Mateus Tosta, G. P. Oliveira, Bin Wang, Zhiming Chen, Q. Liao
{"title":"APyCE:用于解析和可视化3D油藏数字孪生模型的Python模块","authors":"Mateus Tosta, G. P. Oliveira, Bin Wang, Zhiming Chen, Q. Liao","doi":"10.46690/ager.2023.06.07","DOIUrl":null,"url":null,"abstract":": Engineers, geoscientists, and analysts can benefit from fast, easy, and real-time immersive 3D visualization to enhance their understanding and collaboration in a virtual 3D world. However, converting 3D reservoir data formats between different software programs and open-source standards can be challenging due to the complexity of programming and discrepancies in internal data structures. This paper introduces an open-source Python implementation focused on parsing industry reservoir data formats into a popular open-source visualization data format, Visual Toolkit files. Using object-oriented programming, a simple workflow was developed to export corner-point grids to Visual Toolkit-hexahedron structures. To demonstrate the utility of the software, standard raw input files of reservoir models are processed and visualized using Paraview. This tool aims to accelerate the digital transformation of the oil and gas industry in terms of 3D digital content generation and collaboration.","PeriodicalId":36335,"journal":{"name":"Advances in Geo-Energy Research","volume":"29 1","pages":""},"PeriodicalIF":9.0000,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"APyCE: A Python module for parsing and visualizing 3D reservoir digital twin models\",\"authors\":\"Mateus Tosta, G. P. Oliveira, Bin Wang, Zhiming Chen, Q. Liao\",\"doi\":\"10.46690/ager.2023.06.07\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Engineers, geoscientists, and analysts can benefit from fast, easy, and real-time immersive 3D visualization to enhance their understanding and collaboration in a virtual 3D world. However, converting 3D reservoir data formats between different software programs and open-source standards can be challenging due to the complexity of programming and discrepancies in internal data structures. This paper introduces an open-source Python implementation focused on parsing industry reservoir data formats into a popular open-source visualization data format, Visual Toolkit files. Using object-oriented programming, a simple workflow was developed to export corner-point grids to Visual Toolkit-hexahedron structures. To demonstrate the utility of the software, standard raw input files of reservoir models are processed and visualized using Paraview. This tool aims to accelerate the digital transformation of the oil and gas industry in terms of 3D digital content generation and collaboration.\",\"PeriodicalId\":36335,\"journal\":{\"name\":\"Advances in Geo-Energy Research\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":9.0000,\"publicationDate\":\"2023-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Geo-Energy Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46690/ager.2023.06.07\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Geo-Energy Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46690/ager.2023.06.07","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
APyCE: A Python module for parsing and visualizing 3D reservoir digital twin models
: Engineers, geoscientists, and analysts can benefit from fast, easy, and real-time immersive 3D visualization to enhance their understanding and collaboration in a virtual 3D world. However, converting 3D reservoir data formats between different software programs and open-source standards can be challenging due to the complexity of programming and discrepancies in internal data structures. This paper introduces an open-source Python implementation focused on parsing industry reservoir data formats into a popular open-source visualization data format, Visual Toolkit files. Using object-oriented programming, a simple workflow was developed to export corner-point grids to Visual Toolkit-hexahedron structures. To demonstrate the utility of the software, standard raw input files of reservoir models are processed and visualized using Paraview. This tool aims to accelerate the digital transformation of the oil and gas industry in terms of 3D digital content generation and collaboration.
Advances in Geo-Energy Researchnatural geo-energy (oil, gas, coal geothermal, and gas hydrate)-Geotechnical Engineering and Engineering Geology
CiteScore
12.30
自引率
8.50%
发文量
63
审稿时长
2~3 weeks
期刊介绍:
Advances in Geo-Energy Research is an interdisciplinary and international periodical committed to fostering interaction and multidisciplinary collaboration among scientific communities worldwide, spanning both industry and academia. Our journal serves as a platform for researchers actively engaged in the diverse fields of geo-energy systems, providing an academic medium for the exchange of knowledge and ideas. Join us in advancing the frontiers of geo-energy research through collaboration and shared expertise.