物理性质
地质学
先验与后验
反演(地质)
地球物理学
经济地质学
财产(哲学)
工程地质
环境地质学
区域地质
反问题
水文地质学
数学
地震学
岩土工程
数学分析
物理
火山作用
哲学
认识论
构造学
量子力学
末端学
变质岩石学
作者
Xiaolong Wei,Jiajia Sun
出处
期刊:Geophysics
[Society of Exploration Geophysicists]
日期:2022-06-28
卷期号:87 (4): K19-K33
被引量:1
标识
DOI:10.1190/geo2021-0833.1
摘要
The physical property models obtained from geophysical inversions can be converted to a 3D quasi-geology model via a process called geology differentiation. Recent works indicate that the geology differentiation can help maximize the value of the information contained in geophysical data. However, it remains largely unexplored as to how to quantify the uncertainties of a 3D quasi-geology model. We approach this problem by using a recently developed mixed [Formula: see text] norm regularization and a priori physical property measurements. We use mixed [Formula: see text] norm joint inversion to construct a large sequence of physical property models based on the Gzz component of the airborne gravity gradient and magnetic measurements. The available physical property measurements are used to determine which physical property models to accept. We then construct a sequence of 3D quasi-geology models by performing the geology differentiation for all of the accepted models, which allows us to compute the probabilities of our geology differentiation results. We apply our approach to a set of field data collected over the Decorah area located in northeast Iowa. We successfully quantify the uncertainties of the spatial extents for the identified geologic units and compute probabilities of geologic units at any location in our study area. The proposed workflow has broad implications for 3D geologic model building based on multiple geophysical and/or rock sample measurements.
科研通智能强力驱动
Strongly Powered by AbleSci AI