{"title":"A new multiscale imaging method for estimating the depth and structural index of magnetic source","authors":"Yanguo Wang, Ye Tian, Juzhi Deng","doi":"10.1190/geo2022-0674.1","DOIUrl":null,"url":null,"abstract":"The fast automatic technique for determining the source parameter is very commonly used to interpret magnetic data. A new method is proposed to estimate the magnetic source parameter based on the any order analytic signals of magnetic anomalies at different altitudes. The new method is based on the relationship between the location, depth and structural index of the source and the expressions of analytic signals, and employs the altitude z and a depth scaling factor β to establish a new multiscale imaging method called Variable Depth Mirror Imaging (VDMI), whose extreme points are related to the source parameters. Two equations are given to calculate the source depth and structural index on the basis of the vertical positions of the peaks of VDMI sections with two different β. Moreover, a series of solutions of source parameters will be obtained when a number of β are selected, which can make the results more reasonable. The method is stable and can be directly applied to noisy anomalies or high-order derivatives because it is based on magnetic anomalies of upward continuation. In addition, the method is flexible as we can select different β as desired. Moreover, the method can be applied to multisource cases, and can simultaneously estimate the depth and structural index for each source. The method was tested on noise-free and noise-corrupted synthetic magnetic anomalies. In all cases, the VDMI method effectively estimates the depths and structural indices of the sources. The VDMI method was also applied to real aeromagnetic data from the Hamrawien area, Egypt, and ground magnetic data over Neibei Farm of Heilongjiang Province, China.","PeriodicalId":509604,"journal":{"name":"GEOPHYSICS","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GEOPHYSICS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1190/geo2022-0674.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The fast automatic technique for determining the source parameter is very commonly used to interpret magnetic data. A new method is proposed to estimate the magnetic source parameter based on the any order analytic signals of magnetic anomalies at different altitudes. The new method is based on the relationship between the location, depth and structural index of the source and the expressions of analytic signals, and employs the altitude z and a depth scaling factor β to establish a new multiscale imaging method called Variable Depth Mirror Imaging (VDMI), whose extreme points are related to the source parameters. Two equations are given to calculate the source depth and structural index on the basis of the vertical positions of the peaks of VDMI sections with two different β. Moreover, a series of solutions of source parameters will be obtained when a number of β are selected, which can make the results more reasonable. The method is stable and can be directly applied to noisy anomalies or high-order derivatives because it is based on magnetic anomalies of upward continuation. In addition, the method is flexible as we can select different β as desired. Moreover, the method can be applied to multisource cases, and can simultaneously estimate the depth and structural index for each source. The method was tested on noise-free and noise-corrupted synthetic magnetic anomalies. In all cases, the VDMI method effectively estimates the depths and structural indices of the sources. The VDMI method was also applied to real aeromagnetic data from the Hamrawien area, Egypt, and ground magnetic data over Neibei Farm of Heilongjiang Province, China.