CMG Collaborative Research: Model Integration andJoint Inversion for Large-Scale Multi-Modal Geophysical Data

CMG协同研究：大规模多模态地球物理数据模型集成与联合反演

• 批准号: 0724717
• 负责人: Luis Tenorio
• 金额: $ 4.09万
• 依托单位: Colorado School of Mines
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0724717&HistoricalAwards=false
• 关键词: CMG; Collaborative; Research; Model; Integration

Geophysical data analysis and inversion is a highly quantitative field that involves modeling, data processing, inversion, and visualization. In most cases, a geophysical experiment is conducted to collect data that are sensitive to a particular physical property of the earth. The data are processed and inverted to generate or test an earth model of the physical property in question. To better understand the earth's structure, different experiments are conducted using different imaging modalities. Usually the data of each experiment are inverted separately to generate a collection of earth models. An earth model that shares all physical attributes is usually called a common earth model.Common earth models are very important in scientific and commercial applications because integrating all physical information allows earth scientists to better understand important geological and geophysical processes. Since it is understood that utilizing different modalities may improve inversion results, many algorithms rely on empirical constitutive relationships between the different physical models. However, such relations are typically site-dependent, inexact, and hard to obtain. This hinders the use of common earth models and the understanding that could be obtained from them.This is an interdisciplinary research project to create a more systematic framework for joint inversion of multi-modal geophysical data. We pursue two different and complementary approaches: one based on statistics, and the other on geometry. While our methods have applicability across a wide spectrum of inversion modalities, we focus on the joint inversion of seismic and electromagnetic data. The methods we develop will have wider applicability beyond the joint seismic-electromagnetic inversion problems targeted here, and more generally beyond the geosciences in areas such as medical imaging.

地球物理数据分析和反转是一个高度定量的领域，涉及建模，数据处理，反转和可视化。 在大多数情况下，进行地球物理实验以收集对地球特定物理特性敏感的数据。 处理数据并倒置以生成或测试有关物理属性的地球模型。 为了更好地了解地球的结构，使用不同的成像方式进行了不同的实验。 通常，每个实验的数据分别反转以生成地球模型的集合。 共享所有物理属性的地球模型通常称为公共地球模型。通用地球模型在科学和商业应用中非常重要，因为整合所有物理信息使地球科学家可以更好地理解重要的地质和地球物理过程。 由于可以理解，利用不同的方式可以改善反转结果，因此许多算法依赖于不同物理模型之间的经验构成关系。 但是，这种关系通常是站点依赖性，不精确且难以获得的。 这阻碍了普通地球模型的使用以及可以从中获得的理解。这是一个跨学科研究项目，旨在创建一个更系统的框架，用于联合反转多模式地球物理数据。 我们采用两种不同和互补的方法：一种基于统计数据，另一个基于几何形状。 尽管我们的方法在各种反转方式上具有适用性，但我们专注于地震和电磁数据的联合反转。 我们开发的方法将在此处针对的关节地震电磁反演问题以外的更广泛的适用性，更广泛地超出了医学成像等领域的地球科学。