Development of geospatial clustering methods for broadband seismic-facies analysis

宽带地震相分析的地理空间聚类方法的开发

• 批准号: 514549-2017
• 负责人: Wang, Xin
• 金额: $ 4.66万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=668167
• 关键词: Development; geospatial; clustering; methods; broadband

Seismic data acquisition and geospatial information collection are common practice in current engineering and**resource exploration fields. The dynamic nature of today's industry requires new technology and ways of**conducting seismic and geomatics survey continuously, effective and efficient seismic data processing is**important to industry user groups. In this project, we will focus on the development of efficient geospatial**clustering methods and a system prototype to identify groups of similar seismic facies to represent variability in**subsurface content. The project will provide the industrial partner Symroc with a better understanding and**technology of how to efficiently identify seismic facies from a wide range of frequency seismic data. This**project will be coordinated and finished by the team of Dr. Xin Wang at University of Calgary with**collaborators from the industrial partner Symroc. The project offers innovative approaches and distinctive**solutions that can lead to a more systematic and data-driven procedure for semismic data analysis, visualization**and interpretation. It will provide Symroc better software solution to process seimsmic data. The project offers**innovative approaches and distinctive solutions that can lead to more energy-efficient, low cost and reliable**seismic data collection, integration, analytics and visualization process. The developed methods and system can**potentially be used to help natural earthquake studies and researches, resource industry operations, live**monitoring, and other real time environmental monitoring. This project is aligned with Federal, Provincial and**the University of Calgary strategic priorities. Additionally, the expertise and research experience provides**unique training opportunities for HQP.

地震数据获取和地理空间信息收集是当前工程和**资源探索领域的常见实践。当今行业的动态性质需要新技术和**连续，有效，有效的地震数据处理进行地震和地球的调查**对行业用户群体很重要。在这个项目中，我们将重点关注有效的地理空间**聚类方法和系统原型的开发，以识别类似的地震相的组，以表示**地下内容中的可变性。该项目将为工业合作伙伴的Symroc提供更好的理解和**技术，即如何从广泛的频率地震数据中有效识别地震相。这个**的项目将由卡尔加里大学的Xin Wang博士团队与工业合作伙伴Symroc的**合作者进行协调和完成。该项目提供了创新的方法和独特的**解决方案，可以为半数据分析，可视化**和解释提供更系统和数据驱动的程序。它将提供符号更好的软件解决方案来处理SEIMSMIC数据。该项目提供了**创新的方法和独特的解决方案，可导致更节能，低成本和可靠的**地震数据收集，集成，分析和可视化过程。开发的方法和系统可能可用于帮助自然地震研究和研究，资源行业运营，实时**监测以及其他实时环境监测。该项目与联邦，省和**卡尔加里大学的战略重点保持一致。此外，专业知识和研究经验为HQP提供了**独特的培训机会。