磁强计
软件
磁异常
计算机科学
异常(物理)
数据处理
地球物理学
算法
异常检测
数据挖掘
磁偶极子
数学模型
偶极子
磁场
物理
数学
统计
量子力学
程序设计语言
凝聚态物理
操作系统
作者
Olexandr S. Kriachok,Nataliia V. Makarenko
标识
DOI:10.15407/csc.2024.01.062
摘要
Introduction. The application of modern geophysical methods are caused by the challenges of nowadays Ukraine standing with. The high efficiency of geophysical research is shown by the methods of magnetic exploration. Method of analyzing the array of data from the magnetometer is used to localize the magnetic anomaly’s sources. Such localization is implemented by using various mathematical models and algorithms of software systems. Purpose. The aim of the article is to show an overview of mathematical models and algorithms for the localization of magnetic anomalies’ sources (disturbances). They allow to speed up the processing of magnetometric research’s data and visualize the obtained results. Methods. The article examines the mathematical models of the magnetic anomaly< such as magnetic dipole model, the Gaussian model, the Schwartz model. The multilayer model, and also provides the overview of the main methods for the localization of the described anomaly – the filtering method, the least square method, the gradient analysis method. A list of software and online resources is given, this software is used to analyze magnetometer data and locate magnetic anomalies’ sources. Results. Four mathematical models of magnetic anomalies that allow describing objects of various configurations are considered in the article, and the main methods of determining these objects in the magnetometer data array are given. The article presents the most popular software used for magnetometric data processing. Most of the software is used in geophysics for deep research and requires significant computing resources. A software application was proposed and developed. It allows importing data from the moving platform and magnetometer, analyzing data and visualizing the results. Conclusion. The results of the review emphasize the importance of improving existing mathematical models and developing specialized software for magnetic anomalies’ source localization.
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