{"title":"机载自然源电磁数据的多元处理--应用于戈巴比斯(纳米比亚)的实地数据","authors":"A Thiede, M Schiffler, A Junge, M Becken","doi":"10.1093/gji/ggae172","DOIUrl":null,"url":null,"abstract":"Summary As deep-seated ore deposits become increasingly relevant for mineral exploration, the demand for time-efficient and powerful deep-sounding exploration methods rises. A suitable method for efficiently sensing ores at great depth is airborne electromagnetics (EM) using natural signal of atmospheric origin. The method relates airborne magnetic field recordings in the audio-frequency range to reference magnetic field recordings measured at a ground-based site and can achieve greater penetration depths when compared to controlled source airborne EM techniques. However, airborne natural source EM data are prone to noise caused by platform vibrations especially deteriorating data quality at low frequencies and thus narrowing the depth of investigation. Motional noise manifests as coherent noise on all airborne magnetic field components demanding for a powerful processing tool to remove such kind of noise. Unlike the bivariate approach, which is widely used in natural source EM, the multivariate approach is capable of detecting and reducing the effect of coherent noise. We introduce a robust multivariate processing for airborne natural source EM data and present the code implementation. The code was applied to a large-scale data set from the Kalahari-Copper-Belt in Namibia covering over 1, 000 km2. We obtained spatially consistent and smooth sounding curves in a frequency range of 10 to 1, 000 Hz including frequencies with prominent motional noise. Transfer functions are in good agreement with other geophysical and geological information.","PeriodicalId":12519,"journal":{"name":"Geophysical Journal International","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multivariate processing of airborne natural source EM data - application to field data from gobabis (Namibia)\",\"authors\":\"A Thiede, M Schiffler, A Junge, M Becken\",\"doi\":\"10.1093/gji/ggae172\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary As deep-seated ore deposits become increasingly relevant for mineral exploration, the demand for time-efficient and powerful deep-sounding exploration methods rises. A suitable method for efficiently sensing ores at great depth is airborne electromagnetics (EM) using natural signal of atmospheric origin. The method relates airborne magnetic field recordings in the audio-frequency range to reference magnetic field recordings measured at a ground-based site and can achieve greater penetration depths when compared to controlled source airborne EM techniques. However, airborne natural source EM data are prone to noise caused by platform vibrations especially deteriorating data quality at low frequencies and thus narrowing the depth of investigation. Motional noise manifests as coherent noise on all airborne magnetic field components demanding for a powerful processing tool to remove such kind of noise. Unlike the bivariate approach, which is widely used in natural source EM, the multivariate approach is capable of detecting and reducing the effect of coherent noise. We introduce a robust multivariate processing for airborne natural source EM data and present the code implementation. The code was applied to a large-scale data set from the Kalahari-Copper-Belt in Namibia covering over 1, 000 km2. We obtained spatially consistent and smooth sounding curves in a frequency range of 10 to 1, 000 Hz including frequencies with prominent motional noise. Transfer functions are in good agreement with other geophysical and geological information.\",\"PeriodicalId\":12519,\"journal\":{\"name\":\"Geophysical Journal International\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geophysical Journal International\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1093/gji/ggae172\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geophysical Journal International","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1093/gji/ggae172","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
Multivariate processing of airborne natural source EM data - application to field data from gobabis (Namibia)
Summary As deep-seated ore deposits become increasingly relevant for mineral exploration, the demand for time-efficient and powerful deep-sounding exploration methods rises. A suitable method for efficiently sensing ores at great depth is airborne electromagnetics (EM) using natural signal of atmospheric origin. The method relates airborne magnetic field recordings in the audio-frequency range to reference magnetic field recordings measured at a ground-based site and can achieve greater penetration depths when compared to controlled source airborne EM techniques. However, airborne natural source EM data are prone to noise caused by platform vibrations especially deteriorating data quality at low frequencies and thus narrowing the depth of investigation. Motional noise manifests as coherent noise on all airborne magnetic field components demanding for a powerful processing tool to remove such kind of noise. Unlike the bivariate approach, which is widely used in natural source EM, the multivariate approach is capable of detecting and reducing the effect of coherent noise. We introduce a robust multivariate processing for airborne natural source EM data and present the code implementation. The code was applied to a large-scale data set from the Kalahari-Copper-Belt in Namibia covering over 1, 000 km2. We obtained spatially consistent and smooth sounding curves in a frequency range of 10 to 1, 000 Hz including frequencies with prominent motional noise. Transfer functions are in good agreement with other geophysical and geological information.
期刊介绍:
Geophysical Journal International publishes top quality research papers, express letters, invited review papers and book reviews on all aspects of theoretical, computational, applied and observational geophysics.