型的非唯一性。在这方面，我们将制定和评估两种约束的反转策略：一种基于确定性网格的方法，最近在文献中报道了大规模问题的文献，以及一种随机参数方法。因此，我们从这个项目的一般结论中，关于将EMI和GPR数据组合的可能性以及有关EMI数据反演的方法学创新进一步提高了成像功能和EMI方法的适用性。