{"title":"GPR-FWI-Py:基于随机激励源的探地雷达多尺度正则化全波形反演的开源Python软件","authors":"Xiangyu Wang , Hai Liu , Xu Meng , Hesong Hu","doi":"10.1016/j.cageo.2025.105870","DOIUrl":null,"url":null,"abstract":"<div><div>Full Waveform Inversion (FWI) of Ground Penetrating Radar (GPR) is crucial for enhancing subsurface imaging, yet its applications often confronts computational and usability challenges. This paper introduces GPR-FWI-Py, a comprehensive 2D GPR FWI code package that addresses these challenges through a multi-scale strategy, a random excitation source strategy, and Total Variation (TV) regularization. Optimized for high-performance computing, the software is developed in pure Python, ensuring both high efficiency and accessibility. Key features include user-friendly design and readability, which empower users to easily adapt and maintain the software to meet specific project needs. Performance evaluations on layered and Over-Thrust models confirm that our strategies significantly improve FWI results. The modular architecture of GPR-FWI-Py not only simplifies the integration of the FWI algorithm into GPR imaging but also enhances adaptability by supporting the introduction of additional functionalities.</div></div>","PeriodicalId":55221,"journal":{"name":"Computers & Geosciences","volume":"197 ","pages":"Article 105870"},"PeriodicalIF":4.2000,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GPR-FWI-Py: Open-source Python software for multi-scale regularized full waveform inversion in Ground Penetrating Radar using random excitation sources\",\"authors\":\"Xiangyu Wang , Hai Liu , Xu Meng , Hesong Hu\",\"doi\":\"10.1016/j.cageo.2025.105870\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Full Waveform Inversion (FWI) of Ground Penetrating Radar (GPR) is crucial for enhancing subsurface imaging, yet its applications often confronts computational and usability challenges. This paper introduces GPR-FWI-Py, a comprehensive 2D GPR FWI code package that addresses these challenges through a multi-scale strategy, a random excitation source strategy, and Total Variation (TV) regularization. Optimized for high-performance computing, the software is developed in pure Python, ensuring both high efficiency and accessibility. Key features include user-friendly design and readability, which empower users to easily adapt and maintain the software to meet specific project needs. Performance evaluations on layered and Over-Thrust models confirm that our strategies significantly improve FWI results. The modular architecture of GPR-FWI-Py not only simplifies the integration of the FWI algorithm into GPR imaging but also enhances adaptability by supporting the introduction of additional functionalities.</div></div>\",\"PeriodicalId\":55221,\"journal\":{\"name\":\"Computers & Geosciences\",\"volume\":\"197 \",\"pages\":\"Article 105870\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2025-02-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Geosciences\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0098300425000202\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Geosciences","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0098300425000202","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
GPR-FWI-Py: Open-source Python software for multi-scale regularized full waveform inversion in Ground Penetrating Radar using random excitation sources
Full Waveform Inversion (FWI) of Ground Penetrating Radar (GPR) is crucial for enhancing subsurface imaging, yet its applications often confronts computational and usability challenges. This paper introduces GPR-FWI-Py, a comprehensive 2D GPR FWI code package that addresses these challenges through a multi-scale strategy, a random excitation source strategy, and Total Variation (TV) regularization. Optimized for high-performance computing, the software is developed in pure Python, ensuring both high efficiency and accessibility. Key features include user-friendly design and readability, which empower users to easily adapt and maintain the software to meet specific project needs. Performance evaluations on layered and Over-Thrust models confirm that our strategies significantly improve FWI results. The modular architecture of GPR-FWI-Py not only simplifies the integration of the FWI algorithm into GPR imaging but also enhances adaptability by supporting the introduction of additional functionalities.
期刊介绍:
Computers & Geosciences publishes high impact, original research at the interface between Computer Sciences and Geosciences. Publications should apply modern computer science paradigms, whether computational or informatics-based, to address problems in the geosciences.