G Roncoroni, P Koyan, E Forte, J Tronicke, M Pipan
{"title":"一个真实的二维多偏移、多频率合成探地雷达数据集作为测试新算法的基准。","authors":"G Roncoroni, P Koyan, E Forte, J Tronicke, M Pipan","doi":"10.1038/s41597-024-04300-1","DOIUrl":null,"url":null,"abstract":"<p><p>We present a 2D multi-offset, multi-frequency synthetic GPR data set specifically designed to evaluate and test processing, analysis and inversion techniques. The data set replicates realistic subsurface conditions at four sections separated by 2 m. We modeled four multi-offset GPR profiles at 50, 100 and 200 MHz frequencies using realistic wavelets. The data set provides a robust framework for validating advanced GPR algorithms and techniques such as pre-stack depth migration, amplitude versus offset analysis and full waveform inversion. Extensive technical validation ensures data reproducibility and affordability. The standardized, realistic synthetic data set can be used as a reliable benchmark for developing and testing new algorithms and methods, thereby advancing the understanding of subsurface imaging and real-world data interpretation.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"221"},"PeriodicalIF":6.9000,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11802766/pdf/","citationCount":"0","resultStr":"{\"title\":\"A realistic 2D multi-offset, multi-frequency synthetic GPR data set as a benchmark for testing new algorithms.\",\"authors\":\"G Roncoroni, P Koyan, E Forte, J Tronicke, M Pipan\",\"doi\":\"10.1038/s41597-024-04300-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We present a 2D multi-offset, multi-frequency synthetic GPR data set specifically designed to evaluate and test processing, analysis and inversion techniques. The data set replicates realistic subsurface conditions at four sections separated by 2 m. We modeled four multi-offset GPR profiles at 50, 100 and 200 MHz frequencies using realistic wavelets. The data set provides a robust framework for validating advanced GPR algorithms and techniques such as pre-stack depth migration, amplitude versus offset analysis and full waveform inversion. Extensive technical validation ensures data reproducibility and affordability. The standardized, realistic synthetic data set can be used as a reliable benchmark for developing and testing new algorithms and methods, thereby advancing the understanding of subsurface imaging and real-world data interpretation.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":\"12 1\",\"pages\":\"221\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2025-02-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11802766/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-024-04300-1\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-024-04300-1","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
A realistic 2D multi-offset, multi-frequency synthetic GPR data set as a benchmark for testing new algorithms.
We present a 2D multi-offset, multi-frequency synthetic GPR data set specifically designed to evaluate and test processing, analysis and inversion techniques. The data set replicates realistic subsurface conditions at four sections separated by 2 m. We modeled four multi-offset GPR profiles at 50, 100 and 200 MHz frequencies using realistic wavelets. The data set provides a robust framework for validating advanced GPR algorithms and techniques such as pre-stack depth migration, amplitude versus offset analysis and full waveform inversion. Extensive technical validation ensures data reproducibility and affordability. The standardized, realistic synthetic data set can be used as a reliable benchmark for developing and testing new algorithms and methods, thereby advancing the understanding of subsurface imaging and real-world data interpretation.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.